EGU General Assembly 2023  

Humans have impacted the hydrological cycle since the invention of agriculture, but these impacts have grown to global proportions over the last 60 years. The indirect effects of anthropogenic climate change may be the largest, but the direct impacts by dam building, water withdrawals and the emission of pollutants is still formidable, even by comparison. In the first part of this lecture, I will briefly go over the impacts of human water use on global hydrology and water resources and how these impacts have been assessed by observational evidence and global hydrological models. This will also provide the opportunity to highlight some recent advancements in global hydrological modelling. The second part of the lecture will focus on the impacts of human water use on groundwater resources. After reviewing past assessments of global groundwater depletion rates, I will show results of ongoing research in our group on the limits to global groundwater use. These include: physical limits, related to groundwater-surface water interaction, permeability constraints and salinity; economic limits, related to the costs of groundwater extraction when wells become deeper; and ecological limits, related to the impacts of groundwater extraction on groundwater dependent ecosystems.

How to cite: Bierkens, M.: Global Water Resources and the Limits to Groundwater Use, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1844, https://doi.org/10.5194/egusphere-egu23-1844, 2023.

Until the 1970s, global hydrology had to rely on the collection of in-situ observational data and aggregation under condition when electronic computers were not sufficiently available. In the 1980s, earth observation data from artificial satellites began to observe clouds, precipitation, and later surface soil moisture content, and from the beginning of the 21st century, total terrestrial water storage, including groundwater and ice sheets. Along with this, data assimilation systems merging simulated forecasts by numerical models of the atmosphere and in-situ and satellite observations have been developed, and the information on global hydrologic cycles, at least regarding the atmosphere, has become available.

When we applied the atmospheric water balance method to the four-dimensional data assimilation (4DDA) data and compared it with the discharge of major rivers around the world, we found that the seasonal variation was captured well, although the quantitative accuracy was not sufficient. Seasonal variations in total terrestrial water storage are very large in the Amazon Basin and cannot be explained by changes in soil moisture alone. It was suggested that the changes in river water stored in the river channel contributed greatly, but it was necessary to wait until later GRACE observation data were available to obtain conclusive evidence.

In addition, when the atmospheric water balance method is applied, negative runoff is calculated in some regions and seasons, and at first it was thought to be an error in data and the data processing, and an ad hoc correction method was attempted. However, even from the composite of in-situ discharge data, some areas were found where the downstream river discharge was smaller than the upstream, and negative runoff should be estimated. Then, it became apparent that the negative runoff should be mainly due to anthropogenic water withdrawals and consumption, it is necessary to consider human activities in research targeting the actual water cycle, and such interventions can be detected even on a global scale.

Then, starting with storing in and releasing from reservoirs, an integrated water cycle and water resources model that considers human activities such as water withdrawals from rivers and groundwater, irrigation for farmlands, and long-distance water transport through canals has been developed and used. Although such a model was initially for a global scale, it can be applied for local simulation of hydrologic cycles in the Anthropocene considering water supply and sewerage systems and contribute to supporting scientific evidence-based decision makings.

Improvements in observational and computational capabilities alone did not support the development of global hydrology. In addition to the numerical model itself, it should be acknowledged to the development and sharing of critical global data such as topography, land use and land cover, and cropland distribution equipped for irrigation that are essential for proper simulation of the model. Global hydrology is a community-supported discipline and the gift of grassroots solidarity among researchers around the world.

How to cite: Oki, T.: Evolution of Global Hydrology in the Anthropocene, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4076, https://doi.org/10.5194/egusphere-egu23-4076, 2023.

Groundwater is het largest available freshwater resource on earth and is critical to humans and the environment. Groundwater is especially important for irrigated agriculture, and thus for global crop production and food security; approximately 40% of the today’s irrigated agriculture depends on groundwater. In many regions around the world, unsustainable groundwater pumping exceeds recharge from precipitation and rivers. This leads to substantial drops in groundwater levels and losses of groundwater from its storage, especially in intensively irrigated regions, as well as reduction of river flows with possible devastating impacts on freshwater ecosystems.

In my research I simulate groundwater flows and groundwater surface water interactions globally, using a high resolution coupled groundwater and surface water model, and study the impacts of groundwater pumping from the recent past until the far future. In this talk I will present recent findings on current and projected impacts of groundwater pumping on river flows, including an estimate where and when environmentally critical thresholds for groundwater discharge are reached. Second, I will present novel developments and future research steps me and my team will take towards estimating global groundwater availability that can be sustainably exploited and the trade-off between sustainable groundwater use and crop production.

How to cite: de Graaf, I.: Groundwater availability and sustainability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11454, https://doi.org/10.5194/egusphere-egu23-11454, 2023.

Accelerated climate, environmental and societal change and its dynamics challenge the resilience of complex socio-ecological systems and require constant adaptation. It also requires to better integrate uncertainties into the decision-making process. By comparing two case studies in Tanzania and Germany with different foci in human-water interaction and socio-political backgrounds, patterns of decision-making under uncertainty are identified. Using a (semi)participatory qualitative system analysis approach helps identifying the heterogeneity of actors and their specific ways of reasoning. For example, in the case studies the perception of change and uncertainty differed between the stakeholders and were identified as important drivers for different decision rationales and hence different preferred adaptation strategies. While research in reducing environmental uncertainty through e.g. improved physical understanding and models is important, it is only on side of the equation in complex socio-ecological systems. Especially, the interplay of environmental and socio-economic uncertainty and how this uncertainty loop creates different rooms of action and agency is worth considering. The comparison shows that acknowledging heterogeneity is important across regions and water management issues and supports in developing tailor-made adaptation strategies targeting the environmental issue. Additionally, the approach empowers and enables actors to increase their room of action and adaptation capacity by acknowledging their uncertainty perception.

How to cite: Höllermann, B.: Impact of interplay of perceived environmental and socio-political uncertainties on adaptation decisions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-206, https://doi.org/10.5194/egusphere-egu23-206, 2023.

Sea level rise (SLR) causes increasing salt deposition in the soil and groundwater of coastal regions. This will affect coastal farmers, since salinity levels will reduce crop yield, which leads to loss in net annual income of farmer communities. To minimize the impacts and income loss, farmers often adopt adaptation measures, such as irrigation, adding manure and gypsum, switching to salt tolerant crops, or buying less saline lands. When these options are not feasible,  farmers may migrate to inland areas to minimize future impacts and damages.

We adopt an agent-based model (ABM) to simulate adaptation and migration decisions by farmers in Mozambique under sea level rise. . The ABM is coupled to a salinization module for simulating the relation between soil salinity and sea level rise. The decision rules in the model (DYNAMO-M) are grounded in economic theory of subjected expected utility where household maximize their welfare by deciding 1) to stay and face loss from salinization and flooding, 2) stay and adapt (irrigation or buy land) or 3) migrate to safer inland areas. The model runs with a yearly timestep (2020-2100) for simulating salinity levels, but accounts for dynamics in the growing season. (Future-) soil salinity levels are derived from ISRIC (2012) and Hassani et al. (2020). Projections in salinity levels are converted into (reduced-) yield levels following Maas and Hoffman (1977). Country statistics and census data are then used to estimate farmers income from expected yields. The model finally simulates adaptation decisions based on the cost (expected yield loss + adaptation investments) against the benefit (expected yield). Results show how many farming households have stayed with the damage, adapted with a measure, and migrated to inland areas over time and space.  

Keywords: sea level rise, soil salinization, coastal farmers, agent-based model, migration

How to cite: Pandey, K., de Bruijn, J., de Moel, H., and Aerts, J.: Simulating the effects of sea level rise and soil salinization on migration and adaptation in coastal Mozambique, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-409, https://doi.org/10.5194/egusphere-egu23-409, 2023.

The understanding of floods has become more complex as the changing climate has made the floods more unpredictable, recurrent, and intensified. The present study focuses on the analysis of behavior of the sub-basins under the extreme rainfall events. For this purpose, an extreme flood event of 2019 in Koyna River Basin located in the Upper Krishna River Basin, Maharashtra was considered. The hydrological responses of the sub-basins of Koyna River basin during this flood event were obtained using a Process-based Soil and Water Assessment (SWAT) hydrological model. The model was configured using the topographical, land use, soil and metrological parameters, respectively. Fathom FABDEM hydrologically corrected DEM were used to delineate the watershed with an outlet near Karad City, just downstream of the Warunji gauging station. The Indian Metrological Department (IMD) 0.25⁰ * 0.25⁰ daily gridded rainfall data and minimum and maximum temperature were used to set up the model. The simulation runs were taken to obtain the responses of the sub-basins for the period of 2016 to 2020.  The study reveals high value of Coefficient of Correlation (R²) being equal to 0.72 indicating that the simulated runoff is closely related with the observed runoff at Warunji Gauging station. The configured hydrological model would be useful in predicting the sub-basin responses under climate change so that the proper planning and preparedness can be made to evolve the robust policies for handling severe floods in the future.

Keywords: Climate Change, Extreme events, SWAT, FABDEM, Koyna River.

How to cite: Ranjan, R. and Keshari, A. K.: Process-based Hydrological Modeling to Analyse Sub-basin Response Under Extreme Rainfall Events in Koyna River Basin, Maharashtra, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1663, https://doi.org/10.5194/egusphere-egu23-1663, 2023.

Climate change and human activities may cause change points in hydrological processes, which have serious impacts on the stability of watershed hydrological ecosystems. The Pettitt test method was used to identify the change point of discharge in the Yangtze River basin, and ecological water demand was estimated based on generalized extreme value distribution. The results show that: (1) the ecological water demand guarantee rate of the Yangtze River basin increased from a viewpoint of the whole basin during the past decades, especially in dry seasons. Due to the regulation of reservoirs and dams in the Yangtze River Basin, the ecological surplus (ecological deficit) tends to increase (decrease) in the dry season of the Yangtze River Basin, while it tends to reverse in the wet season. (2) The degree of hydrological alterations in the trunk stream of the Yangtze River Basin is the highest (D0 reaches 50% or more), and the river hydrological situation and ecosystem are under high risks (the total DHRAM score is more than 10 points), and the biodiversity shows a significant downward trend. (3) Climate change and human activities have the opposite impact on ecological streamflow of the Yangtze River Basin, that is, climate change increases ecological surplus and decreases ecological surplus. Overall, climate change is the leading factor affecting ecological surplus (the contribution is more than 50%).

How to cite: he, Y. and gu, X.: Ecological Instream Flow in the Yangtze River Basin under the Hydrological Change: Changes, Impacts, and Attributions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2070, https://doi.org/10.5194/egusphere-egu23-2070, 2023.

Anthropogenic actions are progressively affecting most river basins worldwide, resulting in changes in hydrological processes and thus influencing water availability. Despite previous studies aimed at quantifying the relationship between urbanization and extreme flooding events at local to regional scales, it is still unclear how human presence has influenced the occurrence of seasonal surface water. As a result, global patterns remain largely unknown.

In this study, we perform a global analysis of large river basins and uncover global trends of annual maximum flood extent and impervious area, as well as their relationships with rainfall and snowmelt, over the past three decades. Hydrological and urban dynamics are computed by using multiple earth observation datasets.

We find that hydroclimatic variability alone cannot explain changes in annual maximum flood extent for 75% of the analyzed river basins worldwide. We also observe increasing trends in both annual maximum flood extent and the urbanized area within floodplains, especially in Asian and African river basins. Our findings reveal an emerging global reciprocal relationship between urbanization processes and maximum flood extent changes. Both rainfall and urbanized area can explain changes in the annual maximum flood extent in 57% of the analyzed basins.

Our findings highlight the need for a better understanding of the influence of human presence on changes in seasonal water dynamics at the global scale. In view of the worldwide rapid development of urban areas, these findings can inform the process of flood risk management and help improve targeted policy and land use interventions

How to cite: Mazzoleni, M., Dottori, F., Cloke, H. L., and Di Baldassarre, G.: Influence of urbanization on flood extent changes at the global level, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2256, https://doi.org/10.5194/egusphere-egu23-2256, 2023.

For governing river basin systems, social-ecological systems (SES) structures can be reshaped by institutions, such as policies, laws, and norms. Effective (“matched” or “fit”) institutions operate at appropriate spatial, temporal, and functional scales to manage and balance different relationships and interactions between human and water systems, supporting (but not guaranteeing) the sustainability of SES. To better understand how water governance institutions match/mismatch their social-ecological context, we take the Yellow River Basin (YRB), China, as an example to dive into causal links between institutional changes and outcomes. An agent-based model was developed around the Yellow River's most far-reaching water quota institution during the past half century, considering how factors such as human behaviour and environmental change have combined with the institutional shifts to lead to changes in the Yellow River's water use. Our results show regional differences in the impact of the system, with some areas tending to ignore the constraints of the quota system when other provinces embarked on a water-saving transition. Our model demonstrates the dramatic impact of institutional change on socio-hydrological processes and has guidness for the sustainable use of water resources at a time when non-engineered measures of water governance are becoming increasingly common.

How to cite: Song, S., Wang, S., and Fu, B.: Institutional impacts on the evolution of the Yellow River, China: a perspective from socio-hydrological modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4221, https://doi.org/10.5194/egusphere-egu23-4221, 2023.

New Caledonia is a French overseas territory located in the southwest Pacific, 2000 km east of Australia. Geologically, the Antarctic and Australian plates broke up 250 Ma ago as a result of the break-up of Gondwana land. Ocean basins opened up and remnants of the former supercontinent separated and drifted eastwards. The eastern ridge, known as Norfolk ridge, substratum of New-Caledonia sank under the water. The New Caledonian Great Land emerged 34 million years ago after obduction phase. A new terrestrial environment was created. Freshly emerged, it was gradually recolonized by animals and plants from more or less nearby land masses.

New Caledonia’s Island isolation and the particularity of its soils forced the biotope to adapt and develop original, even unique, characteristics, thus contributing to making it one of the world's champions of biodiversity. With 76% plant endemism, this tiny territory (<20,000 km2) ranks third in the world (behind Hawaii and NZ).

The peridotites brought to the surface by obduction developed a thick alteration profile. Nickel and Cobalt, issued from the primary minerals of the peridotites, got concentrated in the saprolite horizon. The exploitation of these ores, was accelerated after the Second World War with the mechanization of extraction. Carried out without precaution, this time-period resulted in very significant environmental damage: deforestation and soil exposure, accelerated erosion, watercourse siltation and hypersedimentation, and flooded low-lying valleys. 

Environmental awareness was finally raised in the 1970s and increasingly triggered the introduction of responsible regulations. The mining and metallurgy companies working in the area, which are among the world's major players, have significantly improved their operational procedures, the quality of their environmental monitoring and remediation methods

On steep slopes and in a climate where rainfall can be very heavy, water management is one of the challenges to be overcome, as well as the revegetation of workings and slopes. This paper will present the results of the audit carried out by the GEME (mine water management and environment) program of the CNRT "Nickel and Environment" (National Technological Research Centre) on these issues and their comparison, based on the benchmark carried out with those of other major mining countries. The results concern the hydro-sedimentary models used, the acquisition of the parameters introduced, the adequacy with the rules of good practice and the evolution of these rules with global changes as well as the effectiveness of water management and revegetation methods.

The increasing involvement of local populations in the environmental management of the sites affected by mining will be discussed. Most of the mines are located on customary land whose inhabitants are now severely impacted by the mistakes of the past and want to become key players of the mine of the future. In a sensitive political context (end of the Nouméa Accord) where the institutional future of the country has not yet been determined, the topic of nickel mining and its environment is one of the levers for a hoped-for end to the crisis. Our communication will mention this in its conclusion.

How to cite: Allenbach, M., Semper, A., and Cote, C.: Management and restoration of the mining maquis ecosystem in New Caledonia (South West Pacific), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4575, https://doi.org/10.5194/egusphere-egu23-4575, 2023.

Damage due to hydrological extremes increase in many regions of the world. A better understanding of the drivers of increasing damage trends is essential for effective flood and drought risk management. However, empirical data is lacking about the processes in complex human-water systems that result in flood and drought damage. We present a benchmark dataset containing socio-hydrological data of paired events, i.e., two floods or two droughts that occurred in the same area. The 45 paired events cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed, and in the quantity of qualitative and quantitative socio-hydrological data. The core of the benchmark dataset comprises: 1) detailed review style reports about the events and key processes and changes between the two events of a pair; 2) an overview table of key data about management, hazard, exposure, vulnerability and impacts of all events; 3) a table of indicators of change between first and second event of each pair. The advantages of the dataset are that it enables comparative analyses across all the paired events and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. A first analysis of the dataset revealed the general pattern that risk management normally reduces the impacts of floods and droughts, but faces difficulties in reducing the impacts of unprecedented events of a magnitude not experienced before (Kreibich et al. 2022a). The dataset can be used by the scientific community for exploratory data analyses and for the development of socio-hydrological models. As such, the dataset can support solving one of the twenty-three unsolved problems in hydrology (Blöschl et al. 2019), namely “How can we extract information from available data on human and water systems in order to inform the building process of socio-hydrological models and conceptualisations?”. The dataset is available to the public through the GFZ Data Services (Kreibich et al. 2022b).

References

Blöschl, G., Bierkens, M. F., Chambel, A., et al. (2019): Twenty-three unsolved problems in hydrology (UPH) – a community perspective. - Hydrological Sciences Journal - Journal des Sciences Hydrologiques, 64, 10, 1141-1158. https://doi.org/10.1080/02626667.2019.1620507

Kreibich, H., Loon, A. F. V., Schröter, K., et al. (2022a): The challenge of unprecedented floods and droughts in risk management. - Nature, 608, 80-86. https://doi.org/10.1038/s41586-022-04917-5

Kreibich, H., Schröter, K., Di Baldassarre, G., et al. (2022b): Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts. https://doi.org/10.5880/GFZ.4.4.2022.002

How to cite: Kreibich, H. and the Flood and drought paired event community: Panta Rhei benchmark dataset: socio-hydrological data of paired events of floods and droughts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4932, https://doi.org/10.5194/egusphere-egu23-4932, 2023.

Although global freshwater resources are vital to the livelihood of humanity and all other life on Earth, 10% of the global population lives in regions with high to critical levels of water stress. In many of these regions the freshwater resources risk depletion of surface water or groundwater resources due to unsustainable use. Such regions are considered as the “hotspots of water scarcity”. Understanding how these hotspots have evolved over time towards their current state of water scarcity, provides important insights for decision-making and implementation of mitigation and water regulation policies.

We present a global intercomparison of the key drivers and pressures causing water scarcity at these hotspots around the world. For our analysis we have applied a Driver-Pressure-State-Impact-Response (DPSIR) framework to a literature search of >175 case studies of the hotspot regions. In this framework natural, social and economic information is combined to identify driving forces and resulting pressures that have deteriorated the state (quality or quantity) of the water resources. The DPSIR literature analysis is supported by observational data analysis to study the temporal evaluation for each hotspot.

We identify the key drivers and pressures to be: hydroclimatic changes (78%), population growth (28%) and agricultural (93%), municipal (54%), and industrial water demand (37%). Subsequent impacts on society are less homogeneous between the hotspots, with damage to ecosystems (25%) and reduced agricultural production (16%) as main impacts. Responses also vary greatly. While some have a positive impact on alleviating water scarcity (e.g. increased storage capacity (25%) or water treatment (23%)), others are ineffective in attempting to alleviate water scarcity or even worsen water scarcity problems (e.g. lack of groundwater regulation policies (12%) or unfair distribution of water rights (12%)).

These outcomes of the DPSIR analysis provide valuable information for constructing causal networks representative to water scarcity problems at the hotspots. Such a causal network will serve as the basis of a conceptual model that represents human-water interactions at the hotspots, thereby providing a better understanding of trade-offs and synergies in different human-water systems around the world.

How to cite: Leijnse, M., Droppers, B., Bierkens, M., and Wanders, N.: Key drivers and pressures of water scarcity at global hotspots, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4956, https://doi.org/10.5194/egusphere-egu23-4956, 2023.

Despite agreement that climate change is increasingly recognized as a threat multiplier in conflict pathways, connections between water flows and conflicts remain unclear. This is affected by incomplete datasets on water-related conflict-cooperation events and poor understanding of socioeconomic and biophysical causes of such conflicts. Disentangling various drivers of water-related cooperation and conflict pathways, with more complete datasets on water-related conflict-cooperation events and a detailed understanding of socio-economic and biophysical causes of such conflicts, is necessary for resolving conflicts and building peace As part of this study we have complied a new global dataset on water-related conflict-cooperation events that extends to 2019, updating previous datasets that covered only up to 2008, yielding important new insights on cooperation-conflict trends. Correlations between events and aspects such as changes in precipitation and socioeconomic variables were then calculated for different change scenarios. Analysis of events shows that cooperation can significantly reduce future conflicts in all tested change scenarios. In addition, cooperation positively affects countries’ socioeconomic development, further reducing the risk of conflict. The new dataset revealed a worrying trend with a shift in the cooperation-conflict balance in the 2000s, with conflict events increasing and outnumbering cooperation events in 2017. Regional analysis shows that changes towards more conflict and fewer cooperation events in Africa could be related to long periods of drought, while changes in Asia are related to irrigation and dam construction. This study shows that water cooperation can be effective for peacekeeping while simultaneously creating positive socio-economic development. The trend towards less cooperation and more conflict in current years highlights the need for effective water management adapted to local and regional drivers of change (climate or anthropogenic) focusing on forming collaborations based on current and projected water availability. Utilizing our newly created and openly available water-related conflict and cooperation database can provide a good opportunity for further research into actions required to change this trend and promote future water cooperation.

Keywords: conflict; cooperation; peacekeeping; climate change; hydrology;

How to cite: Kåresdotter, E., Li, S., Pan, H., and Kalantari, Z.: Humans, Water, and Climate change – Global analysis of Conflicts and Cooperation and their Potential Drivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5319, https://doi.org/10.5194/egusphere-egu23-5319, 2023.

Water drained from agricultural lands is getting more attention as its valuable water is lost from groundwater storage. The historical location of buried agricultural water drainage systems is not known very well. Hence, first, finding the location of those infrastructures is critical. Several methods have been applied in the past, including decision tree classification (DTC), remote sensing based, using radar, etc. However, all the methods neglect the primary cause of the drain application, which is groundwater. Hence, a novel approach is introduced that considers groundwater in the identification procedure. We used two case studies for drain identification, one from Ontario, Canada, and another from Belgium. Furthermore, a physically based and fully distributed modeling approach (SWAT+gwflow) is conducted to investigate the impact of these drainage systems in the catchment hydrology of the Kleine Nete watershed, Belgium.

The result of the drainage system identification has indicated the pitfalls of the already existing methods where accuracy as low as 17% was recorded. On the other hand, the additional filtering based on groundwater head enables us to find an additional 19.4 km² area. Therefore, the use of groundwater level as an additional filtering technique is vital for increasing the accuracy of tile drain/ditch network identification. Next, drains have been shown to affect hydrology, where a 15% decrease in groundwater evapotranspiration, a 50% reduction in groundwater saturation excess flow, and a 39% decline in groundwater discharge to streams are observed.

How to cite: Yimer, E. A., Riakhi, F.-E., Yadollahi, S., Weerasinghe, I., Wirion, C., T. Bailey, R., Nossent, J., and van Griensven, A.: A novel way of identifying agricultural water drainage systems and their impact on catchment hydrology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5799, https://doi.org/10.5194/egusphere-egu23-5799, 2023.

The water cycle is highly interconnected; water fluxes in one part depend on physical and human processes throughout. For example, rivers are a water supply, a receiver of wastewater, and an aggregate of many hydrological, biological, and chemical processes. Thus, simulations of the water cycle that have highly constrained boundaries may miss key interactions that create unanticipated impacts or unexpected opportunities. Integrated environmental models aim to resolve the issue of boundary conditions, however they have some key limitations, and we find a significant need for a parsimonious, self-contained suite that is accessible and easy to setup. With this in mind, we have developed the WSIMOD – a Python package that allows for the representation of the water system’s demands and impacts of multiple sectors and actors’ decisions within a single tool, which is considered beneficial to increasing a shared understanding of system performance and for more collaborative and coherent decisions on integrated water resources, water quality and flood management. The WSIMOD is a self-contained software package that includes modelled representations of key physical and infrastructure elements of the water cycle (urban and rural), with each type of modelled element generically described as a component. Components are written in such a way that any component can interact with any other component. This enables a flexible representation of a water system that is needed to accommodate the wide variety of different built/natural infrastructure configurations and scales. We will showcase how the WSIMOD tool has been developed and successfully tested through a range of applications in the UK, including integrated analysis of urban water systems, catchment water management and urban water neutrality.  

How to cite: Mijic, A., Liu, L., and Dobson, B.: Water Systems Integrated Modelling framework (WSIMOD): A Python package for simulating human-impacted water quality and quantity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6399, https://doi.org/10.5194/egusphere-egu23-6399, 2023.

Water scarcity is a growing concern in many regions worldwide, as demand for clean water increases and supply becomes increasingly uncertain under climate change. Already today, more than 4 billion people experience water scarcity at least one month per year (Mekonnen and Hoekstra, 2016). Developing socio-economic conditions and growing population increase water demands, while climate change leads to changes in freshwater availability. Most studies quantify water scarcity in discrete time windows, with fixed population and climate change signals (e.g., 30 years or long-term averages). Recently, however, Thiery et al. (2021) proposed a novel approach, in which climate change impacts are integrated over a person's lifetime. In this cohort perspective, lifetime impact values are comparable across generations and regions. Evaluating this perspective for natural hazards, they showed, for example, that a newborn will experience a sixfold increase in drought exposure compared to a 60-year-old (Thiery et al., 2021). 

In this study, we use this cohort perspective to study how much water scarcity a person experiences during their lifetime. Based on monthly fluctuations in water demand and availability, we estimate the total amount of water demand not met and refer to it as 'lifetime water deficit'. To this end, we use an ensemble of four global hydrological models (MATSIRO, CWatM, LPJmL and H08), each forced by four GCMs and two RCP scenarios from the InterSectoral Impact Model Intercomparison Project (ISIMIP2b). The simulations account for varying population and socio-economic conditions in the historical and future period, following the SSP2 scenario. Combined with country-based population, cohort distribution and life expectancies, lifetime water deficits are quantified for different generations on a country level. 

Our findings reveal high water lifetime deficit values for regions that are already water scarce today, such as the Mediterranean, North Africa and the Middle East. In these regions, more than 70% of the lifetime water demand is not met when needed. Further comparison reveals differences in spatial, intergenerational and climate change scenarios, and provides information on different scenarios. Overall, this study provides a new perspective on quantifying water scarcity and the climate and population impacts. 

References:

Mekonnen, M. M., & Hoekstra, A. Y. (2016). Four billion people facing severe water scarcity. Science Advances, 2(2). https://doi.org/10.1126/sciadv.1500323

Thiery, W., Lange, S., Rogelj, J., Schleussner, C. F., Gudmundsson, L., Seneviratne, S. I., Andrijevic, M., Frieler, K., Emanuel, K., Geiger, T., Bresch, D. N., Zhao, F., Willner, S. N., Büchner, M., Volkholz, J., Bauer, N., Chang, J., Ciais, P., Dury, M., … Wada, Y. (2021). Intergenerational inequities in exposure to climate extremes. Science, 374(6564), 158–160. https://doi.org/10.1126/science.abi7339

How to cite: Vanderkelen, I., Davin, É., Keune, J., Miralles, D. G., Wada, Y., Müller-Schmied, H., Gosling, S., Pokhrel, Y., Satoh, Y., Hanasaki, N., Burek, P., Ostberg, S., Grant, L., Taranu, S., Mengel, M., Volkholz, J., and Thiery, W.: Quantifying lifetime water scarcity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7949, https://doi.org/10.5194/egusphere-egu23-7949, 2023.

In many mountain regions, the cryosphere is a crucial component of water provision to downstream societies, as it contributes to dry-season flows and sustains diverse ecosystems. However, many of the world’s glacierized watersheds experience far-reaching changes at accelerated pace due to declining glaciers and snowpack, climate change impacts and socioeconomic development in the non-cryospheric parts of the catchment. The implications for downstream water supply are therefore manifold and complex. Coupled effects of reduced and less reliable water availability, changes in water quality, and growing water demand exert increasing pressure on water resources and threaten future water security and management.

We argue that the limited understanding of interactions between the cryosphere, glacial and non-glacial water stores, river runoff and people hamper climate change adaptation and long-term water security. Meaningful assessments of mountain water security require therefore a holistic social-ecological perspective that interlinks the wider catchment hydrology considering both, surface and subsurface stores, and people including human water demand with improved data and process understanding. Water security assessments can then be guided by a fully coupled hydrological risk framework. This approach needs to integrate multiple social-ecological vulnerabilities as well as the degree of exposure to water shortage under a variety of possible future scenarios of glacier shrinkage, catchment alteration and socioeconomic development. Essentially, this requires a thorough understanding of interrelated upstream-downstream systems and the spatiotemporal propagation of meltwater through the terrestrial water cycle.

Improved data and more diverse knowledge collection that point to the missing links in the terrestrial water cycle are a priority. Multiple sources of knowledge should be co-produced and integrated into a collaborative science-policy-community framework, ideally from the early stages of research planning with attention to local practices and governance. This approach can support a wide set of incremental and transformational strategies that guide robust, locally tailored and effective adaptation pathways. These may include, among other, exploring catchment-specific benefits of nature-based solutions to increase the buffer function of wider catchment hydrology against water loss from glacier shrinkage to enhance long-term water security.

How to cite: Drenkhan, F., Buytaert, W., Mackay, J. D., Barrand, N. E., Hannah, D. M., and Huggel, C.: Managing complex social-hydrological systems for water security: the case of the mountain cryosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7977, https://doi.org/10.5194/egusphere-egu23-7977, 2023.

Panta Rhei was launched in 2013 with the purpose of reaching “an improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems.” When the idea of Panta Rhei was conceived socio-hydrology was still in its infancy and global warming was about 0.3 degree centigrade lower than today. The subsequent evolution of the research agenda and environmental change proved that Panta Rhei was a brilliant intuition. By building on the IAHS history and legacy, the idea of Panta Rhei catalysed the feeling that change in hydrology and society was an emerging reason of concern and therefore a fascinating field of research. Panta Rhei achieved a major target: by putting together an interdisciplinary community of researchers – mostly early career ones – it set the theoretical basis for an improved understanding of the complex interaction between water and humans. On the other hand, challenging research questions are still unresolved. I had the fortune of chairing the scientific consultation that led to shaping Panta Rhei. I also had the privilege of attending several phases of the Panta Rhei adventure. With this presentation I would like to offer my perspective on the fascinating interplay between water and humans and the achievements and future evolution of Panta Rhei.

How to cite: Montanari, A.: Everything still flows: achievements and future evolution of Panta Rhei, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8104, https://doi.org/10.5194/egusphere-egu23-8104, 2023.

During the past years, the county of Kitui in Kenya, has experienced severe droughts. Both the short rain season, in March, April and May and the long rain season, in October, November and December have failed for several years in a row. This has had devastating impacts, leading to widespread water and food insecurity. According to local people, the rain seasons have changed over the past years, thereby increasing drought risk. At the same time, flash floods, destroying farmland and water infrastructure are reported to have increased as well. We investigate whether drought and flood risk in Kitui, Kenya, have increased over the past years and what the role of climate, hydrology and humans is in this increase. In addition, we investigate whether droughts are influencing flood risk and vice versa.

How to cite: Barendrecht, M. H., Weesie, R. V., Busker, T. S., Matanó, A., Mazzoleni, M., and van Loon, A. F.: Drought and flood risk in Kitui, Kenya: are they increasing and why?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8612, https://doi.org/10.5194/egusphere-egu23-8612, 2023.

The World’s water resources are under severe pressure as a result of unsustainable exploitation and rapidly changing hydroclimatic conditions. In the National Geographic World Water Map project, we combine state of the art hydrological modelling expertise, with storytelling expertise from National Geographic. The World Water Map aims to shed new light on water problems in the world.

In this project we identify 17 hotspots of water scarcity based on state-of-the-art large-scale hydrological modelling results. For the so called “hotspots” we analyze which policies, regulations and climatic changes have resulted in the development of these areas under pressure. We do this by using a literature study of over 175 scientific publications, which helps to identify the drivers and pressure as well as their impact and response for each hotspot. This information is then all included in the online Water Map that provides the general public, policy makers and peers in science with this information. The map consists of an interactive web portal where we tell the untold stories of water scarcity, support water scarcity literacy so that people understand the problems surrounding water scarcity, and provide an interactive platform where people can identify the vulnerability of their local neighbourhoods.

By combining science and storytelling we can shed light on “hotspots” as well as provide the untold stories in these regions. Together with the local and national policymakers we aim to provide much needed open information on pathways forward and future outlooks for “hotspots” around the world.

How to cite: Wanders, N., Leijnse, M., Droppers, B., van Jaarsveld, B., Hoch, J., Götte, J., and Bierkens, M.: The World Water Map of water scarcity hotspots, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9040, https://doi.org/10.5194/egusphere-egu23-9040, 2023.

The analysis of the factors driving the exploitation of drinking-water sources is fundamental in the modelling and planning of water supply systems. To this end, it is important to assess the impacts of water scarcity, related to periods of hydrological drought, on the use of the available sources. This is of particular interest in touristic regions, where resource management must necessarily take into account also the significant seasonal fluctuation of urban demand.

As part of the European project SIMTWIST (Simulating Tourism Water Consumption with Stakeholders), the study analyses the factors influencing both the demand for drinking-water supply of the city of Rimini and the apportionment of the supply among the different sources available to the water manager (RomagnaAcque-Società delle Fonti SpA). In fact, the city is supplied with both surface water, from the Ridracoli reservoir in the Apennines, and groundwater from well fields on the alluvial fans of the Marecchia and Conca rivers.

The drivers include socio-economic variables (tourist attendance), climatic variables and hydrological availability. In particular, it is analysed how the exploitation of the groundwater source varies as a function of water availability at the Ridracoli reservoir, characterizing such availability through meteorological and hydrological drought indices computed on the upstream catchments.

The analysis, in addition to confirming how the management of the resource cannot, in Mediterranean regions, disregard tourism factors, helps to understand the link between hydrological droughts, governing the availability of river-fed reservoir supply, and the choices made by water managers in the exploitation of the groundwater sources.

How to cite: Toth, E. and Neri, M.: Drinking-water supply sources and hydrological droughts: influence of tourism demand and reservoir availability on groundwater exploitation for the Rimini case study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9402, https://doi.org/10.5194/egusphere-egu23-9402, 2023.

Floodplain urbanization is accelerating at an alarming rate in recent decades, which has posed grand challenges to flood risk management. Hydraulic engineering infrastructure is often co-developed alongside this acceleration to mitigate flood risks, but to what extent this co-development matches up with the floodplain urbanization rate needs to be better quantified. In this study, we leverage a range of multi-source geospatial datasets including high-resolution floodplain maps, urban impervious area maps, global dam/reservoir datasets, and flood fatality data from the Emergency Events Database (EM-DAT) to assess the dynamics of floodplain urbanization (1985–2015) and its interplay with hydraulic engineering development at the global scale. We will report our assessments at both the basin level and the country level to promote the understanding of the hydroclimatic and socioeconomic contexts of floodplain urbanization. Ultimately, results from this study are expected to inform the prioritized regions for flood risk mitigation.

How to cite: Lin, P., Gao, S., Zeng, Z., Wang, J., Zheng, K., Yin, Z., Yuan, Z., Huang, Z., Zhou, X., and Lei, X.: The dynamics of floodplain urbanization and hydraulic engineering development, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11579, https://doi.org/10.5194/egusphere-egu23-11579, 2023.

The Benford’s Law, outlined in 1938, estimates the expected frequency of the significant first or first two digits of a time series of a generic variable based on a logarithmic pattern. Lower digits (i.e., 1, 2…) are expected to occur with frequencies higher than those associated to numbers with higher first digits (i.e., 8, 9). According to this law digit 1 typically occurs about 30% of the time, while 9 appears as significant first digit in less than 5% of the cases. The validity of Benford’s Law has been proven for a wide variety of data sets and in different contexts (e.g., public elections, false accounting detection, street addresses, stock and house prices, population numbers), among which few of hydrological relevance: lengths of rivers, river flow series, lake and wetlands extents. Nonconformity of hydrologic data sets to Benford’s Law could be a consequence of time series alteration and thus a signal of the presence of biases or errors, data modification, as well as of the fact that the sample is not fully representative of the variable or the series is affected by external drivers (e.g. anthropic alteration of the natural dynamics).

In this work we referred to more than 1200 GRDC sites to test the Benford’s Law validity over stream flow series longer than 40 years, as well as on the longest stream flow series (more than 12 million of data). Streamflow records have been investigated in parallel to other hydrological relevant datasets that serve as proxy for quantifying the potential human impact (e.g., GRanD-Global Reservoir and Dam Database, FFRs-Free Flowing Rivers). Results of this study, together with those of previous investigations (Nigrini and Miller, 2007) advocate that large hydrological data set should conform the Benford’s Law. On the contrary, the nonconformity to it might highlight data integrity and authenticity issue, or reveal alterations of the natural variability due to human activities or other driving factors (perhaps climate change).

How to cite: Domeneghetti, A., Caroscio, L., and Ceola, S.: Potential applications of the Benford’s Law for the investigation of hydrological time series alteration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11797, https://doi.org/10.5194/egusphere-egu23-11797, 2023.

１．introduction

During Japan's period of rapid economic growth, water pollution became a problem throughout the country, but water quality has improved rapidly thanks to the enactment of laws and the heightened environmental awareness of society as a whole. However, even now, not only is the concentration concentrated in Tokyo, but urbanization is also progressing in rural areas, and there are still areas with severe water pollution in the suburbs. What used to be point source pollution has spread to non-point source pollution. Due to problems with wastewater treatment facilities in mountainous areas, many large river basins are more polluted upstream than downstream. The results of the ``Survey of the Water Environment in Public Water Areas,'' which has been continued by the government since 1971, and the ``National Simultaneous Survey of Familiar Water Environments,'' which was started in 2004 by citizens' groups, are available on a nationwide scale. I have mainly studied long-term changes in river water quality in Japan. We will also consider the results of measurements by Hosei University in 2020 and 2021.

２．Results and considerations

１）Water quality survey results for public water areas

There were about 1,000 observation points in 1971, but 15 years later, in 1986, the number exceeded 5,000, and since then observations have continued at just under 6,000 points. In 1971, half of the BOD values were 3 or more, but in 1976 half were 2 or less, and recently, 2 or less accounted for about 80% (2018). The number of points with 1 to 4 remained unchanged, but 4 or more decreased, and 1 or less increased to about half of the total.

２）Nationwide Simultaneous Survey of Familiar Water Environment

In 2004, when the survey began, there were about 2,500 sites, but in 2005 there were about 5,000 sites, and after that, although it remained around 6,000 sites, it reached about 7,000 sites in 2018. COD4 or less is about half.

３．conclusion

In addition to the nationwide long-term observation results, data from before 1971 were collected and organized in an attempt to reconstruct past water quality. With regard to recent water quality, we independently conduct observations at more than 1,500 points nationwide every year to clarify the current situation. In addition to the coastal area in 2020, we were able to investigate the inland area in 2021 and the municipality unit in 2022. We would like to improve the accuracy while continuing the wide-area survey.

How to cite: Kodera, K., Oda, M., Igari, Y., and Morimoto, Y.: Study on long-term variation of river water quality in Japan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12379, https://doi.org/10.5194/egusphere-egu23-12379, 2023.

Science - policy - society Nexus is important in achieving Sustainable Development Goals (SDG). The current scientific knowledge is sufficient to allow us to implement the best of knowledge to cover the basic needs such as access to safe water and sanitation; however, the implementation rate is slow. Thus, this work looks at state-society relations in reaching SDGs 6.1. and 6.2. in Kazakhstan.

The survey asssessed available 176 water-related functions in the Government of Kazakhstan using the Integrated water resources  management tool-box. Additionaly, the questionnaire of about 1300 villagers was conducted in all the villages (which are 153 in total) of Atyrau region, Kazakhstan during September-November 2022, to assess the access to drinking water and sanitation services and the needs for improvement.

The findings show that in the “Policy” area the functions for adaptation to climate change are poorly expressed, especially climate resilient WASH systems; the role of customary law in the field of both the use of water resources and access to drinking water and sanitation is barely reflected in the legislation. In the "Organization" area there is a lack of functions in operation and monitoring of decentralized water supply and sanitation services; the organization of civil society is not formally expressed; training of water management specialists is not reflected as a responsibility.  In the field of using various tools of Integrated Water Resources Management, the weakest function of the government is communication with society and their reflection in public policy, in particular, the introduction of the concept of virtual water, water footprint, public awareness and education; economic instruments and effective demand management are little reflected in the functions of the state.

More than half of rural citizens use water from decentralized sources and mainly use pit latrines. The field survey has showed the high level of responsibility of the local villagers for decentralized sanitation and drinking water supply services, with high request to be educated on how to maintain those systems in a more sustainable way. It might be concluded that people do have relatively high rate of responsibility to maintain the water supply and sanitation systems. However, the policy and the govenmental functions do lack meeting these societal needs for education and, in a broder context, integrating people into water projects. "The science" or Reserchers could play an important role bridging State and Society to increase the feasibility of water and sanitation state-run programs. 

How to cite: Tussupova, K. and Zhupankhan, A.: Reaching SDGs 6.1 and 6.2 in Kazakhstan: State - society relations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12572, https://doi.org/10.5194/egusphere-egu23-12572, 2023.

Humans play a key role in the hydrological system, and their decisions influence the entire water system from tributary to river mouth. To fully comprehend how the human-natural water system evolves over space and time, and to investigate the systemic effects of climate change and human interventions, it is important to consider human behaviour and feedbacks to the hydrological system simultaneously at the local household- and large basin scales.

Therefore, we present GEB (Geographical, Environmental and Behavioural model); an agent-based model coupled to a fully distributed hydrological model that can simulate the behaviour and daily bi-directional interaction of more than 10 million individual farm households and reservoir operators with the hydrological system. Through this coupling, each individual farmer with unique characteristics and location can make daily decisions, such as irrigating their crops from surface-, reservoir-, or groundwater, planting and harvesting crops, investing in adaptation options (e.g., irrigation wells and sprinkler irrigation). All these decisions can be based on the available water in their environment, the status of their crops, their risk perception, crop price, water price, and weather conditions etc. Similarly, reservoir operators can regulate the availability of water for irrigation, and downstream releases of water based on the state of the hydrological system as well as communication with farmer agents.

GEB is dynamically linked with the spatially distributed hydrological model CWatM at 30’’ grid resolution (< 1km at the equator). Because many small-holder crop fields are much smaller, CWatM was specifically adapted to implement dynamically sized hydrological response units at field scale / sub-grid level, providing each agent with an independently operated hydrological environment.

While the model could be applied anywhere, we show an implementation with local and basin-wide feedbacks in the heavily managed Krishna basin in India, encompassing ~8% of India’s land area and ~12.1 million farmers. Here, we quantify bi-directional feedbacks such as the reservoir paradox and test various policies, such as providing subsidies for adaptation options (e.g., irrigation wells, sprinkler irrigation), and quantify effects on the hydrological system as well as downstream farmers.

In this implementation, GEB uses approximately 15 GB of RAM memory and can thus be used on an above average personal laptop. Computational requirements scale linearly with basin size, assuming similar farm-size distribution.

How to cite: de Bruijn, J., Smilovic, M., Burek, P., Guillaumot, L., Wada, Y., and Aerts, J.: GEB: A large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12680, https://doi.org/10.5194/egusphere-egu23-12680, 2023.

Flood risk is changing over time. Climate change, land-use change, human interventions and socio-economic developments have an influence on the evolution of flood risk. Thus, the future dynamics of drivers influencing hazard, exposure and vulnerability and consequently flood risk evolution is uncertain. Therefore, flood risk management is confronted with deep uncertainties and need to continuously adapt to future circumstances. New management strategies are required to ensure the safety level of humans and their assets and reduce losses from floods. Adaptive flood risk management is a way to cope with such uncertainties. However, the implementation of adaptive flood risk management requires a flood risk monitoring system that screens critical developments of hazard, exposure, or vulnerability and warns the user when a critical point in flood risk evolution is approached. In order to develop a conceptual framework for a flood risk monitoring system, we conducted a systematic review of flood risk evolution assessments. We analysed how flood risk is conceptualised, which factors are assessed to analyse evolutions in one or more risk component, which methods are used to assess flood risk evolution and which risk outcomes are identified. We discuss the main concepts of monitoring the spatiotemporal changes of the components of risks and how the changes of these components contribute to the evolution of risk. We furthermore discuss the data sources, issues of spatial and temporal scales, and how the components of risk coevolve.

How to cite: Rindsfüser, N., Zischg, A. P., and Keiler, M.: Monitoring flood risk evolution: A systematic review of flood risk evolution assessments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13384, https://doi.org/10.5194/egusphere-egu23-13384, 2023.

Water availability can be linked to a country's stability, internal security, and the occurrence of violence and governability, in the environmental change context. For instance, lack of access to water resources can trigger political conflicts, be used as a tool for political negotiation or attacks on water infrastructure can be used as a source of intimidation. The potential political risks associated with water availability take particular relevance at the scale of international and transboundary hydrological basins and under conditions of water-food scarcity or political instability. To date, although water risks occurring within the boundaries of the hydrological basin have been studied across several case studies in the literature, the issue of risks arising from water upwind-downwind dependency has been overlooked. For instance, precipitation in a hydrological basin or agricultural centre regions with a high dependency on terrestrial moisture recycling may originate in upwind terrestrial areas outside of the basin boundaries. Here we study geopolitical risk related to this water dependency by analizing terrestrial moisture recycling. Our analysis shows that some hydrological basins in Africa, Asia and South America present a high risk of experiencing geopolitical conflicts when there is a large extension of croplands, high moisture recycling dependency and their precipitationsheds extend over warmongering countries. Hence, our results indicate that addressing transboundary water security from a surface perspective can underlook potential geopolitical conflicts that may threaten regional water-food security and peace. These risks need special international attention to guarantee global peace and agricultural production.

How to cite: Posada-Marín, J. A., Salazar, J. F., Wang-Erlandsson, L., Rulli, M. C., and Jaramillo, F.: Geopolitical risk induced by terrestrial moisture supply to agricultural hotspots, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14419, https://doi.org/10.5194/egusphere-egu23-14419, 2023.

Disaster risks are the results of complex spatiotemporal interactions between risk components, impacts and societal response. In the context of the water supply chain, human processes have altered hydrological processes through the construction of reservoirs to dispose of the water resources with higher predictability and productivity. While reservoirs may attenuate flood events and help to bridge through period of water scarcity, they may also aggravate drought events in terms of duration and severity. The long-term effect associated to the presence of reservoirs is an over-reliance on the water supply hypothesized as constant and abundant as provided by the hydraulic structure, which in turn increases the vulnerability and the economic damage in case of a drought event occurrence. In addition, socio-economic and political changes should not be underestimated, as the social, economic, and political context can influence the impact and response to extreme events. Indeed, it has been observed that during long periods of drought, variations in exposure and in vulnerability have occurred, due to social dynamics taking place as a result of the extreme event, e.g. the natural migration of the population to water sources.
Here we aim at understanding the changes in risk components and the resulting impacts of structural measures, such as reservoirs, and also of nature based solutions in relation to consecutive extreme events. Different case studies around the world are considered to untangle the complexity of the dynamic relationship between human and hydrological processes.

How to cite: Ridolfi, E., Soncin, L., Matano, A., Russo, F., Napolitano, F., Di Baldassarre, G., and Van Loon, A.: Assessment of change in drought risk influenced by water management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15219, https://doi.org/10.5194/egusphere-egu23-15219, 2023.

Drought risk is modified through hazard, vulnerability and exposure, and exacerbated by management shortcomings. A quantitative understanding of the combined effects of these drivers is required to effectively lower risk. Yet, knowledge about the dynamics and effects of risk drivers over time and space and the human-natural feedbacks that steer them is largely lacking. In this study, we propose using GEB, the first large-scale coupled-agent based hydrological model that simulates all individual farmers at field scale, to systemically quantify the relations between dynamic hazard, vulnerability, exposure, management and drought risk over a multi-drought period in the Bhima basin, India. First, we parametrized the coupled hydrological model with meteorological and hydrological data to capture hydrological drought  conditions of different paired drought events. Next, we develop the agent based model part to simulate the drought management behavior of two million farmers and how they respond to drought events. To simulate this behavior, we applied the protection motivation theory, supplemented by theory of planned behavior, to describe farmer agent behavior. The parameters of these theories were parametrized with survey data of Indian farmers fitted to the statistical distribution of the two million Bhima basin farmers. To study the dynamic attribution of the three risk drivers, a Global Sensitivity Analysis of all factors was performed at consecutive time intervals, showing the interaction of drivers before and after each drought event, as well as between the two events. The results are expected to further the understanding of drought risk dynamics and what disaster risk reduction measures can optimally reduce impacts in the long term.

How to cite: Kalthof, M., De Bruijn, J., De Moel, H., Kreibich, H., and Aerts, J.: Dynamic risk modelling of a coupled human-drought system under multi-drought conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15238, https://doi.org/10.5194/egusphere-egu23-15238, 2023.

Drought is generally considered a slow process natural hazard. However, the faster onset and strength of recent events have received great attention. Climate change and human activities can both play a role in altering the characteristics of droughts, including their speed of development and intensity. Climate change can, for example, indirectly impact droughts by changing the amount and distribution of precipitation, while human activities, such as land management, can directly alter the water content of the soil. In this study, we run the JULES-W2 land surface model with the counterfactual stationary ISIMIP3a climate dataset, a hypothetical climate without climate change [1], and transient land use changes based on observations. We use soil moisture as a water deficit indicator and a framework for calculating the hydrological drought propagation speed [2] to define drought characteristics. We compare results against those calculated from historical runs with climate-related forcing based on observations (factual) to examine historical imposed long-term changes attributed to human-induced climate change. Our results show that climate change could significantly impact the speed of development and intensity of droughts. Some regions like Congo rainforest, Europe and the western US are simulated as hot spots of more fierce droughts, while others (e.g. East African mountains) may have faced milder droughts as a result of climate change. These changes can have important consequences for the productivity of agricultural lands, the health of ecosystems, and the availability of water for human use. Future climate change highlights the implications of faster droughts on risk management and challenges the research of drought hazard prediction.

[1] Mengel, M., et al. “ATTRICI v1.1 – counterfactual climate for impact attribution.” Geosci. Model Dev., 14, 5269–5284.

[2] WU, Jiefeng, et al. Hydrological drought instantaneous propagation speed based on the variable motion relationship of speed‐time process. Water Resources Research, 2018, 54.11: 9549-9565.

Acknowledgements: “Co-funded by the ERASMUS+ Programme of the European Union” (Contract number: 101004049 — EURECA-PRO — EAC-A02-2019 / EAC-A02-2019-1).

How to cite: Koutroulis, A., Grillakis, M., and Seiradakis, K.: Examining the contribution of human induced climate change on global drought characteristics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16540, https://doi.org/10.5194/egusphere-egu23-16540, 2023.

The coastal zone of northern Java experiences rapid land subsidence. Satellite-derived InSAR data and GPS had provided evidence  displaying the spatio-temporal rates of the subsidence. Interestingly, inhabitants do not always recognize this phenomenon. However, they do recognize that flooding from the sea (called ‘rob’) has changed from gift to disaster, viz. from shallow infrequent flooding that carry inshore fishes, to regular deep and widespread disastrous floods. In the Demak regency, more than 300 families have moved to locations further inland. In some locations rob flooding has caused a coastline retreat of up to 5kms.

Our initial Sentinel-2 analysis comparing 2016 and 2022 images have showed the change of ecosystem in the area. In addition to that, social surveys revealed timely change of the ecosystem and point places where coastlines have moved.

For this study, we use Sentinel-1 imagery for SAR coupled with tide data to determine the behavior of coastline change from 2018-2022. Sentinel-1 is selected due to the temporal resolution and performance in  all-weather. Ground Range Detected (GRD) of Sentinel-1, is single look complex data projected using an earth ellipsoid, will be used as main input in spatial analysis to observe shoreline condition. There are 4 types of polarization of GRD data: HH,VV, HH+HV and VV+HV. Polarization type will be tested and determined to get less noise images result. Image masking and pixel analysis will sequentially be conducted to segregate the land and the sea. The analysis will be managed in Sentinel Application Platform (SNAP).

Tide data plot from nearby station is used to assign at what phase Sentinel-1 imagery is acquired. Additional analysis from tide data plot is applied to predict land/inundation at important sites and when imagery is not available. 

The social research component of the study through preliminary survey data , our initial survey showed residents relocation had been started before the period covered by the SAR data sets. Hence, random purposive sampling will be used for a follow-up mixed-methods survey to gather more data on social and economic dynamics arising from the geomorphological shifts in coastline. 

Ultimately, we hope  our study will help unravel land subsidence and the resulting coastline retreat to provide a strong basis for mitigation and adaptation options by the people and the government.

How to cite: Budiyono, Y., Zahro, Q., Oktaviani, A., Riyalda, B. F., and Siriwardane-de Zoysa, R.: Land subsidence and coastal retreat as observed using Sentinel-1, tide dynamics, and socio-cultural survey of Sayung, Demak, Indonesia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16655, https://doi.org/10.5194/egusphere-egu23-16655, 2023.

In recent years, a great number of Somalis are involuntarily displaced within the country. However, we do not fully understand what and how climatic, environmental, and socio-political drivers push internally displaced persons (IDPs). Among several climatic drivers, what is statistically significant to internal displacement? Is the drought intensity alone a key driver of displacement? Are social network structures important in displacement decisions? To provide quantitative evidence, we developed a bootstrapping temporal exponential random graph model (bTERGM) for internal displacement decisions in Somalia. We used the Protection and Return Monitoring Network dataset with drought indices based on precipitation, temperature, and vegetation from the Somali Water and Land Information Management. We found that IDPs tend to consider both the intensity and successiveness of droughts based on precipitation, temperature, or vegetation. The Intensity of each component alone was not a significant driver for Somali IDPs. Local network structures were not very significant in the temporal model at the monthly scale, while previous displacement experience played a critical role in IDP movements. Our results help us better understand the displacement decision-making process so that policymakers can predict IDP movements and establish adequate policies.

How to cite: Oh, W. S., Rocha, J., and Levin, S.: Drought intensity and successiveness together displace populations in Somalia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17019, https://doi.org/10.5194/egusphere-egu23-17019, 2023.

The success of river restoration is a controversy subject depending on chosen reference conditions and stakeholder perspective. Therefore, the tool to assess the effectiveness of restoring physical conditions in riparian wetlands aims to be a comprehensible piece of evidence to policy-makers. The assessment is based on three hypotheses: (i) the restoration should have standard-based results; (ii) the restoration should respect principle-based results; (iii) the nature is more valuable without human pressures. Therefore, the multi-criteria methodology includes three categories of indicators: (i) to detect results compared to pre-restoration conditions as well as to historical conditions; (ii) to estimate the functionality of physical conditions compared to expert opinion; (iii) to analyze the naturalness of a river site. Each indicator is given a score compared to hypothetically successful effects of the restoration based on an earth scientist approach. The overall score allows to classify the effectiveness of river restoration on a five-class scale from very good to poor. The tool is validated for the Comana Marsh on a second order tributary of the Danube River in Romania. A small-size dam and a system of concrete dykes was built to recreate a marsh upstream, in the floodplain. According to the tool: (i) the effects (e.g., surface-water area, depth) were a success compared to pre-restoration conditions, yet they could not recreate the historical conditions; (ii) new processes (e.g., anastomosing river pattern) appear to be functional when compared to scientific expectations; (iii) the river site gained hybrid features (i.e., rewilding in the context of human pressures). The effectiveness of restoring the Comana Marsh was estimated as being good. The tool could be further developed by integrating other groups of indicators based on stakeholders’ perspective. Understanding the theoretical results of river restoration could help policy-makers to gain confidence and further finance this domain underdeveloped in Romania.    

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS - UEFISCDI, project number PN-III-P1-1.1-TE-2021-0600, within PNCDI III.

How to cite: Ioana-Toroimac, G., Moroșanu, G.-A., Șandor, I.-A., Stoica, C., and Constantin, D.-M.: Tool to assess the effectiveness of restoring physical conditions in riparian wetlands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1853, https://doi.org/10.5194/egusphere-egu23-1853, 2023.

Climate change alters the water cycle, which makes adaptation in water management necessary. The interdisciplinarily coordinated transdisciplinary project KlimaRhön aimed at developing adaptation strategies in water management in the UNESCO biosphere reserve Rhön in Central Germany. Experts agree that scientific and stakeholders’ knowledge should be involved to develop adaptation strategies, which requires good integration tools.

To identify adaptation strategies in the participatory process of the project KlimaRhön, we integrated the knowledge of hydrologists, sociologists and stakeholders while embracing uncertainty with a Bayesian Belief Network. For this, sociologists introduced that the acceptance of relevant actors is needed to implement adaptation measures and hydrologists introduced a range of potential future changes in groundwater recharge. In the first workshops of the participatory process, the stakeholders jointly identified possible adaptation measures. In the last workshops, we focused on two adaptation measures, which are 1) the protection of springs taking into account pasture water supply and 2) the fusion of small water suppliers in a region, and planned to find strategies to stimulate their implementation. For this, the stakeholders identified the relevant actors whose acceptance to implement those adaptation measures is needed. Then, the stakeholders identified and weighted factors that influence the acceptance of the relevant actors to implement the respective adaptation measure. This knowledge was then integrated in two Bayesian Belief Networks (for two adaptation measures) and a suitable communication of the Bayesian Belief Networks, which also focused on the communication of the embraced uncertainty, was developed. In the last workshop in the participatory process, the Bayesian Belief Networks were presented to the stakeholders and discussed. In the presentation, the stakeholders could explore which combinations of factors can enhance the acceptance of the relevant actors for the adaptation measure and thus the probability that they implement it for different degrees of climate change impacts.

The conditional probability tables for the Bayesian Networks were derived directly from the stakeholder weightings. Thus, stakeholders did not need to fill out conditional probability tables, which would have been difficult for most of them, and time-consuming. Bayesian Belief Networks show the uncertainty of possible future conditions through the many possible combinations of factors, which might have enhanced the understanding of stakeholders for the need of flexible adaptation strategies. The stakeholders appreciated the good overview of the many interdependencies and their influence on the acceptance of the relevant actors to implement the adaptation measure. In this contribution, we present our integration approach, the Bayesian Belief Networks, its communication as well as its evaluation by the stakeholders. 

How to cite: Müller, L. and Döll, P.: Transdisciplinary knowledge integration and embracing of uncertainty with Bayesian Belief Networks in water management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2094, https://doi.org/10.5194/egusphere-egu23-2094, 2023.

Hydrology research is regarded as vital for advancing human development and environmental conservation through improved hydrological process understanding and by devising solutions to address water management challenges. This is particularly acute in a time of global change and the need to find pathways to water sustainability.  Success for research in hydrology is often measured through quantitative research outputs, such as the number of journal publications, citation indices, number of students trained, patents, and external research funding. User involvement in the research and development process is rarely considered a metric for success in hydrology. Despite successful scientific or engineering advancements, a greater scientific understanding of hydrology and ever-increasing publications, much of the research has limited uptake by practitioners and implementation into practice, leading to a growing gap between research and practice.  This lack of utilisation is not due to a lack of need by users, but rather is a symptom of the disconnect between these advances and research that would most add value to practitioners and their application needs. We explore some outstanding challenges in translating academic research into practice and make some recommendations to bridge the increasing gaps between research and practice through a transdisciplinary approach, user engagement metrics in funded research and strong knowledge mobilization. We also discuss the success and challenges of these approaches in the Global Water Futures program along with lessons learned.  

How to cite: Pietroniro, A., Rokaya, P., Schuster-Wallace, C., and Pomeroy, J. W.: Translating hydrology research into practice: A Canadian Perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4485, https://doi.org/10.5194/egusphere-egu23-4485, 2023.

As the longest river in Asia, the Yangtze River has shown its impact on human societies with floods recorded since 12th century. In 1931, the Yangtze River has manifested its force again with one of the deadliest floods ever recorded in Chinese history, causing 422,499 deaths, damages to more than 25.2 million people and 58.7 billion m2 farmland. Similar flood occurred again in 1954, resulting in 31,762 deaths, damages to 18.9 million people and 31.7 billion m2 farmland. Researches have shown that 1954 flood being larger and higher compared to 1931 flood. However, it is still unclear for what reason that a more severe flood leading to less damage. Was it because of the change of policy and what can we learn from it? To answer this question, first, we constructed a conceptual framework of 1930s and 1950s agricultural society. Then, the flood inundation process of 1931 and 1954 floods was reconstructed with gauged rainfall dataset. After referring to the investigation report, the inundation information was applied to re-estimate the flood damage on farmland, houses, and residents under different scenarios. Furthermore, apart from traditional countermeasures, the effect of society transformation with floods were estimated using the potential crop production (PCP). Finally, an agent-based model (Farmer Landlord Inundation Production, FLIP) was constructed to simulate the agricultural transformation and its impact on residents’ response. The results have shown that traditional countermeasures were of certain effect. For example, the reinforcement of levees in 1950s was more effective in reducing inundation area of 8% compared to 1931, while the construction of detention basins accounted for 2%. However, with only traditional countermeasures failed to explain the relative success of agricultural product in 1954. Which, according to PCP result, the observed rice production was 12% higher than potential in 1954, while it was 29% lower in 1931. Here we assumed such difference could be ascribed to drastic society transformation in 1930s and 1950s (e.g., increase of absentee landlords in 1930s, land reform movement in 1950s). The effect of which was partially demonstrated with FLIP model, indicating an increase of crop production after eliminating landlords during floods. Our results demonstrate how society transformation are likely to affect the damage of and response to floods in a different (sometimes more important) way from traditional countermeasures in modern Chinese history. We anticipate our research to be a starting point towards deeper understanding of human and hazard, and the knowledge of which is likely to be applicable to many other regions and times.

How to cite: Liu, C., Kawasaki, A., and Shiroyama, T.: Flood protection in a changing society: a perspective from historical agriculture transformation during 1931 and 1954 floods in Yangtze River Basin, China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6794, https://doi.org/10.5194/egusphere-egu23-6794, 2023.

Project Background: The RadClim BSR project aims to establish the feasibility of developing a radar-based precipitation climatology in the Baltic Sea Region (BSR). The project involves partners in countries across the BSR including Sweden, Estonia and Poland. The status of radar data archiving, utility of the data, and any data harmonisation requirements across the partner countries and the BSR in general are being investigated. Partners in Sweden, Estonia and Poland are acting as country coordinators, reaching out to a large range of actors to thoroughly explore their needs pertaining to radar climatology, utilising a user needs survey (ongoing from early February-March 2023). Consultations with the national weather services in Germany and Finland, who have already undertaken steps in radar climatology development, are aiding in ensuring best practices are adhered to. This seed project has the intention of laying the framework for the full development of a radar-based precipitation climatology (datasets and visualisations) spanning the BSR, relevant for a large range of actors in the near future.

EGU poster: At EGU 2023, we will present the results of the user needs survey that was distributed to a wide range of relevant actors in the project partner countries of Sweden, Estonia and Poland. The surveys were translated into each countries official language before being distributed, to maximise participation and ensure all representatives who should offer their perspective could, regardless of English language capacity. Through to the end of the project in early 2024, the results from this survey will be analysed and summarised, to form the user needs assessment for a radar-based precipitation climatology across the BSR.

How to cite: Lowry, B., Hoy, A., and Hashemi, H.: RadClim BSR - Towards a Radar-based Precipitation Climatology for the Baltic Sea Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8725, https://doi.org/10.5194/egusphere-egu23-8725, 2023.

The last decades have seen unprecedented progress in ensemble hydro-meteorological modelling and forecasting on a range of temporal and spatial scales. Such progress also raises new challenges, especially with regards to connecting hydrology from global to local scales, as well as hydrological sciences research to operations. To discuss these challenges, the Joint Virtual Workshop "Connecting global to local hydrological modelling and forecasting: challenges and scientific advances” (29 June - 1 July 2021) was recently organized [*]. It brought together over one thousand people from around the world, including scientists, disaster managers and stakeholders operating at the local, national, continental and global scales. In this study, we summarise the state-of-the-art presented and discussed at the workshop. In particular, we provide an early career perspective on the insights and experiences shared during the workshop, highlighting recent advances and ongoing challenges in hydrological modelling and forecasting, as well as on the use of forecasts for decision-making from global to local scales. From the many topics covered during the workshop, which included hydrological model development (including Earth System modelling, machine learning applications and hybrid dynamic-statistical forecasting), skill assessment, uncertainty communication, forecasts for early action, co-production of services and incorporation of local knowledge, Earth Observations, and data assimilation, we focus on the contributions to science and operations from the hydrological forecasting community. Our analysis highlights the critical need to better connect hydrological services and impact models to societal needs and local decision-making through effective communication, capacity building and co-production. The core work of creating new methods and products and the move towards Earth System modelling need to be balanced by multidisciplinary collaborations that effectively bring tools to practice. We expect that research tackling these challenges will increase further in the next decade.

[*] Workshop organizers: European Centre for Medium-Range Weather Forecasts (ECMWF), the Copernicus Emergency Management (CEMS) and Climate Change (C3S) Services, the Hydrological Ensemble Prediction EXperiment (HEPEX), and the Global Flood Partnership (GFP)

How to cite: Dasgupta, A. and the Joint Virtual Workshop ECMWF-CEMS-C3S-HEPEX-GFP Team: Progress and perspectives in hydrological modelling and forecasting across scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11221, https://doi.org/10.5194/egusphere-egu23-11221, 2023.

The management of water resources, their allocation and use is mainly directed by the policy at the strategic scale. In that way, the different sector interests can be coordinated, as well as principles of sustainable water use and goals of environmental conservation can be ensured. However, even the decision making at the strategic scale (i.e. at the level of the entire country) requires reliable information that provides sufficient support for decision makers in planning the further use of water resources. Accordingly, at the initiative of the decision maker (Ministry of the Environment and Spatial Planning of the Republic of Slovenia) the researchers at the Institute for Water of the Republic of Slovenia have developed a decision support system for water availability estimation in Slovenia. A multi-criteria approach was used, combining scientific approach in estimating the available water amounts (discharge in ungauged locations) and coordinated approach in setting the criteria, indicating the vulnerability of the environment according to specific locations and the attractiveness of that locations in terms of water use. The scientific aspect was used for the establishment of the methodology for the estimation of discharge in ungauged locations. Different machine learning and data mining techniques were tested, however Top kriging (Skøien et al., 2006) method was selected as the most accurate for assessment of the discharge across the country’s catchments, larger than 10 km². Estimated characteristic discharges were then revised according to the environmental needs to evaluate the amounts of water available for further use. However, the selection of the criteria was performed through interdisciplinary collaboration with experts and decision makers from various fields. During settling of the selected criteria, the importance of cooperation was shown. Our initial list of the criteria was not sufficient, as some of the aspects were addressed differently or overlooked. It should also be taken into account that representatives of different fields determined the different importance of the included criteria.

Acknowledgement: The development of the decision-support system was financed by the Ministry of the Environment and Spatial Planning of the Republic of Slovenia through the Institute’s annual work programme for years 2020 – 2023.

How to cite: Šantl, S., Sevšek, M., and Zabret, K.: Decision-support system for water availability estimation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11305, https://doi.org/10.5194/egusphere-egu23-11305, 2023.

Climate change and drought have imposed tremendous pressure on water resources in most parts of the world. Therefore, addressing drought impacts on water resources and socioeconomic conditions has gained attention to develop mitigation and adaptation strategies. Many innovative and cutting-edge modeling systems set up by academic institutions are exclusively available to academics and are not accessible or used by practitioners or policymakers. These constraints are in particular relevant in data poor regions where decision making and drought management are hampered by a lack of drought information. Therefore, within OUTLAST project (Development of an Operational, mUlTi-sectoral globaL drought hAzard forecasting SysTem), we aim to develop and implement the first worldwide, multi-sectoral, and operational drought forecasting system for quantifying drought hazard in water supply, riverine and non-agricultural land ecosystems, rainfed and irrigated agriculture. The forecasts provided by OUTLAST can also support better drought management and therefore contribute to the achievement of several Sustainable Development Goals (SDGs) of the United Nations, particularly SDG1(no poverty), SDG2 (zero hunger), SDG6 (clean water and sanitation), SDG13 (climate action) and SDG15 (life on land). In cooperation with pilot users in the project regions of Lake Victoria (Burundi, Kenya, Rwanda, Tanzania, and Uganda) and West and Central Asia (e.g. Afghanistan, Armenia, Azerbaijan, Iran, Iraq, Lebanon, Oman, Syria, Tajikistan, Turkey, Uzbekistan), the value of global-scale forecasts released for the subsequent six months for data-poor and transboundary basins will be tested. Through co-design, relevant drought indicators will be defined and the web portal and pilot applications of these global forecasts for drought management and water governance will be developed. We also systematically investigate the predictive ability of global-scale drought forecasts based on bias-corrected seasonal ensemble weather forecasts, as well as the factors influencing the predictive skill in terms of (i) the type of drought (soil moisture and hydrological droughts) and the affected sector, (ii) the length of the forecast period, (iii) seasonal and regional differences in predictive quality. Two global-scale models (WaterGAP and GCWM) will be further developed to provide operational and monthly drought forecasts globally at 0.5-degree spatial resolution and for a six-month forecast period. The applicability of the data and models for drought forecasting will be rigorously examined for different locations, sectors, and periods using historical reanalysis data and historical ensemble forecasts. This will entail using historical meteorological "forecasts" to generate drought forecasts for historical drought events reported for these regions and validating them regionally. Finally, an automated operational modeling system will be created to download and process the necessary meteorological input data, calculate the drought indicators, visualize them appropriately, and transfer them to the Global Hydrological Status and Outlook System (HydroSOS) at World Meteorological Organization (WMO). Through a flexible implementation (cloud-based), we will enable a potential transfer of the forecast system to different users. The use of the HydroSOS-portal of WMO to visualize project results and as an outlet of the drought forecast products will make optimal use of synergies and ensure high visibility and impact of the research performed in OUTLAST.

How to cite: Siebert, S., Abbasi, N., Cullmann, J., Döll, P., Trautmann, T., Köthe, H., Kunstmann, H., and Weber, J.: OUTLAST - Development of an operational, multi-sectoral global drought hazard forecasting system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11755, https://doi.org/10.5194/egusphere-egu23-11755, 2023.

The merits of open science for hydrology are firmly established, widely embedded into research culture, and increasingly adopted within operational agencies. In the UK, it is common practice now for data collected by, and/or funded by, public bodies to be made available openly, licensed for both commercial and non-commercial use, and accessible via data portals and APIs. However, these same standards are not routinely applied to the methods and models used to evaluate flood risk.

This work, part of the UK’s community-led 25-year Flood Hydrology Roadmap, considered the potential role of open methods within UK operational practice. A review of the relevant literature was used to establish a definition and framework for open methods, which was refined based on consultation with practitioners. The framework was used to assess the current levels of ‘openness’ across UK practice, placing this in the context of challenges including governance, funding, and development histories. The study also considered international case studies of where open methods have been successfully implemented for hydrology and in other fields.

The review was used to develop an aspirational vision for the future operational use of open methods in UK flood hydrology, identifying key barriers and recommendations to manage and overcome them. Working with artists, creative provocations have been created to further the conversation, both within hydrology and along the subsequent links in the flood risk modelling chain. The review recommendations will be summarised as considerations relevant to both researchers and practitioners.

How to cite: Skinner, C. and Faulkner, D.: Open Methods in Operational Flood Hydrology – Considerations for researchers and practitioners, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11975, https://doi.org/10.5194/egusphere-egu23-11975, 2023.

Water related extreme events are causing most of the disasters worldwide. Between 2001 and 2018 around 74% disasters were water-related and during the past 20 years, the total number of deaths caused only by floods and droughts exceeded 166,000, while floods and droughts affected over three billion people, and caused total economic damage of almost US$700 billion (EM-DAT, 2019). The number of events with water related extremes are expected to increase due to climatic and land use changes.

Thus, it is of utmost importance to identify ways to reduce water related risks. Potential hazards, exposure and vulnerability have to be identified, published and communicated. This is done for example in the European Union in a coordinated way, based on the European Flood Risk Management Directive. However, identifying risk only is not leading to actual actions and is not  sufficient to reduce risks. This became again obvious in 2021 when extreme floods caused more than 180 deaths in Germany and caused around 46 billion Euro damage. This and other events are revealing the need for closing the gap between theory and practise to establish proactive and preventive strategies and implementation of measures.

Ghana is one of the countries most prone to floods in West Africa. Its annual occurrence often leads to disasters that are mostly felt by the urban poor. Despite the existence of salient activities conducted in order to reduce the flood risk in Ghana, there are still persisting challenges (Almoradie et al. 2020).

In order to overcome the implementation gap from science to practice a participatory and transdisciplinary mixed-method approach for Ghana is pursuied. Transdisciplinary research integrates knowledge from various scientific disciplines and non-academic actors.In this way, results can be developed for challenges that are of use to society and science.In the long term, transdisciplinary research strengthens knowledge about the human-water/flood system, the desired state of this system and the way to achieve this state by transformative adaptation.

A participatory mixed-method approach comprising hydrological and hydrodynamic modelling, participatory mapping, questionnaires, workshops, focus group discussion, system dynamic modelling and the analysis of vulnerability including failure of critical infrastrcuture were employed (Evers et al. 2021) for three case study areas in Ghana. The dynamics of human-flood-interaction are identified together with practioneers and adaptation measures were identified in a participatory way. By this approach we are aiming to make our research actionable and to design and implement knowledge translation mechanisms.

Almoradie, A.*, de Brito, M.M.*Evers, M., Bossa, A., Lumor, M., Norman, C., Yacouba, Y., Hounkpe, J. (2020) Current flood risk management practices in Ghana: gaps and opportunities for improving resilience. International Journal of Flood Risk Management, doi:10.1111/jfr3.12664.

Evers, M., Almoradie, A., de Brito, M. M., Höllermann, B., Ntajal, J., Lumor, M., Bossa, A., Norman, C., Yira Yacouba, Y. Y.,J. H. Jean Hounkpe (2021): Flood risk management in Ghana: gaps, opportunities, and socio-technical tools for improving resilience, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12683, doi:/10.5194/egusphere-egu21-12683

How to cite: Evers, M., Almoradie, A., Ntajal, J., Höllermann, B., Johann, G., Meyer, H., Schüttrumpf, A., Kruse, S., Ziga-Abortta, F., Bachmann, D., Schotten, R., Lumor, M., Norman, C., and Adjei, K.: Pro-active flood risk managment using a transdisciplinary multi-method-approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11980, https://doi.org/10.5194/egusphere-egu23-11980, 2023.

Most existing climate impact assessments in Nepal only consider a limited number of generic climate indices such as means. Few studies have explored climate extremes and their sectoral implications, which in turn are key for informing policy and practice. This study evaluates future scenarios of extreme climate indices from the list of the Expert Team on Sector-specific Climate Indices (ET-SCI) and their sectoral implications in the Karnali Basin in western Nepal. First, future projections of 26 climate indices relevant to six climate-sensitive sectors in Karnali are made for the near (2021–2045), mid (2046–2070), and far (2071–2095) future for low- and high-emission scenarios (RCP4.5 and RCP8.5, respectively) using bias-corrected ensembles of 19 regional climate models from the COordinated Regional Downscaling EXperiment for South Asia (CORDEX-SA). Second, a qualitative analysis based on expert interviews and a literature review on the impact of the projected climate extremes on the climate-sensitive sectors is undertaken. We also used widely available global data sets such as DesInventar and national census data and disaster-specific mixed-effects regression models to assess the impact of precipitation extremes on landslide and flood mortality.  Both the temperature and precipitation patterns are projected to deviate significantly from the historical reference already from the near future with increased occurrences of extreme events. Results show winter in the highlands is expected to become warmer and dryer. The hot and wet tropical summer in the lowlands will become hotter with longer warm spells and fewer cold days. Low-intensity precipitation events will decline, but the magnitude and frequency of extreme precipitation events will increase. Furthermore, an increase in one standardized unit in maximum one-day precipitation increases flood mortality by 33%, and heavy rain days increase landslide mortality by 45%.

How to cite: Bharati, L. and Chapagain, D.: Policy and practice relevant climate change impact assessments: Case study, Western Nepal, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13241, https://doi.org/10.5194/egusphere-egu23-13241, 2023.

Over a five year period, a systemic approach to water and climate solutions refer to as social innovation was developed in the framework of the AfriAlliance project. The approach recognised the need to combine five aspects for increased relevance and synergies for the water and climate science, policy and practices. The above mentioned aspects included technological solutions, governance structures, capacity development, a business roadmap and knowledge brokerage events. This manuscript documents lessons learned from the fifteen knowledge brokerage events held across the African Continent.  These events provided a platform to 1060 participants who came across 125 innovations. Policy makers, funders, utility operators, scientists, non-governmental organisations, river’s authorities and organisations, entrepreneurs and practioners were represented. The AfriAlliance knowledge brokerage events covered all the 5 African sub-regions. These events were designed and implemented in an innovative way providing participants ample opportunity to network and engage with innovators after their pitch presentations. Specialised and high-level panels provided policy makers, funders and international cooperating partners an opportunity to share their perspectives with innovators and the audience. Policy makers recurrently indicated the need to align water and climate innovations and solutions to existing priorities and frameworks. Funders and international cooperating partners highlighted the limited capacity from innovators in terms of scalability and access to funding. These events also brought up the difficulty of always getting the right audience especially when the knowledge brokerage event took place in the framework of specialized conferences. The Covid-19 pandemic introduced also an additional layer of complexity and required some adaptation to the face to face set-up that was initially designed. Hence two out of the fifteen events took place online. The virtual setup appeared to reach a broader geographical audience but the interactions were not as effective as those organised in person.  These events have shown a considerable potential to bring together scientists, policy makers and practioners in order to match topical solution providers and the users. On the other hand, these kind of knowledge brokerage events remain project dependent and adhoc in nature for one to expect some long-term impact.

How to cite: Kileshye Onema, J.-M., wehn, U., Tlhagale, M., Sossou, S., and Quayle, T.: Optimisation of the water and climate science, policy and practice nexus: Insights from the AfriAlliance knowledge brokerage events., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13956, https://doi.org/10.5194/egusphere-egu23-13956, 2023.

The Cooperative Institute for Research to Operations in Hydrology (CIROH) is a consortium of 28 institutions to advance the National Oceanic and Atmospheric Administration’s (NOAA) science and services capabilities to provide actionable water resources intelligence. CIROH’s research aims to improve water prediction and supports four broad themes: (1) water resources prediction capabilities; (2) community water resources modeling; (3) hydroinformatics; and (4) application of social, economic and behavioral science to water resources prediction. CIROH outcomes will inform hydrological process understanding, operational forecasting techniques and workflows, community engagement in water modeling, open-source software development, translation of forecasts to actionable products, and use of predictions in decision making.

This presentation will focus on CIROH’s research in community water modelling. In this theme, CIROH research focuses on advancing the predictive capabilities of the next-generation National Water Resources Modeling framework (NextGen framework) that is being developed for operational large-domain water prediction at NOAA’s National Water Center (NWC). The presentation will give examples of ongoing CIROH model development efforts to (1) integrate physical process representations into the NextGen framework across multiple levels of process granularity; (2) assess accuracy-efficiency trade-offs in the numerical solution of model equations across large spatial domains; (3) coupling process components that have hitherto been neglected in large-domain terrestrial system models (e.g., glacier hydrology, snow redistribution, connectivity of wetlands, land-atmosphere interactions over sparse forests, tile drainage, etc.); and (4) use hybrid machine learning methods to advance large-domain parameter estimation capabilities. The presentation will also highlight the establishment of research enabling infrastructure to support CIROH’s ongoing modeling advancement efforts. In summary, we will identify major challenges encountered and the high-priority research that is needed to advance capabilities in large-domain hydrologic prediction.

How to cite: Burian, S., Clark, M., Shen, C., Spiteri, R., Halgren, J., Patel, A., van Beusekom, A., Cohen, S., and Ogden, F.: Advancing community water resources modeling in the Cooperative Institute for Research to Operations in Hydrology (CIROH), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16702, https://doi.org/10.5194/egusphere-egu23-16702, 2023.

Effective natural resources management, especially of wetlands, are vital for the sustainability of livelihoods. This is further buttressed in Southern Africa where competing uses and users are increasingly putting pressure on these finite resources. The Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) with financial support from the African Union and the European Commission in the framework of the GMES programme endeavoured to develop a geoportal tool for effective wetland Management through a project called Wetland Monitoring and Assessment Service for Transboundary Basins in Southern Africa (WeMAST). WeMAST has an emphasis on capacity building and awareness raising for wetland assessment and monitoring in the following four transboundary river basins (Cuvelai, Okavango, Limpopo and Zambezi) across the SADC region. The WeMAST geoportal, developed during phase one, provides hydro-meteorological and physiographic attributes assessment and monitoring of wetlands. These include the spatial and temporal extent and status of wetlands, land cover and uses dynamics, flooding, vulnerability and fire indices. For the second phase, WeMAST puts emphasis on developmental impact on the ground hence some deliberate efforts are in place in order to enhance synergies between the scientists behind the concepts, the users, private sector and local communities on the ground as well as policy makers with the overall responsibilities of guiding the implementations of developmental pathways. In Phase II, policy and decision makers in the target countries (Angola, Botswana, Namibia, South Africa, Zambia and Zimbabwe) need to support upscaling and operationalization of the WeMAST geoportal.  As a result, the project consortium has now been designed in order to foster more interactions between stakeholders involved in wetland management through knowledge brokerage events where the geoportal tool, its products and services are disseminated, tested and validated to a great extent. Similarly an interface with policy makers has been established within the consortium through WaterNet via the Water Resources Technical Committee (WRTC) in order to appraise and involve SADC ministers in charge of water and natural resources management twice annually. The innovative and well-crafted approach of the WeMAST project under GMES offers a considerable room for enhanced synergies between policy makers, Scientists, the private sector and practioners for sustainable and effective wetland Management in the SADC region.

How to cite: Nyatoro, D. T., Onema, J.-M. K., Tacheba, B., and Olwoch, J.: Enhancing the science-policy-practice nexus for effective and sustainable wetland Management in Southern Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17248, https://doi.org/10.5194/egusphere-egu23-17248, 2023.

Recent developments in hydrologic science include a strong focus on open-source data sets and modeling tools. These developments can easily be leveraged into hydrologic education in the form of classroom exercises and term projects. Here we present a computational exercise designed to teach the concept of model structure uncertainty to students, using a specific selection of two catchments and two simple conceptual models from open-source data and tools.

The exercise first familiarizes the students with the modeling tool they will use and then has them calibrate and evaluate model performance on each combination of model and catchment. For these specific catchment and models, model structure uncertainty is the dominant source of uncertainty (compared to data, parameter and objective function uncertainties). The exercise includes guiding questions that help the students reach the defined learning goals. Trials at the Technische Universität Dresden show that the exercises are effective in doing so. This introduction to open-source models and data yields the benefit of being easily expanded on during further exercises and term projects.

How to cite: Knoben, W. and Spieler, D.: An example of using open-source data and hydrology models for classroom exercises and term projects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2675, https://doi.org/10.5194/egusphere-egu23-2675, 2023.

Public and private organizations and institutions distribute a large volume of Open Data on a continuous basis with aim of increasing efficiency, saving time or reducing costs. Technological advancement offers easy access to open datasets that have potentially added value as educational resources in teaching and learning processes. Open Data provides the educational community with learning experiences related to real world problems and allows students to engage with activities normally undertaken by professionals, without increasing the level of difficulty. In this study, we designed an educational intervention that uses open data from the Institute of Marine Biological Resources and Inland Waters, and we investigated how it can be integrated into the Greek secondary school curriculum. The results suggest that this open data-based practice has increased students’ motivation and has had an impact on selfbeliefs on topics of aquatic environments as well as an impact on students’ perception of the importance of aquatic environmental problems in rivers and lakes. 

How to cite: Tziortzioti, C., Dimitriou, E., and Mavrommati, I.: Introducing the use of Open Data into the secondary education: A study on inland water quality, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2741, https://doi.org/10.5194/egusphere-egu23-2741, 2023.

Precipitation is one of the essential parts of the hydrological cycle. Regardless of the important role that precipitation plays for life on Earth, in extreme conditions, such as high intensities and amounts, it can negatively affect various ecosystem services (e.g., flood protection, agriculture). Precipitation is spatially highly variable. Traditionally, precipitation, with rain as the most common type, is measured over very small surface areas (of a few square decimetres) by rain gauges or sensors. However, reliable and representative rainfall data are crucial for understanding the interconnection of different parts of the hydrological cycle (e.g., rainfall interception by vegetation, rainfall erosivity) and quantification of flood, drought, water quality, and other water-related problems. Reducing the negative consequences of the mentioned problems is part of the 2030 Agenda sustainable development goals. Therefore, an interdisciplinary student project on the design and construction of a rainfall simulator was submitted to the University of Ljubljana's call for sustainable development student projects. Rainfall simulators are recognized as important tools for studying the effects of rain on soil. Rainfall simulators can be used in controlled conditions in the laboratory or with additional settings also in the field. The design and construction of the simulator is entirely within the domain of the project team of six students of environmental civil engineering and electrical engineering. This includes the choice of pipe materials, pump capacity, size and type of spray nozzles, development of a control system for monitoring and recording of results, and, last but not least, the determination of rain properties we would like to simulate (e.g., intensity). Three pedagogical mentors and one mentor outside the academia supervise the project. With such a project, group work and co-creation are encouraged among students, theoretical knowledge acquired within the curriculum is transferred into practice and knowledge is exchanged between different disciplines. Skills such as communication, critical thinking, organization of tasks and time management, interdisciplinary problem solving, analytical reasoning, information and technology literacy, are developed in the project. Additionally, such equipment will be used for teaching and research purposes in the future, which is another sustainable feature of this project.

How to cite: Klun, M., Lebar, K., Zabret, K., and Zdešar, A.: Design and construction of a rainfall simulator: an interdisciplinary student project towards sustainable development goals achievement, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5020, https://doi.org/10.5194/egusphere-egu23-5020, 2023.

Active learning strategies such as simulations or problem sets have been shown again and again to be critically useful for helping students understand complex concepts. Students develop a more thorough understanding of processes or problem solving strategies when they are able to practice or explore them with hands-on activities. In hydrology, however, there are several concepts taught, even in introductory classes, where developing suitable activities for this type of learning is difficult. For example, even a simple water balance activity often requires a relatively thorough understanding of spreadsheets or a lot of tedious hand-calculations if students are going to explore relationships between multiple inputs and outputs. Similarly, even the most basic discussion of how a simple box model works is difficult to supplement with an activity that doesn’t involve spreadsheets or writing computer code. Furthermore, it is often beyond the scope of introductory level hydrology classes to teach programming or spreadsheet skills, and hand calculations often take a prohibitive amount of time. Web applications offer a tool to address some of these issues. With the development of tools like Shiny apps for R or Python, instructors with programming experience can relatively easily create interactive learning tools for their classes. Many studies in fields such as statistics and mathematics have shown that these web-apps aid in student learning. Furthermore, hosting and sharing these apps is becoming more accessible, with organizations like CUAHSI running shiny servers. In this presentation, I will show two examples of implementations of a web app to aid in student learning, one on the concept of a water balance, and one on running and parameterizing a basic catchment hydrology model. I will also discuss tools and strategies for building and hosting your own shiny app to address the learning goals for your classes.

How to cite: Gannon, J.: Web-apps as active learning tools in hydrology classrooms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8427, https://doi.org/10.5194/egusphere-egu23-8427, 2023.

Resource use decisions in the extractive resource industry in Canada are supported in various ways by collection and analysis of water resources data.  Data quality assurance and analysis are influenced by the methods taught in academic training, the tools used to teach and practice, and industry standards and culture.  The growth in popularity of computer programming languages such as Matlab, Python, and R, and new web-based collaboration and publishing tools from Project Jupyter (Notebook, Book) have created opportunities for teaching applied hydrology in new ways that can support the evolving nature of data in hydrology practice, namely in treating open-ended problems more typical to industry practice.

The abrupt shift to web-based instruction at the undergraduate level in 2019 spurred development of interactive instructional content in an applied hydrology course at the University of British Columbia, in Vancouver, Canada.  Using the open-source Jupyter Book software framework, we developed open-access course material to complement the hydrology theory curriculum.  The new course content consists of a set of tutorials designed to give students a practical introduction to important components of engineering practice such as data quality assurance, and uncertainty in hydrological models.  The content is provided as an open-access online textbook with an embedded Python code interpreter.   With each successive cohort, the material has adapted to student feedback, namely in treating the types of open problems common in industry, and in the amount of programming experience required. 

How to cite: Kovacek, D. and Weijs, S.: Lessons from Adapting Applied Hydrology Instruction to Open Source Software Tools, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10592, https://doi.org/10.5194/egusphere-egu23-10592, 2023.

Open science is commonly associated with open access publications, and FAIR (findable, accessible, interoperable and reusable) data. Open source code is progressively being considered an essential component of open science, too. However, even if all these ingredients are available and openly accessible, it is often impossible to reproduce the graphs in a paper from the data and code provided. Which script was used on what part of the data to generate a given plot? Which version of a cited database was used, and what query to extract the presented data points? Moreover, even the basic steps of a scientific analysis, i.e. the derivation of mathematical equations, are often not traceable. Ever came across the famous “it follows that”, where, what follows, contains variables that were not present in the preceding equations?

Here I present part of a hydrology course based on a framework designed to address many of the above challenges. It is based on the open-source RENKU platform and deployed in a Jupyterhub instance at https://renkulab.io. RENKU enables the tracking of datasets and their versions, and records executions of code with their respective input and output files, producing a knowledge graph of the entire project and enabling the user to easily re-do all necessary steps to update relevant results whenever a data or code file is updated. RENKULAB uses the docker system to help reproduce the computational environment needed to re-execute the analysis. This greatly facilitates collaborative research and learning, as it removes the need for collaborators and students to recreate the computational environment in their local systems. Integration of GITLAB in RENKULAB facilitates student feedback and collaborative problem solving through issue tracking, where students can gain points by submitting meaningful issues and helping others.

The course also uses an open source package for mathematical derivations (ESSM, https://essm.readthedocs.org), which is based on the Python package Sympy, and facilitates clear definitions of variables including their dimensions and units, and dimensionally consistent fundamental equations. These can then be used to deduce derived equations by automatic solving of systems of equations for unknown variables, derivatives, integrations, and many other mathematical operations contained in Sympy. The package combines graphical depiction of equations, as seen in papers, with computational reproducibility of derivations and transparent re-use of equations in numerical code.

By employing Open Science approaches from the start, students become naturally accustomed to reproducible research and can use the skills they learn in any professional environments, as they are not bound to proprietary software that their future employers and collaborators may or may not have purchased licenses for.

How to cite: Schymanski, S.: The benefits of Open Science approaches when teaching hydrology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12489, https://doi.org/10.5194/egusphere-egu23-12489, 2023.

The UK’s 25-year Flood Hydrology Roadmap was published in 2022. The Roadmap was developed by the UK hydrology community to identify the areas of greatest need and to deliver actions across four themes: Ways of Working, Data, Methods, and Scientific Understanding. Ways of Working Action W5 aims to build the ‘skills, esteem and value’ of flood hydrology but this is currently not possible as there is no baseline available. To provide a baseline, a UK-wide survey of hydrologists and the users of hydrology was conducted.

The survey was designed after consultation with hydrologists working in academia, consultancies, and other authoritative bodies in the UK. The objective of the survey was to baseline the current number, skills, satisfaction, backgrounds, and diversity of hydrologists practicing in the UK. A further consideration was to understand how prepared hydrology is as a discipline for anticipated changes in methods and skill requirements. The survey covered both low and high flow hydrology, not just flood hydrology.

In this presentation, we will summarise the key results of the survey and highlight the implications for hydrology training, education, and teaching. Finally, we will share our recommendations, from the perspective of operational users of hydrology, for the future skills needs in hydrology.

How to cite: Skinner, C., Ockelford, A., King, A., Goodship, E., and Harfoot, H.: The UK Hydrology Skills and Satisfaction Survey, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12552, https://doi.org/10.5194/egusphere-egu23-12552, 2023.

The ubiquitous "field trips in geography" type courses often exclude students on the basis of mobility and flexibility, have a high travel footprint, and rely primarily on passive knowledge.  In the summer of 2022, we taught a master level geography course, Geosensing of the Environment for the first time at the Geography Institute at the University of Bern. The course was team taught by the institute field technician, the assistant and master student, and a researcher in hydrology. This course is unlike anything currently or previously taught at our institute. It put the students in charge of their own scientific trajectories, taking them on a full scientific cycle "journey" from idea and question, to device development and measurement, to analysis and communication. The main goal of the course was for all students to use raspberry pi micro controllers or similar devices and a variety of sensors however they wish to build a scientific measuring device, while maintaining this course's relevance and connection to all physical geography subjects.

The pedagogical framework of the course was innovative in a number of ways, namely bringing together a self-learning module teaching the basics of programming microelectronic boards, a hands-on workshop where they got to build their own sensor device based on their own scientific questions, and a follow-up phase where they got to propose a bigger project using their progress in the workshop as a pilot. Students particularly appreciated the open-ended nature of the course that could be adapted to their interests. Although the students' backgrounds were not technical, by the end of the course, we had one group measuring CO₂ over a freeway, one group analyzing temperature variation caused by balcony vegetation, and one group measuring water temperature profiles around Bern. In the end, one device was based on raspberry-pi pico and a second based on the sparkfun thing plus RP2040. In the future, we hope to put more emphasis on energy management and communication of sensor networks.  Improvements to this course must balance the goal to empower each student to "start from scratch" or to provide ready-to-go kits, leaving students to mainly choose which sensors they use.  Our main lessons learned concern teaching technical subjects in non-technical disciplines, focusing on instrumentation to transcend disciplines, transforming field courses to more accessible and lower-impact formats, and empowering students to build sensing devices starting with a blank sheet of paper (and a raspberry pi).

How to cite: Ceperley, N., Fässler, L., Leiser, P., and Schaefli, B.: Teaching by doing or a field course in our backyard: the first geosensing of the environment course in this geography institute, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13006, https://doi.org/10.5194/egusphere-egu23-13006, 2023.

Regular visitors of the EGU General Assembly are familiar with the ‘MacGyver’ sessions where hydrologists present measuring solution they have designed, build and tinkered (often ducttaped) themselves. We often get asked how we convey the MacGyver mentality to our students: how to teach them the skills and attitude to tackle their own problems hands on?

We teach this in the undergraduate course ‘measuring water’. In this course the learning goals include teaching hydrology students how to measure the different states and fluxes in the water cycle. We approach this by having teams of students design, make and demonstrate their own sensor. This ‘maker-education’ approach is known for stimulating intrinsic motivation in students to work on their projects, but it also comes with its own challenges: how to make sure that all students learn about all different types of sensors and not only about the one they choose? How to steer students towards choosing a project topic that is both challenging enough and not too challenging, without giving them the idea you are curbing their freedom to choose their own topic?

In this presentation we will reflect on lessons learned from a decade of teaching ‘Measuring Water’ and provide take-aways applicable for all geoscientific teaching.

How to cite: Hut, R., Coenders, M., and Vis, G.: Making MacGyvers: lessons from a decade of maker education, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13088, https://doi.org/10.5194/egusphere-egu23-13088, 2023.

Groundwater represents more than 97% of the globally available freshwater resources. Groundwater is situated in geological structures in the subsurface and is therefore not visible, difficult to characterize, and manage. As a consequence, it is often not adequately considered by authorities, the general public – and in education. However, teaching and learning Hydrogeology and Groundwater Management at universities, but also as a part of continuing education training for professionals, is essential to deal with future challenges. For this reason, it is important to use suitable teaching material to improve the understanding of the complex topic of groundwater among these target groups. The recent challenge of the COVID-19 pandemic has increased the demand for digital and remote teaching. An ongoing Erasmus+ cooperation project named iNUX – interactive understanding of groundwater hydrogeology aims to address the need for digital teaching material. The project aims to achieve an interactive and digital learning environment in hydrogeology and groundwater management with a European but also global target of teachers and students.

Existing experience in teaching relevant groundwater subjects from highly reputable European universities will be used to develop interactive and digital teaching material focusing on basic and applied hydrogeology. The teaching material will cover basic theory in combination with field and laboratory applications in different European environments (Northern Europe, Central Europe, and the Mediterranean). The teaching material will comprise (1) various types of videos (e.g., field experiments, lab experiments, screencasts of calculations and software use), (2) interactive Jupyter notebooks that combine explanation with live code (e.g., based on Python), (3) various types of questions and problems that allow different assessments to enhance self-controlled learning of students. All materials are intended as open source and publicly available. The iNUX activities also comprise initiatives to establish interest groups to combine efforts towards larger pools of commonly developed digital teaching material (e.g., question pools) and to link with other activities like the 'Groundwater project' (https://gw-project.org/).

How to cite: Reimann, T., Barthel, R., Birk, S., Fernandez-Garcia, D., and Chen, Z.: Interactive understanding of groundwater hydrology and hydrogeology – the iNUX project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14794, https://doi.org/10.5194/egusphere-egu23-14794, 2023.

This study presents a technique based on the use of quinine as a fluorescent tracer, to estimate sheet flow velocities over various surface coverings (e.g., bare; mulched; vegetated; paved) in low luminosity conditions (e.g., night; twilight; shielded environments). Quinine glows when exposed to UVA light and in the concentrations used is not harmful to the environment. Experimental work was conducted for studying sheet flows in the i) laboratory (using a soil flume), over bare and mulched surfaces, and ii) field, over vegetated and paved surfaces. Flow velocities were estimated based on the injection of a quinine solution into the water flow.  In these experiments, dye and thermal tracer techniques were used as a benchmark for assessing the performance of the quinine tracer. Optical and infrared cameras were used to record the movement of the tracers’ plumes in the flow. The surface velocity of the flow was estimated by tracking the tracers’ plumes leading-edge and calculating their travel distance over a certain time lapse. Overall, the visibility of the quinine tracer was better in comparison to the dye tracer. However, under some circumstances, lower than the visibility of the thermal tracer. Nonetheless, the results show that all three tracers yielded similar estimations of the flow velocities. Therefore, when exposed to UVA light the quinine tracer can be useful to estimate sheet flow velocities over a wide variety of soil and urban surfaces in low luminosity conditions. Despite some inherent limitations of this technique (e.g., invisible under bright light conditions or heavy mulched/vegetated cover; need of a UVA lamp), its main advantage is the high visibility of the quinine fluorescent tracer under UVA light for fade light conditions (e.g., night; twilight; shielded environments such as close conduits), which creates new opportunities for tracer-based surface flow velocity measurements in surface hydrology studies.

How to cite: Zehsaz, S., de Lima, J. L. M. P., de Lima, M. I. P., Isidoro, J. M. G. P., and Martins, R.: Estimating sheet flow velocities using quinine as a fluorescent tracer in low luminosity conditions: laboratory and field experiments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-515, https://doi.org/10.5194/egusphere-egu23-515, 2023.

Monitoring the depth changes in lakes is crucial to understanding hydrological dynamics and water quality changes. In developed countries, the authorities monitor the lake depths regularly; however, it might be different in developing and underdeveloped countries. In this study, we aim to develop a near-real-time SAR-based depth change monitoring system for lakes by focusing on shoreline pixels. For this purpose, we developed a framework using the Sentinel-1 GRD and Sentinel-2 Dynamic World land cover datasets available on the Google Earth Engine. Sentinel-1 data provides us with the necessary temporal resolution for frequent monitoring. For the initial development phase, we consider five ground monitoring stations in Sweden and one in Turkey. The approach starts by detecting water bodies within a selected area of interest using Sentinel-1. Then it extracts shoreline pixels to calculate the change in the VV and VH sigma naught and VV-VH and VV+VH Pauli vectors. Extracted differences are further classified according to the temporally closest Dynamic World data to handle the temporal difference for each land cover type. Next, we eliminate outlier values based on the percentiles, and from the remaining data, we sample each landcover class for modeling. From many of the tested frameworks, we obtained an R² of 0.79 with Gaussian Process Regression. Currently, in this framework, we observed an underestimation of higher values and an overestimation of lower values within a range of ±0.4 cm. Furthermore, considering the chosen six lakes, we observed a negative correlation between depth change and polarimetric features obtained from samples taken from land covers of grass and flooded vegetation, which is typical for natural lakes. In the second step of the development, we will increase the number of samples by including lakes from Switzerland and further develop the model.

How to cite: Ünalan, U. B., Yüzügüllü, O., and Aksoy, A.: Near Real-Time Depth Change Monitoring on Inland Water Bodies Using Sentinel-1 and Dynamic World Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-649, https://doi.org/10.5194/egusphere-egu23-649, 2023.

Monitoring dissolved methane in aquatic ecosystems contributes significantly to advancing our understanding of the carbon cycle in these habitats and capturing their impact on methane emissions. Low-cost metal oxide semiconductors (MOS) gas sensors are becoming an increasingly attractive tool to perform such measurements, especially at the air-water interface. However, the performance of MOS sensors in aquatic environmental sciences has come under scrutiny because of their cross-sensitivity to temperature, moisture, and sulfide interference. In this study, we evaluated the performance and limitations of a MOS methane sensor when measuring dissolved methane in waters. A MOS sensor was encapsulated in a hydrophobic ePTFE membrane to impede contact with water but allow gas perfusion. Therefore, the membrane enabled us to submerge the sensor in water and overcome cross-sensitivity to humidity. A simple portable, low-energy, flow-through cell system was assembled that included an encapsulated MOS sensor and a temperature sensor. Waters (with or without methane) were injected into the flow cell at a constant rate by a peristaltic pump. The signals from the two sensors were recorded continuously with a cost-efficient Arduino UNO microcontroller.. Our experiments revealed that the lower limit of the sensor was in the range of 0.1-0.2 uM and that it provided a stable response at water temperatures in the range of 18.5-28^oC. More information at Butturini, A., & Fonollosa, J. (2022). Use of metal oxide semiconductor sensors to measure methane in aquatic ecosystems in the presence of cross‐interfering compounds. Limnology and Oceanography: Methods, 20(11), 710-720.

How to cite: Butturini, A. and Fonollosa, J.: Metal oxide semiconductor (MOS) sensors to measure methane in aquatic ecosystems. An eficient DIY low  cost application., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1221, https://doi.org/10.5194/egusphere-egu23-1221, 2023.

The river discharge data is one of the most important pieces of information to regulate various water resources, including flood frequency analysis, drought and flood prediction, etc. The missing observer discharge data, even a short gap, influences the whole analysis and gives a totally different result. Filling data gaps in streamflow data is thus a critical step in any hydrological study. Interpolation, regression-based analysis, artificial neural networks, and modeling are all methods for generating missing data. While using the hydrological model to generate the data, we first need to calibrate the hydrological model. The single-site calibration of the hydrological model has its own limitations, due to which it does not correctly predict the streamflow at intermediate gauge locations. This is because, while calibrating the model for the final outlet, we tune the parameters that affect the results for the final outlet only and neglect the intermediate sites' output. In this study, we demonstrate the importance of multi-site calibration and use the calibrated hydrological model to generate the missing data at intermediate sites.

For this study, we selected the Godavari River basin and calibrated it at the final outlet (single-site calibration) and at 18 + 1 outlets (multi-site calibration). The whole basin is divided into 103 subbasins, and the Soil and Water Assessment Tool (SWAT) hydrological model is used for this study. After the successful multi-site calibration, we generated the missing data at 25 different gauging locations. The initial results from single-site calibration (NSE (0.57) and R2 (0.61)) show good agreement between observed and simulated discharge for the final outlet. The multi-site calibration analysis is in progress, and full results will be presented at the conference.

How to cite: Singh, A., Dhaka, H. K., Prajapati, P., and Jha, S. K.: Using the hydrological model for filling the missing discharge data by using multi-site calibration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1636, https://doi.org/10.5194/egusphere-egu23-1636, 2023.

Glacier movement has been measured over the years using commercial units such as those from Leica. The aim is to measure point movements on the glacier surface in order to capture fine-grained data about its movement. This can also help to calibrate satellite-based approaches which have much lower resolution. Commercial dGPS recorders cost thousands of Euros so our project is creating a solution using new lower cost dGPS boards which could enable their use by more earth scientists.

The u-blox Zed-F9P based boards from Sparkfun can be used as a base station to send dGPS corrections to “rover” units on the glacier via a radio link. Each measurement is accurate to about 2cm depending on conditions. In our design the radio is used by the rovers to forward good fixes back to the base station, which then uses off-site communications to send the data home. Two types of internet link have been enabled: using a nano-satellite board (by SWARM) and a more traditional GSM mobile phone board (for locations with coverage). Both these boards are also available from Sparkfun – making most of the modules off-the-shelf. However our power supply is optimised to save power and charge the lithium ion battery from a solar panel. A real-time clock chip is used to wake up the system to take readings and transmit data, so the sleep power is only 0.03 mW enabling a year-long lifetime. The whole system is controlled by a Sparkfun Thing Plus SAMD51 which provides the required four serial connections and a circuitpython  environment. The full system will be installed in Iceland in the summer of 2023 and replace the previous prototype based on Swift Piksi Multi units which had shown the measurement principle to be sound.

How to cite: Martinez, K., Hart, J., Attia, S., Bragg, G., Corbin, M., Jones, M., Kuhlmann, C., Weaver, E., Wells, R., Christou, I., and James, E.: A low cost real-time kinematic dGPS system for measuring glacier movement, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2681, https://doi.org/10.5194/egusphere-egu23-2681, 2023.

Hydrological data, especially water stage and discharge, is very important for water resources planning and development, hydraulic structure design, and water resources management. Thus the hydrological data has to be observed and collected regularly and continuously. The hydrological data can be affected by many factors such as people, instruments, and climate. Therefore, the collected hydrological data still need to be subject to quality control and inspection to eliminate unreasonable data to ensure the accuracy and reliability. Traditionally, the quality control and inspection of stream water-stage is mainly manual. The verification of water stage data needs experienced hydrologists to judge the correctness of the data, and cannot be processed automatically. It is time consumed, costly, and labor intensive to process the quality control of stream water stage. Therefore, it is necessary to develop a feasible model to automatically check stream water-stage for providing reliable and accurate hydrological data.

This study applies Hilbert-Huang Transform (HHT) to process stream water-stage. The HHT is composed of Empirical Mode Decomposition (EEMD) and Hilbert transform (HT). The EEMD decomposes stream water-stage into many intrinsic mode functions (IMFs) and a residual. The first IMF component is used for Hilbert transform conversion to obtain the time amplitude energy relationship diagram. The amplitude fluctuation of the corresponding component of the stream water-stage, the amplitude value of the outliers can be revealed. When the amplitude value is larger than usual, there may be outliers, and vice versa. It depends on the threshold that is established in this study as the basis for filtering the incorrect water-stage. Therefore automatically inspecting the water-stage data can be achieved. The model for automatic inspecting procedure developed by this study will greatly reduce the manual quality control, not only shorten the checking time, save manpower, but also provide reliable and correct river water stage data.

How to cite: Chen, Y.-C. and Hsiao, W.-H.: Quality control of stream water-stage using Hilbert-Huang Transform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4844, https://doi.org/10.5194/egusphere-egu23-4844, 2023.

Understanding the transport behaviour of mismanaged plastic waste in riverine and estuarine environments is growing. However, many studies to date focus on the surface layer transport while a limited number look to measure the vertical distribution of plastic waste within these systems. Factors such as density, shape, the influence of wind and flow velocity can determine the vertical distribution of the plastic waste in a river, but many knowledge gaps remain. With this, and as technology developers move to create innovative river surface focused interception solutions to extract plastic waste, a greater understanding of the transport behaviour of sub-surface plastic debris is required. Here, we present a comprehensive overview of the development stages required to build and deploy a low-cost depth trawl tool designed to sample plastic waste at a depth of up to 5m in a heavily polluted river in Malaysia. Topics covered include tool design concepts, manufacturing methods, onsite testing, river deployment learnings and sampling results. Field data is compiled from over 60 sampling surveys conducted over 14 days in several locations along the Klang River, Malaysia. The depth trawl is mounted to a locally available fishing boat (sampan) and consists of two steel horizontal arms, a steel frame, two winches, cables, weights, five nets, and is operated manually with the assistance of a solar-powered motor. The dimensions of each net are 30cm (W) x 50cm (H) x 100cm (L) with a mesh size of 30mm x 30mm. To ensure that the nets remain aligned vertically during deployment, a weight of 15kg is tied to the bottom of the net system on both sides. Samples were collected every 1 metre to a depth of 5 metres. Each sampling was conducted for 15 minutes, six times per day with an interval of 1 hour between samples to allow for changes in the tide and river flow direction. An ADCP was deployed in parallel to the depth trawl to provide measurements of flow velocity variation at the river surface and with depth. In addition, this paper reviews the depth trawl system’s capabilities and recommendations for further studies and applications in the field.

How to cite: Higgins, D., Correia, R., Kang, H. S., Quen, L. K., Ken, T. L., Vollering, A., Pinson, S., H. Assumpção, T., and Mani, T.: Trials and design iterations experienced developing a low-cost depth trawl to sample macroplastic through the water column of a tidal river., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4878, https://doi.org/10.5194/egusphere-egu23-4878, 2023.

FreeStations are mature low-cost, networked, DIY environmental sensors and data loggers, developed since 2014  and now deployed around the world.  Build instructions are open source at www.freestation.org and based on high availability, low cost but accurate and robust components (with builds typically 3% the parts-cost of an equivalent proprietary monitoring systems).  This allows investment in a network of environmental loggers at the cost of a single, proprietary logger.  

FreeStations have been widely deployed in the DEFRA Natural Flood Management (NFM) national trials in the UK, and analytical methods developed to examine the performance of leaky dams, retention ponds, regenerative agricultural practices and other nature based solutions in mitigating flood risk at downstream assets.

These deployments usually consist of FreeStation weather stations: recording rainfall volume, rainfall intensity, air temperature, humidity and pressure as well as solar radiation, wind speed and direction.  The rainfall volume and instantaneous intensity are the most important for NFM studies.  Alongside weather stations, FreeStation sonar-based stage sensors are used, alongside river profile scan from a FreeStation LIDAR, to monitor change in river discharge due to an NFM intervention, relative to discharge at a downstream asset at risk.  Readings are taken at 10-minute intervals over multiple years.

A series of web based methods have been built as part of the FreeStation //Smart: platform to monitor and manage data from deployments and to analyse data to better understand flood mitigation by the key types of intervention.  In testing at more than 10 sites in the UK over a period of 2-3 years per site, large volumes of data have been collected at low cost and in support of local stakeholders during the H2020NAIAD and H2020ReSET projects.  

The data indicate the importance of careful design in leaky debris dams, the limited impact of inline retention ponds and the significant capacity of low-till farming methods to mitigate downstream flooding.  The effectiveness of NFM depends upon the number and scale of interventions, the proportion of the discharge at the downstream asset at risk which they affect (i.e. the downstream proximity of the asset at risk) and the capital and maintenance costs of the interventions. 

Low-cost approaches to environmental monitoring will be critical for developing the evidence base needed to better understand what nature based solutions work, where for water.  Low cost, internet-connected devices are easy to monitor and maintain, low risk and capable of extensive deployment to address the challenge of geographical variability which means that the impacts of specific NFM interventions are highly site specific. 

How to cite: Burke, S., van Soesbergen, A., and Mulligan, M.: Effectiveness-assessment of nature-based flood mitigation using networked, low cost DIY environmental monitoring from FreeStation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5922, https://doi.org/10.5194/egusphere-egu23-5922, 2023.

How to cite: Aigner, N., Moos, C., and Noyer, E.: Developing a smart sensor network for soil moisture monitoring in forests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8165, https://doi.org/10.5194/egusphere-egu23-8165, 2023.

This study developed a synchronized mapping technique for water quantity and quality via an unmanned surface vehicle (USV). The USV with the acoustic doppler current profiler (ADCP) and the multiparameter sonde of water quality sensors (YSI EXO2) was used for identifying spatial and seasonal patterns of the Daljeon reservoir in South Korea. With this technique, we measured bathymetry and nitrate concentration from August 2021 through July 2022 at the high resolution spatial resolution and tested the sensitivity of estimated nitrate loads to spatial variations of input variables (water volumes and nitrate concentrations). Results showed that measured bathymetry and nitrate concentration varies over the water surface of the reservoir and time, which are associated with seasonal variations of temperature and precipitation. Despite weak spatial variations of the nitrate concentration, the water level of the reservoirs showed strong spatiotemporal variations depending on the topography of the reservoir and the  rainfall occurrence. Furthermore, we figured out using the mean for nitrate load was underestimated by -20% of the nitrate load estimates by considering spatial variation. High-resolution bathymetry measurement play a role in estimating nitrate loads with a minor impact of spatial variations of measured nitrate concentrations. We found that rainfall occurrences more likely increase estimated nitrate loads when it accounts for spatially variations of input variables, particularly water volumes. This study proved the potential utility of USV in simultaneously monitoring water quantity and quality for integrative water resource management for sustainably development of our communities.

How to cite: Lee, K.-H., Ali, S., Kim, Y., Lee, K.-T., Kwon, S. Y., and Kam, J.: Synchronized mapping of water quantity and quality of a reservoir through an unmanned surface vehicle: A case study of the Daljeon reservoir, South Korea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10497, https://doi.org/10.5194/egusphere-egu23-10497, 2023.

We developed automated ablation stakes to measure colocated in-situ changes in ice-surface elevation and climatological drivers of ablation. The designs implement open-source hardware, including the Margay data logger, which records information from a MaxBotix ultrasonic rangefinder as well as a sensor to detect atmospheric temperature and relative humidity. The stakes and sensor mounts are assembled using commonly available building materials, including electrical conduit and plastic pipe. The frequent (typically 1–15 minute) measurement intervals permit an integral approach to estimating temperature-index melt factors for ablation. Regressions of ablation vs. climatological drivers improve when relative humidity is included alongside temperature. We present all materials required to construct an automated ablation stake, alongside examples of their deployment and use in Alaska (USA), Ecuador, Patagonia (Argentina), and the Antarctic archipelago.

a: Alaska, 2012
b: Alaska, 2013
c: Ecuador, 2016
d: Argentina, 2020
e: Antarctica, 2021

How to cite: Wickert, A. D., Barnhart, K. R., Armstrong, W. H., Romero, M., Schulz, B., Ng, G.-H. C., Sandell, C. T., La Frenierre, J. D., Penprase, S. B., Van Wyk de Vries, M., and MacGregor, K. R.: Automated ablation stakes to constrain temperature-index melt models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11411, https://doi.org/10.5194/egusphere-egu23-11411, 2023.

Determining greenhouse gas (GHG) fluxes, water (ET) fluxes and their interconnectivity within the soil-plant-atmosphere-intersphere is crucial, not only when aiming to find solutions for current agricultural systems to mitigate the global climate crises but also to adapt them to related challenges ahead, such as more frequent and severe droughts. In a first attempt for a better understanding, often laboratory and/or greenhouse pot experiments are performed, during which gas exchange is predominately measured using especially manual closed chamber systems. Commercially available systems to determine gas exchange in terms of CO₂ and ET are, however, costly and measurements itself labour-intensive. This limits the amounts of variables to be studied as well as possible repetitions during a study. Additionally, it resulted in the long-term focus on agroecosystems of the northern hemisphere while agroecosystems of sub-Saharan Africa as well as Southeast Asia are still being underrepresented.

We present an inexpensive (<1.000 Euro), Arduino based, multi-chamber system to semi-automatically measure 1) CO₂ and 2.) ET fluxes. The systems consists of multiple, self-sufficient, closet-shaped PVC “coffins”. The “coffins” a closed by a frontal door and periodically ventilated through a sliding window. Relays connected to the microcontroller are used to steer closure/opening (linear actuator) and ventilation (axial fans). CO₂ and ET fluxes are determined through the respective concentration increase during closure by a low-cost NDIR CO­₂ (K30FR; 0-10,000 ppm, ± 30 ppm accuracy) and rH sensor (SHT-41). Parallel measurements of relevant environmental parameters inside and outside the “coffins” are conducted by DS18B20 (temperature) and BMP280 (air pressure) sensors. Sensor control, data visualization and storage, as well as steering closure/opening and ventilation is implemented in terms of a wifi and bluetooth enabled, socket powered (9V), compact microcontroller (D1 RS32) based logger unit. Here, we present the design, and first results of the developed, low-cost multi-chamber system. Results were validated against results of customized CO2 and ET measurement systems using regular scientific sensors (LI-COR 850) and data logger components (CR1000), connected to each “coffin” by a multiplexer.  Flow-meter were used for measurement synchronization.

How to cite: Hoffmann, M., Al Hamwi, W., Lück, M., Schmidt, M., and Dubbert, M.: A low cost multi-chamber system (“Greenhouse Coffins”) to monitor CO2 and ET fluxes under semi-controlled conditions: Design and first results, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11777, https://doi.org/10.5194/egusphere-egu23-11777, 2023.

Mediterranean agriculture is facing the challenge to produce sustainably with a water resource under pressure. As irrigated areas expand in response to increasing vulnerability to drought, it is essential to support water users towards better agricultural water management. We set up two Fab Labs on the shores of the Mediterranean (France and Tunisia) to bring together water users around a collective project: co-constructing innovations to address local water management issues. A range of low-tech, low-cost and open source IoT-based sensors emerged from this process. The technologies were tested with users during the 2022 irrigation season. The aim of this study is to provide feedback on this participatory method as a facilitator for creating and sharing innovation in rural territories and to discuss the opportunities, benefits and limitations related to the use of these new technologies. We believe that this work contributes to make the measurement of water flows - and thus their understanding and better management - more accessible to the agricultural sector.     

How to cite: Vandôme, P., Leauthaud, C., Moinard, S., Mekki, I., Zairi, A., and Belaud, G.: Water user Fab Labs: co-design of low-tech sensors for irrigated systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12622, https://doi.org/10.5194/egusphere-egu23-12622, 2023.

This study proposes a novel method for rainfall intensity estimation from acoustic and vibration data with low-cost sensors. At first, a precipitation measurement device was developed to collect sound and touch signals from raindrops, composed of Raspberry Pi, a condenser microphone, and an accelerometer with 6 degrees of freedom. To figure out whether rainfall occurred or not, a binary classification model with the XGBoost algorithm was considered to analyze long-term time series of vibration data. Then, high-resolution acoustic data was used to investigate the main characteristics of rainfall patterns at a frequency domain for the period when it was determined that rainfall occurred. As a result of the Short Time Fourier Transform (STFT), the highest frequency, mean and standard deviation of amplitudes were selected as representative values for minute data. Finally, different types of regression models were applied to develop the method for rainfall intensity estimation from comparative analysis with other precipitation measurement devices (e.g., PARSIVEL, etc.). It should be noted that the new device with the proposed method functions reliably under extreme environmental conditions when the estimated rainfall intensity was compared with measured data from ground-based precipitation devices. It shows that low-cost sensors with sound and touch signals from raindrops can be effectively used for rainfall intensity estimation with easy installation and maintenance, indicating a strong possibility of being considered in a wide range of areas for precipitation measurement with high resolution and accuracy

Acknowledgement

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2022R1A4A3032838).

How to cite: Hwang, S., Lee, J., Sung, J., Kim, H., Kim, B., and Jun, C.: Precipitation Measurement from Raindrops’ Sound and Touch Signals, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13072, https://doi.org/10.5194/egusphere-egu23-13072, 2023.

River networks in the Alps are very complex and hold many unanswered research questions. For example, various assumptions must be made to when studying tributaries and small rivers. Namely, there is not a widely accepted tool to measure streamflow in small, mountain streams that can overcome their specific challenges affordably without large installations. For example, alteration between extremely high and no discharge volume is characteristic of intermittent rivers and ephemeral streams (IRES). Conventional measuring devices all require streambed installation, which exposes them to displacement or destruction by abruptly rising water levels. One solution, thus, is to remove the sensor from the streambed and measure from a distance. We have experimented with an acoustic sound recorder mounted above the stream as an alternative tool to assess water level. We designed a low-cost audio sensor powered by a microcontroller with an audio shield specifically for recording IRES. To ensure reproducibility, we used Arduino for programming the Teensy 3.2. Images of the water level in an IRES were simultaneously captured when possible (daylight) and used for calibration. The water level visible in the images correlated well with that determined from the audio recordings from our self-developed audio sensor (R² = 95%). Based exclusively on the audio recording of an IRES, we can obtain a time series of the water level, at least when water was present. We are currently unable to determine consistently whether water is present nor state with certainty when the streambed is dry based solely on acoustic data. Nevertheless, this new sensor allows us to measure an alpine channel network at more locations and over longer time periods than previously feasible.

How to cite: Fässler, L., Ceperley, N., Leiser, P., and Schaefli, B.: Monitoring an ephemeral stream with a Teensy 3.2 + audio shield to determine water level only from the noise of a stream, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14370, https://doi.org/10.5194/egusphere-egu23-14370, 2023.

The development of artificial reservoirs plays a considerable role in regulating the spatial and temporal distribution of irrigated rainfall and guaranteeing sustainable agricultural development. Many studies have used the area-storage relationship to obtain the storage capacity of on-farm reservoirs (OFRs), but it does not work for OFRs with persistent water surface area. In this study, we proposed an effective method to estimate the water storage of irrigated OFRs by combining multi-source remote sensing data and ground observation. We quickly derived the location of irrigated OFRs by using seasonal characteristics of irrigated OFRs and obtained high-precision water surface area using an object-oriented segmentation. We estimated water storage of irrigated OFRs by combining three different ways (i.e., Lidar-based, ground observation-based (photos), and surface area-based). The method performs well in three aspects, i.e., identifying on-farm reservoirs, extracting water surface area, and calculating water storage. The accuracy of identification reaches 94.1%, and the derived water area agrees well with the surveyed results, i.e., an overall accuracy of 97.8%, the root mean square error (RMSE) and the mean absolute errors (MAE) are 962 m² and 766 m², respectively. The obtained water storage is reliable using three different ways (i.e., the area-storage, Lidar-based, and photo observations-based methods), with accuracy of 98.8%, 95.2%, and 94.1%, respectively. The proposed method enables monitoring of the storage of multiple types of irrigated OFRs, particularly the photo observation-based method can deal with the storage of OFRs with persistent water areas, showing huge potential to promote irrigated water resource utilization efficiency.

How to cite: wang, Y.: Monitoring water storage of on-farm reservoirs using remote sensing and ground observation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15372, https://doi.org/10.5194/egusphere-egu23-15372, 2023.

Hydrology is still one of the most data scarce natural sciences. The large number of variables to measure, their extreme spatiotemporal gradients, and the often harsh and hostile environmental conditions all contribute to this issue. This challenge is even more pronounced in remote and extreme environments such as the tropics, and mountain regions, where the need for robust data is most acute.

Many new and emergent technologies can help with building more cost-effective, robust, and versatile hydrological monitoring systems. However, the speed at which these new technologies are being incorporated in commercially available systems is slow and dictated by commercial interests and bottlenecks.

An alternative solution is for scientists to build their own systems using off the shelf components. Open-source hardware and software, such as the Arduino and Raspberry Pi ecosystems, make this increasingly feasible. As a result, a plethora of global initiatives for open-source sensing and logging solutions have emerged.

But despite these new technologies, it remains a major challenge to build open-source solutions that equal the reliability and robustness of the high-end commercial systems that are available on the market. Sharing experiences, best practices, and evidence on the real-world performance of different designs may help with overcoming this bottleneck.

In this contribution, I summarize the experience gained from developing and operating over 300 open-source data loggers, built around the Riverlabs platform. This platform is mostly a compilation of existing open-source hardware and software components and solutions, which were refined further and tweaked for robustness and reliability in extreme environments. Our loggers have been installed in locations as diverse as Arctic Norway, the high Andes of Peru and Chile, the Nepalese and Indian Himalayas, the Somali desert, and the Malaysian rainforest, providing a wide range of real-world test-cases and performances.

How to cite: Buytaert, W.: Towards a robust, open-source logging platform for environmental monitoring in challenging environments: the Riverlabs toolbox, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15989, https://doi.org/10.5194/egusphere-egu23-15989, 2023.

The air quality monitoring is a core topic for European environmental policies and worldwide. At the same time technologies such as electrochemical or NDIR gas sensors became affordable and easy to implement in a customized design. A highly flexible monitoring station has been designed and build in order to obtain a customizable and affordable device. It is composed of two boards, one in charge of connectivity and processing while the other allows to insert up to 11 gas sensors. Such number is achieved through the use of three multiplexers that allow to spare input pins of the processor. Moreover the flexibility at the moment is achieved using sensors with the same form factor but adapters are under development to increase the adaptability of the system, both hardware and software. An Arduino MKR zero runs the application that can be run in three different modes: single measurement, time driven or position driven. The last feature is obtained through an optional on-board U-blox GNSS module that allows to georeference the performed measurements. This mode is mainly used when the measurement cell is applied on moving object, such as drones. The system is able to send the data collected and receive commands using MQTT protocol (HiveMQ broker) through a NB-IoT connection and interact with the user from an online dashboard created using Thingsboard. The use of the MQTT protocol allows to send the data to multiple endpoints if the data should be provided also to third parties. Moreover, the data and some parameters are also saved on a sd card. All the system is built on stand alone boards to achieve easy maintaince of the system and to allow a rapid change in the used technology (a plug and play LoRaWan module is under development). Being a multi-application platform, price of the device is of course highly dependent on the chosen set of sensors thus, in the end, on the application itself (i.e. Air pollution or gas emission in barns). To sum up, the device described is a possible solution for an affordable gas concentration measurement system that can be adapted to fit a large variety of use cases combining software and hardware solutions.

How to cite: Renzi, F., Cammillozzi, F., Cecchini, G., Filippi, A., and Valentini, R.: Design of an affordable and highly flexible IoT station for multiple gas concentration monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17527, https://doi.org/10.5194/egusphere-egu23-17527, 2023.

Many countries fund catchment observatories and networks to provide observational data, test models and hypotheses, discover new insights, catalyse the development of new technologies and enhance interdisciplinary collaboration. These catchment networks provide a wealth of observational data, yet synthesising information across catchment observatories to produce process-based understanding is challenging. To generalise findings from place-based studies, we need greater synthesis across catchment networks and thus careful consideration of the design and topology of catchment observatories and monitoring networks.

In this paper, we collate information from 80 catchment observatories/networks and conduct 21 questionnaires with project leads with the aim of reviewing the strengths and weaknesses of catchment observatories to provide recommendations that can inform future catchment observatory and network design. The catchment observatories encompass a wide range of flow regimes, science questions and spatial/temporal scales with 25, 33 and 22 observatories from the UK, Europe, and North America respectively. Most catchment observatories in the monitoring catalogue are concentrated in upland catchment systems monitoring flashy flow regimes, with very few focused on lowland systems and no catchment observatories focused on urban catchments. The choice of catchment observatory location was focused upon logistics and catchment characteristics, with logistics and the day-to-day running of the observatory highlighted as the aspect catchment observatory programme managers found most difficult. Many interviewees noted that the design of the observatory was a key phase in planning and an aspect they would have done differently.

Finally, we recommend key design guidelines for future catchment observatory and networks. This includes the need for a scoping and planning phase, community co-designed, digital infrastructure that enables FAIR data provision, and flexible and extensible catchment topology. Critically, knowledge transfer needs to be built in from the beginning of catchment observatories to enable transferability of new insights and understanding across linked catchment networks to tackle grand challenges within hydrology.

How to cite: Coxon, G., Bloomfield, J. P., Buytaert, W., Fry, M., Old, G., and Wagener, T.: Lessons learned from catchment observatory and network design in the UK, rest of Europe and North-America, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1088, https://doi.org/10.5194/egusphere-egu23-1088, 2023.

Recently, digitalization has impacted drought and flood forecasting systems, and makes the application of technologies and advanced data processing techniques in the water management field possible. Especially, digital twin in the field of water management aims to effectively diminish unprecedented water-related issues such as floods and droughts using 3D objects and high-resolution spatial data. Climate change effects are expected to increase flood and drought risk through more frequent heavy precipitation and global temperature rise, and the water disaster sector is so complex, dynamic, and unpredictable that requires sophisticated management systems. The digital approaches showed effective prediction and decision-making support. This paper presents the state-of-the-art of digital twin concepts along with different digital technologies and techniques in water management contexts. The digital twin platform developed by K-water is a virtual representation of water management for dam operation and urban flood warning with water-related data. It presents a general framework of the digital twin in risk management, optimal operation, and decision-making in the water management and disaster forecasting field. This review also described the water data management, modeling including artificial intelligence, Radar, CCTV, rainfall-runoff module, analysis, prediction, and communication aspects of a digital twin. Digital twin platforms can support decision-makers as the next generation of digitalization paradigm by continuous and real-time water management of the cyber world and simulating the various events in the cyber world.

Keywords: Digital Twin, Dam Operation, River, Spatial Data, AI, Urban Flood

How to cite: Kim, J., Kim, K., Lee, J., Kwon, M., Kim, H., and Jo, Y.: Digital Twin Water Management Platform - Innovative approach for optimal water management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4589, https://doi.org/10.5194/egusphere-egu23-4589, 2023.

Rapidly collected river discharge data can be used for flood forecasts, hydraulic structure design, and impromptu response during floods. This calls for the monitoring of both water level and velocity at the same time, which is not feasible using conventional invasive methods. Non-contact techniques like doppler radar and satellite remote sensing techniques are the sole options. Doppler radar sensors are gaining popularity in the recent decade due to their accuracy and user-friendly operation. The study was conducted using data collected at two gauging sites at Devprayag on Bhagirathi and Ganga, two significant Himalayan Rivers. This study compares the observed discharge measured using a current meter and ADCP with the entropy-based discharge estimated using radar telemetry data for water level and surface velocity. Radar-derived water level and one-point surface velocity observations were used to estimate the discharge using probability-based Shannon and Tsallis Entropy laws. The discharge varied from 77.09 to 4265.4 cumec, while the surface velocities ranged from 0.283 to 8.35 m/s. The estimated discharges using radars were compared with observed discharges using Goodness-of -fit statistics which showed a good agreement between observed and estimated discharges as well as velocities, suggesting that radars can be effectively used to estimate real-time discharge for its improved applications in Himalayan mountainous rivers.

How to cite: Kumar, A. and Jain, M. K.: Non-contact Entropy-based flow Estimation in Himalayan Rivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4765, https://doi.org/10.5194/egusphere-egu23-4765, 2023.

The operator effect is a prominent error source in image-based velocimetry methods. The LSPIV method is known to be sensitive to the parameters and choices of the user, as shown in the literature and emphasized by the results of a video gauging intercomparison, the Video Globe Challenge 2020 (VGC2020) (Le Coz et al., 2021). The intercomparison was carried out during the COVID-19 lockdown of spring 2020 and involved 15 to 23 participants using the LSPIV method among other techniques on 8 videos representative of the diversity of river gauging conditions and imaging viewpoints. Each video came with a discharge reference and associated uncertainty.

An in depth investigation of the intercomparison results has been carried out to identify the most sensitive parameter(s) for each video and also to review the common setting mistakes (cf. Bodart et al., 2022). The investigation highlighted the strong impact of the image temporal sampling (extraction framerate) and of the velocity filtering on the discharge errors. The ortho-rectification and the surface coefficient were also found to be impacting in given cases.

Based on these observations, several assistance tools and automated filters are proposed to reduce the operator effect. They are evaluated on the intercomparison dataset. The assistance tools use available information (e.g. transect data) or basic user inputs (e.g. manual spotting of some velocities) to determine the optimal extraction framerate, grid points and searching area (SA) for LSPIV computation. The sequence of automated filters is built for the specific context of discharge measurement: spatial coherency of the velocities in a local neighborhood and temporal coherency of the velocities computed at a point. These velocity filters are systematic and do not require any input from the user.

The application of the assistance tools and automated filters to the intercomparison dataset leads to a significant improvement of the results. On the eight videos, the mean interquartile range of the percent error initially at 17% is reduced to 2% and the mean median of the percent error initially at -9% is reduced to 0.6% with the assistance tools and filters. The results are encouraging and can be implemented in software tools for the operational deployment of the LSPIV method for discharge measurement.

Le Coz, J., Hauet, A., and Despax, A. (2021). The Video Globe Challenge 2020, a video streamgauging race during the Covid-19 lockdown, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2116, https://doi.org/10.5194/egusphere-egu21-2116, 2021

Bodart, G., Le Coz, J., Jodeau, M., and Hauet, A.: Quantifying the operator effect in LSPIV image-based velocity and discharge measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4457, https://doi.org/10.5194/egusphere-egu22-4457, 2022.

How to cite: Bodart, G., Le Coz, J., Jodeau, M., and Hauet, A.: Reducing the operator effect in LSPIV image-based discharge measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5779, https://doi.org/10.5194/egusphere-egu23-5779, 2023.

Hydrometric stations may be influenced by the sea tide, disrupting the stage-discharge relation and making it difficult to estimate discharge through a traditional rating curve. Twin-gauge stage-fall-discharge (SFD) rating curves, based on a flow friction equation and stage and water slope measurements, are a possible alternative, but they were found to perform poorly when the tide effect is strong. To capture the complex flow dynamics, including flow reversal, an approach via a 1D hydrodynamic model is proposed.

To set up the model, the cross-sectional geometry, friction coefficient, upstream discharge and downstream water level are required. In hydrodynamic modelling, the friction coefficients are the main calibration parameters and spatial changes of roughness combined with unsteady flow make their manual calibration difficult. Moreover, the understanding and quantification of uncertainties associated with data and model is an important step of the calibration process. Therefore, an automatic calibration of friction coefficients is proposed via Bayesian inference. In terms of numerical tools, the selected 1D hydrodynamic code is Mage, developed by INRAE, solving the 1D Saint-Venant equations for subcritical, transient flows. Likewise, the Bayesian Modeling (BaM) framework (https://github.com/BaM-tools) is used to specify prior information and estimate friction coefficients and their uncertainty, using stage and discharge observations.

The case study is the Lower Seine River in France, because it comes as a simple hydraulic model with a strong tidal effect with gauging campaigns and stage records available. Discharge time series of the Seine at Poses and of the Eure, the only significant tributary, are specified as upstream boundary conditions.  The downstream boundary condition is the stage time series of the Seine at Saint-Léonard, reflecting the tidal signal. Calibration data include stage records at different stations and times, and ADCP discharge measurements at Rouen during several tidal cycles.

For all reaches, a lognormal distribution with 95% probability interval [33; 49] is used as a prior for the Strickler coefficient. Bayesian estimation then provides their posterior distributions, represented by a large number of samples generated by means of a Markov Chain Monte Carlo (MCMC) algorithm. These samples can be used to identify optimal “maxpost” coefficients (maximizing the posterior density), but also to quantify and propagate their uncertainty. Thereafter, a propagation is performed to estimate the stage and discharge series of all cross-sections along with their uncertainty.

This study aims to provide an alternative solution for the continuous monitoring of discharge from stage records and upstream discharges in tidal rivers in order to improve flood forecasting, warning systems and the understanding of tidal-influence on hydrometric stations.

How to cite: Mendez Rios, F., Le Coz, J., Renard, B., and Terraz, T.: Bayesian calibration of a 1D hydrodynamic model used as a rating curve in a tidal river: Application to the Lower Seine River, France, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6587, https://doi.org/10.5194/egusphere-egu23-6587, 2023.

Obtaining real-time water level estimations is crucial for effective monitoring and response during emergencies caused by heavy rainfall and rapid flooding. Typically, this type of monitoring can be a difficult task, requiring river reach preparations and specialized equipment. Moreover, in extreme flood events, standard observation methods may become ineffective. This is why the possibility of developing low-cost, automatic monitoring systems represents a significant advancement in our ability to monitor river courses and allow emergency teams to respond appropriately.

Image-based methods for water level estimation facilitate the development of a low-cost river monitoring strategy in a quick and remote approach. These techniques are faster and more convenient regarding the setup than traditional water stage monitoring methods, allowing us to efficiently monitor the river from different locations with a cost-effective approach. By increasing the density of the observation network, we can improve flood warning and management.

The approach presented involves placing cameras in secure locations to capture images of the river, for which we have previously modelled the terrain in 3D using Structure from Motion (SfM) algorithms supported by GNSS data. With the images obtained every 15 minutes, we perform a Convolutional Neural Network (CNN) segmentation based on artificial intelligence algorithms that allow us to automatically extract the contours of the water surface area. In this study, two different neural network approaches are presented to segment water in the images.

Using a photogrammetric strategy, we reproject the water line extracted by the AI on the 3D model of the scene. This reprojection is also supported by the use of a keypoint detection neural network that allows us to accurately identify the ground control points (GCPs) observed in the images captured by the surveillance camera. This approach allows us to automatically assign to each image the real coordinates of the GCPs and subsequently estimate the camera pose.

This AI segmentation and automatic reprojection into the 3D model has allowed us to generate a robust centimetre-accurate workflow, capable of estimating the water level in near-real time for daylight conditions. In addition, the automatic detection of the GCP has permitted to obtain automatic water level measurements over a longer period of time (one year). This approach represents the basis for obtaining other river monitoring parameters, such as velocity or discharge, which allow a better understanding of river floods and represent key steps for the development of early warning systems for flood events.

How to cite: Eltner, A., Zamboni, P., Hedel, R., Grundmann, J., and Blanch, X.: Image-based methods for real-time water level estimation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6745, https://doi.org/10.5194/egusphere-egu23-6745, 2023.

The use of image velocimetry techniques for river monitoring has been increasing in the last few years, but there are some limitations to be solved related mainly to natural environmental conditions and operative framework (Dal Sasso et al., 2021). Along with these issues, the need for surface tracking features or homogeneously distributed materials across the cross-section represents one of the challenges for outdoor applications. In a natural environment, flows can present low seeding densities or locally distributed tracer clusters. These conditions can introduce a high variance and underestimate the flow velocity field, especially near the riverbanks.

In this work, the Farnebäck dense optical flow method (Farnebäck 2003) implemented in SSIMS-Flow software (Ljubicic, 2022) was tested and compared with LSPIV technique (Thielicke et al., 2021) to estimate surface flow velocities under different seeding conditions. The application was carried out on the Arrow River (UK) along two meandering river reaches during low-flow conditions. Four different seeding conditions were experimented from low (natural) to high (artificial) seeding density of tracers . Tracers were manually distributed onto the water surface and videos were acquired from DJI Phantom 4 Pro. Seeding metrics were used to estimate seeding conditions including: mean tracer area, seeding density, spatial tracer distribution, and the SDI index (Pizarro et al., 2020). Conventional velocity measurements were used as benchmark purposes along various transects.

This study highlighted the good performances of the two tested image velocimetry methods, with results comparable to traditional techniques. On the one hand, the Farnebäck optical flow method proved to be more sensitive to changing setting parameters (e.g., feature extraction rate) with respect to LSPIV. On the other hand, optical flow showed low sensitivity to seeding density (error reduction 30-40%). This is due to the capacity of the Farnebäck method integrated with an ad-hoc pooling technique for spatial velocity averaging to represent surface velocity under sporadic and uneven seeding (e.g., near the convex bank).

References

Dal Sasso, S. F., Pizarro, A., Manfreda S. (2021). Recent Advancements and Perspectives in UAS-Based Image Velocimetry. Drones 5, 3: 81.

Farnebäck, G. (2003). Two-frame motion estimation based on polynomial expansion, Scandinavian conference on Image analysis. Springer, Berlin, Heidelberg.

Ljubicic, R. (2022). SSIMS-Flow: UAV image velocimetry workbench, https://github.com/ljubicicrobert/SSIMS-Flow

Pizarro, A., Dal Sasso, S.F., Manfreda, S. (2020). Refining image-velocimetry performances for streamflow monitoring: Seeding metrics to errors minimization. Hydrol. Process. 2020, 34, 5167–5175.

Thielicke, W., Sonntag, R. (2021). Particle Image Velocimetry for MATLAB: Accuracy and Enhanced Algorithms in PIVlab. Journal of Open Research Software, 9, Ubiquity Press, 2021.

How to cite: Dal Sasso, S. F., Ljubicic, R., Pizarro, A., Pearce, S., Maddock, I., and Manfreda, S.: Image-based velocity estimations under different seeded and unseeded river flows, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6936, https://doi.org/10.5194/egusphere-egu23-6936, 2023.

In July 2021, several western European countries were stricken by extreme floods due to exceptional rainfall events. In North-Eastern France overbank flows started to occur in several rivers on July 14^th. The local field hydrologists of the national hydrological service (Vigicrues) managed to conduct mobile-boat ADCP discharge measurements during the floods at many hydrometric stations. They often observed dramatic high-flow rating shifts, typically with measured discharges being 20% to 60% smaller than the discharges computed from the stage-discharge rating curves. Such unusual rating shifts are substantially larger than the uncertainty of the ADCP discharge measurements (5%-10%). To avoid biases in flood forecast, the rating curves had to be recalibrated with limited information on the fly, which was uncomfortable. The local field hydrologists reported that the rating shifts may be due to the floodplain vegetation being very different from the winter conditions of the flood discharge measurements used to build the high-flow ends of the rating curves. In July 2021 indeed, floodplains were covered with high summer crops that had not been harvested due to the unusually cold and rainy weather.

To test this assumption on a hydraulic basis, the rating curves of seven stations on the rivers Aisne, Oise, Helpe Majeure, Chiers and Loison in North-Eastern France were re-analysed using the Bayesian method BaRatin implemented in the BaRatinAGE open-source software. At all of these stations, the identified controls include the main channel (and possibly other low-flow controls) and a relatively wide, rural floodplain. For each station, two rating curves and their uncertainty envelopes are computed: the “normal” rating curve using all valid discharge measurements except those of the July 2021 flood, and the “July 2021” rating curve using no flood discharge measurements but those of the July 2021 flood. For the “July 2021” rating curve, the prior height (offset) of the floodplain is usually taken as the posterior (calibrated results) of the “normal” rating curve, but the coefficient of the floodplain control is calibrated using the July 2021 ADCP discharge measurements. The obtained rating curves are consistent with the rating curves estimated manually by the local field hydrologists. The floodplain friction factors  estimated by BaRatin for the “July 2021” rating curve are decreased by a factor of 1.6 to 14, typically (i.e. Strickler coefficients from 15-20 m^1/3/s to 2-10 m^1/3/s), which is spectacular but consistent with available look-up tables for friction factors in bare or vegetated fields.

The proposed Bayesian analysis appears useful for field hydrologists to evaluate the possible extent of rating shifts due to unusual floodplain roughness at their stations, and to be prepared for the recalibration of their rating curves would an overbank flood occur outside the winter season again. It is also a convenient way for them to inform and prepare the flood forecasters on the causes and occurrence of such rating shifts, and on the related discharge uncertainty they would have to take into account.

How to cite: Le Coz, J., Lang, M., Poligot-Pitsch, S., and Janet, B.: Quantifying high-flow rating shifts due to unusual floodplain roughness during the July 2021 European flood, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6984, https://doi.org/10.5194/egusphere-egu23-6984, 2023.

The moving-boat Acoustic Doppler Current Profiler (ADCP) gauging method is extensively used to measure the discharge of rivers and canals. Inter-comparison of ADCP measurements are necessary not only to validate the instruments and their deployment, but also to study the discharge measurement uncertainty. Uncertainty estimates provided by the propagation methods cannot be validated for in situ conditions because of the complexity of the ADCP data workflow and the uncertainty of discharge references in rivers and canals. To solve this issue, a complementary approach to uncertainty propagation methods is the repeated measures experiments, also known as inter-laboratory comparisons. ADCP inter-comparisons have been done for decades and with very different conditions. These data sets are precious in order to test and validate uncertainty propagation methods.

The OURSIN ADCP uncertainty analysis is validated using empirical uncertainty estimates on inter-comparison experiment. This propagation method has been implemented in the QRevInt software which provides an ADCP data quality review. QRevInt is developed by Genesis HydroTech LLC (Mueller, 2021) with the guidance and contributions from an international board of hydrological agencies. QRevInt helps to clean ADCP measurements from avoidable errors and to homogenize the discharge computations irrespective of the instrument manufacturer and model.

However, post-processing inter-comparison results is a long and complicated process particularly if users want to determine and quantify uncertainty sources. There are as many practices as there are hydrometric services. Uncertainty is an indispensable component of discharge measurement and should be estimated for as many measurements as possible. To popularize these practices and homogenize them, a user-friendly tool has been developed.

From raw ADCP measurements, it applies QRevInt post-process quality analysis, the OURSIN uncertainty propagation method, and the empirical uncertainty computation based on the repeated-measures experiment. The tool applies Grubbs and Cochran statistical tests to validate the measurement selection. It returns tables with a row for each measurement with information, such as, discharge and uncertainty decomposition from QRevInt. It also returns an overview of the inter-comparison with graphs of the discharge and its uncertainty among measurements, computed uncertainty, and empirical uncertainty. The tool allows replaying data with homogeneous parameters and users can manually exclude a measurement if it does not seem consistent. The tool will be open source and freely available.

Beyond the operational application, it could be used to replay historical inter-comparisons. With an inter-comparison database, it will be possible to study diverse types of rivers to improve and validate uncertainty estimation in various conditions. A first synthesis is proposed from one inter-comparison data set and will be extended to as much data as possible in the future.

How to cite: Calmel, B., Le Coz, J., Alexandre, H., Aurélien, D., and Mueller, D.: Comparing ADCP inter-comparison results using an automated post-processing tool, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7073, https://doi.org/10.5194/egusphere-egu23-7073, 2023.

The measuring of flood events is associated with many challenges. Among them is the determination of flow velocities for the derivation of discharge. Most of the applied methods for velocity determination the disadvantage that they work in direct contact with water. This often makes measuring under critical flow conditions dangerous. Optical measurement methods have a great advantage because they can work remotely, i.e., without water contact.

For representative discharge measurements, flow velocity measurements over the entire width of the river cross-section are required. This is a major challenge in the application of PTV, because visible particles must be present across the entire cross-section, which is not always the case. The potential measurement gaps in the surface velocity distribution have a negative effect on the quality of the discharge determination. Because optical measurement methods are relatively new in hydrology, there is not yet a standardised procedure with which the discharge can be determined. 

The "OptiQ" method presented here is an approach for determining discharge using PTV. This method is based on the continuity equation, which is dependent on two variables, the flow area and the mean flow velocity. The challenge here is to determine the depth-averaged flow velocity, because PTV is used to determine the surface velocity. To get the depth-averaged flow velocities, the PTV results are averaged over a transect and converted using a velocity coefficient. The arithmetic mean, the velocity area method (DIN EN ISO 748:2008-02) and the moving average are considered as averaging methods. A statistical approach was chosen for closing measurement gaps that occurred in the velocity distribution. In this approach, the measurement results with similar discharge conditions in the entire time series, i.e. PTV results for the same water levels, are statistically analysed, filtered and summarised in a lookup table. The gaps in the measurements due to missing particles are filled with the data from the lookup table.

For the data collection, three camera gauges were installed at regular gauging stations of the Saxon State Agency for Environmental and Agricultural Monitoring (BfUL). The camera gauges recorded short video sequences at regular time intervals, which were used to determine the velocity distributions using the FlowVelo tool (Eltner et al., 2020). This resulted in three time series covering a period of 10-15 months. For the validation of the optical discharge time series, the regular water level and discharge measurements of the BfUL are used. 

The application of "OptiQ" shows a significant adjustment of the optically determined discharge data to the reference measurement at all three gauging stations. While acceptable results were determined with the arithmetic mean only at higher discharge, the results with the velocity area method and the moving average are similarly good at all discharges. At the gauging station in Elbersdorf, the average difference from the reference value could be reduced from 29% to 15% with "OptiQ". In the next step, it is planned to further develop the statistical model "OptiQ" by using Deep Learning.

How to cite: Kutscher, A., Grundmann, J., Eltner, A., Blanch, X., and Hedel, R.: Application of optical Particle Tracking Velocimetry (PTV) to determine continuous discharge time series, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9946, https://doi.org/10.5194/egusphere-egu23-9946, 2023.

In November 2021, an atmospheric river swept the Pacific Northwest region, causing one of the costliest natural disasters in Canadian history. Among others, the Coldwater River in Merritt, British Columbia caused widespread flooding on November 15^th, 2021, resulting in extensive damage to the infrastructure and total evacuation of the residents.

Estimating the magnitude of this flood is difficult, as it damaged the local flow monitoring station and altered the surrounding landscape. However, parts of this flooding event, including the flow close to its peak, were filmed by local residents using mobile devices or drones. Though with significant perspective distortion and imprecision, they still provide valuable information on the extreme flow event, which would have otherwise been lost or neglected. The objective of this study is to apply image velocimetry techniques to these videos, with limited resources and geodata, for reconstructing surface velocities and discharges during the flood.

The analysis method consists of using LSPIV and Farneback optical flow on the original clips where possible. Objects are identified in the videos, then geolocated or surveyed after the flood, for rectification of raw velocities. This allows multiple iterations, accounting for uncertainties in the rectification parameters. Discharges are then calculated using surveyed or reconstructed transects, and water surface elevations estimated from the video frames.

Preliminary results of both methods will be presented and compared on the use of lens distortion correction, different contrast enhancement block sizes, and interrogation area or filter sizes. Validations of the calculated discharges against flow observations from the Water Survey of Canada will also be included.

How to cite: Yang, J. J. S. and Weijs, S. V.: Use of image velocimetry techniques on citizen videos of the November 2021 flooding event flows in Merritt, British Columbia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10094, https://doi.org/10.5194/egusphere-egu23-10094, 2023.

Reliable and accurate river streamflow or discharge measurement and reporting are essential for engineering, economic, and social decision-making. Discharge values are often perceived as true and deterministic by users, modelers, and decision-makers. In this study, the processes of discharge estimation by the Water Survey of Canada, WSC, are presented. The process of inferring the discharge (water volume over time) based on stage (water level) through stage-discharge relationships or “rating curves” including related terminologies is described. Multiple practices of rating curve construction and discharge estimation across WSC hydrometric stations are explored. Major processes of "override" and "temporary shift" which significantly affect the discharge estimation are elaborated. The reproducibility of the published discharge data using data from the production process for approximately 1750 active hydrometric stations operated by WSC is examined. Other impacts of temporary shift and override have been evaluated on the properties such as discharge residuals or performance metrics. Recommendations are made for wider access to metadata and measurements that are essential to quantify the reproducibility and uncertainty of reported discharge values. Open science, particularly Earth system modeling, demands clear communication of reproducibility, and uncertainty of published discharge.

How to cite: Gharari, S., Liu, H., Freer, J., Whitfield, P., Stadnyk, T., Pietroniro, A., and Clark, M.: Reproducibility and uncertainty for national Canadian hydrometric stations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10348, https://doi.org/10.5194/egusphere-egu23-10348, 2023.

We perform hydrodynamic modelling using a 2D HEC-RAS model to assess the hydraulic habitat suitability in a data-constrained reach (7 km) of the Ganga River. This reach of the Ganga River is located within two structural barriers of the upper Ganga plain, namely the Bijnor barrage in upstream and the Narora barrage in downstream. It is an active river dolphin and gharial habitat. To setup and run the 2D flow simulation in HEC-RAS, we used topographic data from a LiDAR drone survey, channel bathymetry from field campaigns, time-series river stage (to define the boundary conditions of the model domain), and water surface slope from using the real-time kinematic GPS. We use water level time series data from a satellite altimeter (downstream) and discharge measured in the field using an ADCP for model calibration and validation, respectively.

We found that the study reach has poor habitat suitability at low flow, which improves at median flow. The use of altimeter datasets for model calibration is quite handy when the in-situ data is not readily available. This study provides a methodological framework to assess the hydraulic habitat suitability in rivers near structural interventions.

How to cite: Sonkar, G. K. and Gaurav, K.: Hydrodynamic modelling to assess habitat suitability of the Ganga River, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11248, https://doi.org/10.5194/egusphere-egu23-11248, 2023.

Accurate and reliable streamflow monitoring data are urgently needed for many new locations to tackle the on-going climate emergency, where we now see increasingly severe impacts on society from extreme flows. Yet, traditional river monitoring methods depend on empirical rating-curve methods for which it typically takes many years or decades to obtain reliable data, in particular for extreme flows. This gap between increasing needs and current monitoring capabilities calls for new methods to be developed.

Drones provide an unprecedented ability to measure both the physical and hydraulic characteristics of a river in an efficient manner. Topography, water surface slope, surface water velocity and even bathymetry can be derived from drone images and drone lidar data. We exploited this potential by incorporating drone data into the framework for Rating curve Uncertainty estimation using Hydraulic Modelling (RUHM). The RUHM framework combines a one-dimensional hydraulic model with Bayesian inference and together with drone data it allows us to efficiently estimate a reliable rating curve and its associated uncertainty based on as few as three gaugings.

We present our results from applying RUHM to Swedish gauging stations where we model rating curves and streamflow based on drone data. We primarily used low-cost camera drones to collect both the input (DEM, vegetation, bathymetry) and calibration data (water surface slope, surface velocity) for the hydraulic model, but also tested the capabilities of drone lidar data. Our aim was to estimate reliable rating curves with RUHM based only on data from the drone flights. We assessed the uncertainty in the drone-derived model input and calibration data compared to traditional fieldwork techniques, as well as their impact on the RUHM-modelled rating curves and streamflow results.

We find that careful planning of when to fly the drone is important for obtaining good-quality model input and calibration data. Using a combination of drone camera and drone lidar data we were able to obtain all the data needed for RUHM from the drone flights. Extreme low and high flows were reliably modelled with RUHM with constrained uncertainty based on as few as three low and middle flow gaugings, without the need for gauging extreme flows. We conclude that using RUHM with drone data is an efficient and promising alternative to traditional streamflow monitoring methods, being much less time-consuming and costly, as well as involving fewer risks to field staff.

How to cite: Westerberg, I., Mansanarez, V., Lyon, S., and Lam, N.: Rapid streamflow monitoring with drones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12058, https://doi.org/10.5194/egusphere-egu23-12058, 2023.

Bedload transport is a natural process that strongly affects the Earth’s surface system. An important component of quantifying bedload transport and establishing early warning systems is obtaining the parameters at the onset of bedload motion. Bedload transport can be monitored with passive acoustic methods, e.g., hydrophones. Yet, an efficient method for identifying the onset of bedload transport from long-term continuous acoustic data is still lacking. Benford’s Law defines the specific frequency distribution of the first digits of datasets that have been used to distinguish stochastic from chaotic processes in nature when this process causes higher energy events than baseline. Here, we apply Benford’s law to continuous acoustic recordings from Baiyang hydrometric station, a tributary of Liwu River, Taiwan at the frequency of 32 kHz from stationary hydrophones deployed for three years since 2019. We construct a workflow to parse sound combinations of bedload transportation and analyze them in the context of hydrometric sensing constraining the onset, and recession of bedload transportation. We identify two bedload transportation events that lasted 17 and 45 hours, respectively, covering about 0.35% of the time per year. Our workflow allows filtering 99% of background signal and focuses on two events including bedload motions. Given that fluvial seismology has successfully monitored fluvial processes, continuous monitoring in three directions (N-S, W-E, vertical) brings board discussion orientations, e.g., the direction of source or migration of mass movement. Therefore, we suggest that the application of Benford’s law on seismic data of Earth's surface processes has great potential.

How to cite: Yang, C.-J., Turowski, J. M., Zhou, Q., Tang, H., Nativ, R., and Chen, W.-S.: Measuring bedload motion time at sub-second scale using Benford's law from long-term acoustic recordings, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13332, https://doi.org/10.5194/egusphere-egu23-13332, 2023.

Real-time monitoring networks are increasingly prevalent in supporting the management of environmental systems as the technology for live data collection becomes more accessible. Additionally, ecosystem and water resource pressures have persisted and intensified under climate pressures and an expanding anthropogenic footprint. The way in which models and data are fused in the day-to-day management of water resources operations, as well as for long-term planning and investment, has been a critical field of research. An adaptive real-time monitoring-integrated learning modelling approach was developed and applied to improve the understanding of the mixing dynamics in a water supply reservoir in Queensland, Australia. This was accomplished through the combination of sequentially linked catchment and reservoir models with in situ real-time measurements of temperature and flow along with meteorological forecasts from an Australian numerical weather model, to produce short-term water quality forecasts. An adaptive learning catchment model was developed and linked for each inflow arm of the reservoir using the Australian Water Balance Model. This framework enabled automated online communication to researchers and managers around the current performance of the inflow predictions and the confidence expected in the current forecasts. Moreover, this live learning catchment model was coupled with a real-time adaptive three-dimensional hydrodynamic model of the reservoir iteratively training using data from the deployed real-time temperature monitoring system. A prototype internet-connected remotely operable autonomous surface vessel was deployed with a winching system for conducting dynamic water quality profiling operations under the guidance of waypoints guidance generated from the real-time adaptive modelling forecasts. Data collected by ASV was subsequently provided back to the modelling system in real-time. The complete system facilitated the online adaptive forecasting of mixing dynamics in the reservoir and the automated identification of features of interest for water quality profiling, as well as dynamically monitoring the areas potentially most valuable for model learning development to improve system-wide understanding and forecast certainty through addition into the live dataset for ongoing training and evaluation. Evidence was found in support of a rolling iterative calibration procedure for increasing model skill sensitivity to different processes occurring over temporal and spatial scales across both catchment and receiving water models. Dynamically guided spatial monitoring generated from maximum predicted areas of variation and parameter sensitivity in the real-time adaptive receiving water model demonstrated that monitoring of the receiving water inflow arms during inflow events was necessary during inflow events to train the model on the strongest signal of the driving force of changes in the receiving water environment. Overall, the uncertainty in rainfall events from both forecasted and observed sources cascading with the uncertainty in catchment simulations with only static indirect monitoring of flow (ungauged at any of the inflow arms to the reservoir) was found to be the most significant hindrance to the utility of the applied real-time adaptive modelling framework. The application of an adaptive computer vision-based stream gauging approach was then trialled on one of the ungauged inflow arms in order to supplement this gap.

How to cite: Hutley, N., Deering, N., Wagenaar, D., Beecroft, R., Soutar, J., Grinham, A., Gibbes, B., and Albert, S.: Adaptive real-time forecasting using model-driven monitoring of catchment inflows and water supply reservoir dynamics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14020, https://doi.org/10.5194/egusphere-egu23-14020, 2023.

In the last years, several methods to establish surface flow velocities and river flow from camera videos have been developed and codified into software. Together with a hardware setup, these may be used to establish near real-time observations of river flow. The hardware setup used and associated quality of the camera, methods to pre-process, process and post-process the videos may all result in errors, and uncertainties. In this contribution we assess what the main sources of uncertainty are, and under what conditions these may appear, focusing on both hardware and processing methods. We do this by co-locating two different camera setups, and using two different software processing methods. For camera setups we use a very simple and low cost FOSCAM FI9900EP running at its maximum of 4Mbps and a much better quality Vivotek IB9367-EHT running at 20Mbps. As systems we use the DischargeKeeper and pyOpenRiverCam.

The cameras were co-located over a significantly long period at a site in Limburg in The Netherlands, and footage analyzed with 15-minute intervals. Videos were treated with as much as possible the same settings, reprojection resolution and window. Results were compared in terms of the ability to resolve velocities (amount and quality) and the impact of post-processing. Integrated flow over a cross-section is also compared. We assess under what conditions flow and velocity estimates are robust and similar and under what conditions these diverge focusing on the platform used, light conditions, and flow conditions.

Keywords: River flow monitoring, stage-discharge relationships, OpenRiverCam, DischargeKeeper, computer vision

The work leading to these results has received funding from the German Federal Ministry of Education and Research (BMBF) and the CLIENT II program (Drought-ADAPT, FKZ: 01LZ2002B) and the European Horizon Europe Programme (2021-2027) under grant agreement no. 101086209 (TEMBO Africa). The opinions expressed in the document are of the authors only and no way reflect the European Commission’s opinions. The European Union is not liable for any use that may be made of the information.

How to cite: Winsemius, H., Peña-Haro, S., Annor, F., Hagenaars, R., Luxemburg, W., Van den Munckhof, G., Grimmeisen, F., and Van de Giesen, N.: Sources of uncertainty in video-based flow observations, revealed by co-location experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14234, https://doi.org/10.5194/egusphere-egu23-14234, 2023.

Measuring the volumetric water flow in ephemeral streams, typical of semi-arid climates, in which water rarely flows, is challenging since water only flows some days per year and some times it is in the form of flash floods. In this type of conditions it is important to detect when there is water in the stream. For this, we have implemented a machine learning algorithm for water detection and for stream gauge measurement.

Machine learning was used to differentiate pixels of the image that contains water from those those that do not via image segmentation. Different segmentation models have been proposed, but in our case we used an encoder-decoder DNN architecture based on DeepLabV3. To train the model, we used the ArtificiaL And Natural waTer-bodIes dataSet (ATLANTIS) data-set. However not all the images were used since these data-set includes classes that are not representative for our application, hence the total number of images used for training was 685. Additionally the original defined classes were merged to reduce the problem to a semantic binary segmentation problem, since our objective is to simply detect the presence of water on the stream. In addition to those images, we have used other images recorded by fix cameras looking at some ephemeral streams to improve the training.

The trained network was used to analyze 50 images with different water levels or no water. To evaluate its performance and indicator was defined which considered the number of pixels classified as water inside the image area covered by the stream over the total number of potential pixels having water, and a 60% threshold was used to determine if there is water in the stream. From the 50 images analyzed, only 3 were wrongly classified giving promising results.

This work has been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017861 and also by projects RTC2019-007159-5 and Ramon y Cajal Grant RYC2018-025580-I, funded by MCIN/AEI/10.13039/501100011033, “FSE invest in your future” and “ERDF A way of making Europe”

How to cite: Peña-Haro, S., Hernandez, D., and Cecilia, J. M.: Machine learning for water detection in ephemeral streams, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14752, https://doi.org/10.5194/egusphere-egu23-14752, 2023.

The use of modern digital technologies in water management is an important driver for obtaining better data for assessing the status of water bodies and their development. These data can be beneficially implemented for the monitoring and management of rivers and especially waterways.

In the BMDV-funded project RiverCloud, an autonomous tandem system consisting of an Unmanned Aerial Vehicle (UAV) and an Unmanned Surface Vehicle (USV) is being developed under the coordination of the gia of RWTH Aachen University, which will provide spatially and temporally high-resolution data for the development and maintenance of waterways as well as for river management. The contribution introduces the developed coupled UAV/USV tandem system with its mounted sensors for high resolution data acquisition and continuously accurate georeferencing and presents some significant results using the example of a study area on the Rhine River (Tomateninsel).

The data presented are, among others, camera-based flow measurements using an image processing method, discharge data of a precise ADCP (Acoustic Doppler Current Profiler) with 2000 kHz frequency and ten water quality parameters using a multi-parameter probe. All data mentioned were simultaneously collected in two locations of the study area on the Rhine River in September 2022. The 4 seconds videos collected by the UAV-camera were processed using an image processing method based on the surface velocity after implementing a new developed stabilisation tool. The cross-section data collected by ADCP were used for the configuration of the two sites. The agreement between ADCP and camera-based flow and discharge data was very good on both sites with less than 5% deviation for a discharge value of approx. 600 m³/s and 1.63 m/s mean velocity. The water quality parameters collected during the measuring campaign were temperature, conductivity, salinity, pH value, oxygen concentration, oxygen saturation, ammonium, turbidity, Total suspended solids (TSS) and total dissolved solids (TDS). The water quality data were in the expected ranges for river water (e.g. average values: pH 7.8, T 21.8°C, EC 0.35 mS/cm, Sal 0.71%, O₂ 7.5 mg/l, NH4⁺ 0.3 mg/l).

The results, specific requirements of the developed solution and challenges under the measuring conditions of the study area are presented in this paper. The data collected are used as the input of an overview report for river or waterway water flow and quality monitoring.

How to cite: Hansen, I., Peña-Haro, S., Lüthi, B., Weber, F.-A., Ramirez, J., Eberhardt, B., Gattung, T., Teege, J., Neumann, E., Becker, R., and Blankenbach, J.: Quantitative and Qualitative River Monitoring Using an Innovative UAV-USV Tandem System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16552, https://doi.org/10.5194/egusphere-egu23-16552, 2023.

In recent years the changing climate has resulted in an increased prevalence of extreme weather, with corresponding extreme precipitation and surface flow events. Adapting management of water and other natural resources to these conditions requires accurate and robust tools to measure water flow, and in particular the development of non-contact measurement methods.

Once such method is Infrared quantitative image velocimetry (IR-QIV), which is a large scale surface velocimetry method that uses infrared imagery to calculate the mean and instantaneous velocity at high resolution in space and time, over large spatial areas (Schweitzer & Cowen, WRR 2021). IR-QIV can operate continuously for extended periods (days, weeks, etc.) without requiring artificial illumination or particle seeding of the flow. The high resolution, continuous, measurement capabilities of IR-QIV make it particularly well suited to applications where the spatial and temporal variance of the flow must be resolved, such as fishery management, air-water heat and gas exchange, and flow-structure interaction studies.

We present metrics of turbulence, estimates of gas transfer rates, and other hydrodynamic properties calculated from velocity measurements conducted by IR-QIV at the surface of several rivers in California, and Michigan, USA. The measurements were made as part of fishery management projects, motivated by efforts to better understand and manage the interaction of migrating fish and the hydrodynamic environment. Results are validated by comparison with acoustic velocity measurements. 

How to cite: Schweitzer, S. and Cowen, E. A.: Turbulence metrics at the surface of rivers, measured by Infrared Quantitative Image Velocimetry (IR-QIV), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16919, https://doi.org/10.5194/egusphere-egu23-16919, 2023.

Human settlements and infrastructure in alluvial floodplains face erosional risk due to the lateral migration of meandering rivers. There is a large body of scientific literature on the dominant mechanisms driving river migration. However, it is challenging to make accurate forecasts of river meander evolution over multiple years. This is in part because deterministic mathematical models are not equipped to account for stochasticity in the system. Besides, uncertainty due to model deficits and unknown parameter values remains. For a more reliable assessment of risks, we therefore need probabilistic forecasts. In this work, we suggest a workflow to generate river-migration risk maps using probabilistic modeling. Forecasts for river channel position over time are generated by Monte Carlo runs, using a distribution of model parameter values inferred from satellite data, enabling us to make risk maps for river migration. We demonstrate that such risk maps are more informative in avoiding false negatives, which can be both detrimental and costly, in the context of assessing erosional hazards due to river migration. 

How to cite: Wani, O., Noh, B., Dunne, K., and Lamb, M.: Generating risk maps for river migration using probabilistic modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17240, https://doi.org/10.5194/egusphere-egu23-17240, 2023.

The usage of hydrological models is diverse and omnipresent. For practical purposes, these models are applied to, for example, flood forecasting, water allocation, and climate change impacts. Numerous methods exist to execute any modelling study. Choosing a method creates a narrative behind each model result. This implies that models are not neutral. So, how do modellers make these decisions? We conducted fourteen semi-structured interviews between September and December 2021 with nine modellers from six different water authorities and five modellers from four different consultancy companies in the Netherlands. The interviews were all recorded and transcribed. We executed an inductive content analysis on the transcriptions. We will discuss the motivation modellers have to make choices during the modelling process. With these insights, we aim to contribute to a discussion on how models, despite their unavoidable non-neutrality, can be robust and dependable to support decision making. Standardisation, e.g. automation, can be a way to achieve this. Understanding the social aspects behind the modelling process is necessary to move forward in modelling and modelling workflows, as well as being able to share and reflect on the model results including the narrative behind it.

How to cite: Remmers, J., ter Horst, R., Teuling, R., and Melsen, L.: A Modeller’s Compass: How Modellers Navigate Dozens of Decisions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-556, https://doi.org/10.5194/egusphere-egu23-556, 2023.

Most systematic bias correction approaches which are developed based on the bias of the statistical properties of interest perform well to bias correct the current climate simulations with respect to observations. However, the significance of the application of systematic bias correction approaches on the raw output of climate model simulations remains a debate due to the unavailability of future climate observation to validate the approach.

The output of a recent ultra-high resolution climate model simulation, UHR-CESM, demonstrates the best performance to simulate variability of sea surface temperature (SST) in the tropical Pacific with an exception of a small bias in mean. This knowledge encouraged us to use the outputs of the model to represent the truth both in current and future climates. We use the output of the model in response to the current climate CO₂ concentration as the representative of the current climate. While the outputs of model simulation in response to doubling and quadrupling CO₂ concentrations are used as the representative of the truth of future climates.

We bias correct monthly SST simulations for 8 (eight) Coupled Model Intercomparison Project 6 (CMIP6) over the Niño 3.4 region having the same CO₂ concentration as our reference model using a novel time-frequency continuous wavelet-based bias correction (CWBC). The results show a nearly perfect correction of distributional, trend, and spectral attributes biases in the 8 (eight) climate model simulations in the current climate and a consistent reduction of the biases in the model simulation in response to doubled CO₂ concentration. Although the overall quality of the statistical attributes is improved after the application of bias correction in response to the more extreme change of quadrupled CO₂ concentration, a degradation in the spectral attributes is observed. It shows that a systematic bias correction approach has its upper limit. Therefore, while the application of bias correction approaches is recommended prior to the further use of raw climate model simulations, up to what extent future climate simulations are reliably bias corrected should be handled carefully.

How to cite: Kusumastuti, C., Mehrotra, R., and Sharma, A.: Is there an upper extent to systematic bias correction of climate model simulations? Application to low-frequency variability within the Niño3.4 region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-579, https://doi.org/10.5194/egusphere-egu23-579, 2023.

Hydrological models play a key role in contemporary hydrological scientific research. For this study, 400+ scientific hydrological vacancies were analyzed, to evaluate whether the job description already prescribed which model must be used, and whether experience with a specific model was an asset. Of the analysed job positions, 76%  involved at least some modelling. Of the PhD positions that involved any modelling, the model is already prescribed in the vacancy text in 17%  of the cases, for postdoc positions this was 30%. A small questionnaire revealed that also beyond the vacancies where the model is already prescribed, in many Early-Career Scientist (ECS) projects the model to be used is pre-determined and, actually, also often used without further discussion. There are valid reasons to pre-determine the model in these projects, but at the same time, this can have long-term consequences for the ECS: experience with the model will influence the research identity the ECS is developing, and might influence future opportunities of the ECS - it might be strategic to gain experience with popular, broadly used models, or to become part of an efficient modelling team. This serves an instrumental vision on modelling. Seeing models as hypotheses calls for a more critical evaluation. We can educate ECS the current rules of the game, while at the same time actively stimulate critically questioning these rules.

How to cite: Melsen, L.: Recruitment of early career scientists for hydrological modelling positions: implications for model progress, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-904, https://doi.org/10.5194/egusphere-egu23-904, 2023.

Model intercomparison studies are carried out to test and compare the simulated outputs of various model setups over the same study domain. The Great Lakes region is such a domain of high public interest as it not only resembles a challenging region to model with its trans-boundary location, strong lake effects, and regions of strong human impact but is also one of the most densely populated areas in the United States and Canada. This study brought together a wide range of researchers setting up their models of choice in a highly standardized experimental setup using the same geophysical datasets, forcings, common routing product, and locations of performance evaluation across the 1x10⁶ km² study domain. The study comprises 13 models covering a wide range of model types from Machine Learning based, basin-wise, subbasin-based, and gridded models that are either locally or globally calibrated or calibrated for one of each of six predefined regions of the watershed. This study not only compares models regarding their capability to simulated streamflow (Q) but also evaluates the quality of simulated actual evapotranspiration (AET), surface soil moisture (SSM), and snow water equivalent (SWE).

The main results of this study are:

• The comparison of models regarding streamflow reveals the superior quality of the Machine Learning based model in all experiments performed.
• While the locally calibrated models lead to good performance in calibration and temporal, they lose performance when they are transferred to locations the model has not been calibrated on.
• The regionally calibrated models exhibit low performances in highly regulated and urban areas as well as agricultural regions in the US.
• Comparisons of additional model outputs against gridded reference datasets show that aggregating model outputs and the reference dataset to basin scale can lead to different conclusions than a comparison at the native grid scale.
• A multi-objective-based analysis of the model performances across all variables reveals overall excellent performing locally calibrated models as well as regionally calibrated models.
• Model outputs and observations produced and used in this study are available on an interactive website (www.hydrohub.org/mips_introduction.html#grip-gl) and on FRDR (http://www.frdr-dfdr.ca).

How to cite: Mai, J., Shen, H., Tolson, B., Gaborit, É., Arsenault, R., Craig, J., Fortin, V., Fry, L., Gauch, M., Klotz, D., Kratzert, F., O'Brien, N., Princz, D., Rasiya Koya, S., Roy, T., Seglenieks, F., Shretha, N., Temgoua, A. G., Vionnet, V., and Waddell, J.: The Great Lakes Runoff Intercomparison Project (GRIP-GL), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-968, https://doi.org/10.5194/egusphere-egu23-968, 2023.

Conceptual hydrological models are irreplaceable tools for large-scale (i.e., from regional to global) hydrological predictions. Large-scale modeling studies typically strive to employ one single model structure regardless of the diversity of catchments under study. However, little is known on the optimal model complexity for large-scale applications. In a modeling experiment across 700 catchments in the contiguous United States, we analyze the performance of a conceptual (bucket style) distributed hydrological model with varying complexity (5 model versions with 11–45 parameters) but with exactly the same inputs and spatial and temporal resolution and implementing the same regional parameterization approach. The performance of all model versions compares well with those of contemporary large-scale models tested in the United States, suggesting that the applied model structures reasonably account for the dominant hydrological processes. Remarkably, our results favor a simpler model structure where the main hydrological processes of runoff generation and routing through soil, groundwater, and the river network are conceptualized in distinct but parsimonious ways. As long as only observed runoff is used for model validation, including additional soil layers in the model structure to better represent vertical soil heterogeneity seems not to improve model performance. More complex models tend to have lower model performance and may result in rather large uncertainties in simulating states and fluxes (soil moisture and groundwater recharge) in model ensemble applications. Overall, our results indicate that simpler model structures tend to be a more reliable choice, given the limited validation data available at large scale.

How to cite: Merz, R., Miniussi, A., Basso, S., and Tarasova, L.: More Complex is Not Necessarily Better in Large-Scale Hydrological Modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2008, https://doi.org/10.5194/egusphere-egu23-2008, 2023.

The eWaterCycle platform introduced in 2022 (https://doi.org/10.5194/gmd-15-5371-2022) provides hydrologists with an online platform to conduct numerical studies involving hydrological models. It allows hydrologists to work with each other's data and datasets directly from a webbrowser. The workflow of the experiment done is clearly visible, reproducible and easily adaptable because of how eWaterCycle separates the model (the algorithm) used from the experiment done with the model. eWaterCycle is designed such that research conducted on the platform is ‘FAIR by design’. Using eWaterCycle, studies can be done in less time, more transparently and by more junior members of the hydrological community than was possible a few years ago. 

In this presentation, we will explain the capabilities of the eWaterCycle platform and show them by describing recently (published) works of MSc and PhD members of our team, including a model coupling study, a large sample hydrology study and a climate impact assessment study.

How to cite: Hut, R., Aerts, J., Wiersma, P., Hoogelander, V., van de Giesen, N., Drost, N., Kalverla, P., van Werkhoven, B., Verhoeven, S., Alidoost, F. (., Vreede, B., and Liu, Y.: The eWaterCycle platform for open and FAIR hydrological collaboration, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5702, https://doi.org/10.5194/egusphere-egu23-5702, 2023.

Historically, snow physics models were developed to forecast avalanches. Over the years, their application has broadened to hydrological, climatological, ecological and permafrost studies to cite but a few. However, the structure of mid-latitude mountain snowpacks upon which snow physics models are based (generally deep snowpack with snow denser at the bottom than at the top because of compaction) differs considerably from the structure of high latitude snowpacks (generally shallow snowpack with dense wind-compacted snow at the top and large snow crystals at the bottom). This difference has been known for decades to be a potentially large source of uncertainty when simulating heat exchanges in the Arctic and Antarctic. Therefore, with Arctic warming having consequences on the global climate, why have snow physics modellers not developed a model with a high latitude or “arctic snowpack” yet? Taking this question as a case-study to understand the role that subjective decisions play at every phase of model developments, we interviewed more than twenty snow physics model users (e.g. ecologists, anthropologists, remote sensing and climate scientists) and developers to understand the following: what motivates model developments? What or who determines which parametrization, which process is to be prioritised over others? What role does the research question play? What about funding or staff availability? We will show that positionality, anchoring bias and interpersonal relationships play far more prominent roles in the physical sciences that commonly acknowledged and will draw lessons from the social sciences to increase transparency in our modelling practice.

How to cite: Ménard, C., Rasmus, S., and Merkouriadi, I.: What motivates model developments? A multi-perspective case study from snow physics models., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7800, https://doi.org/10.5194/egusphere-egu23-7800, 2023.

The reliability of rainfall-runoff models in reproducing hydrological drought events is of primary importance for multiple applications (e.g. water resource management or agricultural risk assessment), especially in a context of expected future water scarcity. Typical model performance metrics are often not enough to assess the accuracy in the simulation of droughts. In fact, it is necessary to consider drought-specific indices taking into account, e.g., low flow characteristics, duration and deficit volumes as well as their seasonality and timing. Understanding which hydrological processes are (or are not) adequately modeled and why, in respect to such drought-specific performances, allows to assess the strengths and weaknesses of each model and may provide guidance on how to improve model set-up and its reliability.

Through the application of a conceptual semi-distributed model on a set of Alpine basins, the aim of this preliminary work is to analyse the relationship between drought-specific performance metrics, basin characteristics and model parameters. In particular, the specific influence of the different model state variables (e.g. snow water equivalent, evapotranspiration and soil moisture) on the reproduction of drought events is investigated.

The model used is a semi-distributed modelling framework based on the airGR rainfall-runoff models (Coron et al. 2017), applied through the R package airGRiwr (Dorchies 2022). The case study is a set of Alpine catchments, characterised by a high degree of “nestdness” which allows to fully implement the semi-distributed model structure and to perform its diagnosis.

The major advantage of a semi-distributed model, if properly set-up, is its ability to differentiate hydrological dynamics between the sub-catchments. In mountainous basins, for instance, simulating in a separate way the upstream headwater sub-catchments may substantially improve the accuracy in the simulation of snow storage and melting, which strongly affect the occurrence and timing of drought events. For this reason, the work will also analyse the benefits of an increasing spatial resolution of the semi-distributed set-up of the model, comparing the outcomes obtained when sequentially calibrating the model in a semi-distributed fashion on the upstream sub-catchments in respect to the baseline of a lumped configuration.

References

Coron, L., Thirel, G., Delaigue, O., Perrin, C. and Andréassian, V. (2017). The Suite of Lumped GR Hydrological Models in an R package. Environmental Modelling and Software, 94, 166-171, doi: 10.1016/j.envsoft.2017.05.002.

David Dorchies (2022). airGRiwrm: 'airGR' Integrated Water Resource Management. R package version 0.6.1. https://CRAN.R-project.org/package=airGRiwrm

How to cite: Neri, M. and Toth, E.: On the accurate simulation of hydrological droughts in Alpine regions: investigating the multiple role of rainfall-runoff model dynamics and basin characteristics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8153, https://doi.org/10.5194/egusphere-egu23-8153, 2023.

The virtual research environment V-FOR-WaTer provides functionalities to store and access hydrological and other environmental data from various sources and disciplines. We propose a framework to run containerized tools within the V-FOR-WaTer toolbox, that is intended to solve the problem of combining software or scripts developed in different programming languages.

The framework is used to manage Docker containers, which can contain software like tools for data analysis or environmental modeling. Alongside the well-known advantages of containerization, such as development speed and efficiency, isolation from the local system, dependency management and portability, the usage of containers also ensures a high degree of reproducibility.

Given a scientific context, containers are especially useful to combine scripts in different languages following different development paradigms. To do so, we developed a framework-agnostic container specification which standardizes inputs and outputs from and to containers to ease the development of new tools. As of now we also provide templates for tools developed in Python, R, Octave and NodeJS.

We present an exemplary workflow for the CATFLOW hydrological model. Data from the V-FOR-WaTer environment is loaded using a Python tool and preprocessed with an existing R tool. After running the FORTRAN model, existing tools in Python, R and MATLAB are used for analysis and presentation of results. When executing the workflow, the user does not need to be familiar with the different programming languages of individual tools, since the containerized tools are self-contained by definition.

How to cite: Dolich, A., Mälicke, M., Manoj J, A., Wienhöfer, J., and Zehe, E.: Using Docker in environmental research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8553, https://doi.org/10.5194/egusphere-egu23-8553, 2023.

For scientific products to be considered actionable for stakeholder purposes they must meet certain epistemic and contextual conditions of adequacy. In evaluating the adequacy of a scientific product derived from Earth system models for actionable purposes—such as adaptation or resilience planning— there is a tendency to engage in the evaluation of raw model output and subject it to postprocessing to gain desired reliability and fitness. However, this reductive approach and focus on data ignores questions of whether the simulations, model configurations, and representational features of the models are themselves adequate and reliable for the actionable applications. This talk will lay out the reasons why we need to shift our practices to evaluating models and their products in a more holistic manner and provides insight into a framework for doing so. Scientific models—in this case Earth system models—are constructed with certain purposes and research questions in mind. These purposes, and more detailed research questions, engender representational values, which are reflections of what we want to know and why we want to know it. When model development is informed by these representational values underlying our questions and purposes, they are determinants of the decisions made during model construction about what we choose to represent and how we choose to represent it. The consequence is that the models constructed reflect these representational values and occupy a representational perspective, one that is fit for answering the questions and purposes that governed its development, but not those questions and applications that lie outside that perspective. To avoid increasing epistemic risk when using models for actionable purposes, which can result in downstream social harms, we need to assess the adequacy and reliability of our instruments and their products further upstream, in terms of consistency between the representational values that are embedded in the model in virtue of its development pathway and those that are implied in the actionable science questions the model could be applied to answer. More holistic, tailored assessments will allow us to avoid increases in epistemic risk due to how stakeholder representational values and conditions of adequacy can be inconsistent with those values being reflected in the representational content of the model being employed.

How to cite: Morrison, M.: Adequacy and Reliability of Earth System Models: Actionable Purposes, Model Inadequacy and Epistemic Risk, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8858, https://doi.org/10.5194/egusphere-egu23-8858, 2023.

The COVID-19 pandemic has shown the importance of modeling in guiding decision-making for governments and society, and the significant influence that modelers hold, especially during times of crisis. Water modelers may also encounter similar situations where their models are caught up in political debates, shaping people's everyday lives. 

This paper discusses the cultural and professional norms around water modeling practice that need to be established or revisited in order to make modeling work more responsible, through a review of models developed for COVID-19. It introduces six areas of study for "responsible water modeling" that can advance future theoretical and practical discussions on the topic: (1) building a common appreciation of the concept of responsibility, (2) interactions between science and policy, (3) the influence of boundary judgments on the model's outcome, (4) the politics of uncertainty, (5) stakeholder involvement, and (6) integration and coordination

The paper suggests that by focusing on these subjects, the fundamental principles and characteristics of responsible modeling can be established in order to address and respond to water challenges while also serving the public good.

How to cite: Nabavi, E.: Navigating Responsible Water Modeling in the Wake of COVID-19, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9710, https://doi.org/10.5194/egusphere-egu23-9710, 2023.

Good modelling practice has many requirements. Above all, the process should be complete and transparent enough so that the credibility of its conclusions can be comprehended, or even assessed, by its intended audience. And the more complex, uncertain and cross-sectoral the problem being modelled, or potentially devastating its consequences may be, the more the need for good practice. Consequently, good modelling practice is essential in addressing not just climate change issues, but also cross-sectoral issues such as occurs with water, energy, agriculture and the socio-economy. Yet despite widespread acknowledgment of the grand socio-environmental challenges facing the planet, practices as seen in the major literature largely remain meagre, and most often are pathetically inadequate.

The presentation begins with a list of specific technical complaints around poor practice, ones that could be easily remedied by modellers, to concede this unnecessary state of affairs. We argue for a suitable ontology around concepts for anchoring good modelling practice, including trustworthiness, assurance, robustness, reproducibility and credibility, along with fitness-for-purpose notions of usability, reliability and feasibility. We also emphasize the often-overlooked role of human factors in the modelling process, including assumptions and choices made by the modeller, and consider how consequent biases or uncertainties can be reduced. We then synthesize the steps in the modelling process as recognized in the scientific and grey literature, and provide examples of checklists of questions that merit addressing for each step. Many of these questions prompt consideration of methodological choices, especially around uncertainty and scale. Good modelling practice warrants greater transparency in documenting, justifying and, wherever possible, comparing methodological choices and related assumptions. We argue that the level of robustness to choices be made clearer.

The modelling community must however address how to advance modelling so that good practice becomes not just well-known but common practice. Instruments for achieving this are posited around: regulation by journals in terms of standards that they require for relevant papers published; developing incentives for following good practice; promoting an institutional/community culture around it, and expanding education and capacity building in modelling that focusses from the start on good practice as being fundamental.

How to cite: Jakeman, A., Elsawah, S., and Hamilton, S.: Instrumenting good modelling practice as common practice, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10230, https://doi.org/10.5194/egusphere-egu23-10230, 2023.

Many hydrological modelling groups face similar challenges, with untapped opportunities to share code and concepts across different model development groups. An active community of practice is emerging, where the focus is not so much on developing a community hydrological model, and more on advancing the science and practice of community hydrological modelling. This presentation will summarize our recent efforts to develop open-source models, methods, and datasets to enable process-based hydrological prediction across large geographical domains. This presentation summarizes our recent efforts to advance the science and practice of hydrological modelling, focusing on recent work to (1) develop multi-source probabilistic hydrometeorological forcing datasets on continental and global domains; (2) advance a flexible approach to represent a myriad of physical processes in a unified modelling framework; (3) improve the numerical robustness and efficiency of large-domain terrestrial system model simulations; and (4) develop extensible and reproducible modeling workflows. The presentation will highlight major scientific challenges, future research needs, and some key opportunities for community collaboration.

How to cite: Clark, M., Knoben, W., Tang, G., van Beusekom, A., Arnal, L., and Spiteri, R.: Improving the science and practice of hydrological modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10527, https://doi.org/10.5194/egusphere-egu23-10527, 2023.

In several hydrological studies the need for consistency in hydrological modeling was highlighted. To achieve model consistency, it is required that all relevant hydrological processes are evaluated for accuracy in their spatio-temporal representation under consideration of available observations. In this study, we transfer the idea of hydrological consistency to water quality modeling. We focus on water quality modelling in rural mesoscale catchments and the interaction with agricultural production systems and their management. Based on several studies, we have developed a guideline which includes the following six challenges:

• Representation of rural landscape: Spatial and temporal patterns of land use and land management are critical to adequately represent water quality in models. Remote sensing and land use models are very useful resources to be exploited.
• Accuracy in model structure and model parameters: The transfer of a model diagnostic analysis to water quality leads to a better understanding of how water quality variables are controlled by model structures and corresponding model parameters.
• Check of multiple model output for consistency: Assessing multiple model outputs regarding their temporal, spatial and process performance using observed time series, remotely sensed spatial patterns, knowledge about transport pathways and even soft data can significantly enhance model consistency.
• Joint multi-metric calibration of discharge and water quality for all magnitudes: Multi-metric calibration using performance metrics and signature measures both for discharge and water quality, such as flow and nitrate duration curve, leads to more balanced model simulations that represent all magnitudes of discharge and water quality accurately.
• Scenarios and storylines for reliable land management: Scenarios and storylines should be co-developed with stakeholders in the river basin to increase realism and the acceptance of model results. They should be coherent in space and time, and provide a mix of available management options.
• Consistent interpretation of impacts on water quality: The interpretation of scenarios can be supported by diagnostic tools to show the effectiveness of measures and their combinations while considering their costs and impacts on ecosystem services.

In our contribution, we give examples and further details regarding each challenge to give insights how to achieve consistency in water quality modelling.

How to cite: Kiesel, J., Fohrer, N., Wagner, P. D., Haas, M., and Guse, B.: A guideline for consistent water quality modeling in rural areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11062, https://doi.org/10.5194/egusphere-egu23-11062, 2023.

Everyone wants their hydrologic models to be as good as possible. But how do we know if a model is accurate or not? In the spirit of rigorous and reproducible science, the answer should be: we calculate metrics. Yet, as humans, we sometimes follow a scheme of "I know a good model when I see it" and manually inspect hydrographs to assess their quality. This is certainly a valid method for sanity checks, but it is unclear whether these subjective visual ratings agree with metric-based rankings. Moreover, the consistency of such inspections is unclear, as different observers might come to different conclusions about the same hydrographs.

In this presentation, we report a large-scale study where we collected responses from 622 experts, who compared and judged more than 14,000 pairs of hydrographs from 13 different models. Our results show that overall, human ratings broadly agree with quantitative metrics in a clear preference for a Machine Learning model. At the level of individuals, however, there is a large amount of inconsistency between ratings from different participants. Still, in cases where experts agree, we can predict their most likely rating purely from qualitative metrics. This indicates that we can encode intersubjective human preferences with a small set of objective, quantitative metrics. To us, these results make a compelling case for the community to put more trust into existing metrics—for example, by conducting more rigorous benchmarking efforts.

How to cite: Gauch, M., Kratzert, F., Gilon, O., Gupta, H., Mai, J., Nearing, G., Tolson, B., Hochreiter, S., and Klotz, D.: Peeking Inside Hydrologists' Minds: Comparing Human Judgment and Quantitative Metrics of Hydrographs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12261, https://doi.org/10.5194/egusphere-egu23-12261, 2023.

Hydrological models are crucial to understand water systems and perform impact assessment studies. However, these models require a lot of accurate data, especially if the model is spatially distributed. However, sufficiently accurate datasets while available, for example from earth-observations, need to be converted into model-specific, sometimes idiosyncratic, file formats. Therefore, hydrological models require various steps to process raw input data to model data which, if done manually, makes the process time consuming and hard to reproduce. Hence, there is a clear need for automated model instance setup for increased transparency and reproducibility in hydrological modeling.

HydroMT (Hydro Model Tools) is an open-source Python package (https://github.com/Deltares/hydromt) that aims to make the process of building hydrological model instances and analyzing their results automated and reproducible. Compared to many other packages for automated model instance setup, HydroMT is data- and model-agnostic, meaning that data sources can easily be interchanged without additional coding and the generic model interface can be used for different model software. This makes it possible to reuse workflows to prepare input from different datasets or for different model software that require the same parameter (e.g. Manning roughness derived from land use maps) and thereby supporting controlled model intercomparison and sensitivity experiments. 

In this contribution we show the application of HydroMT for flood hazard modeling using the distributed hydrological Wflow model and the reduced-physics hydrodynamic SFINCS model, both open-source models. We use HydroMT to setup a controlled and reproducible model experiment. We test the sensitivity of both models to various data sources used- and assumptions taken in the model instance building process and compare the skill to simulate peak discharge. Using this application, we discuss the merits and limitations of HydroMT and next steps toward FAIR hydrological modeling.

How to cite: Boisgontier, H., Eilander, D., Bouaziz, L., Buitink, J., Couasnon, A., de Goede, R., Hegnauer, M., Leijnse, T., and van Verseveld, W.: Towards FAIR hydrological modeling with HydroMT, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13770, https://doi.org/10.5194/egusphere-egu23-13770, 2023.

Skillful today, inept tomorrow. Today's hydrological models have pronounced and complex error dynamics (e.g., small, highly correlated errors for low flows and large, random errors for high flows). Modellers generally accept that simple, variance based evaluation criteria — like the Nash-Sutcliffe Efficiency (NSE) — are not fully able to capture these intricacies. The (implied) consequences of this are however seldom discussed.

This contribution examines how evaluating the model over two data partitions (above and below a chosen threshold) relates to a global model evaluation of both partitions combined (i.e., the usual way of computing the NSE). For our experiments we manipulate dummy simulations with gradient descent to approximate specific NSE values for each partition individually. Specifically, we set the NSE for runoff values that fall below the threshold, and vary the NSE of the simulations above the threshold as well as the threshold itself. This enables us to study how the global NSE relates to the partition NSEs and the threshold. Intuitively, one would wish that the global NSE somehow reflects the performance on the partitions in a comprehensible manner. We do however show that this relation is not trivial.

Our results also show that subdividing the data and evaluating over the resulting partitions yields different information regarding model deficiencies than an overall evaluation. The downside is that we have less data to estimate the NSE. In the future we can use this for model selection and diagnostic purposes.

How to cite: Klotz, D., Gauch, M., Nearing, G., Hochreiter, S., and Kratzert, F.: The persistence of errors: How evaluating models over data partitions relates to a global evaluation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15221, https://doi.org/10.5194/egusphere-egu23-15221, 2023.

Various models are available to hydrologists, including models of different structures, spatial and temporal discretisation, or multiple parameter sets of a single model. But the "trustworthiness" of these models is called into doubt when they reproduce runoff equally well in the calibration period (equifinality), but diverge in their simulation outputs outside this period. A common way to account for modelling uncertainty is to use so-called ensembles that combine several model members. However, it has been debated/discussed that models that do not provide “the right answers for the right reasons” and, consequently, yield poor performance in a prediction or forecasting mode, should be omitted from such ensembles. Various evaluation protocols aimed at detecting such models have emerged over the years, however, this remains an open research question, and more research is needed especially in the context of shifting hydrologic regimes in a changing climate.

Adopting the consistency in model performance in reproducing runoff as an additional criterion to select among multiple models emerges as a plausible way to identify the most “trustworthy” ones. We propose an approach that relies on detailed analyses of model performance across subperiods of increasing length contained within the calibration period. A good performance in both short and longer subperiods is crucial as the former can be quite extreme (e.g., extremely dry or wet), while the latter “expose” a model to various hydroclimatic conditions. To analyse the consistency in model performance, an efficiency measure (e.g., the Kling-Gupta coefficient, KGE) can be computed in each subperiod, and each model can be ranked in each subperiod according to the measure. Models yielding the most consistent and the highest performance can then be selected either (1) as a certain percentage of models with the highest rank averaged across all subperiods, or (2) by imposing a rank threshold that has to be reached in every subperiod. We here further propose to additionally evaluate the selected subset of consistent and high-performing models over an independent period using various other performance indicators (e.g., Nash-Sutcliffe coefficient or volumetric efficiency) as well as model ability to reproduce hydrological signatures (e.g., mean, high and low flows, or runoff dynamics). The evaluation performance of the selected models can then be compared to the best (reference) model obtained from the calibration over the full calibration period with the selected efficiency measure (here KGE) as the objective function.

To showcase the advantages of the proposed approach, it is here applied to two different models (3DNet-Catch and GR4J) each with 20,000 randomly sampled parameter sets in three unimpaired catchments. In addition to the promising results, the proposed approach is characterised by its ease-of-use and flexibility, i.e., it can be implemented with any ensemble of models (e.g., randomly selected parameter sets of a single model, or different models created e.g., from a modular framework), or with any other aspect of model performance.

How to cite: Todorović, A. and Teutschbein, C.: Consistency in Model Performance as a Criterion for Trustworthy Hydrological Modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15300, https://doi.org/10.5194/egusphere-egu23-15300, 2023.

Model and data are essential for current geoscientific research. Too many hydrological models are available for potential modelers, plus too much spatial terrestrial data related to modeling is accessible to users. More importantly, reproducibility is one of the key features in science,  which is barely discussed in hydrological models. Two significant reasons are that (1) the various hydrological models are incompatible since they require different variables, even if some of them share the same terminology, and (2) the complexity of model structure makes it impossible to deploy a model swiftly in any new research area. 
Our project is to establish a Global Hydrological Data Cloud (GHDC, https://shuddata.com) providing essential terrestrial variables for generic hydrological modeling, as modelers provide the watershed boundary and model requests. The data retrieved from the GHDC covers terrain, topology, soil/geology, landuse, hydraulic parameters and meteorological time-series data. The demonstration of three watershed examples with the Simulator of Hydrologic Unstructured Domains (SHUD),  can be a standard paradigm for physically-based hydrological modeling and instructive for other modeling processes, as the procedures are transferable to other hydrological models and regions. 

How to cite: Shu, L., Chang, Y., Meng, X., Ullrich, P., Duffy, C., Chen, H., Lyu, S., Zhang, Y., and Li, Z.: Open, Quick and Reproducible Hydrological Model Deployment Cloud Platform, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16869, https://doi.org/10.5194/egusphere-egu23-16869, 2023.

In the analysis regarding the stability of river dikes, the interactions between the load magnitude of the flood level and the resulting percolation are found to be a highly relevant process. After all, the seepage line separates the cross-sectional area into the water-saturated and the unsaturated crosssectional parts. For homogeneous levees, the position of the seepage line in the stationary case is imprinted in the system by the outer cubature and is well on the safe side for real flood events. In the non-stationary case, the position of the seepage line depends primarily on the changing water level of a flood hydrograph, the resulting water content and suction stresses in the dike, as well as the saturated permeability of the dike construction materials. In the current dimensioning practice according to DIN 19712 and the German DWA-M-507, the characteristic of the hydrograph is not directly applied. So far, for example, the resulting damming duration of a flood hydrograph is only considered indirectly.
This paper presents a methodology, which quantifies natural dependency structures for a selected dike section by synthetically generated dimensioning hydrographs in a probabilistic design. These results are then integrated directly into the geohydraulic process of water penetration. Based on selected water level and discharge time series at a dike section, flood waves can be described in five parameters using the extended flood characteristic simulation according to MUNLV¹. After successfully adapting suitable distribution functions, dependencies in the load structure are quantified in the next step using Copula function. Subsequently, any number of synthetic flood hydrographs can be generated by combining these parameters. In keeping with the principle of the Monte Carlo simulation, a sufficiently high number of synthetic events results in extreme conditions with a low probability of occurrence being reliably represented.
Using a developed routine, the process of moisture penetration for the individual flood hydrographs can be simulated and visualized in a transient, geohydraulically numerical model at different points in times. Finally, statements regarding the behavior patterns of the resulting seepage lines, based on the loading situation can be derived and predicted. Based on these results, a reliability analysis then shows the stability of the dike section under the given extreme conditions.

¹Ministerium für Umwelt, Landwirtschaft, Natur und Verbraucherschutz des Landes Nordrhein-Westfalen

How to cite: Öttl, M. A., Bender, J., and Stamm, J.: Probabilistic analysis of river levees under consideration of time-dependent loads, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5, https://doi.org/10.5194/egusphere-egu23-5, 2023.

We propose Physics Informed Machine Learning (PIML) algorithms to estimate surface soil moisture from Sentinel-1/2 satellite images based on Artificial Neural Networks (ANN). We have used Improved Integral Equation Model (I2EM) to simulate the radar images backscatter in VV polarisation. In addition, we selected a set of different polarisations, i.e.; (VH, VH/VV, VH-VV), incidence angle, Normalised Difference Vegetation Index (NDVI), and topography as input features to map surface soil moisture. We have used two different approaches to predict soil moisture using PIML. In the first approach, we developed an observation bias in which we selected the difference of backscatter value at each pixel in VV polarisation from satellite and derived from theoretical model derived as one of the input features. Our second approach is based on learning bias, in which we modified the loss function with the help of the I2EM model. Our result shows the learning bias PIML outperforms the observation bias PIML with R = 0.94, RMSE = 0.019 m³/m³, and bias = -0.03. We have also compared the performance with the standalone benchmark algorithms. We observed the learning bias PIML emerged as the most accurate model to estimate the surface soil moisture. The proposed approach is a step forward in estimating accurate surface soil moisture at high spatial resolution from remote sensing images.

How to cite: Singh, A. and Gaurav, K.: A physics-informed machine learning approach to estimate surface soil moisture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-487, https://doi.org/10.5194/egusphere-egu23-487, 2023.

The use of “hybrid” models that combine elements from physics-based and data-driven modelling approaches has grown in popularity and acceptance in recent years, but these models also present a number of challenges that must be addressed in order to ensure their effectiveness and reliability. In this project, we propose a toolbox of methods based on information theory as a step towards a unified framework for the diagnostic evaluation of “hybrid" models. Information theory provides a set of mathematical tools that can be used to study input data, model architecture and predictions, which can be helpful in understanding the performance and limitations of “hybrid” models.

Through a comprehensive case study of rainfall-runoff hydrological modelling, we show how a very simple physics-based model can be coupled in different ways with neural networks to develop “hybrid” models. The proposed toolbox is then applied to these “hybrid” models to extract insights which guide towards model improvement and refinement. Diagnostic scores based on the entropy (H) of individual predictions and the Kullback-Leibler divergence (KLD) between predictions and observations are introduced. Mutual information (I) is also used as a more all-encompassing metric which informs on the aleatory and epistemic uncertainties of a particular model. In order to address the challenge of calculating quantities from information theory on continuous variables (such as streamflow), the toolbox takes advantage of different estimators of differential entropy, namely: binning, kernel density estimation (KDE) and k-nearest neighbors (k-NN).

How to cite: Álvarez Chaves, M., Guthke, A., Ehret, U., and Gupta, H.: UNITE: A toolbox for unified diagnostic evaluation of physics-based, data-driven and hybrid models based on information theory, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4039, https://doi.org/10.5194/egusphere-egu23-4039, 2023.

We introduce and illustrate our recently developed Augmented Information Physical Systems Intelligence (AIPSI), leveraging and enhancing our proprietary Information Physical Artificial Intelligence (IPAI) and Earth System Dynamical Intelligence (ESDI) to further the mathematically robust, physically consistent and computationally efficient holistic articulation and integration across the latest advances in fundamental physics, geophysical sciences and information technologies.

In theoretical terms, AIPSI brings out a more general principled lingua franca and formal construct to complex system dynamics and analytics beyond traditional hybridisation among stochastic-dynamic, information-theoretic, artificial intelligence and mechanistic techniques.

In practical terms, it empowers improved high-resolution spatiotemporal early detection, robust attribution, high-performance forecasting and decision support across multissectorial theatres of operation pertaining multiple interacting hazards, natural, social and hybrid.

With operational applications in mind, AIPSI methodologically improves the sharp trade-off between speed and accuracy of multi-hazard phenomena sensing, analysis and simulation techniques, along with the quantification and management of the associated uncertainties and predictability with sharper spatio-temporal resolution, robustness and lead.

This is further supported by the advanced Meteoceanics QITES constellation providing coordinated volumetric dynamic sensing and processing of gravitational and electrodynamic fluctuations, thereby providing an instrumentation ecosystem for anticipatory early detection of extreme events such as flash floods, explosive cyclogenesis and imminent disruptive structural critical transitions across built and natural environments.

With the methodological developments at hand, a diverse set of applications to critical theatres of operation are presented, ranging from early detection, advance modelling and decision support to environmental and security agencies entrusted with the protection and nurturing of our society and the environment. Contributing to empowering a more robust early detection, preparedness, response, mitigation and recovery across complex socio-environmental hazards such as those involving massive wildfires, floods and their nonlinear compound interplay, their underlying mechanisms and consequences.

The presentation concludes with an overview of a new large-scale international initiative on multi-hazard risk intelligence networks, where an eclectic diversity of actors ranging from academia and industry to institutions and the civil society come together to co-create emerging pathways for taking this challenging quest even further, in a fundamental coevolution between cutting-edge science, groundbreaking technology and socio-environmental insights to further enrich the ever-learning system dynamic framework at the core of our multi-hazard research and service.

Acknowledgement: This contribution is funded by the Εuropean Union under the Horizon Europe grant 101074004 (C2IMPRESS).

How to cite: Perdigão, R. A. P. and Hall, J.: Augmented Information Physical Systems Intelligence (AIPSI) for enhanced spatiotemporal early detection, attribution, prediction and decision support on multi-hazards, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6617, https://doi.org/10.5194/egusphere-egu23-6617, 2023.

Globally, agriculture irrigation accounts for 70% of water use and is facing extensive and increasing water constraints. Well-designed irrigation scheduling can help determine the appropriate timing and water requirement for crop development and consequently improve water use efficiency. This research aims to assess the probability of irrigation needed for agricultural operations, considering soil moisture, evaporation, and leaf area index as indicators of crop water requirement. The decision on irrigation scheduling is taken based on a three-step methodology. First, relevant variables for each indicator are identified using a Random Forest regressor, followed by the development of a Long Short-Term Memory (LSTM) model to predict the three indicators. Second, errors in the simulation of each indicator are calculated by comparing the predicted values against the actual values, which are then used to calculate the error weights (normalized) of the three indicators for each month (to capture the seasonal variations). Third, the empirical distribution of each indicator is obtained for each month using the estimated error values, which are then adjusted based on the error weights calculated in the previous step. The probabilities of three threshold values (for each indicator) are considered, which correspond to three levels of irrigation requirement, i.e., low, medium, and high. The proposed approach provides a probabilistic framework for irrigation scheduling, which can significantly benefit farmers and policymakers in more informed decision-making related to irrigation scheduling.

How to cite: Srivastava, S., Kumar, N., Malakar, A., Choudhury, S. D., Ray, C., and Roy, T.: An ML-based Probabilistic Approach for Irrigation Scheduling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8388, https://doi.org/10.5194/egusphere-egu23-8388, 2023.

Inference of causality and understanding of extreme events are two intensively developing multidisciplinary areas highly relevant for the Earth sciences. Surprisingly, there is only a limited interaction of the two research areas.

Quantification of causality in terms of improved predictability was proposed by the father of cybernetics N. Wiener [1] and formulated for time series by C.W.J. Granger [2]. The Granger causality evaluates predictability in bivariate autoregressive models. This concept has been generalized for nonlinear systems using methods rooted in information theory [3]. The information theory of Shannon, however, usually ignores two important properties of Earth system dynamics: the evolution on multiple time scales and heavy-tailed probability distributions. While the multiscale character of complex dynamics, such as the air temperature variability, can be studied within the Shannonian framework in combination with the wavelet transform [4], the entropy concepts of Rényi and Tsallis have been proposed to cope with variables with heavy-tailed probability distributions. We will discuss how such non-Shannonian entropy concepts can be applied in inference of causality in systems with heavy-tailed probability distributions and extreme events. Using examples from the climate system, we will focus on causal effects of the North Atlantic Oscillation, blocking events and the Siberian high on winter and spring cold waves in Europe, including the April 2021 frosts endangering French vineyards. Using the non-Shannonian information-theoretic concepts we bridge the inference of causality and understanding of the occurrence of extreme events.

Supported by the Czech Academy of Sciences, Praemium Academiae awarded to M. Paluš.

[1] N. Wiener, in: E. F. Beckenbach (Editor), Modern Mathematics for Engineers (McGraw-Hill, New York, 1956)

[2] C.W.J. Granger, Econometrica 37 (1969) 424

[3] K. Hlaváčková-Schindler  et al., Phys. Rep. 441 (2007)  1; M. Paluš, M. Vejmelka, Phys. Rev. E 75 (2007) 056211; J. Runge et al., Nature Communications 6 (2015) 8502

[4] M. Paluš, Phys. Rev. Lett. 112 (2014) 078702; N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Paluš, Geophys. Res. Lett. 43(2) (2016) 902–909

How to cite: Paluš, M.: Non-Shannonian information theory connects inference of causality and understanding of extreme events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10707, https://doi.org/10.5194/egusphere-egu23-10707, 2023.

This research investigated the applicability of a probabilistic physics-informed Deep Learning (DL) algorithm, i.e.,deep autoregressive network (DeepAR), for rainfall-runoff modeling across the continental United States (CONUS). Various catchment physical parameters were incorporated into the probabilistic DeepAR algorithm with various spatiotemporal variabilities to simulate rainfall-runoff processes across Hydrologic Unit Code 8 (HUC8). We benchmarked our proposed model against several physics-based hydrologic approaches such as Sacramento Soil Moisture Accounting Model (SAC-SMA), Variable Infiltration Capacity (VIC), Framework for Understanding Structural Errors (FUSE), Hydrologiska Byråns Vattenbalansavdelning (HBV), and the mesoscale hydrologic model (mHM). These approaches were implemented using Catchment Attributes and Meteorology for Large-sample Studies (CAMELS), Maurer datasets. Analysis suggested that catchment physical attributes such as drainage area have significant impacts on rainfall-runoff generation mechanisms while catchment fraction of carbonate sedimentary rocks parameter’s contribution were insignificant. The results of the proposed physics-informed DeepAR simulation were comparable and somewhat superior to the well-known conceptual hydrologic models across CONUS.  

How to cite: Sadeghi Tabas, S. and Samadi, V.: A Probabilistic Physics-informed Deep Learning Model for Rainfall-runoff Prediction across Continental United States, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11222, https://doi.org/10.5194/egusphere-egu23-11222, 2023.

The standard approach of modeling lake level dynamics today is via process-based modeling. The development of such models requires an extensive knowledge about the investigated system, especially the different hydrological flow processes. When some of this information is missing, these models could provide distorted results and could miss important system characteristics.

In this study, we show how data-driven modeling can help the identification of the key drivers of lake level changes. We are using the example of the Groß Glienicker Lake, a glacial, groundwater fed lake near Berlin. This lake has been experiencing a drastic loss of water in recent decades, whose trend became even faster in the last few years. There is a local controversy whether these changes are mainly weather driven, or caused by water use; and what mitigation measures could be used to counteract them. Due to the strong anthropogenic influence from multiple water-related facilities near the lake, and the lack of geological information from the catchment, there are many unknows about the properties of the hydrological processes, hence the development of a process-based model in the area is challenging. To understand the system better we combine data-driven models with water balance approaches and use this methodology as an alternative to classic hydrological modeling.

The climatic model input (catchment-average precipitation and actual evapotranspiration) is generated by the Central European Refinement dataset (CER), which is a meteorological dataset generated by dynamically downscaling the Weather Research and Forecasting model (Jänicke et al., 2017). First, a data-driven model is constructed to predict the changes in lake levels one day ahead by using precipitation and evapotranspiration values from the last two months, a time interval that was selected after an extensive parameter analysis. This model is then further extended by additional inputs, such as water abstraction rates, river and groundwater levels. The fits of the different simulated lake levels are evaluated to identify the effects of the relevant drivers of the lake level dynamics. For a more mechanistic interpretation, a monthly water balance model was created using the same dataset. By calculating the different fluxes within the system, we were able to estimate the magnitudes of unobserved hydrological components.

With the help of our modeling approach, we could rule out the influence of one of the nearby waterworks and a river. We have also found that the lake level dynamics over the last two decades was mainly weather-driven, and the lake level fluctuations could be explained with changes in precipitation and evapotranspiration. With the water balance modeling, we have shown that the long-term net outflux from the lake catchment has increased in the last few years. These findings are used to support the development of a local high-resolution hydrogeological model, which could be used to further analyze these processes.

References

Jänicke, B., Meier, F., Fenner, D., Fehrenbach, U., Holtmann, A., Scherer, D. (2017): Urban-rural differences in near-surface air temperature as resolved by the Central Europe Refined analysis (CER): sensitivity to planetary boundary layer schemes and urban canopy models. Int. J. Climatol. 37 (4), 2063-2079. DOI: 10.1002/joc.4835

How to cite: Somogyvári, M., Fehrenbach, U., Scherer, D., and Krueger, T.: Identifying the drivers of lake level dynamics using a data-driven modeling approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13068, https://doi.org/10.5194/egusphere-egu23-13068, 2023.

Streamflow monitoring is a key input to water resource management, as it is an important source of information for understanding hydrological processes and prediction catchment behaviour and resulting flows. Both the monitored and the predicted flows support important decisions in areas such as infrastructure design, flood forecasting and resource allocation. It is therefore essential that the predictive information we have about our water resources serves these various needs.

Since observations are from the past and our decisions affect the future, models are needed to extrapolate measurements in time. Similarly, streamflow is not always measured at places where the information is needed, so interpolation or extrapolation is needed in space or across catchment properties and climates. Recent advances in publicly available large datasets of streamflow records and corresponding catchment characteristics have enabled succesful applications of machine learning to this prediction problem, leading to increased predictability in ungauged basins.

Since information content is related to surprise, we could see the objective of monitoring networks as manufacturing surprising data. This is formalized in approaches for monitoring network design based on information theory, where often the information content of the sources, i.e. the existing monitoring stations, has been investigated, including the effects of redundancy due to shared information between stations.

In this research, we argue that information content is related to unpredictability, but is inevitably filtered through several layers, which should be considered for monitoring network design. Examples of such filters are the models used for extrapolation to ungauged sites of interest, the target statistics of interest to be predicted, and the decision making purpose of those predictions. This means that the optimal monitoring strategy (where to measure, with how much precision and resolution, and for how long) depend on evolving modeling capabilities and representation of societal needs. Also, biases in the current neworks may exist as a function of how they are funded.

In this presentation, these theoretical aspects are investigated with examples from an ongoing project to investigate the streamflow monitoring network in British Columbia, Canada, which recently experienced record-breaking floods. 

How to cite: Weijs, S., Werenka, A., and Kovacek, D.: Manufacturing surprise: How information content, modeling capabilities and decision making purpose influence optimal streamflow monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14704, https://doi.org/10.5194/egusphere-egu23-14704, 2023.

Process-Based Modeling (PBM) and Machine Learning (ML) are often perceived as distinct paradigms in the geosciences. Here we present differentiable geoscientific modeling as a powerful pathway toward dissolving the perceived barrier between them and ushering in a paradigm shift. For decades, PBM offered benefits in interpretability and physical consistency but struggled to efficiently leverage large datasets. ML methods, especially deep networks, presented strong predictive skills yet lacked the ability to answer specific scientific questions. While various methods have been proposed for ML-physics integration, an important underlying theme  — differentiable modeling — is not sufficiently recognized. Here we outline the concepts, applicability, and significance of differentiable geoscientific modeling (DG). “Differentiable” refers to accurately and efficiently calculating gradients with respect to model variables, critically enabling the learning of high-dimensional unknown relationships. DG refers to a range of methods connecting varying amounts of prior knowledge to neural networks and training them together, capturing a different scope than physics-guided machine learning and emphasizing first principles. In this talk we provide examples of DG in global hydrology, ecosystem modeling, water quality simulations, etc. Preliminary evidence suggests DG offers better interpretability and causality than ML, improved generalizability and extrapolation capability, and strong potential for knowledge discovery, while approaching the performance of purely data-driven ML. DG models require less training data while scaling favorably in performance and efficiency with increasing amounts of data. With DG, geoscientists may be better able to frame and investigate questions, test hypotheses, and discover unrecognized linkages. 

How to cite: Shen, C., Appling, A., Gentine, P., Bandai, T., Gupta, H., Tartakovsky, A., Baity-Jesi, M., Fenicia, F., Kifer, D., Liu, X., Li, L., Feng, D., Ren, W., Zheng, Y., Harman, C., Clark, M., Farthing, M., and Kumar, P.: Differentiable modeling to unify machine learning and physical models and advance Geosciences, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15968, https://doi.org/10.5194/egusphere-egu23-15968, 2023.

Turbulence at the biosphere-atmosphere interface refers to the presence of chaotic and chaotic-like fluctuations or patterns in the exchange of energy, matter, or information between the biosphere and atmosphere. These fluctuations can occur at various scales. Turbulence at the biosphere-atmosphere interface can affect the transfer of heat, moisture, and gases. In this study, we use causal discovery to explore how high-frequency data (i.e., 10 Hz) of different variables at a flux tower, such as wind speed, air temperature, and water vapor, exhibit interdependencies. We use Directed Acyclic Graphs (DAGs) to identify how these variables influence each other at a high frequency. We tested the hypothesis that there are different types of DAGs present during the daytime at the land-atmosphere interface, and we developed an approach to identify patterns of DAGs that have similar behavior. To do this, we use distance-based classification to characterize the differences between DAGs and a k-means clustering approach to identify the number of clusters. We look at sequences of DAGs from 3-minute periods of high-frequency data to study how the causal relationships between the variables change over time. We compare our results from a clear sky day to a solar eclipse to see how changes in the environment affect the relationships between the variables. We found that during periods of high primary productivity, the causal relationship between water vapor and carbon dioxide shows a strong coupling between photosynthesis and transpiration. At high frequencies, we found that thermodynamics influences the dynamics of water vapor and carbon dioxide. Our framework makes possible the study of how dependence in turbulence is manifested at high frequencies at the land-atmosphere interface.

How to cite: Kumar, P. and Rodriguez, L. H.: Evolution of Causal Structure of Interactions in Turbulence at the Biosphere-Atmosphere interface, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16510, https://doi.org/10.5194/egusphere-egu23-16510, 2023.

Recent years have seen an uptick in the frequency of flood records occurring in the United States, with South Carolina (SC) being particularly hard hit. This study developed various deep recurrent neural networks (DRNNs) such as Vanilla RNN, long short-term memory (LSTM), and Gated Recurrent Unit (GRU) for flood event simulation. Precipitation and the USGS gaging data were preprocessed and fed into the DRNNs to predict flood events across several catchments in SC. The DRNNs are trained and evaluated using hourly datasets, and the outcomes were then compared with the observed data and the National Water Model (NWM) simulations. Analysis suggested that LSTM and GRU networks skillfully predicted the shape of flood hydrographs, including rising/falling limb, peak rates, flood volume, and time to peak, while the NWM vastly overestimated flood hydrographs. Among different climatic variables that were forced into the DRNNs, rainfall amount and spatial distribution were the most dominant input variables for flood prediction in SC.

How to cite: Heidari, E. and Samadi, V.: Application of Deep Recurrent Neural Networks for Flood Prediction and Assessment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16678, https://doi.org/10.5194/egusphere-egu23-16678, 2023.

The Mediterranean has been characterized as a region of enhanced climatic variability. Transitions between dry and wet conditions have repeatedly occurred over the last millennium in various spatial and temporal scales. However, the frequency of these shifts is poorly assessed due to the low amount of paleoclimatic reconstructions and the substantial heterogeneity of the Mediterranean. Here, we examine how often Mediterranean regions have transitioned between different hydroclimatic regimes over the last millennium. For this purpose, we use the Paleo Hydrodynamics Data Assimilation (PHYDA) simulation results to identify transitional changes based on Köppen-Geiger climate types. Our results indicate which regions are more likely to experience transitions between hydroclimatic regimes and their duration distribution. We also examine how the intensity of the shifts have fluctuated during the study period and quantify the uncertainties involved. Our findings contribute to a better understanding of the past hydroclimatic variability, which is crucial for further determining the current state and future aridification in the Mediterranean region.  

How to cite: Sanz i Gil, A., Rahmati Ziveh, A., Abbasizadeh, H., Thakur, V., Hanel, M., Maca, P., Rakovec, O., and Markonis, Y.: How often did Mediterranean regions transition to different hydroclimatic regimes in the last millennium?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-451, https://doi.org/10.5194/egusphere-egu23-451, 2023.

Accurate evapotranspiration (ET) estimates in mountainous regions are needed for better understanding the hydrological cycle and managing water resources within watersheds. However, the complex topography of these areas can have significant effects on ET, making it challenging to monitor at all scales. In this study, we sought to improve the accuracy of thermal remote sensing-based ET estimates in the High Atlas region of Morocco by taking into account the effect of topography. To do this, we used two ET models, both driven by LANDSAT optical/thermal data: the Two-Source Energy Balance (TSEB) model and the contextual Water Deficit Index (WDI) model. The meteorological data (such as air temperature, wind speed, and humidity) used to force the models were taken from ERA5-Land reanalysis products and specifically disaggregated at 30 meters to account for elevation effects, while the solar radiation data were obtained using the Samani et al. method to consider sun exposure effects. We compared the ET estimates produced by both models to measurements taken at two Eddy covariance towers in the mountains at different elevations (900 and 3850 m.a.s.l). Our results showed that the TSEB model was able to accurately estimate ET in the region, with a high level of consistency (r² = 0.72, rmse = 43 Wm^-2). The relative performance of both TSEB and WDI models was assessed. We also found that topography significantly influences ET in the High Atlas Mountains, emphasizing the importance of considering it when estimating ET at the watershed scale. This outcome can be used to better understand the hydrological cycle and manage water resources in mountainous areas.

How to cite: Sebbar, B., Merlin, O., Khabba, S., Pénot, V., Simonneaux, V., Bouchet, M., and Chehbouni, A.: Evaluating the Impact of Topography on Satellite-Derived Evapotranspiration Estimates in the High Atlas Mountains of Morocco, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3345, https://doi.org/10.5194/egusphere-egu23-3345, 2023.

Assessing urban water supply from karstic groundwater reservoirs through two hydrological models and the Exploitation Index in the southeast of Spain

Teresa Palacios-Cabrera¹, Antonio Jodar-Abellan², Ryan T. Bailey³, Dámaris Núñez-Gómez², Derdour Abdessamed⁴, Seyed Babak Haji Seyed Asadollah⁵, Pablo Melgarejo²

¹Faculty of Geology, Mines, Petroleum and Environmental Engineering. Central University of Ecuador. teresaalejandrap3@gmail.com

²Centro de Investigación e Innovación Agroalimentario y Agroambiental (CIAGRO), Miguel Hernández University (UMH). Orihuela, Spain.

³Dept. of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, USA.

⁴Laboratory for the Sustainable Management of Natural Resources in Arid and Semi‑arid Zones. University Center Salhi Ahmed Naama (Ctr Univ Naama). P.O. Box 66, Naama 45000. Algeria.

⁵Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Abstract:

Nowadays, numerous urban settlements in arid and semiarid areas are supplied by groundwater from adjacent small aquifers. Climate change with expected decreases in averages precipitation values jointly with increases in the frequency of heavy rainfall events does not show a clear pattner to how water resources in karstic aquifers are going to evolve. This work, focused in the Guadalest watershed (province of Alicante, southeast of Spain) assesses the behaviour of four karstic aquifers (the Mela, Beniardá-Polop, Benimantell and Serralla-Aixorta aquifers), whose resources supply urban water consumption for close municipalities. In these aquifers, we estimate groundwater recharge, extractions and their relation within the Exploitation Index (EI) by using the SWAT and SIMPA models, previously calibrated and validated in this watershed, during the period 1980-2016. These groundwater estimations were tested (validated) with field measurements performed by local authorities during the above mentioned period. Thus, in the Mela aquifer an EI of 0.19 was estimated with SWAT and SIMPA while an EI of 0.13 was obtained by local authorities; in the Beniardá-Polop aquifer an EI of 1.43 was estimated while an EI of 1.26 was obtained in the fieldwork; in Benimantell an EI of 0.25 and an EI of 0.22 were estimated and obtained respectively; and finally in the Serralla-Aixorta aquifer an EI of 0.19 and an EI of 0.2 were estimated and obtained respectively. Our results denote that: i) both models simulate correctly groundwater abstractions; ii) assessed aquifers depict a clear reduction of their reserves during the study period which represent an important issue considering that currently groundwater extractions are the unique water source of these populations. Therefore, it will be necessary to design supply strategies for these inhabitants and to carry out them, meeting budget restrictions and avoiding potential water shortages.

Keywords: groundwater; SWAT; SIMPA; Exploitation Index; urban water supply; southeast of Spain.

How to cite: Palacios Cabrera, T. A., Jodar Abellan, A., Núñez Gómez, D., Melgarejo, P., Abdessamed, D., Bailey, R., and Haiji Seyed, S. B.: Assessing urban water supply from karstic groundwater reservoirs through two hydrological models and the Exploitation Index in the southeast of Spain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3584, https://doi.org/10.5194/egusphere-egu23-3584, 2023.

Mountain areas constitute the headwaters of river basins, biodiversity hot-spots, and have a high value as ecosystem resources provision zones. Within the context of climate change, their meteorological trends and projections of future climate scenarios show a high resource vulnerability, highlighting the need to reduce the uncertainty associated with the dynamics of ecological-hydrological-meteorological processes. In these semiarid regions, there is a generalised increase in temperature, especially in summer, a decrease in average annual precipitation with an increase in torrentiality, and a decrease in snow's frequency and persistence. These can change the vegetation's phenological cycle, behaviour, and distribution. In addition, the socio-economic activities linked to these rural Mediterranean systems would be affected.

This study aims to establish a bridge between the different sources of available ecological-hydrological-meteorological information  and the local information that the final user needs, defining eco-hydrological indicators. Our long-term goal is to improve the management and conservation of Mediterranean mountains in the framework of climate change adaptation. 

For this purpose, we carried out a spatiotemporal analysis of precipitation and temperature historical trends (1960-2022, with nonparametric Mann-Kendall (MK) statistical test) as basic eco-hydrological indicators in the pilot area of the Sierras Subbéticas Natural Park (1570 m.a.s.l.) a  representative Mediterranean Mountain Range (Southern, Spain). This analysis constitutes the basis for the definition of targeted eco-hydrological management indicators. Among the different management challenges identified (e.g., sustainable olive tree production, preservation of autochthonous forest formations, water availability in groundwater reservoirs), we focus on the conservation of natural holm oak forest. Therefore, we selected as a targeted eco-hydrological indicator the occurrence of extreme drought periods in spring (3-months SPI in June), which is considered a primary meteorological factor influencing leaf development.

The trends analysis’ results reflect a significant increase in average annual mean temperatures, especially in the central and lowest areas of the mountain range. Regarding annual precipitation, there is great variability between dry and wet years, with a decreasing trend (-0,821 mm/year) without statistical significance. In the same way, the selected eco-hydrological indicator shows a non statistically significant trend.  This index directly influences the maintenance and regeneration of the Natural Park forest masses, which are of particular interest for managing its ecosystem services. In addition, this indicator constitutes an example of how these specific indicators allow us to use climatic-hydrological data sources in a practical application, with the future goal of integrating meteorological forecasts into the pipeline.

Acknowledgment: This work has been funded by project MONADA - "Hydrometeorological trends in mountainous protected areas in Andalusia: examples of co-development of climatic services for strategies of adaptation to climatic change", with the economic collaboration of the European Funding for Rural Development (FEDER) and the Andalusian Office of Economic Transformation, Industry, Knowledge and Universities. R+D+i project 2020.

How to cite: Calbet, A., Andreu, A., Aparicio, J., Polo, M. J., Torralbo, P., and PImentel, R.: Trend analysis on eco-hydrological indicators as management tools in Mediterranean Environmental Protected Areas: The case study of Sierras Subbéticas Natural Park (Spain), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6360, https://doi.org/10.5194/egusphere-egu23-6360, 2023.

The computation of the water budget of irrigated fields is generally difficult because of unknown irrigation amounts and timing. Automatic detection of irrigation events could greatly simplify the water balance of irrigated fields. The combination of high spatial resolution and high-frequency SAR (Sentinel-1) and optical satellite observations (Sentinel-2) makes the detection of irrigation events potentially feasible. Indeed, optical observation allows following the crop development while SAR observation can provide an estimation of the Surface Soil Moisture (SSM). However, uncertainties due to acquisition configuration or crop geometry and density might affect the retrieval of SSM. Here, an algorithm for irrigation events detection is assessed considering several aspects that could affect SSM retrieval (incidence angle, crop type, crop development) and specific characteristics of irrigation events (irrigation frequency, frequency of observations). Additionally, an alternative soil water budget model, the force-restore approach, is compared with the original bucket soil water budget algorithm. A European dataset of irrigation events collected during the ESA Irrigation+ project (5 sites in France, Germany, and Italy over three years) is used. The performances are analyzed in terms of the F‑score and the seasonal sum of irrigation. Overall, the analysis corroborated that the scores decrease with SSM observation frequency. The impact of the Sentinel-1 configuration (ascending/descending, close to 39°/far from 39°) on the retrieval results is low. The lower scores obtained with small NDVI compared to large NDVI were almost systematic, which is counter-intuitive, but might have been due to the larger number of irrigation events during high vegetation periods. The scores decreased as irrigation frequency increased, which was substantiated by the fact that the scores were better in France (more sprinkler irrigation) than in Germany (more localized irrigation). The strategy of merging different runs versus the strategy of interpolating all SSM data for one run has produced comparable results. The estimated cumulative sum of irrigation was around -20% lower compared to the reference dataset in the best cases. Finally, the replacement of the original SSM model by the Force-restore provided an improvement of about 6% on the F‑score, and also narrowed the error on cumulative seasonal irrigation. This study opens new perspectives for the advancement of irrigation retrieval at large scale based on SSM data sets through an in-depth analysis of results as a function of satellite configuration, irrigation techniques, and crops.

How to cite: Le Page, M., Nguyen, T., Zribi, M., Boone, A., Dari, J., Modanesi, S., Zappa, L., Ouaadi, N., and Jarlan, L.: Irrigation timing retrieval at the plot scale using Surface Soil Moisture derived from Sentinel time series in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6597, https://doi.org/10.5194/egusphere-egu23-6597, 2023.

Global warming is affecting hydroclimatic parameters determining changes in temperature and precipitation patterns. In addition, human-induced activities act on the land use and land cover (LULC) features of catchments. Runoff generation can be affected by these factors in both natural and anthropogenic basins. The aim of the current study is to investigate the relationship between the runoff coefficient (Rc), computed by exploiting long-term rainfall and streamflow records, and several features that can potentially affect it, namely meteorological parameters, soil water storage (SWS), and LULC changes through the wavelet coherence analysis. The method has been applied over the Upper Tiber basin at Ponte Nuovo outlet, in central Italy. To facilitate the understanding of the current catchment conditions in terms of surface water availability, a trend analysis has been performed using the Mann-Kendall (MK) test. For the long-term period of 1927-2020, the results reveal a decreasing trend of Rc. In addition, the MK test for seasonal temperature and SWS shows increasing and decreasing trends, respectively. Based on the wavelet analysis, a significant positive correlation is observed between Rc and SWS in the annual cycle with a phase shift of less than one month, while a strong negative correlation is observed between Rc and temperature in the annual period with a phase shift of 3-6 months. The study of the relationship between Rc and LULC changes shows a weak correlation. The lower phase shift between Rc and SWS indicate that Rc is susceptible to SWS in a faster way than other components. These results allows a better understanding of the main factors influencing the Rc over the pilot area; moreover, an extension to other Mediterranean basins is foreseen as a follow-up of this work.

How to cite: Rahi, A., Rahmati, M., Dari, J., saltalippi, C., and Morbidelli, R.: Assessment of factors controlling the runoff coefficient in the Mediterranean context: a case study in central Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6661, https://doi.org/10.5194/egusphere-egu23-6661, 2023.

How to cite: Guisiano, P.-A., Santoni, S., Huneau, F., Garel, É., and Mattei, A.: Importance of baseflow contribution in mountainous Mediterranean watersheds highlighted by geochemical and isotope tracers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6734, https://doi.org/10.5194/egusphere-egu23-6734, 2023.

The present study aims to evaluate the performance of a hydrological model to simulate spring runoff processes, analyze the effect of snowmelt on seasonal flow, and identify the snowmelt contribution rate based on the snow water equivalent (SWE) in the Moroccan High Atlas watersheds.

The main objective of this study is to evaluate the daily SWE in a poorly instrumented mountainous watershed using an improved hydrological model. The model algorithm improvement is considered an essential approach for better understanding the initial basin conditions that influence these hydrogeological behaviors. For this purpose, a seasonal analysis was performed to select flood events that reproduce this phenomenon.

To this end, the calibration has been done by forcing the model with rainfall, runoff, temperature, and snow water equivalent (SWE), with an amelioration of the model algorithm. Interestingly enough, this improvement achieved 13% based on the Nash-Sutcliffe efficiency coefficients. Hence, the spring event flows were influenced by the snowmelt process, these results will have direct implications for flood event replication modeling and flood forecasting in these regions.

The study demonstrates that this region is sensitive to the seasonal effect of snowmelt. Therefore, it is essential to take into account the contribution of snow in hydrological studies developed at the level of the Moroccan High Atlas mountainous watersheds. This approach is a great challenge that will improve the reproduction of seasonal flood events and allow a better forecast of flood events to reduce the uncertainties and risks of flooding in mountainous basin areas facing the same climate conditions.

Keywords: Precipitation, SWE, Hydrological modeling, Calibration, Mediterranean climate, flood events, Zat basin.

How to cite: Benkirane, M., Gascoin, S., Amazirh, A., Sourp, L., Laftouhi, N.-E., and Khabba, S.: Hydrological modeling using an improved algorithm for a better evaluation of the snow water equivalent (SWE) during spring floods in the Moroccan High Atlas Mountains., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7444, https://doi.org/10.5194/egusphere-egu23-7444, 2023.

Nowadays, there is observable evidence from all continents and most oceans that many natural systems have been affected by regional climate changes, particularly by the increase in temperature. This increase has also influenced the phenology of plants. As the olive tree is a plant characterizing the Mediterranean area, it is obvious that its phenology could serve as an indicator of the impact of global warming on this area. In this study, we will use the PMP model and observations of the tree phenology to predict its flowering date, which is the most remarkable and easiest to observe development phase. On the other hand, we will study by simulation the impact of climate change on the flowering of the olive tree under the conditions of Haouz of Marrakech according to three contrasting scenarios of a possible climate change. The PMP software is a tool that facilitates the development of mechanistic phenological models. It is based on thermal time calculations. In the present work, we chose to test three thermal time models: the ForcTT model, the TT model and the UniForc unified forcing model. The first two models are two versions of Growing Degree Days (GDD) which corresponds to a linear relationship of forcing rate from the initial date t₀ and a threshold temperature T_b. The third UniForc model is a sigmoidal function of temperature with the initial time t₀ as an unknown. The tests were carried out using two databases, the first recorded in the meteorological stations of the Haouz region covering the period 1985 - 2012 and the second observed on the phenology of the olive tree in the Tassaout area for the periods 1986 - 1991 and 1997 - 2012. The first result obtained shows that the UniForc is the most robust model, it is therefore retained for the study of the impact of global warming on the olive tree.In the second part of this work we have chosen three scenarios of greenhouse gas emissions, SRES (Special Report on Emissions Scenarios), which explore future development paths (demographic, economic and technological). Each of the three scenarios chosen is based on a degree of temperature increase according to the imagined development pathway: the more optimistic B1 scenario (increase of 1.1°C), the medium degree A1B scenario (increase of 2.8°C) and the more pessimistic A1F1 scenario (increase of 6.4°C). All the simulations carried out according to the chosen SRES scenarios confirm that the increase in temperature leads to the advancement (earliness) of the flowering date, this advancement varies between 0.3 and 27.3 days. The higher the temperature increase, the earlier the flowering date. Thus, the flowering date of the olive tree is univocally linked to the type of greenhouse gas emission scenario chosen. Our results therefore confirm that this agronomic variable is a good indicator of the severity of global warming that could occur in the region.

How to cite: Moumni, A., Abouseir, I., and Lahrouni, A.: Modeling the Impact of Global Warming on the Phenology of the Olive Tree in the Mediterranean region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7854, https://doi.org/10.5194/egusphere-egu23-7854, 2023.

The Tensift basin is prone to drought and, with the increasing frequency of extreme events, their forecasting and monitoring are becoming more complex. The present work aims to shed light on the interactions between meteorological and agricultural droughts while using multiple drought indices, and analyzing its temporal and spatial patterns over the Tensift basin in Morocco. To this purpose, we initially performed a trend analysis of the main parameters used in this study namely precipitation, temperature, NDVI, and soil moisture using the Mann-Kendall test. Moreover, a data-driven approach was adopted here to reveal the impact of lack of precipitation on the soil and vegetation cycles. Remote sensing data of precipitation from ERA5Land and soil moisture data from ESA-CCI as well as land surface temperature and NDVI from MODIS are used to calculate the standardized precipitation index (SPI), the vegetation condition index (VCI), the temperature condition index (TCI), and the soil moisture condition index (SMCI) for the period 2001–2021. A comparison analysis was conducted to test the performance and concordance of the indices. Then, to analyze the propagation of meteorological drought to the other components we conducted a cross-correlation study between drought indices.  The results reveal an upward trend of NDVI which is noticeable from the first decade (2009) and is attributed to the development of irrigated areas in this period. In contrast, the basin has shown a significant decline in monthly soil moisture for the period extending from 2001 to 2021, which could be explained by the way how soil moisture is retrieved in the ESA CCI product, and the trend in vegetation. On the other hand, the monthly precipitation and land surface temperature time series show no significant trend. The comparison between the indices showed moderate to low agreement. Correlations between TCI and SPI were eventually negative and significant at small time scales. A moderate correlation was observed between SPI1, SPI3, and TCI (0.45). The strongest correlations between SMCI and SPI were found at the 3 and 6-month time scales. Furthermore, the concordance between VCI and SPI is stronger at larger SPI time scales, the best correlation was observed between the indices VCI and SPI at 12 months with a correlation coefficient of 0.44. The correlations in the Tensift basin reflect spatial heterogeneities where some indices are more prevailing than others. Lag analysis results demonstrate valuable insights into the leading and preceding behavior of different variables regarding SPI. Relevant responses were identified at short, mid, and long-term influence of precipitation deficits on soil moisture, vegetation, and temperature. The results of this study highlight the interest in analyzing drought with different indices dedicated to each type of drought in order to improve early warning systems and risk management strategies for semi-arid areas.

How to cite: oukaddour, K., Fakir, Y., and Le Page, M.: Interactions between meteorological and agricultural droughts at different temporal and spatial scales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7926, https://doi.org/10.5194/egusphere-egu23-7926, 2023.

Although weather stations provide accurate measurements of ground climate conditions in close proximity to the station, they are expensive and require periodic recording of measurements. In addition, weather stations are therefore distributed sparsely, especially in developing countries. Conversely, satellites see entire landscapes and are therefore able to offer precise measurements at each location. This paper compares the performance of satellite products with weather station observations at three sites characterized by different climates Ounagha, Chichawa, and R3 in Morocco.

Precipitation and temperature data over the period of 2 years (2018 - 2019) at the three sites were collected. Data based on satellite imagery were collected for two satellite products, namely ERA5 and POWER over a similar period. The data were compared and analyzed through inferential statistics such as the root-mean-square error (RMSE), and the coefficient of determination (R²  ). The results showed that the temperature minimum daily simulated using the ERA5 satellite reached the highest coefficient of determination R² = 0.92, with RMSE=1.34 (daily for Ounagha), R² = 0.94, and with RMSE=1.27 (daily for Chichawa), R² = 0.96, and with RMSE=1.13 (daily for R3). The temperature maximum daily simulated through the POWER satellite showed the best coefficient of determination R² =0.924 with RMSE=2.174 (Ounagha daily). In contrast, the ERA5 satellite presents a better coefficient of determination R² =0.97 in Chichawa and R3 stations. The results of comparing the observed weather stations and the satellite data in terms of precipitation show that the acceptable performance was attributed to the ERA5 data for cumulative, decadaire, and monthly precipitation in the three sites.

The use of satellite products is a good way to solve the lack of weather stations and to make data available to the scientific community for further investigation. Furthermore, since our interest in monitoring drought in the Smimou region and our need for climate data in this area, which lacks a meteorological station, the results of this study encourage us to use the ERA5 satellite to collect climate data for the region.

How to cite: el moussaoui, E. H., Moumni, A., Khabba, S., and Lahrouni, A.: Evaluation of two climate production satellites over the region of Marrakesh Safi Morocco, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8147, https://doi.org/10.5194/egusphere-egu23-8147, 2023.

Due to its unique structure and excellent purification efficiency (e.g., 98% for organic matter and between 94 and 100% for nutrients), multi-soil-layering (MSL) has emerged as an efficient eco-friendly solution for wastewater treatment and environmental protection. Through infiltration-percolation, this soil-based technology allows pollutants to move from the MSL upper layers to the outlet while maintaining direct contact with its media, which helps in their removal via a variety of physical and biochemical mechanisms. This paper attempts to comprehensively evaluate the application of MSL technology and investigate its progress and efficacy since its emergence. Thus, it will attempt via a bibliometric analysis using the Web of Science database (from 1993 to 01/06/2022) related to MSL technology, to give a clear picture of the number of publications (70 studies), the most active academics, and countries (China with 27 studies), as well as collaborations and related topics. Furthermore, through hybrid combinations, pollutant removal processes, MSL effective media, and the key efficiency parameters, this paper review will seek to provide an overview of research that has developed and examined MSL since its inception. On the other hand, the current review will evaluate the modeling approaches used to explore MSL behavior in terms of pollutant removal and simulation of its performance (R² > 90%). However, despite the increase in MSL publications in the past years (e.g., 13 studies in 2021), many studies are still needed to fill the knowledge gaps and urging challenges regarding this emerging technology. Thus, recommendations on improving the stability and sustainability of MSLs are highlighted.

How to cite: Sbahi, S., Mandi, L., Masunaga, T., Ouazzani, N., Hejja, A., and Lahrouni, A.: Multi-Soil-Layering, the Emerging Technology for Wastewater Treatment: Review, Bibliometric Analysis, and Future Directions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8268, https://doi.org/10.5194/egusphere-egu23-8268, 2023.

Water scarcity is a major problem in the arid and semi-arid areas of Morocco, where irrigation is essential for agriculture. Crop growth models can enhance water use efficiency, thus providing an economic benefit while reducing pressure on water resources. In this study, we evaluated the modeling performance of the DSSAT-CERES-Wheat model in estimating Evapotranspiration (ETa), Total soil water (TSW), Grain yield, Tops weight and phenological stages of winter wheat in the semi-arid region of Tensift Al Haouz, Marrakech. The simulation was performed at a daily time step during two successive growing seasons 2002/2003 and 2003/2004. The model calibration was done firstly on two fields and ETa, TSW phenological stages, and productive variables were calibrated after the comparison of the simulated and observed data. Afterward, the validation was performed on four fields during the two growing seasons. The results showed that the model simulates reasonably good Grain yield, Tops weight and phenological stages. Moreover, The average values of  RMSE  between observed and measured ETa, TSW, Grain yield and Tops weight were respectively, 0.70mm/day, 25mm, 0.6 t/ha and 2 t/ha for the validation fields. Statistical parameters like R2, d, and NRMSE were additionally used and showed that the model simulates acceptably the above-mentioned parameters. Furthermore, The Penman-Monteith FAO56 and Priestley and Taylor Evapotranspiration simulation methods were compared, the average values of d  and R2 were respectively 0.85, 0.70 for the Penman-Monteith method, and 0.80, 0.65 for the Priestley and Taylor method. Thus, the DSSAT model can be considered a useful tool for monitoring the management of wheat in arid and semi-arid regions.

Keywords: DSSAT, wheat, irrigation, water scarcity, crop model

How to cite: Ech-chatir, L., Er-Raki, S., Meddich, A., Rodriguez, J. C., and Khabba, S.: Performance assessment of the DSSAT-CERES-Wheat model under different irrigation strategies in the semi-arid region of Marrakesh, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11935, https://doi.org/10.5194/egusphere-egu23-11935, 2023.

Floods are the most visible and destructive hydrologic phenomenon in terms of human and economic loss. Typically, flash floods are caused by large amounts of runoff due to short duration and high-intensity rainfall. Floods also lead to environmental and social problems, such as damage to roads, farms, and infrastructures and sometimes pollute surface water resources via the transfer of industrial waste, creating many health problems. In late October 2016, a flash flood severely damaged the surroundings of the city of Laayoune in the Saquia El Hamra basin in southern Morocco. The country’s climate is arid and semi-arid and is prone to destructive floods. The purpose of this study is to evaluate this flash flood and monitor wetland areas after this event using a technique that relies on remote sensing technology. This work was accomplished using Sentinel 2 satellite images, from the European Space Agency, based on classification methods and change detection techniques. Before and after the occurrence, the SVM classifier was employed to map land cover and land use. The overall accuracy (Kappa coefficient) was 94.41 % (0.91), and 87.33 % (0.81), respectively for both dates, when compared to the ground-truth data. The decision tree was built with the maps produced by the SVM classification for both dates as inputs, producing a change detection map with increased detail. The remote sensing technology has enabled us to monitor the damage that has been done to the area following the catastrophe with details on the buildings affected, farms flooded, and the extent of the river.

How to cite: El-alaouy, N., Moumni, A., Laftouhi, N.-E., and Lahrouni, A.: Remote Sensing Monitoring of Flood hazard in Arid Environments. A Case Study of Saquia El Hamra Watershed Morocco, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12908, https://doi.org/10.5194/egusphere-egu23-12908, 2023.

The Mediterranean Basin is classified as one of the hot-spots for climate change, where a significant decrease of precipitation and an increase of temperature are expected. This will most likely lead to a redistribution of water within Mediterranean catchments. However, the scale and magnitude and spatial differences of the impact of climate change on water security across the Mediterranean is still uncertain. Here we present the preliminary results of a systematic review on the impact of climate change on water security in the Mediterranean Basin. In this systematic review we focused on studies performed in the Mediterranean Basin that apply a hydrological model forced by climate model output and report changes in blue and/or green water, i.e. water stored in rivers and reservoirs (e.g. runoff or reservoir storage) and water stored in soils (e.g. groundwater recharge). The variables obtained from the studies include variables related to study area, climate and hydrological models, and model output. Our preliminary results show that the general tendency is a decrease of precipitation and an increase of temperature, which will cause a decrease of projected blue and green water. This will have serious consequences for the potential of irrigated agriculture, industry and household water use in the Mediterranean Basin, which heavily rely on the availability of blue water. But also for rainfed agriculture, where a decrease of green water may force farmers to abandon their land or transform to irrigated agriculture.

We acknowledge funding from the Spanish Ministry of Science and Innovation (AEI) (PID2019-109381RB-I00/AEI/10.13039/501100011033).

How to cite: Eekhout, J. and de Vente, J.: The impacts of future climate change on water security in the Mediterranean Basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13882, https://doi.org/10.5194/egusphere-egu23-13882, 2023.

Estimating crop evapotranspiration (ETc) is of primary importance for irrigation management. The model commonly used for this purpose is the FAO-56 approach which consists of accurately estimating the basal crop coefficient K_cb. Historically, K_cb is derived from optical indices such as NDVI giving its sensitivity to vegetation cover fraction and to the Leaf Area Index. Nevertheless, optical data are disturbed by the presence of clouds. In this context, the objective of this work is to investigate the potential use of all-weather radar data as a substitute of NDVI to derive K_cb. The study is conducted over two winter wheat fields (Field 1 and Field 2) in Morocco, monitored during two agricultural seasons 2016-2017 and 2017-2018. Each field is equipped with an eddy covariance station allowing the estimation of ETc every 30 minutes. In addition, a weather station was installed over an alfalfa plot near the study fields. First, the backscattering coefficient and the interferometric coherence ( ρ at VV polarization) are derived from Sentinel-1 data with a 6-day revisit time and a spatial resolution of 10 m. Second, empirical relationships have between established between K_cb, on one hand, and the interferometric coherence and the polarization ratio, on the other hand and the results are also compared to the classical K_cb-NDVI (derived from Sentinel-2) method. The results show that good statistical metrics are obtained between K_cb and NDVI (R=0.77 and RMSE=0.14 for Field 1). Similar results are obtained also using ρ (R=0.76, RMSE=0.18). Finally, the K_cb is estimated from the calibrated relationships on one season and then used to estimate ET_c. The results demonstrate reasonable estimates of ET_c on Field 1 (R=0.70, RMSE=0.75 mm/day and bias=-0.18 mm/days) using K_cb-ρ. By contrast, a significant overestimations is highlighted both with  (bias=0.73 mm/day) and NDVI (bias=1.46 mm/day) over Field 2. Interestingly, the K_cb-ρ relationship is more consistent in the estimation of ET_c when changing from one field to another. These outcomes open new perspectives for the estimation of ET_c from radar data as a potential substitute of NDVI in case of persistent cloud cover.

How to cite: Ouaadi, N., Jarlan, L., Khabba, S., Le Page, M., Chakir, A., Er-Raki, S., and Frison, P.-L.: C-band Sentinel-1 data for estimating the basal crop coefficient and evapotranspiration of winter wheat , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14819, https://doi.org/10.5194/egusphere-egu23-14819, 2023.

The Po valley (northern Italy) hosts important economic activities and contributes to a significant fraction of the national agricultural production. On its coastal region (the Po Delta) reclaimed agricultural lands coexist, largely below the mean sea level, with natural areas of outstanding environmental relevance. Besides affecting the socio-economic and ecological dynamics within its basin, the modulation of the hydrological regime of the Po river also plays a major role in controlling the oceanographic processes occurring in the northern Adriatic Sea, from coastal circulation to deep ventilation and thermohaline circulation at the Mediterranean scale. In this framework, the severe drought that affected large areas of Europe in Spring and Summer 2022 hit the Po river system with particular intensity, with heavy impacts on productive activities and extensive saltwater intrusion in the coastal areas.

By means of observed discharge records and precipitation data from reanalysis and climate models, this contribution presents an analysis of the 2022 drought event, investigating its exceptionality in the recent past climate and exploring its possible recurrence in future conditions. Ensemble projections of rainfall regimes on the Po River basin in two climate change scenarios (RCP4.5 and RCP8.5) show that persistent negative rainfall anomalies like the one that characterised the 2022 event will unlikely become typical features of the future climate, but could remarkably increase their frequency. Furthermore, the impacts of these events will be magnified by rising temperatures, enhancing evapotranspiration rates in agriculture and water demand. Particularly in severe climate change scenarios, heavier and more frequent episodes of water shortage, combined with a rising sea level, are expected to intensify the pressure of saltwater intrusion in the coastal areas of the Po Delta, increasing the risk for environmental impoverishment and for loss of agricultural lands.

Besides investigating in a climate change perspective a recent severe event that struck an important economic and ecological region, the present contribution aims at stimulating the development of advanced climate change adaptation strategies in riverine, deltaic and estuarine systems, emphasizing the importance of an integrated source-to-sea approach to this process. 

How to cite: Bonaldo, D., Bellafiore, D., Ferrarin, C., Ferretti, R., Ricchi, A., Sangelantoni, L., and Vitelletti, M. L.: The summer 2022 drought in the Po valley (Italy): a glimpse of the future climate?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15504, https://doi.org/10.5194/egusphere-egu23-15504, 2023.

The Versilia coastal plain hosts an important and strategic aquifer for water supply. Like all coastal aquifers, it is particularly vulnerable to the saltwater intrusion, which can be amplified not only by fresh water over-exploitation, but also by the effects of climate change, including the increase of extreme events that are deeply altering the hydrology of the Mediterranean regions. In order to protect this precious resource, both in quantitative and qualitative terms, an adequate knowledge of the aquifer system is necessary through the development of conceptual and mathematical hydrogeological models. Based on integrated multidisciplinary approach the conceptual hydrogeological model was defined using stratigraphic, hydrogeological and geochemical data elaboration. Subsequently, groundwater flow mathematical models were created using the ModFlow code and Groundwater Vistas like graphical interface. The models allowed to better understand this aquifer system and to identify and, where possible to quantify, the main processes and groundwater components involved. The most important feeding groundwater component, both in terms of water quantity and quality, is the fan of the Versilia River, mainly fed by the river itself in the foothill zone. Even if, in the summer season some piezometric depressions, tied to groundwater exploitation, tend to expand and move towards the coast, thus favouring the seawater intrusion process, in general, the Versilia fan component seems at present to be able to guarantee relative protection against marine ingression. However, this precarious balance could be disrupted by the extreme rainy events that frequently occur in the Apuan Alps region. The huge quantity of water that quickly flows by the river up to the sea during extreme events represents a lack of feeding respect to the aquifer, and consequently the mitigation role of the fan component towards seawater intrusion can be significantly weakened. Thanks to the water budget achieved by numerical model and considering real extreme events occurred in the Apuan-Versilian region it was possible to make considerations about possible effects of these climate regimes on the aquifer system. These extreme events as those occurred in the area in the past, and awaited more frequently in the future, represent a concrete threat for the coastal aquifer system that over next decades could suffer more and more seawater intrusion. Given the reliance of local human activities on groundwater, far-sighted actions of water management (e.g. managed aquifer recharge) are recommended for mitigating such as climate effects.

How to cite: Menichini, M. and Doveri, M.: Conceptual and numerical modelling of the Versilia coastal aquifer (NW-Tuscany, Italy) for quantitative evaluations on groundwater components and possible effects of climate extreme events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15981, https://doi.org/10.5194/egusphere-egu23-15981, 2023.

In recent decades, climate change has led to a sharp increase in water demand. Particularly in agriculture, this has put a great strain on already scarce water resources, increased the need for irrigation water, and led to overuse of groundwater. Therefore, sustainable management of water resources while maintaining good agricultural yield by monitoring crop water status is necessary for sustainable and rational management of these resources, especially in arid and semi-arid regions. For this purpose, a detailed knowledge of the different processes describing the diurnal water cycle of plants in a large area is essential. However, micrometeorological or physiological experimental measurements and their partitioning are laborious to perform and not very representative of large areas.

In this regard, remote sensing is a particularly suitable tool for monitoring agricultural areas because of its global and repeated observation. Several studies have highlighted the sensitivity of radar data to vegetation water content especially over the rainforest with spatial scatterometers that observe differences between morning and evening acquisitions. On the other hand, in situ radar experiments with high temporal frequency have made it possible to analyze radar responses over tropical and boreal forests.

This study relates to a similar experiment conducted on an olive orchard located in the semi-arid Mediterranean region of Chichaoua in central Morocco. It allows the acquisition of in situ C-band radar measurements in crop fields, which are acquired continuously, from a tower-based radar system, with a time step of 15 minutes.

The temporal evolution of the interferometric coherence r is analyzed on different baselines Dt, ranging from 15 minutes to 30 days, for the main physiological stages of the olive tree. Four different two-month periods, from December 2020 to November 2022, are chosen as the main physiological stages based on field observations.

The obtained results of r, especially at 15-min min-steps, show a global behavior similar to that observed in tropical and boreal forests: high values (r ≈1) are observed during the night (weak wind, vegetation resting), then a decrease/increase during the day mainly anti-symetric to the wind cycle. As over boreal and tropical forest, a decrease in r is observed before the wind picks up, with is time coincident with sap flows and ETR variations, traducing its sensitivity to water plant content.

Results show that over olive orchard, the r diurnal cycle is less marked than over boreal and tropical forests, due to lower ETR rates and certainly due to a significant soil contribution over this less dense vegetation layer. Furthermore, r values decrease when temporal baselines increase, but values are still meaningful for Dt = 6 days (r = 0.3 compared to 0.6 for Dt = 15 min. for the summer period), available with Sentinel-1 missions.

The present study provides particularly interesting results confirming the sensitivity of C-band coherence to vegetation water status, especially in the early morning. Further work needs to be pursued to verify if we are able to detect the water stress of these plants in semi-arid areas such as Chichaoua through coherence.

How to cite: Chakir, A., Frison, P., Khabba, S., Villard, L., Le-dantec, V., Ouaadi, N., Fanise, P., and Jarlan, L.: Analysis of the radar temporal coherence at C band over an olive orchard in semi-arid region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16445, https://doi.org/10.5194/egusphere-egu23-16445, 2023.

This research aims at establishing an integrated modelling framework to assess the impact of climate change on water supply and demand across an arid area in the western Haouz plain in Morocco. Five General Circulation Models (GCM) are used to evaluate future water resources availability under Representative Concentration Pathways (RCP4.5 and RCP8.5 emission scenarios). The projected crop water demand and irrigation water demand were analysed using Aquacrop software, taking into account the impact of climate change on both reference evapotranspiration and crop cycle lengths. The future water balance is simulated by means of Water Evaluation And Planning (WEAP) Tool, including several socioeconomic and land use scenarios under RCP4.5 and RCP8.5. The results reveal an important decrease in net precipitation with an average of -36.2% and -50.5% under RCP4.5 and RCP8.5, respectively. In terms of water balance, the “business as usual” scenario would lead to an increasing of unmet water demand of about +22% in the 2050 horizon and to an increased depletion of the water table that could reach 2m/year. Changing water management and use practices remains the only solution to ensure sustainable water use and deal with the projected water scarcity.

How to cite: Abdessamad, H., Elmehdi Saidi, M., El Khalki, E. M., Aachrine, B., Saouabe, T., and Ait Elmaki, A.: Water demand versus supply in a Mediterranean Arid Region : current and future challenges, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17188, https://doi.org/10.5194/egusphere-egu23-17188, 2023.

West Africa has a complex climate regime. It affects hydrological predictivity in the region where the majority population depends on agriculture. With a warming planet, the challenge is further exacerbated by frequent hydroclimatic extremes. To achieve secured livelihoods and resilience, hydrological understanding is a key. However, there is an elemental challenge of missing measured weather data. Weather variables that are drivers of the water and energy balance are necessary for the setup of robust hydrological models. We focus on the Ouémé River Basin in Benin, which lacks spatially representative in-situ temperature observations. To fill this gap, the study evaluates global earth datasets in the form of reanalysis products that are emerging useful for hydrological modeling. We perform an intercomparison of five temperature reanalysis datasets for the basin using the hydrological model Soil and Water Assessment Tool (SWAT). These datasets are CFSR, CPC, ERA5, EWEMBI, and PGFv3, available at a daily temporal resolution. We test their performance on the simulation of hydrological processes in the Ouémé basin.

To evaluate each temperature data, a multi-site calibration is performed in SWAT using daily discharge time series. Validation is carried out as a two-fold process. The first is point validation performed using discharge data at five gauge sites and the second is spatial validation on the sub-catchment level conducted using satellite-derived actual evapotranspiration (AET) data from GLEAM v3.5b. This multi-gauge and multi-variable approach is used to minimize uncertainties associated with the application of SWAT.

This study is one of a kind for the basin, testing the datasets for their hydrological performance and overcoming a major gap toward achieving robust models. Temperature reanalysis products provide high temporal resolution, long time series, and spatially representative datasets. However, the response to input data errors can vary significantly given the non-linear interaction of parameters in a hydrological model. Therefore, hydrological evaluation is an important step before reanalysis data can be used for modeling and decision-making. We also demonstrate the significance of testing multiple water fluxes to assess the performance of climate datasets. A higher variation in performance for temperature datasets is observed for AET than for the streamflow component. It is an important outcome to determine the most suitable temperature product for the Ouémé basin.

How to cite: Jalan, I., Merk, F., Tuo, Y., and Disse, M.: Hydrological performance evaluation of temperature reanalysis products for the Ouémé River Basin in West Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-601, https://doi.org/10.5194/egusphere-egu23-601, 2023.

Abstract:  Flood-attributed damages to infrastructure and public safety are expected to escalate in the future due to climate change, land use change, and associated hydrologic changes. In recent years, the reliability of flood forecasts has increased due to the availability of meteorological and hydrological data and advancements in flood prediction science. However, there is limited effort to apply emerging advanced hydrological models for flood prediction in poorly gauged watersheds. The overall objective of this study is to demonstrate applicability of climate model products to generate reliable flood predictions for data-limited and flood-prone areas. In this study, the most recent high-resolution climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were evaluated to assess the impacts of projected climate change on the flood-prone areas of the Lake Tana basin, Ethiopia. The ensemble means of the top five CMIP6 climate model forcing data were used to calibrate and validate a free open-source, spatially distributed hydrological model known as Wflow_sbm. Model-independent multi-algorithm optimization and parameter estimation tool is implemented for calibration and validation of Wflow. In terms of simulating runoff and flood events, application of Wflow_sbm to the Lake Tana basin provided promising results. This study serves as a major step towards the development and implementation of climate model product-driven hydrological model to assess flooding damages of future climate projections within the poorly gauged Lake Tana basin.

How to cite: Alaminie, A., Amarnath, G., Padhee, S., Ghosh, S., Tilahun, S., Mekonnen, M., Assefa, G., Seid, A., Zimale, F., and Jury, M.: Application of Advanced Wflow_sbm Model with the CMIP6 climate projection for flood prediction in the data-scarce: Lake-Tana Basin, Ethiopia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1113, https://doi.org/10.5194/egusphere-egu23-1113, 2023.

The filling of the Grand Ethiopian Renaissance Dam (GERD) started in 2020, posing additional challenges for downstream water management in Sudan, which is already struggling to cope with the effects of climate change. This is also the case for many transboundary rivers that observe a lack of cooperation and transparency during the filling and operation of new dams. Without information about water supply from neighbouring countries, it is risky to manage downstream dams as usual and operation information is needed to apply modifications. This study aims to test the applicability of using lumped hydrological modelling coupled with remote sensing data in retrieving reservoir filling strategies in regions with limited data availability. Firstly, five rainfall products (namely; ARC2, CHIRPS, ERA5, GPCC, and PERSIANN-CDR) were evaluated against historical measured rainfall at ten stations. Secondly, to account for input uncertainty, the best three performing rainfall products were forced in the conceptual hydrological model HBV-light with potential evapotranspiration and temperature data from ERA5. The model was calibrated during the period 2006 - 2019 and validated during the period 1991 - 1996. Thirdly, the parameter sets that obtained very good performance (NSE > 0.75) were utilized to predict the inflow of GERD during the operation period (2020 - 2022). Then, from the water balance of GERD, the daily storage was estimated and compared with the storage derived from Landsat observations to evaluate the performance of the selected rainfall products. Finally, three years of GERD filling strategies were retrieved using the best-performing simulation of CHIRPS with RMSE of 1.7 billion cubic meters (BCM) and NSE of 0.77 when compared with Landsat-derived reservoir storage. It was found that GERD stored 14% of the monthly inflow of July 2020, 41% of July 2021, and 37% and 32% of July and August 2022, respectively. Annually, GERD retained 5.2% and 7.4% of the annual inflow in the first two filling phases and between 12.9% and 13.7% in the third phase. The results also revealed that the retrieval of filling strategies is more influenced by input uncertainty than parameter uncertainty. The retrieved daily change in GERD storage with the measured outflow to Sudan allowed further interpretation of the downstream impacts of GERD. The findings of this study provide systematic steps to retrieve filling strategies for data-scarce regions, which can serve as a base for future development in the field. Locally, the analysis contributes significantly to the future water management of the Roseires and Sennar dams in Sudan. 

How to cite: Mohammed Ali, A., Melsen, L., and Teuling, R.: Inferring reservoir filling strategies under limited data availability using hydrological modelling and Earth observation: the case of the Grand Ethiopian Renaissance Dam (GERD), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2056, https://doi.org/10.5194/egusphere-egu23-2056, 2023.

In this study, the spatio-temporal changes in Rainwater Productivity (RP) and its sensitivity to the changes in precipitation and temperature predicted by climate models in various climatic zones across the rainfed agricultural areas of Ethiopia were analyzed. First, the future precipitation, air temperature, and shortwave radiation from multiple GCM projections were downscaled to a 0.05°x0.05° grid resolution, considering three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) and three future periods: 2020-2049, 2045-2074, and 2070-2099 using the present climate (1981-2010) as a reference. Next, the reference potential evapotranspiration was computed using the FAO Penman-Monteith and the actual evapotranspiration was simulated using a daily soil water balance model. Then, the relative crop yield (i.e., the ratio of the actual and water-limited potential yield) was determined as a function of the evaporative stress index and crop yield response factor (Ky) for the two growing seasons -- the main (meher) growing season (May-Sep) and the shorter (belg) growing season (Feb-May) for the present and future climates. The computed relative yield was used as a proxy for RP, under the assumption that effective rainfall is the limiting factor for crop yield. Finally, the sensitivity of RP to projected changes in precipitation and temperature was analyzed based on the one-at-a-time (OAT) approach for warmer and drier versus warmer and wetter climate scenarios.

The results show that under the present climate, the median RP (percent of the potential RP) during the Meher and Belg seasons ranges from about 52% and 34% in semi-arid climates to 93% and 45% in humid climates. The projected Meher RP in the future shows either a slight change or a decrease by up to 10% across the majority of the RFA regions under all SSPs and future periods. Conversely, the Belg season RP is likely to increase by up to 15% across the major Belg-producing regions by the end of the century. The observed changes are the combined effects of the nearly consistent but spatially variable increase in precipitation (for example up to 30% under SSP5-8.5 in the 2080s) and rising temperature (up to 5°C under SSP5-8.5 in the 2080s) over the RFA region. The OAT sensitivity analysis reveals that RP under warmer and drier climates is strongly sensitive to precipitation. However, under warmer and wetter conditions the climate sensitivity of RP is determined by the rainfall regime, i.e, in the areas with unimodal rainfall regimes, changes in RP are dominated by the changes in precipitation while in areas with strongly erratic or bimodal rainfall distribution, temperature, or both precipitation and temperature control the changes in RP. Such analyses are useful for assessing the future climate risks to crop yield due to water stress associated with the expected increases in atmospheric evaporative demand, identifying vulnerable areas across the RFA region as well as possibilities for agricultural expansion.      

How to cite: Wakjira, M. T., Peleg, N., Six, J., and Molnar, P.: Climate change impacts on rainwater productivity across agricultural landscapes of Ethiopia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2819, https://doi.org/10.5194/egusphere-egu23-2819, 2023.

African Easterly Waves (AEWs) are the most important precipitation-producing dynamic systems in tropical Africa and Atlantic, where dust in the atmosphere is abundant. But the past studies lack consensus on the sign and magnitude of the dust radiative forcing impact on AEWs primarily because of the disagreement in calculating dust solar radiation absorption. The incapability of coarse-resolution models to represent various dust-AEW interactions is another source of uncertainty. The present study uses a high-resolution atmospheric general circulation model, HiRAM, to investigate the sensitivity of AEWs to the dust direct radiative forcing when dust shortwave absorption varies within the observed limits. Global simulations are conducted with the 25 km grid spacing to adequately simulate AEWs and associated circulation features. Four 10-year experiments are conducted: One control experiment without dust and three others with dust assuming dust is an inefficient, standard, and very efficient shortwave absorber. The results show that AEWs are highly sensitive to dust shortwave absorption. As dust shortwave absorption increases, AEW activity intensifies and broadens the wave track shifting it southward. The 6-9 day waves are more sensitive to dust shortwave absorption than the 3-5 day waves, where the response in the former has a stark land-sea contrast. The sensitivity of AEW to dust solar radiation absorption arises from a combination of energy conversion mechanisms. Although baroclinic energy conversion dominates the energy cycle, the responses to dust shortwave heating in barotropic and generation terms are comparable to that in baroclinic conversion.

How to cite: Bangalath, H. K., Raj, J., and Stenchikov, G.: Sensitivity of African Easterly Waves to Dust Direct Radiative Forcing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4000, https://doi.org/10.5194/egusphere-egu23-4000, 2023.

Semiarid regions shaped as a mosaic of savanna-type rangelands, croplands, and other uses such as livelihoods, or natural reserves, cover large areas in Southern Africa. They constitute an essential example of multiple uses of natural resources, combining a high environmental value with great importance in the rural economy and development. These systems are water-limited and highly sensitive to changes in climate, environmental conditions, and land management practices. Although the vegetation of these areas is adapted to variable climatic conditions and dry periods, the increase in drought intensity, duration, and frequency precipitate their degradation. 

In Southern Africa, recurrent droughts have strained rainfed agriculture and pasture production, decimating livestock and wildlife. During 2015 and 2016, South African savannas were subjected to a severe drought associated with a strong El Niño event. Open-source satellite time series provide vital information to assess water availability and long-term drought, to help design early warning and conservation strategies. 

In this work, we applied the TSEB (Two Source Energy Balance) model integrating MODIS-derived products (1 km) from 2000 to 2021 over the Kruger National Park (KNP) in South Africa. The model was previously validated over the Skukuza experimental site with good agreement. ET followed precipitation rates, although some years with low precipitation maintained average ET values. This may be caused by the ability of the trees to reach groundwater (deep fractured aquifers and alluvial aquifers can be found in the KNP). During some years (e.g., 2004, 2009), annual total ET was much higher than mean annual values. This may be caused by an extreme annual evaporative atmospheric demand and relatively high precipitation. The anomalies of the ratio of ET to reference ET were used as an indicator of agricultural drought on annual scales, and 2002/2003, 2007/2008 and 2015/2016 years stood out for their negative values. The approach helped to model drought over Kruger Park in the long term, providing an insight into the characteristics of the events.

Acknowledgment: This work has been carried out through the project "DroughT impACt on the vegeTation of South African semIarid mosaiC landscapes: Implications on grass-crop-lands primary production" funded by the European Space Agency in the framework of the "EO AFRICA R&D Facility".

How to cite: Dube, T., Ramoelo, A., Shoko, C., Dominic, M., Gonzalez-Dugo, M. P., Nieto, H., and Andreu, A.: Drought monitoring over the Kruger National Park (2000-2020) integrating remote sensing data., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6608, https://doi.org/10.5194/egusphere-egu23-6608, 2023.

Water accounting frameworks assess water availability and consumption of various users and are key tools to inform decision and policy making for integrated water resources management. This study presents a modelling framework that integrates a spatially explicit hydrological model and climate change scenarios with the Water Accounting Plus (WA+) tool to anticipate future water resource challenges and provide mitigation measures. The fully distributed mesoscale Hydrologic Model (mHM), spatially calibrated with multiple satellite remote sensing products, is used to predict water fluxes, stocks and flows in the transboundary Volta River basin (VRB) in West Africa. The mHM model is forced with a large ensemble of climate change projection data from eleven general circulation models (GCMs) downscaled by four regional climate models (RCMs) under the representative concentration pathway RCP8.5, obtained from CORDEX-Africa. Outputs from mHM are used as inputs to the WA+ framework to report on the state and trends of water resources over the historical baseline period 1991-2020 and the near-term future 2021-2050. The basin-scale WA+ reporting is reinforced with a multi-scale summary of water accounts across spatial domains including four climatic zones, four sub-basins and the six riparian countries.

The long-term multi-model ensemble mean of the net inflow to the basin is found to be 419 km³/year with an inter-annual variability of 11%, and is projected to slightly increase in the near-term future (2021-2050), due to the increase in rainfall, thereby highlighting the need for adaptation strategies to optimize the water-energy-food-ecosystem nexus in the VRB.

How to cite: Dembélé, M., Salvadore, E., Zwart, S., Ceperley, N., Mariéthoz, G., and Schaefli, B.: Multiscale water accounting under climate change in a transboundary West African basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8955, https://doi.org/10.5194/egusphere-egu23-8955, 2023.

Droughts are increasing in frequency and intensity in many African countries. Their occurrences severely affect agricultural production and thus potentially contribute to human displacement. Yet, the way in which droughts influence patterns of human settlements remain poorly understood. Here we show that drought occurrences across Africa are often associated with (other things being equal) human displacements towards rivers and cities. Our results show that 73-81% of African countries exhibit larger human mobility towards water bodies and urban areas during drought conditions, as compared to non-drought periods. This may result into increasing floodplain population, and thus into potentially larger flood losses, or overcrowding urban areas. As such, our results shed light on the interplay between hydrologic extremes and society, bolstering the analysis on the spatiotemporal dynamics of drought risks in a warming world.

How to cite: Ceola, S., Mård, J., and Di Baldassarre, G.: Droughts influence patterns of human settlements in Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11856, https://doi.org/10.5194/egusphere-egu23-11856, 2023.

The study investigates the sensitivity of water resources, droughts and hydropower generation to climate change in the Lake Malawi and Shire River basins, covering three different aspects:

• Analysis of the variability and trends of meteorological and hydrological droughts based on observational data from 1970 to 2013;
• Drought analysis for future conditions and investigation of potential changes in water balance and various drought indicators;
• Hydrological simulation and sensitivity analysis of the Lake Malawi water balance and water level, as well as its discharge and associated hydropower generation in the Shire River.

The key findings of these analyses are:

• Between 1970 and 2013, meteorological droughts have increased in intensity and duration. This can be attributed to a decrease in precipitation and an increase in temperatures and evaporation.
• The hydrological system of Lake Malawi reacts to meteorological droughts with a time lag (up to 24 months), so that hydrological droughts can be predicted up to 10 months in advance by meteorological drought parameters. Hydrological droughts are characterized by water levels below 474.1 m asl in Lake Malawi.
• Despite all the differences and uncertainties in climate projections, they agree that meteorological droughts will continue to increase in the future, in the form of increasing drought intensities DI (+25% to +50% for 2021-2050 and +131% to +388% for 2071-2100) and increasing drought months DM (3-5 and 7-8 more drought months per year, respectively).
• The water level in Lake Malawi, as a residual of the catchment water balance, is very sensitive to changes in precipitation and evaporation. Outflow from the lake is a direct function of lake water level, and the combination of projected precipitation decline and temperature increase ultimately leads to significantly reduced flow in the Shire River and a decline in annual hydropower production of between 1% and 2.5% (2021-2050) and 5% and 24% (2071-2100). Sometimes, individual projections even suggest that the outflow from Lake Malawi would temporarily dry up and the power supply in the country would be interrupted.

It is shown that failure to meet the 1.5°C global temperature increase target will have a severe impact on droughts and water resources in Malawi. This in turn has implications for hydropower production, as a result of which the achievement of most of the Sustainable Development Goals (SDGs) will be at risk.

How to cite: Bronstert, A., Mtilatila, L., and Vormoor, K.: Impacts of climate change on hydrological extremes and hydropower production in tropical Africa: catchments of Lake Malawi and the Shire River in Malawi, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12047, https://doi.org/10.5194/egusphere-egu23-12047, 2023.

The African Flood and Drought Monitor (AFDM) is a satellite-model based system for monitoring and forecasting flood and drought conditions for the African continent. It has been running operationally since 2008 in various forms, providing useful information on flood and drought risks to a variety of end-users, as well as information for a wide range of water-related applications, including food and energy security, health risks, and migration. This paper provides an overview of the latest version of the system, which incorporates updated versions of hydrological models and meteorological data at high resolution, as well as the state-of-the-art short-term and seasonal forecast models. We also describe the tailoring of the AFDM to national systems across southern Africa and the process of co-design of these systems with national agencies and end-users. The system has been evaluated on several time scales, historically and for short-term (flood) and seasonal (drought) forecasts. Predictability is discussed with respect to end-users needs, especially at the community scale, and how more recent approaches to predict at the community scale are being incorporated into these monitoring systems, using high-performance computing, machine learning and data assimilation.

How to cite: Sheffield, J., Kimball, J., Du, J., and Verbist, K.: Approaches to community–scale drought and flood early warning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16309, https://doi.org/10.5194/egusphere-egu23-16309, 2023.

Data-sparse hydroclimates across the globe are often the most vulnerable to climate shocks and their populations to food insecurity. Drought monitoring and famine early warning in these regions have for too long relied on poor parameterizations of atmospheric evaporative demand (E₀)—no less than the demand side of drought and of consumptive use by agriculture—either relying on physically poor process representations of E₀ or on climatological mean estimates. However, by exploiting the advent of long-term, spatially distributed, and accurate reanalyses of the land-atmosphere system and its drivers we can put new data to use to save livelihoods and lives by improving drought monitoring, famine early warning, and multi-scale agricultural risk assessment.

Here we describe one such effort—to create a daily, long-term, accurate, global operational dataset of E₀. Funded by the Famine Early Warning Systems Network (FEWS NET) and its partners, we have developed a nearly 42-year long, daily, 0.125-degree, global dataset of Penman-Monteith reference evapotranspiration as a fully physical metric of E₀. This new E₀ dataset is driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)—an accurate, fine-resolution land-surface/atmosphere reanalysis. We verified the accuracy of the dataset against (i) point-estimates of E₀ derived by Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) initiative in Southern Africa, a region with sparse ground-truth data and significant humanitarian need, and (ii) on a spatially distributed basis against E₀ derived from other reanalyses (Global Data Assimilation System and Princeton Global Forcing) that, although global, are otherwise unsuitable for operational food-security decision-making.

We summarize the various uses to which the new E₀ dataset is already being put in support of food-security monitoring and decision-making in food-insecure countries within the FEWS NET framework: to provide input data for a global implementation of the Evaporative Demand Drought Index (EDDI), which examines anomalies in E₀ to permit early warning and ongoing monitoring of agricultural flash drought and hydrologic drought, both crucial drivers of food insecurity; and to diagnose the anomalies in E₀ that lead to or signal drought into the relative contributions from its drivers, examining canonical droughts across Africa (e.g., the 2015 drought in Malawi, and the 2016 Horn of Africa drought, and the current multi-year East African drought). We also present use-cases that verify the operational applicability of the new E₀ dataset in long-established drought, famine, crop- and pastoral-stress metrics, and in predictability assessments of drought forecasts. Driven by this new dataset, these analyses should significantly contribute to a more holistic understanding of drought and food-security across the African continent and the rest of the world.

How to cite: Hobbins, M., Boiko, O., Dewes, C., Hoell, A., Husak, G., Jayanthi, H., Magadzire, T., McNally, A., Sarmiento, D., Senay, G., and Turner, W.: A new global reference evapotranspiration reanalysis: global opportunities in operational drought monitoring and famine early warning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16989, https://doi.org/10.5194/egusphere-egu23-16989, 2023.

Rangeland water is critical to food security early warning systems in Africa.  Rangelands feed more than half of Africa’s livestock, providing a source of income to 268 million pastoralists and agropastoralists. Rangeland ponds are a vital source of water for pastoral livestock, directly contributing to household food security and health.  However, rangeland areas of the Sahel and East Africa are water-limited, drought prone, and very food insecure.  In December 2022, the United States Agency for International Development’s (USAID) Famine Early Warning Systems Network (FEWS NET) identified >35 million extremely food insecure people in the countries located in the Sahel and East Africa. 

The NASA-funded “Earth Observation-Based Monitoring and Forecasting of Rangeland Water Resources” (Rangelands Monitoring and Forecasting System) project partners with FEWS NET to develop new capabilities for monitoring and forecasting water availability in African rangeland ponds.  FEWS NET partner, the U.S. Geological Survey, maintains the Water Point Viewer (https://earlywarning.usgs.gov/fews/software-tools/25), an interactive map that monitors the relative depth and area of 338 water points across arid and semi-arid regions of the Sahel and East Africa, from Senegal to Somalia.  The Rangelands Monitoring and Forecasting System project aims to significantly expand and improve the existing FEWS NET Water Point Viewer by increasing the locations monitored, developing new time series of water point surface area using high-resolution satellite data, improving overall model physics, and developing new forecasting capabilities.  These advanced data streams aim to improve pastoral resilience to climate shocks by increasing the capacity of stakeholders to plan for and respond to drought emergencies.

In this presentation, we introduce the Rangelands Monitoring and Forecasting System project and present first results from the 2022 field season.  During the 2022 West African rainy season, Action Contre la Faim collected water level observations from staff gauges installed in twelve ephemeral ponds located along transhumance corridors in Senegal.  Over the same period, the surface water extent of each pond was estimated using Sentinel 1 synthetic aperture radar, Sentinel 2 multispectral data, and Landsat multispectral data.  Additionally, the FEWS NET Water Point Viewer simulated water levels in nearby ponds.  The observed water levels were compared to the modeled surface water levels and the satellite data-based surface water extents to understand how well the FEWS NET Water Point Viewer and remotely sensed data streams capture the seasonal variation of water availability in the ponds.

This presentation: 1) presents the comparison results and discusses the accuracy of the model- and satellite-based estimates of water availability; 2) discusses the limitations of using remotely sensed estimates of water availability in the West Africa Sahelian region; and 3) presents lessons learned from conducting a field campaign in rural areas of West Africa.  The results from the first year of the project will inform the development of the next generation of the FEWS NET Water Point Viewer and new satellite-based remote sensing data streams for monitoring water availability in pastoral regions.

How to cite: Slinski, K., Senay, G., Rowland, J., Budde, M., Shukla, S., McNally, A., Adoum, A., Fillol, E., Ndiaye, B., and Assane Diallo, C.: In Situ and Earth Observation-Based Monitoring of Water Availability in Rangeland Areas of the Sahel and East Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17140, https://doi.org/10.5194/egusphere-egu23-17140, 2023.

Despite the riparian state of river Yamuna and local groundwater reserves, Delhi depends on other rivers to fulfil the rising demand for drinking water.  In the last ten years, the water demand has increased by 39% (2006-2016). In this study, we have tried to understand the domestic water supply system by studying the spatiotemporal variation in the stable isotopic composition of tap water. The stable water isotopes are powerful tracers of hydrological processes in natural and human-managed systems. There are three primary sources with distinct stable water isotopic composition River Yamuna, Upper Ganga canal, Munak canal and local groundwater reserves; the glacial-fed Himalayan rivers and canals fulfil around 90% of the water demand. Numerous government-operated treatment plants in Delhi purify the water from one of the above sources and supply it to consumers. We collected the water sample at every stage of the water supply, from the primary source to the sink, such as samples of canal or river water, raw water before treatment, filtered water after treatment, storage reservoirs, groundwater samples and finally, the household tap waters. 

Contrary to the river, canal water’s isotopic composition shows no spatial variation. Also, the isotopic composition of raw water is similar to the filtered water, indicating no significant loss due to evaporation or any other hydrological process. However, the isotopic composition of tap water shows considerable variation and deviation from its source value. In most regions, tap water’s isotopic composition is higher than that of source water. In Delhi, among all the other sources, the isotopic composition of surface water is lower than that of groundwater. Thus, only the mixing of groundwater with surface water before supplying it to households can explain the observed large variation in the isotopic composition of tap water. Furthermore, our observation suggests groundwater extraction for domestic purposes has increased from 2019 to 2021. The demand for domestic water per capita is rising with the increase in the population. However, the production of treated water is almost constant and depends upon the raw water availability. The excess extraction of groundwater fulfils the gap between supply and demand. Our study suggests that the surface water (river and canal water), or the number of treatment plants, is insufficient to meet the rising water demand in Delhi, which has led to the overexploitation of limited groundwater reserves in the past few years. Therefore, besides irrigation, the excessive groundwater extraction for domestic purposes results in a drop in the North-west India groundwater table. 

How to cite: Ajay, A. and Sanyal, P.: An increase in domestic tap water consumption led to a decline in the groundwater reserves of Delhi, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-583, https://doi.org/10.5194/egusphere-egu23-583, 2023.

The general aim of this work was to define a methodology for setting the environmental flows (E-Flows) in a temporary river with limited data availability through a case study. In the literature, there are many methods to set up an E-Flow, however, the issue is still an emerging discipline in non-perennial rivers due to the lack of specific guidelines at the European and national level and the limited availability of data (i.e., hydrological/biological).

The study area is the Locone river basin (219 km²) located in southern Italy. The climate is typically Mediterranean. The flow regime shows a pattern of low flow and zero flow in summer. The Locone is classified by the River Basin Authority as a temporary river. Upstream of the dam, streamflow was measured from 1971 to 1983. The main land use is winter wheat (64% of the total area), followed by broad-leaved woods (6.6%) and broad beans (5.4%). The main hydrological pressure in the basin is represented by the Locone dam. It was built in 1986 for agricultural purposes (approximately 5,000 hectares are irrigated) and for a hydroelectric power station (1,693,000 kWh / year).

To compensate for the lack of hydrological and ecological data, which characterizes these types of rivers, the open-source Soil and Water Assessment Tool Plus (SWAT +) model was applied. SWAT + is a completely revised version of the SWAT model, which is a physical scale and watershed model, which operates on a daily time step (Arnold et al., 1998). The model was calibrated (NSE = 0.720; Pbias = -11.514 and R2 = 0.84) and validated (NSE = 0.42; R2 = 0.45; Pbias = -12.5). The flow regime has been characterized under un-impacted conditions over a long period (1971-2020) using hydrological alteration indicators (IHAs) based on modeled daily flows. The E-Flow was set by fixing the variability range of each IHA within the interquartile (25th-75th percentile) by applying the Range of Variability Approach. For the Locone reservoir, the mean monthly flow of water releases, the magnitude, and duration of high and low flows, as well as the timing and frequency of floods and drought conditions were defined.

This work made it possible to test the SWAT+ model in a Mediterranean environment, confirming its potential. The applied method represents a first useful evaluation analysis that should be revised following ecological data monitoring actions to corroborate the eco-hydrological relationships.

How to cite: Leone, M., Gentile, F., Lo Porto, A., Ricci, G. F., and De Girolamo, A. M.: Predicting un-impacted flow regime in a Mediterranean catchment with SWAT+ for setting an Environmental Flow, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-775, https://doi.org/10.5194/egusphere-egu23-775, 2023.

In the Mediterranean Region basins are characterized by a specific hydrological regime that generally includes periods of absence of flow and flash flood events. Lithological and geological features are factors that greatly affect the flow regime. In this work, the Soil and Water Assessment Tool (SWAT) model was applied to simulate the Canale d'Aiedda (Apulia, Italy) flow regime, a Mediterranean temporary karst river basin with limited data availability. Different basin delineations and model parameterizations were adopted that include: (i) cut-off of karst areas in GIS (Configuration A); (ii) setting up the basin including the karst areas (Configuration B) and (iii) parameterizing, in the calibration process, the Crack Flow function in the karst sub-basins (Configuration C). The model performed satisfactorily for daily streamflow for configurations B and C and good for A. A better simulated large floods. C was the best solution for monthly flow from May to July. Regarding the water balance, C showed higher surface runoff values and lower total water yield values than A and B. The Crack flow function proved to be a valid option to improve the simulation of hydrological processes in karst areas. Several factors, such as the final aim of the study, data availability, and basin characteristics should be considered in selecting the best model configuration.

How to cite: Centanni, M., Ricci, G. F., De Girolamo, A. M., and Gentile, F.: Different approaches to model temporary hydrological regimes in a Mediterranean karst basin using the SWAT model., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-778, https://doi.org/10.5194/egusphere-egu23-778, 2023.

Syria is now witnessing the dramatic effects of a multiyear drought that has been afflicting the country since 2006. The drought has impacted several regions, but the north-eastern Al Jazira region, corresponding to the Middle Euphrates River basin and considered the Syrian “breadbasket”, has been hammered particularly severely.

With this paper we aim at contributing to the knowledge on the consequences of multiyear meteorological drought on food security in the basin of the middle range of the Euphrates River in Syria.

Annual precipitation data were collected from 11 ground meteorological stations for the period 1983–2020 covering an area of 96800km². Data were provided by the Syrian Ministry of Agriculture. In addition, the series of two satellite-based indices, namely Vegetation Condition Index (VCI) and Vegetation Health Index (VHI) were collected to analyse the vegetation responses to the meteorological drivers. These indices were downloaded at a resolution of 4-km for the time range 1983-2020, from the Centre for Satellite Applications and Research (STAR) of the National Oceanic and Atmospheric Administration (NOAA). The crop production data, including yields of cotton, wheat, and maize, were collected at provincial level over the period of 1983–2020 from Syria Statistical Yearbook.

Recent changes in meteorological drought features (e.g., frequency and intensity) throughout Syria for the years 1983–2020 were assessed by means of the Standard Precipitation Index (SPI), to characterize the meteorological draughtiness for the Al-Jazira region.

SPI was computed on a 12-month timeline to account for the delayed effect of rainfall deficiency on crop output. Commonly, agricultural droughts are evaluated using drought indices at these long timeframes (e.g., 18 and 24 months) because these longer timescales reflect the accumulated influence of meteorological drought that might alter soil water content and stream flow. The correlation matrices of the series of SPI, averaged at different time scales to focus on the effect of multiyear drought events, with the series of VCI and VHI, will be presented.

This work is preliminary to the GIS application of simplified Benfratello’s water balance method (Barontini et al., 2021) to assess the proneness to water scarcity and the irrigation deficit of different areas of the basin.

References

Barontini, S., Rapuzzi, C., Peli, M., and Ranzi, R.: A GIS based application of Benfratello's method to estimate the irrigation deficit in a semiarid climate, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12936, https://doi.org/10.5194/egusphere-egu21-12936, 2021.

How to cite: Mohammad, H., peli, M., and Barontini, S.: The Impact of Meteorological Drought on Vegetation Health in the Middle Euphrates River Basin (Syria), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-780, https://doi.org/10.5194/egusphere-egu23-780, 2023.

Yellow River is the mother river of the Chinese nation. It has provided available water resources for more than 5000 years and makes the Yellow River Basin (YRB) a significant grain-producing in China. Recently, promoting the high-quality development of the YRB has been proposed as a Chinese national strategy, highlighting the high status of the YRB in China. However, covering a large area of the arid and semi-arid region, hydrometeorological extremes such as droughts have often occurred in historical periods in the YRB, with prolonged effects on agricultural production. In addition, water conflicts (i.e., water shortage) between human beings’ needs and water resource availability have been much more severe due to population growth and global warming, affecting the ecological health of basins and challenging the lives of riparian residents. Baseflow is a stable flow during the drought season to discharge total streamflow from the groundwater and other delayed sources, which is significant for maintaining the ecological health of river basins and promoting sustainable economic development in arid and semi-arid catchments. Therefore, it is urgent to investigate baseflow characteristics and their determinants for understanding the hydrological processes better and provide scientific foundations for mitigating water shortage problems in the YRB.

Based on that, we collected the daily streamflow records from the main catchments in the YRB. The daily ensembled mean baseflow records derived from Lyne-Hollick, Chapman-Maxwell, Eckhardt and United Kingdom of Institute Hydrology (UKIH) separation algorithms were obtained after the 21^st century to reduce simulation uncertainties. Dynamics hydrological signatures were extracted to investigate baseflow spatiotemporal variations and their determinants. Catchments’ physical properties, including topography, vegetation, soil and human activities, were selected. The stepwise model was conducted to see how these catchments’ properties influence the hydrological signatures variability and the ranking of their importance. Our findings showed significant spatial distribution patterns of hydrological signatures in the YRB. Most of them had higher values in upstream and downstream reaches, while low values were in the middle reaches. The magnitude of temporal variation of hydrological signatures was strongly correlated with the catchment topography, vegetation conditions and cropland coverage. It is challenging to discover one single controlling property influencing hydrological signatures for all catchments across the YRB. For most of the hydrological signatures, soil textures, precipitation and vegetation conditions are the most significant influencing factors, indicating the baseflow processes are influenced by a synergistic effect in the YRB.

This study comprehensively investigated the baseflow characteristics in the whole YRB. It can not only provide scientific foundations for water resources management in the YRB but also take an example of how to quantitively evaluate the baseflow characteristics in large semi-arid and arid catchments.

How to cite: Lyu, S. and Zhang, J.: Evaluation of baseflow processes in the Yellow River Basin, China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-975, https://doi.org/10.5194/egusphere-egu23-975, 2023.

Growing forests is an effective way of removing CO2 from the atmosphere. Forestation projects were started in China, Germany, and the Middle East. Saudi Arabia announced its ambitious “Saudi Green Initiative,” intending to plant ten billion trees. Given the insufficient rainfall to support the initiative, vegetated areas will require irrigation, effectively increasing evaporation. In addition, those areas have a lower albedo than bare land, absorbing more solar radiation. Enhancing precipitation due to the recycling of evaporated water is important as it reduces the amount of freshwater required for irrigation.

In this study, we focus on the regional climate impact of irrigated forested or vegetated areas on temperature and precipitation over the Arabian Peninsula to quantify their effect on livability and evaluate the water recycling potential. First, we studied the climate effect of irrigated farming developing over vast areas in Saudi Arabia since the 1980s. The agricultural areas were mapped using available satellite-based observations from the Landsat platforms, which capture optical and thermal data every 16 days at a resolution of 30 m to 100 m. Second, we projected the climate impact of widespread forestation over the Arabian Peninsula.

The analysis of the long-term precipitation changes caused by irrigated farming is hindered by the lack of in situ observations and the limitations of global-scale observation data sets. Most reanalysis products have contradictory evaporation trends and indicate an overall reduction in rainfall since the 1980s. The recycled precipitation cannot be estimated reliably because of reanalysis increments and background rainfall variability. Presumably, the local increase in rains occurs downstream of the irrigated areas rather than over them. Along with the analysis of observations, we conducted numerical experiments mimicking the effect of irrigated agricultural fields using a non-hydrostatic regional meteorological model (WRF), covering the whole Arabian Peninsula by a 9x9 km2 grid, with 3x3 km2 nesting over the irrigated areas. Irrigation water is accounted for by tagging moisture evaporated from agricultural regions. The amount of tagged water vapor falling as rain represents recycled precipitation. The simulated evaporation and local temperature response strongly depends on the level of irrigation. Large-scale subsidence suppresses the local deep convection over most parts of the Arabian Peninsula. Strong turbulence quickly mixes evaporated water vapor within a six km thick atmospheric boundary layer, preventing precipitation in shallow convection so that the fraction of recycled rainfall appears to be low.

How to cite: Dufour, A., Mostamandi, S., Johansen, K., Lopez Valencia, O., and Stenchikov, G.: Impact of Forestation and Land-use Changes on Desert Climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1745, https://doi.org/10.5194/egusphere-egu23-1745, 2023.

Precipitation is the main component of the hydrological cycle; it is a crucial source of data in hydroclimate applications for water resources management. However, several regions, especially mountainous and arid regions, suffer from limited data from a ground measurement network. Remotely sensed data may provide a viable alternative for these regions. This study aims to evaluate six high spatio-temporal resolution satellite products (GPM-F, GPM-L, GPM-E, CHIRPS, PERSIANN-CCS-CDR and PDIR-Now) in the sub-Saharan regions of Morocco during the period September 2000-August 2020. The record data from 33 rain-gauge stations was used to evaluate these products on two spatial scales (pixel and basin scales) and three temporal scales (daily, monthly and annually), adopting a quantitative and qualitative evaluation. For all examined timescales, the results showed that the GPM-F product performed the best quantitatively, while at the detection capability tested for different threshold and at daily time scale, the GPM near real-time products (GPM-E and GPM-L) were better at detecting more intense rainfall events higher than 40 mm/day. At the daily time scale, GPM-E and GPM-L and, on monthly and annual scales, CHIRPS and PERSIANN-CCS-CDR, provided satisfactory precipitation estimates. Moreover, the evaluation based on the altitudes of rain gauges revealed a bias increasing from low to high altitudes. The findings also highlight that the continental and mountainous basins showed the lowest performance compared to the other locations closer to the Atlantic Ocean. The latitude-based analysis showed a decrease of bias and increase of correlation towards the most arid zones. These results provide valuable information for a scarcely gauged and arid regions, showing that GPM-F could be a valuable alternative to rain gauges.

How to cite: Rachdane, M., El Khalki, E. M., Saidi, M. E., Nehmadou, M., Ahbari, A., and Tramblay, Y.: Assessment of six satellite precipitation products in a Moroccan arid area, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1808, https://doi.org/10.5194/egusphere-egu23-1808, 2023.

A novel quantitative assessment of late Holocene precipitation in the Levant is presented, including mean and variance of annual precipitation and their trends. A stochastic framework was utilized and allowed, possibly for the first time, linking high-quality, reconstructed rises/declines in Dead Sea levels with precipitation trends in its watershed. We determined the change in mean annual precipitation for 12 specific intervals over the past 4500 yr, concluding that: (1) the twentieth century was substantially wetter than most of the late Holocene; (2) a representative reference value of mean annual precipitation is 75% of the present-day parameter; (3) during the late Holocene, mean annual precipitation ranged between −17 and +66% of the reference value (−37 to +25% of present-day conditions); (4) the driest intervals were 1500–1200 BC and AD 755–890, and the wettest intervals were 2500–2460 BC, 130–40 BC, AD 350–490, and AD 1770–1940; (5) lake-level rises and declines probably occurred in response to trends in precipitation means and are less likely to occur when precipitation mean is constant; (6) average trends in mean annual precipitation during intervals of ≥200 yr did not exceed 15mm per decade. The precipitation trends probably reflect shifts in eastern Mediterranean cyclone tracks.

How to cite: Morin, E., Ryb, T., Gavriely, I., and Enzel, Y.: Mean, variance, and trends of Levant precipitation over the past 4500 years from reconstructed Dead Sea levels and stochastic modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2519, https://doi.org/10.5194/egusphere-egu23-2519, 2023.

The arid Tarim River Basin, situated in the Eurasia hinterland, serves as the heart of China’s Silk Road Economic Belt. It covers an area of 1.02 million km² and is surrounded by the Tienshan Mountains to the north, the Kunlun Mountains to the south and the Pamir to the west. During the past few decades, the contradiction between economic growth and environmental protection is particularly evident. For example, the desert riparian forest vegetation has declined along the lower reaches of the Tarim River.

Under global warming, the climate has experienced significant warming and moistening trend during 1961–2018, and the most dramatic increase has occurred since the mid-1980s. The increased precipitation and temperature and the resulted hydrological and ecological changes lead to a hot debate about the “warm–wet” trend. This study systematically investigated the climate change and their impact on hydrological and ecological processes. The temperature increased at a rate of 0.224 ℃ per decade and an evident jump was detected in 1998. For precipitation, about 72.3% meteorological stations experienced significant increase, with an average increasing rate of 7.47 mm per decade. The changes in climatic factors contribute to the changes in the accumulation and ablation of snow and glaciers, which resulted in changes in hydrological processes. The total lake area in the Tarim River has expanded at a rate of 23.79 km² per year during 2012–2021. More specially, the lake area of Ayakum Lake (located near the northern boundary of the Tibetan Plateau) has increased by 50% since 1990, with an increment of 111.61 km² during 1990–2000 and 401.4 km² during2000–2020. The runoffs of the headwaters (i.e., Kaidu River, Aksu River, Yarkant River and Hotan River) of the Tarim River have also increased by a rate of 2.06×10⁸m³, 2.11×10⁸m³, 1.12×10⁸m³ and 2.56×10⁸m³ per decade, respectively.

However, the changes in ecological systems don’t reflect the wetter trend in the Tarim Basin. The negative effects of climate change on the region’s vulnerable ecology have intensified. The snowfall fraction experienced an overall declining trend, increasing at a rate of 0.6% per decade prior to the mid-1990s, followed by a downward trend at a rate of 0.5% per decade. Potential evaporation decreased at a rate of 41.66mm/10a per decade prior to the mid-1990s, and inversed to increase at a rate of 56.68 mm per decade. Prior to 1998, the normalized difference vegetation index (NDVI) of natural vegetation exhibited an increasing trend at a rate of 0.012 per decade, but from 1999 onwards, the NDVI started decreasing at a rate of 0.005 per decade. The bare soil areas of the Taklamakan Desert boundaries expanded by 7.8 % since 1990. Excessive water use, including unrestrained overpumping of groundwater, causes the loss of groundwater.

This study sheds light on the debate of changes in climate and ecological security under global warming in the endoreic Tarim River Basin. However, more efforts should be made on the continuity of these changes, which is crucial for local development and water and ecological security along the Silk Road.

How to cite: Li, W., Li, Z., Chen, Y., and Fang, G.: Is there a turning-point towards improved water and ecological security at the arid Tarim River Basin?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3315, https://doi.org/10.5194/egusphere-egu23-3315, 2023.

The Sahara is the largest and perhaps the driest desert in the world. This desert however, has not always been this dry. In fact, it is presumed that a few thousand years ago it was much wetter. Moreover, it is projected that, by the end of the 21^st century, the Sahara will exhibit the strongest relative increase in precipitation outside the polar regions. To better grasp this information, however, we need to answer some questions: wetter than what? What is the present-day rainfall climatology of the Sahara and what are the synoptic conditions during rainstorms in the desert?

Currently, rainstorms in the Sahara are considered a rare phenomenon. However, rain-bearing cyclones intruding from wetter neighboring regions are possible, and can lead to heavy precipitation events (HPEs) which cause hazardous desert floods. When rainfall occurs, the chances for it to be observed and measured at the ground are close to zero due to the scarcity of rain gauges and the small scale of the precipitation systems. Consequently, the characteristics of rainfall during Saharan rainstorms were seldom analyzed, especially at the scale of the whole desert. In this study, we use high-resolution satellite precipitation estimates (IMERG) and meteorological reanalysis (ERA5) to (a) identify thousands of HPEs that occurred over the Sahara in the past 21 years, (b) characterize rainfall properties during these events, and (c) identify the governing atmospheric conditions on HPE-days, with a focus on surface cyclones.

Our results show that HPEs may occur throughout the entire Sahara. Summer events happen mainly in the southern Sahara. They tend to be short-lived (on average ~12 h) and small in size (~8000 km²), with high-intensity convective rainfall. Conversely, winter HPEs occur primarily in the northern and western parts of the desert, they are longer (~16 h) and larger (15,000 km²) and produce higher rainfall volumes with lower rainfall intensities. When associated with cyclones (29% of events), HPEs exhibit 15% lower rainfall intensities, and 46% higher volumes. This is likely due to a much greater (+64%) areal extent. Our analysis compensates the small number of events at each location with the huge area of the desert, so that a HPE is observed on average every second day. The high-resolution datasets we use enable us to characterize small-size events, with substantial implications for the local scales. Hopefully, such an analysis can serve as a starting point to cope with natural hazards and better understand the future of HPEs in the Sahara.

How to cite: Armon, M., de Vries, A. J., Marra, F., Peleg, N., and Wernli, H.: Heavy precipitation events where there’s no rain: Saharan rainfall climatology and its relationship with cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4167, https://doi.org/10.5194/egusphere-egu23-4167, 2023.

There are many hydrological models for normal terrestrial environments based on precipitation related erosion, but few of them work well in arid and hyper-arid conditions. These extreme arid regions can be good Mars analogue sites to test and model the conditions and laws of precipitation fed runoff and produced erosion on the Red Planet and infer to past periods. The hydrological model we have developed is primarily designed for Martian conditions and has been tested and validated in the Zafit subbasin of the Zin basin of the Negev desert, the eastern part of Israel. The calculated model data were also compared with data from hydrological models and field measurements in the area. Our applied hydrological model without precipitation data is able to estimate the main hydrographic characteristics of the sample area, such as flow discharge, flow velocity, flow depth, and the model is also able to estimate the Formation Timescale (FTS) of some surface features, as well as vertical erosion rates. The model was developed in the open source QGIS software using SAGA and GRASS GIS modules. It uses input variables that can be measured not only under terrestrial conditions but also measured or estimated under Martian conditions, and there are good quality datasets of them. Examples of such variables are the aridity index, which plays an important role in determining the flow discharge, or the density of the rock that makes up the grains, water density, gravity, and grain size classes. The model can be run on any DTM (Digital Terrain Model), the most important constraint being that the linear unit of projection used is defined in SI metres. The hydrological part of the model is complete however under continuous development, and the final model will be complemented by a further developed erosion model to simulate long term surface evolution and change, thus facilitating the understanding of not only terrestrial but also fluvial erosion produced Martian surface changes.

How to cite: Steinmann, V. and Kereszturi, Á.: Testing hydrological model for Mars using Negev desert based field observations on the Earth., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5987, https://doi.org/10.5194/egusphere-egu23-5987, 2023.

Atmospheric water, or non-rainfall water inputs (NRWIs) are a critical, albeit largely overlooked, component of the global hydrological cycle. Water vapor adsorption specifically, is not only the least studied form of NRWI but likely the most common one in arid areas.

Lysimeter measurements in the Negev desert during the summers of 2019-2022 indicate that water vapor adsorption in loess soil amounts to at least 33 mm when looked at cumulatively over the summer (0.3-0.5 mm night^-1): about ~30% of annual rainfall (116 mm). Given the challenges using lysimeter measurements, attempts to quantify NRWI amounts and duration have generally been limited to short time periods at point or local scales. Determining the true importance of NRWIs in arid and extremely arid environments, which comprise 20% of the terrestrial surface, requires new approaches to measure water content in the 0.5-5% range.

Using weighing lysimeters as a reference, we tested of-the-shelf temperature and relative humidity sensors to assess changes in water content with high temporal resolution over longer periods of time for sand and loess soils. Relative humidity was converted to water potential (Kelvin equation). The water content was then determined using a water retention curve measured with a vapor sorption analyzer. Results showed diurnal patterns in water content consistent with lysimeter measurements. Maximum increase in water content correlated well with lysimeter measured NRWIs. While not all issues are yet resolved, this direction opens possibilities to expand our measurement capacity over longer periods of time and increase the number of measurement locations at relatively low cost. This provides one step forward in trying to understand the magnitude of NRWIs in arid environments across the globe.

How to cite: Kool, D. and Agam, N.: Atmospheric water capture by desert soils: can we measure it?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6074, https://doi.org/10.5194/egusphere-egu23-6074, 2023.

Intermittent and ephemeral rivers are characterized by periods of drying and rewetting which occur along different reaches of the channel. Where the channel dries or develops into ponds related to factors such as discharge, topography, geology and riparian vegetation. The aim of this work is to evaluate the spatial patterns and dynamics of intermittency in reaches of a Brazilian semiarid river. Using repeated surveys with unmanned aerial vehicles (UAVs), we characterize its connectivity by identifying locations with different water condition. The Umbuzeiro River (approximately 80 km long; 6.65°S, 40.41°W) is the main river in the Benguê catchment (~1000 km²) that is controlled by the Benguê reservoir, with a storage capacity of 18 hm³. Umbuzeiro is an intermittent/ephemeral river and spatially coherent streamflow occurs mainly in the wettest months of the rain season. We conducted UAV surveys each month from March to June 2022, allowing us to produce detailed hydrological characterizations along different sections of the river. The imagery sets from different UAVs, i.e. DJI Phantom 4 pro and eBee SQ, provided relatable characteristics for a same reach. Visually analysing the reaches, their water condition was determined for smaller subsets, i.e. ponds or dry spots. Observing the temporal and spatial patterns of the presence of water on the riverbed in the different reaches for each survey, we conclude that the patterns are not only dependent on the contributing area of each section, but also on the river’s natural sinuosity, riffle-pool sequences and riparian vegetation. Our results highlight and provide an explanation for the hydrological diversity of semiarid rivers which is important to understand their ecological role and habitat.

How to cite: Soares, N. S., Costa, C. A. G., Francke, T., Medeiros, P. H. A., Mohr, C., Schwanghart, W., and De Araújo, J. C.: Spatial distribution of intermittency in a Brazilian Semiarid river, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7066, https://doi.org/10.5194/egusphere-egu23-7066, 2023.

The Atacama desert is one of the most promising places on Earth for developing solar power energy due to its aridity, irradiation, and market conditions. However, the high levels of dust attenuate solar power production. This problem is solved by frequent cleaning of the solar panels, which requires a significant amount of water in one of the driest places in the world. Despite the drought condition, the fog and dew formed at the coastal zone of the desert arise as a complementary water source that can potentially be tapped. In this study, we assess the potential of atmospheric water for usage in four solar power plants. We conduct this assessment by combining a satellite-spatial analysis of fog and low cloud frequency, a thermodynamic vertical characterization of the marine boundary layer, and an observational analysis of fog and dew collection using different instruments. Our results reveal that fog and dew are a regular phenomenon in the solar power plants analyzed, being present between 3% and 20% of the year. Oceanic conditions control such phenomena through the inland advection of the marine boundary layer. This layer interacts with a complex topography characterized by natural corridors that allow fog and low clouds to penetrate farther inland. Our observations show that fog and dew are collected mainly during the night, with average rates between 0.1 and 0.2 L m^-2 day^-1. Our research confirms that atmospheric water potential vastly exceeds the solar power plant water demand, demonstrating that atmospheric water is a reliable source for the industry.

How to cite: Lobos Roco, F., Suarez, F., Escobar, R., Osses, P., Ramirez, C., Keim, K., Aguirre, I., Aguirre, F., Vargas, C., Abarca, F., and del Rio, C.: The usage of fog and dew in solar power plants of the Atacama Desert, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9376, https://doi.org/10.5194/egusphere-egu23-9376, 2023.

The Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) when combined with traditional data sources (geochronology, geochemistry, hydrology, modelling) can enhance our understanding and monitoring of elements of hydrologic systems including recharge of reservoirs, groundwater flow direction and rates, and the impacts of climate change on watersheds worldwide.  We cite a few examples. Large seasonal fluctuations (peak: Nov./Dec.; trough: July/Aug.) in Lake Nasser's surface water levels are accompanied by an increase in GRACE_TWS (average: 50 ± 13 mm/yr, up to 77 ± 18 mm/yr) over Lake Nasser in Upper Egypt and by a progression of a front of increasing GRACE_TWS values (> 50 ± 13 mm) away from the lake reaching distances of up to 700 km some 3 to 5 months following peak lake level periods. Those patterns are consistent with rapid turbulent groundwater flow from Lake Nasser along preferred flow directions (networks of faults and karst topography). The Tigris Euphrates watershed (30 dams) showed an impressive recovery following a prolonged drought (2007–2018; Average Annual Precipitation [AAP]: ~400 km³) by an extreme precipitation event in 2019 (726 km³) with no parallels in the past 100 years. This recovery (113±11 km³) compensated for 50% of the losses endured during drought by impounding a large portion of the runoff within the reservoirs (capacity: 250 km³). The Aswan High Dam, with its storage capacity of 150 km³ represents one of the best-engineered systems that enabled Egypt to ride out droughts and avoid extreme flooding events that affected neighboring Sudan. Additional engineering structures are recommended to take advantage of the excess Lake Nasser waters (35 km³), now residing in the Tushka lakes. In basins lacking artificial reservoirs, a different response to extreme precipitation events is observed from temporal GRACE solutions. Extreme precipitation events (2011-2022) over northern Arabia (PPT: Hail: 8.43 km³; Ad-Dahna: 2.22 km³ and Medina: 3.71 km³) and central Arabia (PPT: Riyadh: 4.66 km³ and Mecca: 0.21 km³) produced an increase in GRACE_TWS that lasted for a few months only. Cyclones over Oman (2011and 2015; PPT: 6 and 6.6 km³, respectively) had a similar effect. Findings demonstrate that highly engineered watersheds are better prepared to deal with the projected increase in the frequency and intensity of extreme rainfall and drought events in the 21st century.

How to cite: Sultan, M., Abdelmohsen, K., Saleh, H., and Karimi, H.: Recharge from Reservoirs, Groundwater Flow, and Response to Climate Variability in Arid Basins: Revelations from GRACE Observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9959, https://doi.org/10.5194/egusphere-egu23-9959, 2023.

In Mongolia, overuse and degradation of groundwater is a serious issue. The authors have recently applied a process-based eco-hydrology model, NICE (National Integrated Catchment-based Eco-hydrology) to urban and mining hubs to explicitly quantify spatio-temporal variations in water availability (Nakayama et al., 2021a, 2021b). In this study, NICE was scaled up to the total of 29 river basins in the entire country (Ministry of Nature, Environment and Tourism, 2013). The model simulated the effect of past climatic change and human activity on water resources during 1980-2018 there. The model reasonably reproduced observed river discharge with a maximal value during summer rainfall seasons. The simulation also revealed heterogeneous distributions of hydrologic budget and its response to climatic and anthropogenic disturbances. In addition, the authors detected hot spots of groundwater degradation by anthropogenic activity in the national scale. Analysis of relative contribution of environmental factors further clarified the characteristics in these areas and quantified spatio-temporal trends in groundwater level due to the effects of changes in precipitation and various water uses. Generally, the result showed changes in precipitation had a large effect on changes in groundwater levels until 2000. In contrast, the model clarified human activities have recently had a large impact on groundwater level changes (Banerjee et al., 2014). This trend was particularly conspicuous in river basins with urbanization and mining development such as Orkhon, Kharaa, Tuul, Galba, Ongi, Altain Uvur Govi, and Taats River Basins. This methodology is powerful to resolve future competition for water resources in areas with fewer inventory data that could potentially trigger conflicts between urban, mining, industry, herders and local communities.

References;

Banerjee, R., et al. 2014. 2030 Mongolia: Targeted Analysis on Water Resources Management Issues, https://www.2030wrg.org/mongolia-targeted-analysis-wrm-issues/.

Ministry of Nature, Environment and Tourism. 2013. Basin Boundary Data in Mongolia, Ulaanbaatar.

Nakayama, T., et al. 2021a. Ecological Modelling, doi:10.1016/j.ecolmodel.2020.109404.

Nakayama, T., et al. 2021b. Ecohydrology & Hydrobiology, doi:10.1016/j.ecohyd.2021.07.006.

How to cite: Nakayama, T.: Impacts of anthropogenic activity and climate change on water resources for the whole of Mongolia by using process-based eco-hydrology model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10173, https://doi.org/10.5194/egusphere-egu23-10173, 2023.

The Groundwater-Surface water (GW-SW) interaction governed by vertical connectivity, drainage pattern, subsurface lithology, vegetation cover, and land use determines the water availability in semi-arid dryland regions. It plays a crucial role in eco-hydrology, effective water resource management and overall socio-economic development in these marginal environments. Furthermore, the perennial dryland rivers flowing through these semi-arid dryland regions undergo substantial precipitation and flow variability, thus making sustainable water management challenging. Nevertheless, an understanding of the GW-SW dynamics, its spatial variability and the processes influencing the water supply in the semi-arid perennial dryland rivers are still lacking. For this purpose, the stable isotopes of oxygen and hydrogen, in terms of δ¹⁸O, δ²H and d-excess parameters of water samples, have been used to assess the GW-SW interaction in the semi-arid perennial Mahi River basin, India. The Mahi River has a length of ~560 km and a drainage basin area of ~34k km². In total, 53 samples of groundwater and 14 samples of river water were collected during the dry season. In a given river transect, GW samples were collected from both river banks at a distance of around 1 km and 2km, respectively. The result shows changes in GW-SW connectivity at the reach scale. The SW in the downstream and middle reaches (36 to 208km from the river mouth) is characterised by a progressive decrease in δ¹⁸O from -1.3 ‰ to -2.6‰. The decrease in the δ¹⁸O value in the middle and downstream reaches indicates the mixing of depleted GW into the river. The trend changes in the upstream reaches (208 to 491km), where the SW becomes progressively enriched in δ¹⁸O from about -2.1‰ to 0.08‰, with reach scale variability. The upstream reaches also show a decrease in d-excess value from -3.2‰ to -7.2‰, along with the increasing δ¹⁸O values suggesting enhanced evaporation of SW during the low flow conditions. The average δ¹⁸O of SW in the middle and downstream reach is -1.9 ‰, whereas the average δ¹⁸O of the upstream reach is -0.5 ‰. The slope of the GW δ¹⁸O-δ²H regression line is lower than that of the Global Meteoric Water Line (GMWL), suggesting that the GW undergoes substantial evaporation. The variability of isotopic values and mixing of GW with SW demonstrates that the river channel shows enhanced vertical connectivity for middle and downstream reaches even during the dry season. However, there is vertical disconnectivity in the upstream reaches. This study highlights the need for different management strategies for various reaches of the spatially variable and dynamic perennial dryland rivers in a semi-arid region.

How to cite: Raj, A., Jain, V., Bind, V. K., Padhya, V., and Deshpande, R. D.: The GW-SW dynamics of a perennial dryland river in the semi-arid region, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12017, https://doi.org/10.5194/egusphere-egu23-12017, 2023.

Sardinia island is a reference for ecohydrological studies on past and future climate change effects, representing typical conditions of the western Mediterranean Sea basin. Ecosystems are heterogenous, and trees optimize the use of water through the root systems, uptaking water from the deep layers.

Two micrometeorological towers have been installed in two different sites under different precipitation conditions. The first is installed in Orroli (annual precipitation of about 600 mm), in a patchy mixture of wild olive trees and C3 herbaceous that grow in a shallow under a rocky layer of basalt, partially fractured (soil depth 15 40 cm), with a tree cover percentage of 33% in the footprint. Instead, the second is in a mountainous forest site of Quercus ilex characterized by steeper slopes and rocky outcrops (mean annual precipitation of about 800 mm), and tree cover percentage of 68% in the footprint. In both sites land surface fluxes and CO₂ fluxes are estimated using the eddy correlation technique while soil moisture was estimated with water content reflectometers, and periodically leaf area index (LAI) were estimated.

The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture and CO₂ for two contrasting sites; 2) assess the impact of vegetation dynamics and type on the CO₂ and water balance dynamics; 3) evaluate the soil effect on water and energy budgets.

The Orroli site is more controlled by rainfall seasonality, and vegetation species use the source of water stored in the deep rocky layer to sustain their physiological activity. In the Orroli site we found seasonal dynamics in the CO2 flux and in the evapotranspiration (ET) terms, which are higher when grass and woody vegetation species are present and lower when the grass component dies. Instead, we found a constant flux of ET in the Marganai highlighting the high efficiency of tree species in extract the deep sources of water. ET is higher in the Orroli site if the grass species are present in live form, and then LE is higher in the Marganai forest. The ET of Quercus ilex in the Marganai forest seems being not controlled by surface soil moisture, because the annual precipitation is enough for sustain the transpiration needs of that fraction of tree cover. The results confirm a threshold of 700 mm/year of rain, below which rain can restrict tree cover growth.

How to cite: Corona, R., Sirigu, S., Montaldo, N., and Katul, G. G.: On the Evapotranspiration estimates of two contrasting and Heterogenous Ecosystems in Sardinia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13957, https://doi.org/10.5194/egusphere-egu23-13957, 2023.

Understanding the groundwater-surface water (GW-SW) interaction is critical for river management, especially in water-stressed regions such as semi-arid and arid areas. The pattern of GW-SW interaction may vary across variable valley settings, floodplain width and river planform.

This study aims to analyse the pattern of GW-SW interaction in different River Styles reaches. The study is carried out in the Sabarmati River basin in using stable isotopes. Sabarmati River is an intermittent River of 419 km in length that drains a 21,085 km² area in the semi-arid region of Western India. Representative sites of each River Styles were selected for water level measurement and stable isotope samples. The study was conducted in the post-monsoon period of 2021-22, which represents groundwater contribution to river system after major runoff seasons. Samples at each River Styles reach were collected along a cross-section. 1 river water and up to 4 groundwater samples (2 from each bank) were collected along the transect. A total of 48 samples were collected along 11 such transects. The depth of groundwater and stage of river water at each sample site was also measured.

The GW depth and river stage data indicate GW-SW connection for 9 sites (all except 1 are from the upstream region), while was inconclusive for 2 (all in the middle and lower reaches). Stable isotope-based analysis suggests a similar scenario. The upper reaches, which are gaining, have enriched δO18 composition and lower d-excess than the groundwater. The depleted isotopic composition of groundwater indicates faster groundwater recharge from the meteoric water. Such reaches are characterized by boulders and gravel beds. The reach-scale variability of the river from the losing-gaining stream also collaborates with the reach-scale variation of δO18 isotopic values. The losing reach has a depleted δO18 isotopic composition than the groundwater, thus indicating recharge of groundwater from the river water and the impact of evaporation. The integration of the River Styles map and GW interaction study suggests the following – (a) Generally, River Styles that were showing connected and gaining reaches were found to have low sinuosity  (b) River Styles with occasional and discontinuous flood-plains showed an inconclusive result about river aquifer connectivity by both methods (c) For all confined or partly unconfined reaches with bedrock margin-controlled settings, a connected river aquifer system was noted. The study highlights geomorphic control on the important process of GW-SW interaction in a semi-arid river channel.  

Keywords: River style, stable isotope, river-aquifer interaction

How to cite: Duggad, Y., Jain, V., Padhya, V., and Deshpande, R.: Water level and stable Isotope based river aquifer interaction in different river styles of a semi-arid river, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14719, https://doi.org/10.5194/egusphere-egu23-14719, 2023.

Understanding and quantifying hydrology processes represent a mandatory step in semi-arid and arid regions for defining the vulnerability of these environments to climate change and human pressure, as well as for providing useful data to steer mitigation and resilience strategies. This generally valid concept becomes even more stringent for highly sensitive ecosystems, such as small islands.

It is the case of Pianosa Island (Tuscan Archipelago) that extends a few more than 10 km² within the Tyrrhenian Sea and it is characterised by a flat morphology (maximum altitude 29 m a.s.l.) and semi-arid climate conditions (550 mm and 17 °C as mean annual precipitation and temperature).

Because of the morphology and the medium-high permeability of superficial bio-calcarenite rocks, superficial water are absent. Nevertheless, the peculiar geological-hydrogeological setting guarantee a storage of groundwater in a phreatic aquifer and semi-confined/confined system, hitherto able to satisfy the local human water demand, mainly tied to seasonal tourism (thousands of visitors/year) and domestic exigencies (less than 30 permanent people). Evapotranspiration represents the most important voice of the water budget, given the windy and relative high temperature conditions.

In the precarious hydro-equilibrium for biosphere and human communities, and considering sea-level rise and climate regime trends that the Mediterranean is experiencing, HYDRO-ISLAND project (UNESCO’s program) intends to deploy a multi-disciplinary approach (geology, hydrogeology, geochemistry, geophysics, remote sensing-smart technology) for better understanding and quantifying the hydrological processes affecting the water availability and for sharing data and transfer knowledge to the community and younger generations, possibly suggesting best practices for water sustainability.

First results pointed out as over the last decade the annual rainfall weakly tended to increase, but at the same time such increasing resulted concentrated in summer and autumn seasons, whereas during winter and spring a decreasing tendency is even observed. This precipitation regime has led to a major rate of evapotranspiration and minor effective infiltration that caused a decreasing of piezometric level over several years. Quantity and chemical-isotopic features of rainfall and effective infiltration water measured/collected by a raingauge and a high precision lysimeter describe the hydrological processes at soil level and characterize the rate and seasonality of groundwater recharge in an experimental site. Using multispectral data by drone, we are trying to extend the experimental site information to a wider area in order to understand the general behaviour at island scale. Measurements, water sampling and analyses for shallow and deep wells, together with the study of geological constraints, are highlighting the distribution and relationship among different groundwater components, including the seawater that intrudes the aquifer from the SE side of the island. Furthermore, the comparative analyses of continuative data monitoring in wells and weather station showed the presence of possible concentrated water infiltration processes during rainfall extreme events that induce a quick response of groundwater systems in terms of water level rise and decrease of electrical conductivity. Thus, elements of vulnerability of the aquifer to pollution are pointed out, as well as the possibility to provide technical solutions for enhancing water infiltration and groundwater availability.             

How to cite: Doveri, M., Menichini, M., Foresi, L., Berton, A., Costanza, L., Baneschi, I., Da Prato, S., Milaneschi, L., Raco, B., Santilano, A., Trifirò, S., Giannecchini, R., and Burlando, M.: Hydrological processes in the semi-arid small island of Pianosa: a multidisciplinary approach to increase knowledge, awareness and education on a highly climate-sensitive environment (HYDRO-ISLAND project UNESCO’s program), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15835, https://doi.org/10.5194/egusphere-egu23-15835, 2023.

Despite a warm and dry climate, the city of Nouakchott has been facing constant flooding for almost a decade, making part of the city inhabitable and posing long-term health threats. Groundwater levels are relatively constant over the year, except for October, when the groundwater table rises at the end of the rainy season, resulting in an almost doubled flooded area in the city compared to drier periods. Saltwater intrusion maintains a constant level in the water table beneath the city. However, the infiltration of most of Nouakchott’s used water acts as systematic artificial aquifer recharge, thus increasing the risk of groundwater saturation excess and flooding. Hence, in comparison to the driest decade (1971-1980), flooding in the city today cannot only be attributed to the slight increase in precipitation over the last decade. This project hypothesizes that increasing the resilience to urban flooding in the city of Nouakchott can be achieved by using salt-tolerant plants to lower the water table level. This work presents a joined interdisciplinary ecohydrology and plant physiology approach for monitoring and modeling the transpiration and dewatering capacity of different local tree species. The project aims to provide scenarios for an integrated and sustainable afforestation strategy for Nouakchott. In addition to increasing the city’s resilience to flooding, the role that afforestation could play to enhance the provision of sustainable services for the people and the economy (e.g., shade in the streets, potential fruit harvesting and wood market, etc.) will also be discussed. The first field campaign of the project allowed to monitor five observation wells with automatic water depth measurements and 12 sap flow sensors on three tree species. Eventually, to reinforce the relatively scarce groundwater data, a spatiotemporal time series of the city's flooded areas was also reconstructed using remote sensing data, and its reliability to calibrate an eco-hydrogeological model will be discussed.

How to cite: Perona, P., Dubois, E., Marshall, M., Boukhreiss, F., Ahmed Cherif, S. M., Chenal, J., and Grossiord, C.: Enhancing Urban Resilience to flooding using Afforestation: the case of Nouakchott city, Mauritania, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16423, https://doi.org/10.5194/egusphere-egu23-16423, 2023.

Rainfall in arid and semi-arid areas converts faster in the local SPAC system. Deluge in drylands may be an important source of groundwater recharge. We have been conducting a thirty-year observational in the Mu Us sandy land at the northwest China, we use remote sensing imagery to observe changes in the water body area and in situ observations to monitor rainfall infiltration. A total of 30 periods of Landsat remote sensing images were processed using the Google Earth platform to obtain the characteristics of surface water body changes. The results show that there are strong seasonal characteristics in the changes of water bodies area in the Mu Us sandy land, with two peaks in April and August, and the inter-monthly area increases of 44.867 km² (28.60%) and 47.832 km² (28.31%) respectively. 379.770 km² to 275.492 km², a total reduction of 104.278 km² (27.46%). Deep soil as a percentage of annual precipitation of woodland, shrubland, grassland, farmland and bare land were 2.88%, 17.36%, 3.64%, 1.21% and 44.30%, respectively. The change in the water body area in the Mu Us sandy land is mainly influenced by three factors, rainfall, vegetation coverage, and human activities, with a correlation coefficient of 0.57 (α=0.05) between rainfall and water body area. The correlation coefficients were 0.79, 0.79 and 0.86 (α=0.05) for the years 1991-1997, 1998-2005 and 2006-2017, respectively; vegetation coverage and water body area were negatively correlated overall in 30 years. The correlation coefficient was 0.57 (α=0.05), indicating that human activities in the Mu Us sandy land have a greater impact and human activities in the sands should be reduced in order to manage the sands.

How to cite: Cheng, Y., Bai, X., Ma, X., Xin, Z., Feng, W., Yang, W., and Zhou, J.: Response of ecological restoration to rainfall in arid zones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17048, https://doi.org/10.5194/egusphere-egu23-17048, 2023.

Forest cover influence the isotopic composition of precipitation before it eventually reaches the ground, especially through rainfall interception processes. Many plot scale recent studies focusing on throughfall and stemflow fluxes have demonstrated the role of forest canopy cover in (mostly) enriching their isotopic signature. However, the common approach in small catchments (even forested ones) remains to sample rainfall only at one single location (generally in an open area), assuming that the spatial variability of the isotopic composition of precipitation is small. Only a handful of studies have focused on the spatial variability of the isotopic composition of precipitation, and very few have included the role of forest cover. Nonetheless, a correct characterization of the isotopic composition of the incoming precipitation is essential in isotope-based catchment hydrology, for example to proceed hydrograph separation, as well as for process understanding or models development.

The aim of this study is to investigate the spatio-temporal variability of the isotopic composition of precipitation in a small Mediterranean catchment (0.6 km²) where forest cover roughly 2/3 of the catchment. Precipitation was sampled at the event scale in 31 locations across the catchment with bulk collectors consisting of plastic funnels (130mm diameter) connected to a 0.5-L plastic bin positioned 100cm above ground before each rain event and collected the day after. The sampling locations were distributed ±80m along 5 elevation lines every 50m (from 1150 to 1350m), 15 in open areas and 16 under forest (i.e., collecting throughfall). The percentage of canopy cover above each sampling location was determined using hemispherical photographs. For all events, rainfall was also measured every 5min at 3 locations with tipping bucket rain gauges and meteorological variables at 2 locations (at the ground level and above the forest canopy). Sampled events were analysed both altogether and separating open areas and under forest locations to determine the factors affecting the spatio-temporal variability of the isotopic composition of precipitation at the catchment scale and their relative influence.

Results show that mean δ¹⁸O of the events for the whole catchment varied from -11.96 to -3.6‰ along the year, with a mean coefficient of variation of 39%. Locations under forest were always more enriched than in open areas at the same elevation (+0.67‰ on average). Data analysis using the time stability approach (Vachaud et al., 1985) showed that forest locations had lower persistence of δ¹⁸O spatial patterns than open areas, indicating that spatial variability of isotopic composition was less predictable in forest locations compared to open areas. The elevation effect on δ¹⁸O, often observed in open area locations, was much less apparent in forest locations, confirming that forest introduced additional complexity on the spatial variability of the isotopic signal. Our findings highlight the actual need of taking into account the effect of both elevation and forest cover to assess a catchment scale representative isotopic composition of precipitation.

How to cite: Saurat, P., Llorens, P., Alharfouch, L., and Latron, J.: Influence of forest cover on the spatio-temporal heterogeneity of the isotopic composition of precipitation at the small catchment scale, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-496, https://doi.org/10.5194/egusphere-egu23-496, 2023.

Landscapes in the humid tropics are undergoing change in land cover. Besides ongoing deforestation of old-growth forest there is also natural regrowth and active reforestation. These changes in land cover affect soil hydrological properties, eg. saturated hydraulic conductivity (Ks), and thus influence hydrological flow paths. While it has been well documented that removing forest in favour of pasture establishment frequently leads to soil compaction and hence increased occurrence of overland flow and erosion, the effect of reforestation on soil hydraulic properties is less studied, especially not in terms of longer time series of forest regrowth.

We monitored the development of Ks in three reforested catchments in the Panama Canal Watershed, two reforestation trials with native species and teak and a secondary succession, over the course of 10 years. We measured Ks on undisturbed soil cores from the depths of 0-6 and 6-12 cm, applying the constant-head method. We compare the results to a previous study based on a space-for-time substitution in the same area.

Our results show a marked increase in Ks variability in both depths after the first five years of measurement. This points to a non-uniform influence of vegetation development across the catchments. Median Ks values in the topsoil increased at all three reforestation sites over the course of the monitoring period and reached values that considerably exceeded those previously measured in 100 year-old forests in the region, which appears at odds with an assumed continuous increase of Ks with increasing forest age. Further comparisons with soil and vegetation characteristics will be used to explain this apparent contrast.

How to cite: Hassler, S. K., Hall, J. S., van Breugel, M., and Elsenbeer, H.: Changes in saturated hydraulic conductivity during forest regrowth over 10 years in the humid tropics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1457, https://doi.org/10.5194/egusphere-egu23-1457, 2023.

Vegetation growth is sensitive to climatic variations which has a critical implication for hydrological regimes. However, the intertwined associations of climate-phenology-hydrology have rarely been explored in tropical/subtropical regions particularly. In this study, we synthesize hydroclimate records in forested watershed, central Taiwan for last five decades (1975-2020), and the results indicate that the incidences of meteorological and hydrological droughts are becoming prominent after 2001. We further examine the influences of temperature and precipitation on vegetation growth of watershed scale using EVI (enhanced vegetation index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) at monthly scale, and explore the effects of seasonal precipitation on the variations of landscape phenology and following watershed streamflow between 2001 and 2020. The EVI and temperature shows a linear relationship (R² = 0.50, p < 0.001) without time-lag effect, whereas EVI and precipitation exhibits a log-linear relationship with two months lag (R² = 0.40, p < 0.001), showing the accumulative rainfall during relatively dry period (winter-spring) is crucial for vegetation growth. Structural equation modeling reveals that earlier start of growing season (SOS) caused by relatively high spring rainfall (February-March) leads to longer growing season (LOS) and higher P-Q deficit (precipitation minus runoff) during the growing season. Nevertheless, the large amount of precipitation during growing season has no effect on the end of growing season (EOS), LOS and P-Q deficit. Realizing the vegetation growth responding to climatic variations is necessary for current and future hydrologic regime, especially under changing climate.

How to cite: Chang, C.-T., Lee, J.-Y., Chiang, J.-M., Wang, H.-C., and Huang, J.-C.: The climate-vegetation interactions and subsequent hydrological effect of a subtropical forested watershed, central Taiwan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2052, https://doi.org/10.5194/egusphere-egu23-2052, 2023.

Ongoing warming due to climate change has generally led to lengthened growing seasons and subsequent changes in evapotranspiration (ET) and streamflow seasonality. This has been well studied in seasonally dry, snowmelt dominated watersheds, but not in humid, temperate forested watersheds without significant seasonal snowmelt. In this study, we investigate how seasonal streamflow patterns have responded to variability in vegetation phenology in the southern Appalachians over the last four decades. We characterize seasonal shifts in low-frequency streamflow peaks using 50^th percentiles of cumulative daily precipitation, streamflow, and soil moisture measurements, and investigate interactions with remotely sensed, long-term greenup anomalies in the deciduous-dominated forested watersheds. After removing a dominant precipitation control, one-day earlier greenup is associated with about one-day early spring flow peak at the low-elevation deciduous catchment. This indicates that the strong dependency of seasonal flow regimes on precipitation is mediated by warming-induced extended growing season, especially by early greenup. In contrast, we find less significant correlations of the greenup anomalies on flow percentiles of an adjacent evergreen and a high-elevation deciduous catchment. At a plot scale, similar correlations of cumulative soil moisture days were found only at an upslope topographic position, where precipitation also showed tighter coupling with soil moisture patterns than downslope. This indicates that early greenup in deciduous forests leading to early ET increase, in turn results in early soil moisture dry-down patterned by hillslope positions, and earlier seasonal streamflow peaks and subsequent declines. Our study suggests that spring flow peaks are likely to shift earlier by warming-induced early greenup even in snow-free regions, which has great implications for future freshwater availability in the southeastern US.

How to cite: Hwang, T., Band, L., Oishi, C., and Kang, H.: Early greenup impact on seasonal streamflow and soil moisture dynamics in humid, temperate forests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2852, https://doi.org/10.5194/egusphere-egu23-2852, 2023.

Deforestation has a wide range of effects on hydrological and geochemical processes. Dissolved organic carbon (DOC) dynamics, a sensitive environmental change indicator, is expected to be affected by deforestation, with changes in atmospheric sulfur (S) deposition compounding this. However, how precisely anthropogenic disturbance (deforestation) under a declining atmospheric S input scenario affects the underlying spatiotemporal dynamics and relationships of river DOC and sulfate with hydro-climatological variables e.g., stream water temperature, runoff, pH, total dissolved iron (Fetot), and calcium (Ca²⁺) remains unclear. We, therefore, examined this issue within the TERENO Wüstebach catchment (Eifel, Germany), where partial deforestation had taken place in 2013. Wavelet transform coherence (WTC) analysis was applied based on a 10-year time series (2010–2020) from three sampling stations, whose (sub) catchment areas have different proportions of deforested area (W10: 31%, W14: 25%, W17: 3%). We found that water temperature and DOC, sulfate, and Fetot concentrations showed distinct seasonal patterns, with DOC averaging concentrations ranging from 2.23 (W17) to 4.56 (W10) mg L^-1 and sulfate concentration ranging from 8.04 (W10) to 10.58 (W17) mg L^-1. After clear-cut, DOC significantly increased by 59, 58% in the mainstream (W10, W14), but only 26% in the reference stream. WTC results indicated that DOC was negatively correlated with runoff and sulfate, but positively correlated with temperature, Ca²⁺, and Fetot. The negative correlation between DOC with runoff and sulfate was apparent over the whole examined 10-year period in W17 but did end in W10 and W14 after the deforestation. Sulfate was highly correlated with stream water temperature, runoff, and Fetot in W10 and W14 and with a longer lag time than W17. Additionally, pH was stronger correlated (higher R²) with sulfate and DOC in W17 than in W10 and W14. In conclusion, WTC analysis indicates that within this low mountainous forest catchment deforestation levels over 25% (W10 and W14) affected the coupling of S and C cycling substantially more strongly than “natural” environmental changes as observed in W17.

How to cite: Wang, Q., Qu, Y., Robinson, K.-L., Bogena, H., Graf, A., Vereecken, H., Tietema, A., and Bol, R.: Deforestation alters dissolved organic carbon and sulfate dynamics in a mountainous head water catchment—A wavelet analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2853, https://doi.org/10.5194/egusphere-egu23-2853, 2023.

Afforestation, as one of the major drivers of land cover change, has the potential to provide a wide range of ecosystem services (ES). Aside from carbon sequestration, it can improve hydrological regulation by increasing soil water storage capacity and reducing surface water runoff.  However, afforested areas are rarely studied at the appropriate time scale to determine when changes in soil hydrological processes occur as the forest grows. This study investigates the seasonal soil moisture and temperature dynamics, as well as the event-based responses to precipitation events and dry periods between a mature and juvenile forest ecosystem over a 5-year time period. Generally, soil moisture was higher in the juvenile forest than in the mature forest, indicating less physiological water demand. However, following the 2018 drought, soil moisture dynamics in the growing juvenile plantation began to match those of the mature forest, owing to canopy development and possibly also to internal resilience mechanisms of the young forest to external perturbations. On the other hand, soil temperature dynamics in the juvenile plantation followed air temperature patterns closely, indicating lower thermal regulation capacity compared to the mature forest. While our findings reveal that an aggrading juvenile plantation achieves mature forest soil moisture dynamics at an early stage, well before maturity, this was not the case for soil temperature. Our results shed light on long-term trends of seasonal and event-based responses of soil moisture and temperatures in different-aged forest systems, which can be used to inform future assessments of hydrological and ecosystem responses to disturbances and forest management.

How to cite: Rabbai, A., Wendt, D. E., Curioni, G., Quick, S. E., MacKenzie, A. R., Hannah, D. M., Kettridge, N., Ullah, S., Hart, K. M., and Krause, S.: Soil moisture and temperature dynamics in juvenile and mature forest as a result of tree growth, hydrometeorological forcings, and drought., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3830, https://doi.org/10.5194/egusphere-egu23-3830, 2023.

The multidimensional arrangement of upper canopy features is a physical driver of energy and water balance under various canopies, and standard modeling approaches integrate leaf area index (LAI) and canopy closure (CC) to describe canopies. However, it is unclear how the canopy affects the component and interception of rainfall within the forest system. We generated multi-layered forest point clouds from trunk to canopy using fusion of drone and terrestrial LiDAR data then classified wood and foliage elements using a clustering algorithm to build a high precision physical model for describing throughfall, stemflow and interception. The experiment was conducted in the thinning plantation forest located in Tochigi prefecture, Japan. Rainfall observation for the three components is important for model development. Throughfall was computed from 20 rain gauges distributed on a grid under the forest canopy, 3 stemflow collectors was set up around the tree trunks connected to a bucket with water level sensor. We developed a capacity model to describe canopy saturation with foliage points, a voxel-based method was used to create 3D representations of forest canopies, and an analysis of these point-derived canopy structures and volume were performed to assess the canopy's capacity to contain rainfall. For stemflow modeling, we use a runoff model to simulate the additional rainfall accumulates to the tree trunk through branches when the tree canopy is saturated. Preliminary simulation results show that: (1) fusion and registration of drone and terrestrial LiDAR data can greatly improve the point cloud accuracy and enrich the information contents such as coordinate geo-reference and filling of missing structures; (2) a strong correlation between the rainfall observed canopy interception results and the estimated canopy volume, and the volume-based interception prediction model has a high accuracy, with an R² from 0.84 to 0.91 compared to past observations. (3) stemflow is related to the projected volume of the canopy and the proportion of wooden structure point clouds, and as the runoff path increases, there is a greater probability that oversaturated precipitation will concentrate on the trunk rather than drip off. High accuracy physical model of tree canopy can well describe the interactions between the rainfall to canopy and illustrate the mechanism.

How to cite: Zhang, Y., Onda, Y., Tan, Y., You, H., Pham, T. L., Hashimoto, A., Chiu, C., Gomi, T., and Takamura, S.: Estimation of rainfall interception from merged drone and terrestrial LiDAR data by modeling 3D canopy structure in plantation forest, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4325, https://doi.org/10.5194/egusphere-egu23-4325, 2023.

Ecosystem functions of temperate forests are expected to be severely impacted by future climate change - particularly hydro-meteorological extremes (heavy precipitation events, droughts, and heat waves) that will increase in frequency, duration, magnitude, and extent. Previous studies have shown that both structural and tree species diversity may act as buffers against the impacts of climate extremes.

To better understand the influence of structural and tree species diversity, we use two models to analyze the influence of species and structural diversity on hydrologic dynamics during recent drought events. The well-equipped test sites are located in central Germany and represent typical forests in this area. One model is the individual forest gap model FORMIND. Using a newly developed technique, it allows us to analyze local heterogeneous patterns on a 2 meter scale of carbon and water cycling, flow, and water stress, and their relationship to structural and species diversity. The second model is mHM, a mesoscale hydrological model. We parameterize mHM for two catchments in central Germany (Nägelstedt and Upper Saale). We further analyze the relevance of local heterogeneity in structural and species diversity and the resulting local heterogeneity in water fluxes on the fluxes at the mesoscale.

This two-model and interdisciplinary workflow allows us to consider various soil-plant-atmosphere interactions in drought disturbed ecohydrological systems

How to cite: Bohn, F. J., Attinger, S., Kihm, C., and Hildebradt, A.: Modeling interactions of water fluxes with species and structural diversity in temperate forests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6746, https://doi.org/10.5194/egusphere-egu23-6746, 2023.

Climate changes are expected to trigger changes in all water budget components at any scale. For Central Europe, higher evapotranspiration (ET) rates are already observed, other factors like land use or land cover characteristics change in parallel, but experimental evidence of the interdcations is limited, as it requires challenging long-term measurements. We take advantage of the well-documented hydro-meteorological dataset from the forested research catchment Wernersbach in Saxony, Germany, covering 52 years between 1968 and 2019 (Pluntke & Bernhofer et al., 2023).

We analyzed hydro-climatological time-series for linear trends and for breakpoints. Significant positive trends were found for global radiation, mean air temperature and grass-reference evaporation, as well as for the difference between catchment precipitation and runoff (P-R; hydrological estimate of ET). Precipitation increased and runoff decreased over the 52 years, but not significantly.

Air temperature and global radiation show significant breakpoints around 1988 and 1996, respectively, with below average conditions before and above average conditions after the breakpoints. Temperature change is associated with global warming, and possibly with the independent regional effect of air pollution. Since the 1960s, large sulphur dioxide emissions from fossil fuel burning led to a high aerosol density in the troposphere reducing solar radiation over most of Europe and North America. While this effect was reduced by filtering the emissions elsewhere in the early 1980s, it continued in neighboring parts of today’s Germany, Poland, and Czech Republic until the early 1990s. Breakpoint of grass reference evaporation coincides with air temperature (1988), and the breakpoint of P-R is a few years later.

We attributed changes in ET to changes in land use and climate by applying an adapted Budyko framework and enabled insights into their interactions. The sulphur dioxide emissions triggered widespread forest dieback in regions over 600 m in Saxony. Consequences were decreasing ET in the 1970s/1980s. The Wernersbach catchment (390 m) shows a similar tendency (not significant). Since the 1990s, both climate (increasing atmospheric demand) and land use (healthier forest stands and improved management practices) led to an increase of ET. In 2010s, climate induced damages of forest stands (due to droughts, storms, snow load, and bark beetle infestations) led to a drastic decrease of ET in Wernersbach despite favorable climatic conditions for ET. Since the intensity and frequency of such extreme events are likely part of climate change, they may cause greater regional changes in the water balance than direct effects of climate change, and may cause lasting damage to Ecosystem Services of forests, like flood mitigation, or carbon sequestration.

Our results show the need for climate adaptation measures in forests, such as the establishment of a more site-specific mixed forest, and a sustainable  forest management.

References

Pluntke T. & Bernhofer C., Grünwald T., Renner M., Prasse H.: Long-term climatological and ecohydrological analysis of a paired catchment – flux tower observatory near Dresden (Germany). Is there evidence of climate change in local evapotranspiration? J Hydrol 617 (2023), https://doi.org/10.1016/j.jhydrol.2022.128873

How to cite: Pluntke, T., Bernhofer, C., Grünwald, T., Renner, M., and Prasse, H.: Climate and land use induced changes in evapotranspiration - experimental evidence from a forested catchment in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8182, https://doi.org/10.5194/egusphere-egu23-8182, 2023.

Throughout the Caribbean, hillside quarrying has become a common practice. While these activities remove large sections of the critical soil zone, very little work has been done on how hillside quarrying impacts rainfall runoff response and catchment water storage. We hypothesised that the removal of the critical soil zone during hillside quarrying will increase the timing and magnitude of streamflow response to storm events due to its close proximity to the river, while also reducing the overall storage of the watershed. The aim of this study is to understand the landuse impacts on rainfall runoff response and catchment storage. A paired catchment study between the 3.6 km² Acono (forested) and the adjacent 3.6 km² Don Juan (quarried) watersheds in Trinidad and Tobago was conducted using a hydrometric and geochemical approach. Direct measurements of rainfall and streamflow and bi-weekly water sample collections for geochemistry and stable isotopes of ¹⁸O and ²H from rainfall, baseflow, soils, springs and groundwater were done. Fraction of young water (Fyw) an inverse transit time proxy was computed along with the mean transit time distributions (MTTDs) by sine wave fitting were used as important descriptors of runoff generation and the catchment storage. The quarried watershed had higher streamflow levels during the wet season than the forested watershed. However, during the dry season there is a reversal.. The quarried watershed responded faster to rainfall events with a lag time between 1–3 hours with a higher peak rate of streamflow versus a lag time of 2-4 hours in the forested watershed with a lower peak rate of flow. In the upper quarried watershed 18.4 % of the stream water were younger than 0.46 years and 20.3% were younger than 0.55 years in the lower portion of the catchment. In the upper forested catchment 5.2 % of the stream water was younger than 2.71 years whereas 4.7% of the stream water was younger than 3.04 years in the lower catchment. The data suggest that the quarry leads to the faster delivery of water during storm events while also reducing the overall storage in the catchment. With an anticipated increase in hillside quarrying, this study provides important information for land use and water resource managers.

How to cite: Farrick, K. and Mathura, N.: Hillside Quarry Impacts on Streamflow and Stormflow response in a Tropical Watershed:  A Geochemical and Hydrometric Investigation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9930, https://doi.org/10.5194/egusphere-egu23-9930, 2023.

As a consequence of global change, forests worldwide are undergoing a restructuring process. The expectations for forests of the future are ambitious: Providing resilient forest ecosystems that capture large amounts of carbon but also provide stable groundwater recharge rates. To balance the interests of both forestry and water management authorities, scientists and practitioners need to be able to investigate and predict which forest types and combinations of tree species are most likely to fulfill these needs.

Methods based on the analysis water stable isotopes have been used extensively for studying water uptake depths of vegetation, groundwater recharge, transit times, and water sources in general. Despite being arguably the superior tool when not only amounts but also knowledge of the sources of an (eco-)hydrological flux are needed, the highly dynamic nature of water transport processes within the soil-plant-atmosphere continuum (SPAC) could hardly be captured in the past. With the advent of  laser spectroscopy in the last decade, we are now able to measure water stable isotopes continuously and in all compartments of the SPAC.

In this keynote, we present and review the most recent advances (2016-now) of combined soil and plant in-situ water isotope measurements carried out in different ecosystems worldwide. We then critically discuss the gain in process-understanding of in-situ monitoring approaches and demonstrate how in-situ methods could be integrated with traditional and novel methods to advance forest hydrology.

In-situ and semi-in-situ (i.e., sampling of water vapor) water stable isotope methods have been greatly improved within the last five years. Initial disadvantages (e.g., comparability to traditional methods, complicated & laborious setup & maintenance, expensive) have been carefully addressed, and improvements have been implemented. Recent research has proven that i.) highly dynamic and heterogenous processes (e.g., stem flow, groundwater recharge through preferential pathways, change of uptake depths in response to rainfall/drought, disentangling water use of different tree species in mixed forests) can be captured exceptionally well using in-situ isotope methods; ii.) water-vapor equilibration methods represent the isotope composition of mobile water better compared to destructive methods, and iii.) using continuous water isotope data reduces parameter uncertainties in SPAC modeling.

In summary, we state that the benefits of using in-situ or semi in-situ techniques outweigh the disadvantages by far and strongly encourage the water stable isotope community to integrate them regularly into studies of dynamic soil-plant-atmosphere feedbacks.

How to cite: Beyer, M., Kuehnhammer, K., van Haren, J., Kuebert, A., Birkel, C., Sanchez-Murillo, R., and Marshall, J.: Dynamic processes require appropriate methods to capture them: Why in-situ water stable isotope monitoring needs to become a standard method in forest hydrological research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10827, https://doi.org/10.5194/egusphere-egu23-10827, 2023.