A European vision for hydrological observations and experimentation  

On dryland hillslopes, vegetation water availability is often subsidized by the redistribution of rainfall runoff from bare soil (sources) to vegetation patches (sinks). In regions where rainfall volumes are too low to support spatially continuous plant growth, such functional connectivity between bare soil and vegetated areas enables the establishment and persistence of dryland ecosystems.  Increasing the connectivity within bare soil areas can intensify runoff and increase water losses from hillslopes, disrupting this redistribution and reducing the water available to sustain ecosystem function.  Inferring functional connectivity (from bare to vegetated, or within bare areas) from structural landscape features is an attractive approach to enable rapid, scalable characterization of dryland ecosystem function from remote observations. Such inference, however, would rely on metrics of structural connectivity, which describe the contiguity of bare soil areas.  Several studies have observed non-stationarity in the relations between functional and structural connectivity metrics as rainfall conditions vary. Consequently, the suitability of using structural connectivity to provide a reliable proxy for functional connectivity remains uncertain and motivates the work here. 

Rainfall-runoff simulations across a wide range of dryland hillslopes, under varying soil and rainfall conditions, are used to establish relations between structural and functional connectivity metrics.  The model results identify that the relations vary between two hydrologic limits -- a `local' limit, in which functional connectivity is related to structural connectivity, and a ‘global’ limit, in which functional connectivity is most related to the hillslope vegetation fraction regardless of the structural connectivity of bare soil areas. The transition between these limits within the simulations depends on rainfall intensity and duration, and soil permeability. While the local limit may strengthen positive feedbacks between vegetation and water availability, the implications of these limits for dryland functioning need further exploration, particularly considering the timescale separation between storm runoff production and vegetation growth.

How to cite: Crompton, O., Katul, G., Thompson, S., and Lapides, D.: Bridging structural and functional hydrological connectivity in dryland ecosystems, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-37, https://doi.org/10.5194/egusphere-gc8-hydro-37, 2023.

The post-mining landscape of Freiberg, Saxony, Germany is characterized by soils with elevated concentrations of non-essential elements, particularly arsenic (As), cadmium (Cd) and lead (Pb). While literature on soil mineralization and factors influencing the soil-plant transfer in managed agroecosystems is extensive, information on the accumulation in native woody plant species, including soil-associated factors influencing their accumulation, is still lacking. In this study, we evaluated the concentrations of 24 elements, including As, Cd and Pb in leaves and branches of three taxa of tree species (Betula pendula, Populus tremula and Salix spec.) throughout the study area and compared the results with data on potentially plant available element concentrations in soil (sequential extraction), total element concentrations as well as with remote sensing data on surface soil moisture and water availability in the root-zone. Populus tremula and Salix spec. were identified as plant species that are suitable for bioindication of soil pollution. Leaf concentrations were substantially higher compared to branches. The concentrations in leaves largely reflected the availability of elements in soil. Concomitantly, higher soil-plant-transfer of elements correlated with remote sensing data, onsurface water accumulation and water content in the root-zone. This suggests that higher soil water contents increase the availability of the toxic elements to plants and/or impacts the translocation of elements to aboveground plant parts. The contribution of soil-associated factors and plant-associated factors to the hyperaccumulation observed remains a field for further research. Nevertheless, we could demonstrate that coupling leaf analysis with remote sensing data on soil moisture could be a promising approach in environmental assessments as well as in phytoremediation and phytomining approaches.  

How to cite: Lovynska, V., Wiche, O., Montzka, C., Syntyk, S., Sivaprasad, V., Samarska, A., and Mengen, D.: Influence of soil hydrological conditions on the accumulation of heavy metals in tree species in the post-mining landscape of Freiberg, Germany (Saxony), A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-38, https://doi.org/10.5194/egusphere-gc8-hydro-38, 2023.

Improving water resource management in the western United States is critically needed to achieve sustainability between the competing demands of water supplies for cities and towns, for agriculture, particularly irrigated regions, by industries principally for generating electricity, and for the environment (i.e., providing adequate ecosystem services). The last decade marked by historically severe droughts revealed the need for new water management policies and environmental regulations. Moreover, the impact of climate change not only has exacerbated droughts but also may be causing episodic extreme wet periods requiring a new paradigm on water management strategies for surface water reservoirs and groundwater aquifers. The Sustainable Groundwater Management Act (SGMA) is an example of developing a water management policy for sustainability of water resources in California. California produces 80% of the world’s almonds, is the 4^th largest wine producer worldwide while also providing three-quarters of the fruits and nuts in the U.S. Much of the production requires reliable water sources for irrigation.  This has motivated research into designing networks of evapotranspiration (ET) flux tower measurements in grape and tree crop systems in conjunction with developing new remote sensing tools for mapping crop water use, ET, to efficiently use and conserve water resources across the over 1.5 million acres of woody perennial crop production fields.  This acreage is largely irrigated and uses approximately 70% of freshwater resources in the region.  The two projects, GRAPEX (Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment) and T-REX (Tree-crop Remote sensing of Evapotranspiration eXperiment) have the overall goal to identify management opportunities to maximize water use efficiency in vineyard, almond and other woody perennial crops.  This presentation will describe the measurement network used for understanding the water and energy flux exchange of these complex cropping systems and in validating and refining remote sensing modeling tools from UAS and satellite platforms for estimating ET and crop water stress from plant and sub field to regional scales required for improving water management strategies of these agricultural systems.

How to cite: Kustas, W., Bambach, N., McElrone, A., Knipper, K., Torres-Rua, A., Roby, M., Alsina, M. M., Prueger, J., Alfieri, J., Castro, S., Hipps, L., McKee, L., Belfiore, O., and D'Urso, G.: Improving water resource management through the development of a flux tower network and remote sensing modeling of evapotranspiration and water stress of woody perennial crops in California, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-32, https://doi.org/10.5194/egusphere-gc8-hydro-32, 2023.

Precision agriculture is a modern approach based on farm and irrigation management to improve the efficiency in the use of water resources. Precision agriculture, therefore, maximizes crop productivity and yield through technologies that identify, analyze, and monitor variability within a field and optimize profitability, sustainability, and land protection. This study proposes a combination of approaches to monitor a suite of environmental variables with the goal of improving agricultural management. We selected the experimental vineyard of Grignanello (Tuscany, Italy), located on a mild slope at 350 m.a.s.l in the famous Chianti wine region, where extensive ecohydrological data are available. In combination with this set of ground-based observations, the Environmental Policy Integrated Climate Model (EPIC) is adopted to model key variables for crop production, including soil temperature and soil water content. Using the EPIC model, we generate three sets of simulations based on three different parameterizations (i.e., original cosine, enhanced cosine, and pseudo heat transfer). By comparing model output against ground-based measurements and UAV-based soil temperature, we assess what model set-up is more accurate and for which environmental variable of interest. Furthermore, a new set of soil temperature and soil moisture estimates is obtained by taking the mean of the three EPIC simulations. Thus, we assess the possibility to improve the performance of the single models, as shown in previous studies across the Central Valley in California. Outcomes from this work will provide a solid basis towards developing a decision guidance system for precision agriculture management. 

How to cite: Maggioni, V., Massari, C., Kandasamy, J., Xue, Y., Modanesi, S., De Santis, D., Manca di Villahermosa, F. S., Penna, D., Benettin, P., and Dionigi, M.: Monitoring Environmental Variables to Promote Precision Agriculture, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-54, https://doi.org/10.5194/egusphere-gc8-hydro-54, 2023.

Agriculture is the main source of pressure on water resources, so accurate estimates of irrigation demands play a key role in sustainable water management. The INCIPIT (INtegrated Computer modeling and monitoring for Irrigation Planning in Italy) project (funded by Italian Min. Univ. and Research) aims to address the gaps between research and practical application in monitoring irrigation water use in six Italian regions [1].

It is designed to meet the requirements of sustainable water policies, such as the Water Framework Directive and the MIPAAF Ministry Decree, by providing accurate measurements and estimations of irrigated areas and water volumes. The project uses the ESA Sentinel-2 (S2) satellites as a valuable source of information to map irrigated areas and estimate distributed irrigation water requirements.

This study presents the results of the IRRISAT methodology, the first Italian satellite-based irrigation advisory service [2], which was applied in the Campania region. The methodology uses a one-step approach, based on the Penman-Monteith equation, and is adjusted with canopy parameters from S2 data, to quantify irrigation water abstraction. Effective irrigated areas were assessed by using pre-existing maps, unsupervised clustering, and supervised machine learning algorithms applied to vegetation index data [3].

The results of the methodology for the irrigation seasons of 2019 and 2020 will be presented for seven Irrigation and Land Reclamation Consortiums, which vary in size, irrigation scheme, farm delivery, irrigation methods, and crop types.

[1] INCIPIT Project, www.principit2017.it

[2] Vuolo F., D’Urso G., De Michele C., Bianchi B., Cutting M.: Satellite-based irrigation advisory services: a common tool for different experiences from Europe to Australia”. Agricultural Water Management, Elsevier, vol. 147: 82-95; dx.doi.org/10.1016/j.agwat.2014.08.004 (2015).

[3] Falanga Bolognesi S., Pasolli E., Belfiore O. R., De Michele C., D’Urso G.: Harmonized Landsat 8 and Sentinel-2 Time Series Data to Detect Irrigated Areas: An Application in Southern Italy". Remote Sensing, MDPI, vol.12, no. 8: 1275; doi.org/10.3390/rs12081275 (2020).

How to cite: D'Urso, G., Belfiore, O. R., Coppola, A., Comegna, A., Toscano, A., Baroni, G., Consoli, S., Vanella, D., Longo Minnolo, G., Ippolito, M., De Caro, D., Castagna, A., and Gandolfi, C.: Earth Observation data for the monitoring of irrigation water use in Italy: The case study of the INCIPIT project., A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-60, https://doi.org/10.5194/egusphere-gc8-hydro-60, 2023.

Groundwater resources are biodiversity hotspots, and provide crucial ecosystems services. Yet, groundwater dependent ecosystems (GDEs) are exposed to several anthropogenic threats, including climate and land use change. Tackling these threats requires improving the on-the-ground identification of GDEs at the global scale and especially in vulnerable areas such as the Mediterranean biome where water is scarce.

In order to identify the location of groundwater dependent vegetation (GDV) in the landscape and create a harmonized global map of GDV a novel multi-instrument and multi-scale approach was developed. The approach combines a geodata-based potential GDV zones-index (pGDVZ) together with high-resolution vegetative, hydrogeological and topographic remote sensing parameters.

The pGDVZ integrates global and openly available datasets to combine groundwater vegetation interaction, land use, soil characteristics and landscape wetness potential. The index is currently tested for the whole Mediterranean. Results can help to pinpoint areas of high GDVZ potential where regional high-resolution identification of GDV is necessary.

The regional GDV-mapping concept implements different criteria aiming at: 1) high vitality and wetness during dry periods (e.g., Enhanced Vegetation Index, Normalized Difference Vegetation Index, Normalized Difference Water Index), 2) low seasonal changes in vitality, 3) low interannual changes in vitality, 4) high topographic potential of water accumulation and low water table depth and 5) general topography (elevation, slope). Processing of different remote sensing data (e.g., Sentinel 1;2, Digital Elevation Models, MODIS) is performed using the Google Earth Engine. Botanical mapping as well as integration of several geodata is used for validation and calibration of derived GDV-likelihoods. Furthermore, the integration of vegetation plots extracted from sPlot, the global vegetation database introduces a novel methodology to train machine learning algorithm for classification and modelling of GDV.

After successfully testing the mapping approach at local scale in the ‘Cilento, Vallo di Diano and Alburni National Park’ in Campania (Italy), a two-step upscaling methodology is currently designed to implement the concept on regional (county) and global (biome) scale.

How to cite: El-Hokayem, L., De Vita, P., and Conrad, C.: Mapping of potential groundwater dependent vegetation zones in the Mediterranean using a simple index based on global-available geodata and high-resolution remote sensing, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-61, https://doi.org/10.5194/egusphere-gc8-hydro-61, 2023.

Near-surface soil moisture is an important parameter for estimating the water balance of ecosystems, especially for the exchange of water between atmosphere and soil. In the past decades, global and continental products, e.g. the Soil Water Index (SWI) of ESA, have been developed for large-scale monitoring from passive and active microwave data. ESA SWI was developed for Europe based on the surface soil moisture product derived from Sentinel-1 C-band SAR data (1km resolution) and Metop ASCAT surface soil moisture (12.5km). However, for practical, small-scale applications on the local level, there is currently little data available. This contribution elaborates on the validation of the SWI for temperate agricultural regions at the example of the agrometeorological network of the JECAM test site DEMMIN in Northeast Germany. For this purpose, two resampling methods, a bilinear interpolation and a statistical downscaling approach using Random Forest were tested on SWI data from 2019. The statistical downscaling approach integrates Sentinel satellite data and the Topographical Wetness Index based on a 10m resolved elevation model. Both resampling methods showed similar results. Over time, the SWI significantly overestimates the in situ data before and after the crop growing season. A higher agreement is observed in the summer months. For 19 of the 29 investigated agrometeorological stations a statistically positive correlation with R>0.5 was found. The remaining stations showed little to no correlation, most likely due influences of various crops types on the remote sensing data. The results suggest a temporally limited applicability of the SWI 1km data for local assessments of soil moisture.

How to cite: Conrad, C., Schmelzer, J., Schlaak, J., and Löw, J.: Downscaling and validation of 1km ESA Soil Water Index for soil moisture monitoring on agricultural land in temperate climate conditions, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-97, https://doi.org/10.5194/egusphere-gc8-hydro-97, 2023.

Hydrology relies on the measurement of various variables, among which snow water equivalent (SWE) plays a crucial role in predicting runoff, particularly for catchments with high levels of snow accumulation. However, SWE measurements are rare and limited to point scales, making it difficult to obtain accurate spatialized estimates. While current satellite missions do not directly measure SWE, they offer valuable proxy information that can be used to reconstruct SWE. We propose using optical and radar sensors from MODIS, Sentinel-2, and Landsat missions to extract data on snow persistence on the ground and merge this multi-scale information to obtain accurate estimates of SWE. The technique involves observing snow patterns at high spatial resolutions from Landsat and Sentinel-2 missions and using this information to reconstruct a low-resolution image from MODIS. Additionally, information on the duration of melting can be obtained using Synthetic Aperture Radar (SAR) from Sentinel-1. In-situ air temperature data is used to estimate potential melting, and snow depth observations are used to determine if accumulation is occurring. The final output is daily high-resolution SWE maps. This approach has the advantage of not relying on precipitation observations, which are often uncertain in high-elevation catchments. We investigate the effectiveness of this approach in estimating peak snowmelt discharge for two monitored catchments in South Tyrol (Italy), comparing the results to those obtained using state-of-the-art hydrological models such as GEOtop and New Age. These results have the potential to significantly improve snowmelt estimation in poorly monitored basins.

How to cite: Bertoldi, G., Premier, V., Bozzoli, M., and Marin, C.: A comparison of a new remote sensing-based SWE estimation method  with physical models for improving snow melt estimation in alpine catchments, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-100, https://doi.org/10.5194/egusphere-gc8-hydro-100, 2023.

Spatio-temporal variability of throughfall (TF) in forested catchments depends on climatic forcing, forest stand parameters, and rainfall characteristics. Identifying and quantifying these controls is fundamental for a correct analysis and modelling of interception and catchment hydrological response. Despite many studies carried out at the stand and hillslope scale focused on the analysis of controls on TF variability, very little is known about the role of hillslope topography and the associated tree population characteristics in shaping throughfall spatio-temporal variability. In addition to ground-based measurements, satellite and unmanned aerial vehicle (UAV)-data can be explored to obtain a more robust assessment of the main drivers of TF variability. Therefore, this work aimed at i) identifying the dominant factors on throughfall variability in a European beech stand along a steep hillslope; and ii) quantifying forest interception at the hillslope scale and upscaling it at the small catchment scale using ground-level measurements and UAV-derived and satellite observations.

The experimental activities were carried out in the upper part of the Re della Pietra catchment, Tuscany Apennines, Central Italy. The hillslope is roughly 110 m long and 60 m wide, has a mean slope of 30°, and is dominantly covered by European beech trees. The TF experimental plot consists of 126 throughfall collectors divided in two square grids of 144 m² with 49 collectors at the bottom and the top of the hillslope, and a transect of 28 collectors from the bottom to the top grid. TF was manually measured from the collectors approximately monthly and compared with gross precipitation. Moreover, five automatic gauges were installed along the hillslope to increase the temporal resolution. Topographic surveys were conducted to measure the main physiological characteristics (diameter, height and age) of the trees in the TF plot. Leaf Area Index (LAI) was estimated using a ceptometer above each sampler in four dates in the dormant and in the growing season.

The 40 manual measurements revealed a large spatial and temporal variability of the TF/precipitation ratio (mean 68%, standard deviation 37%). In the growing period, the TF/precipitation ratio showed higher spatial variability compared to the dormant season (66±29% and 85±31%, respectively), suggesting that the crown expansion can be an important control on TF variability. Moreover, TF was consistently lower in the bottom plot, characterized by larger tree size compared to the top grid indicating a control by trees size. Event-scale data from the gutter gauges show a rainfall intensity control on TF but showed no correlation between TF and hillslope position.

To corroborate the preliminary observations on crown and tree size, in early March 2023 a UAV survey will be conducted to determine the crown architecture and lateral expansion, and relate this parameters to the observed TF. Furthermore, LAI ground measurements will be compared with LAI data derived from Sentinel-2 data to establish a relation between ground measurements and satellite observations. This relationship will be then use to upscale LAI and its possible associate control on TF variability from the hillslope to the small (0.3 km²) catchment scale.

How to cite: Verdone, M., Llorens, P., Massari, C., van Meerveld, I., and Penna, D.: Identifying controls on throughfall variability at the hillslope scale through satellite data and UAV-assisted techniques, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-69, https://doi.org/10.5194/egusphere-gc8-hydro-69, 2023.

Most of the climate scenarios forecast increased water scarcity in semi-arid and arid areas, such as Hungary. Since only 2% of Hungary’s agricultural land is irrigated where mostly outdated irrigation technology is applied, there is a huge need for act to enhance advanced irrigation. The general aim of the present research was to develop the basis of variable rate irrigation for a water-saving precision sprinkler irrigation system on an maize site (85 ha) located in the reference area of the Tisza River Basin. There are limited available water resources at the site, therefore alternative water sources utilization system was set up for irrigation to adapt to climate change and reduce fertilizers. As the alternative water resource for irrigation, inland excess water, treated wastewater, and biogas fermentation sludge are collected in a water reservoir with a capacity of 114,000 m³. For proper irrigation scheduling, heterogeneity of topography, hydrological, soil and crop conditions have to be explored and monitored. For this reason, UAV-based surveys were carried out with high spatial and temporal resolution by which DEM, DSM, multispectral vegetation data was conducted both on irrigated and non-irrigated parts of a maize field in Hungary this site. Supplementing these data with physically based modelling of the soil and crop status, and the water balance surveying is tested to use for accurate irrigation scheduling.

In the surveys we used a DJI Matrice 300 RTK UAV drone equipped with a Zenmuse L1 LiDAR payload with integrated RGB Surveying Solution and a DJI Zenmuse H20T thermal camera, which measures in the spectral range from 8000 to 14,000 nm. A DJI Mavic 2 Zoom drone equipped with a Sentera Double 4K sensor that can calculate NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red-Edge Index) by filtering out red and NIR wavelengths was used for the multispectral research. These data enables the monitoring of crop height and biomass and the assessment of the thermal properties and the photosynthetic activity of the crop, respectively. A crucial work phase is the data management of these remotely sensed data by which we gain point-cloud and raster from semi-raw formats and photogrammetry analysis can commence. For validation, the results of field measurements for crop height, general status and chlorophyll content were applied by virtue of the high spatial resolution provided by the sensors. Based on the results, the considerable relation was found between the field and RS based data to survey the surface, the height and health status of the maize, which contributes to the mapping of a proper vegetation patterns fostering variable rate irrigation prescription maps.

The abstract was funded by European Union’s Horizon 2020 “WATERAGRI Water retention and nutrient recycling in soils and steams for improved agricultural production” research and innovation programme under Grant Agreement No. 858375. This research was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences

How to cite: Nagy, A., Buday-Bódi, E., Szabó, A., Fehér, Z. Z., and Tamás, J.: Assessment of UAV-based LiDAR and photogrammetry data in crop morphology monitoring for advanced irrigation, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-103, https://doi.org/10.5194/egusphere-gc8-hydro-103, 2023.

Traditional water quality monitoring in River Systems is both labor intensive and expensive. However, in order to better understand the different phenomena occurring in river systems, it is vital to have robust data available. Satellite observations have been successful in monitoring different environmental systems, but generally, current available spatial resolutions and cloud cover in inland waters limit the monitoring of rivers. Recent developments in the use of Unmanned Aerial Systems (UAS) highlighted the potential to address this gap in environmental monitoring. 

In this study, UAS and image processing techniques were utilized to gather an overview of the water quality variability, specific to turbidity level and pollutant transport, along the Sarno River, which is the most polluted river in Europe, and the river pollution has long been subject to disputes between many sectors. Preliminary findings highlighted the potential of image processing and allowed to identify the  variability in river water quality along the main river by adopting a sampling protocol in several points of the Sarno River. While there were few observations of plastic in river banks, organic transport was mostly observed and interestingly, there is a water quality spatial mixing in the river mouth, which is difficult to observe using traditional in situ point measurements. This study only covers the initial phase of the river monitoring activities. 

Keywords: UAS river monitoring, sediment transport, image processing, spectral indices, remote sensing, drones, water quality assessment

References:

Miglino, D., Jomaa, S., Rode, M., Isgro, F., & Manfreda, S. (2022). Monitoring Water Turbidity Using Remote Sensing Techniques. Environmental Sciences Proceedings, 21(1), 63.

How to cite: Saddi, K. C., Miglino, D., Jomaa, S., Rode, M., Isgro, F., and Manfreda, S.: Utilizing Unmanned Aerial Systems in River Water Quality Variability Monitoring, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-106, https://doi.org/10.5194/egusphere-gc8-hydro-106, 2023.

Non-perennial rivers are characterized by periods with dry bed or chains of isolated ponds. Given the extremely high biodiversity and various ecosystem services, these environments require careful management. The main obstacle to the implementation of correct management practices is related to the lack of information about the duration and frequency of zero-flow periods, that are the primary determinants of ecosystem processes in this kind of streams.

In many cases, the presence of non-perennial reaches within the river network is unknown. Given the high extension of the network of non-perennial rivers and their strong spatial inhomogeneity, traditional gauging systems are not adequate to provide measures with adequate spatial coverage. Moreover, point measures cannot capture the space-pattern of presence/absence of water. On the other hand, field surveys of water patterns have a limited temporal resolution and therefore lack in capturing the regime’s time-patterns. In this context, satellite data can make a key contribution thanks to the possibility of monitoring large areas with high temporal resolutions. Their use for monitoring the regime of non-perennial rivers has so far been limited by the availability of images with adequate resolution and accessible costs.

In this work, we explored the potential of medium-resolution multispectral Sentinel-2 data to identify non-perennial rivers and to assess their degree of intermittency. Examining the spectral signatures of water, sediment and vegetation covers, the bands in which these classes are most differentiated were identified. Exploiting these bands, we generated false-color image in which the pixels covered by water stand out from the background. From the false-color composite images, it was possible to identify the three distinct flowing status of non-perennial rivers: “flowing”, “ponding” and “dry” . The classification of flowing status was checked against ground truth, showing very good agreement. To enable a wider audience to identify flowing status along non-perennial rivers, we have developed and made freely available a code on the Google Earth Engine platform. For all the archive images (since 2015) we identified one of the three possible flowing status: flowing, ponding and dry bed. The obtained dataset allowed to train a random forest (RF) model able to predict the daily occurrence of a specific flowing status using as predictors spatially interpolated rainfall and air temperature data. The analysis was performed for 5 reaches of the streams Sciarapotamo, Mingardo and Lambro (Campania region, Italy), for which a RF model was calibrated. Classification RF models performed well in terms of accuracy (ranging from 82% to 97%) and true skill statistic (ranging from 0.65 to 0.95). All the studied reaches showed a no-flow condition during the observation period. Three of the five reaches resulted to have a dry bed condition each year while the other two reaches never dry up completely. With its ability to monitor the presence and absence of water in a cost-effective manner, this method has the potential to significantly improve the management and the conversation of non-perennial rivers, enabling a better understanding of their ecological status, as required by the European Water Framework Directive 2000/60/EC.

How to cite: Cavallo, C., Papa, M. N., Negro, G., Ruello, G., Gargiulo, M., and Vezza, P.: Using Sentinel-2 multispectral imagery to assess flow-intermittency in non‑perennial rivers, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-11, https://doi.org/10.5194/egusphere-gc8-hydro-11, 2023.

High-resolution monitoring of rivers is important because rivers are severely affected by climate change and both frequency and magnitude of extreme events are changing rapidly. Advanced in-situ monitoring technologies need to be combined with satellite Earth Observation (EO) to provide accurate, reliable, and spatio-temporally resolved information for effective decision support, risk assessment, investment analysis for climate change adaptation, and operational forecasting/surveillance.

Traditional hydrometric monitoring of rivers is in-situ and station-based. In-situ monitoring networks lack spatial resolution, have been declining in many regions, and data accessibility is increasingly restricted because of growing conflicts between countries over water resources allocation. To solve this problem, hydrometric monitoring using satellite earth observation needs to be combined with drone-borne hydrometric monitoring technology for validation, deployment in remote and inaccessible regions, and for reliable and accurate estimation of river discharge.

The Horizon Europe UAWOS project develops an Unmanned Airborne Water Observing System to provide key hydrometric variables (bathymetry, velocimetry, water surface elevation) at high spatial resolution/coverage, and data-based products/services to support management and decision making. UAWOS integrates airborne data streams with Copernicus water bodies and water level services for cross validation and to estimate river discharge from satellite EO data.

This contribution outlines the UAWOS work programme and reports first results of airborne surveys using (i) radar altimetry for water surface elevation mapping, (ii) water penetrating radar and sonar for bathymetric mapping and Doppler radar for surface velocity monitoring. The combination of these datasets for river discharge estimation as well as for validation and enhancement of satellite radar altimetry datasets will be discussed.

How to cite: Bauer-Gottwein, P., Olesen, D., Nielsen, K., Rietz, A., Coppo Frías, M., Dobrovolskiy, A., Kadek, A., Orlic, N., Grubesa, T., Hiller, T., Grosen, H., Nielsen, S., Tarpanelli, A., Giordan, D., Barbetta, S., Gustafsson, D., Wennerberg, D., Disse, M., Merk, F., and Romero, L. and the UAWOS project team: UAS Hydrometry – Contactless airborne measurements of water level, depth, flow velocity and discharge in rivers and streams, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-52, https://doi.org/10.5194/egusphere-gc8-hydro-52, 2023.

Heterogeneity in below canopy precipitation has often been hypothesized to induce spatial variation of soil water content especially in forests. However, we are not aware of any observational study relating the spatial variation of soil water content directly to net precipitation or alternatively to deep percolation. Here, we investigate whether throughfall patterns affect the spatial heterogeneity of soil water response in the main rooting zone. We assessed rainfall, throughfall and soil water contents (two depths: 7.5 cm and 27.5 cm) in a very dense observation network on a 1‐ha temperate mixed beech forest plot in Germany during two growing seasons. Because throughfall and soil water content cannot be measured at the same location, we used kriging to derive the throughfall values at the locations where soil water content was measured. 

Throughfall spatial patterns were related to canopy density. Although spatial auto-correlation decreased with increasing event sizes, temporally stable throughfall patterns emerged, leading to reoccurring high and lower input locations across precipitation events. A linear mixed effect model analysis showed, that soil water content patterns were only poorly linked to throughfall spatial patterns, and it was rather shaped by unidentified but time constant factors. Instead the increase soil water content after rainfall corresponded more closely to throughfall input patterns. Furthermore, soil water patterns additionally affected how much water was stored, and ancillary data suggest that this was related to preferential flow. 

In this comprehensive study we show that throughfall patterns imprint less on soil water contents and more on soil water dynamics shortly after rainfall events, therefore only partly confirming previous modelling with data. Our findings highlight at the same time systematic patterns of times and locations where the capacity to store water is reduced and water probably conducted quickly to greater depth. Our results indicate percolation patterns may already be triggered in the canopy.

How to cite: Hildebrandt, A., Fischer-Bedtke, C., Metzger, J. C., Demir, G., and Wutzler, T.: Spatial patterns for canopy drainage translate into soil moisture dynamics – empirical evidence, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-114, https://doi.org/10.5194/egusphere-gc8-hydro-114, 2023.

Cosmic-ray neutron sensors (CRNS) measure soil moisture in real-time at the field scale, bridging the gap between in situ measurements and remote sensing products. This is promising and has the potential to enhance hydrological model predictions through the assimilation of CRNS data and improve the estimation of model parameters. In this study, soil moisture measurements from a network of 13 CRNS in the Rur catchment (~2000km², Germany) were assimilated into the integrated model Terrestrial System Modelling Platform (TSMP) by the ensemble Kalman filter (EnKF). In total 128 ensemble members were generated by perturbing atmospheric forcing variables and soil textures to account for the uncertainties. The data assimilation experiments (with and without soil hydraulic parameter estimation) were carried out in both a wet year (2016) and a dry year (2018), and later validated using an independent year (2017) without assimilation. The objectives of this study were to investigate the potential of CRNS assimilation for improving soil moisture and evapotranspiration (ET) characterization, estimation of soil hydraulic parameters at the catchment scale, and analysis of whether the data assimilation performance differs between wet and dry years. The data assimilation experiments showed that soil moisture estimation was significantly improved during the assimilation period at measurement locations, with a root mean square error (RMSE) reduction (compared to open loop simulations without assimilation) in the range of 36-60% either in the dry or wet year, and the improvements were limited by the measurement error of CRNS (0.03 cm³/cm³). The joint state-parameter estimation gives better performance than state estimation alone (more than 15% RMSE reduction), and 9% RMSE reduction in the verification period with the updated parameter. The jackknife experiments revealed that the measurement network (~1 site per 200 km²) was insufficiently dense because soil moisture characterization at independent verification locations only improved marginally with large differences between wet and dry years (with an RMSE reduction of 40% in 2016 and 16% in 2018). The improved predictions from the jackknife experiments, however, imply that the assimilation of soil moisture data from a CRNS network still has the potential to improve the soil moisture characterization on the catchment scale by updating the spatially distributed soil hydraulic parameters of the subsurface model. The comparison of simulated ET with the data from eddy covariance (EC) stations demonstrates that it is challenging to achieve great improvements in ET simulations through CRNS soil moisture assimilation (with the RMSE reduction of monthly ET ranging between 6% and 21%).

How to cite: Li, F., Reemt Bogena, H., Bayat, B., Kurtz, W., Vereecken, H., and Hendricks Franssen, H.-J.: Assimilation of soil moisture data from cosmic-ray neutron sensors into the integrated Terrestrial System Modeling Platform TSMP (case study: Rur catchment in Germany), A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-17, https://doi.org/10.5194/egusphere-gc8-hydro-17, 2023.

The Long Term (Socio-) Ecological Research LT(S)ER site IT25 - Val Mazia/Matschertal is a catchment covering an elevation range between 900 and 3700m a.s.l., in South Tyrol (Italian Alps). While nivo-glacial processes dominate runoff production, lower sideslopes have a relatively dry climate, (ca. 500 mm at 1500m a.s.l.), mainly as summer convective precipitation, and therefore the site is appropriate for space-to-time substitution experiments for understanding mountain eco-hydrologic processes along climatic gradients.

For a better understand of the ecological, hydrological, and climatic processes in the catchment, a spatially distributed micro-meteorological network has been installed since 2009. The measurement infrastructure consists of about 20 stations among all dominant land-use types (grassland, forest, river, proglacial area) covering an elevation range from 1000 to 2700 m a.s.l.. The parameters monitored are mainly related to the 1) Microclimate (air temperature, humidity, wind) 2) Hydrological cycle (soil moisture, soil water potential, runoff, evapotranspiration, solid/liquid precipitation) 3) Energy balance (short/longwave/net radiation, surface heat fluxes) 4) Optical reflectance (Phenocam, NDVI/PRI Sensors). 5) Vegetation (sap-flow. O-H stable isotope monitoring).

The talk will focus on the capability of the collected observations to clarify if the water used by vegetation is coming from snowmelt or mainly from summer precipitation, which is one of the key open research questions in the perspective of a future elevational increase of the rain-snowfall transition zone.

In this contribution, we would like to highlight the potential of the site in a network of hydrological observatories in Europe that allows the testing of hydrologic hypotheses for different environments and climatic regions.

How to cite: Bertoldi, G., Niedrist, G., Zandonai, A., Obojes, N., Fontana, V., Brighenti, S., Comiti, F., and Tappeiner, U.: An observatory to monitor long-term eco-hydrological changes in Alpine environments: the LTER Matschertal/Val di Mazia., A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-93, https://doi.org/10.5194/egusphere-gc8-hydro-93, 2023.

Vehicle-mounted, wide-angle cameras combined with deep learning algorithms are proving to be a powerful mapping tool (e.g. Google Street View). Such tasks include facilitating adaptation to the increasingly common extreme rainfall events attributed to climate change. Repeatable rapid surveys of agricultural parcels have the potential to combine ground and satellite information over large areas, enabling cost-effective planning of cultivation tasks such as more efficient nutrient supplementation, pest management, irrigation water use. In this paper we describe our experience with a photogrammetric data acquisition system (FODAR).

The vehicle mounted Geometer device takes images every two metres along the routes travelled, which can be evaluated on its cloud-based geographic information platform. The geospatial data can then be displayed and evaluated interactively. On-the-move survey control is also provided. A powerful on-board computer can be used to monitor the recording during fieldwork. After the survey, the software automatically converts the recording metadata for cloud-based processing. It is also possible to determine the geographic position of point objects and measure distances and areas. The artificial intelligence used by the system uses deep learning algorithms to recognize and pinpoint with high accuracy on the map various objects on the surveyed road sections, such as traffic signs, but also fire hydrants, sewer covers, stormwater drains and other objects related to urban hydrology.

The use of such equipment in precision agriculture is not yet widespread, despite the fact that due to its vehicle mountability also can be used for mapping of ploughs or orchards and for effective assessment of crop growth. Our aim in using the tool was to build a prototype workflow to evaluate the data set that is expected to become available in the near future.

Patterns in the data, such as vegetation health, that are present in the data and have not been investigated so far, could lead to an increase in the profitability of management decisions by including the near-infrared band in photogrammetric analyses. In contrast to teaching deep learning algorithms, the object detection and image classification itself can be done with relatively little hardware effort, but future trends must be taken into account. For processing a large number of images submitted by cloud-connected vehicles, it may be worth considering a dynamically scalable hardware infrastructure. In addition, objects of agricultural interest identified by the technology could also serve as calibration data for aerial or even spaceborne imagery.

The abstract was funded by European Union’s Horizon 2020 “WATERAGRI Water retention and nutrient recycling in soils and steams for improved agricultural production” research and innovation programme under Grant Agreement No. 858375. Project no. TKP2021-NKTA-32 has been implemented with the support provided from the Na-tional Research, Development and Innovation Fund of Hungary, financed under the TKP2021-NKTA funding scheme.

How to cite: Tamás, J., Fehér, Z. Z., Kiss, N., Pásztor, D., and Nagy, A.: Mobile photogrammetric raster clouds to apply classification of time series data, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-104, https://doi.org/10.5194/egusphere-gc8-hydro-104, 2023.

Soil drainage flux is crucial for determining agrochemical loading and groundwater recharge. Because soil drainage is difficult to measure, it is typically predicted using soil moisture models. However, different soil moisture models have been shown to produce different drainage values although they all respected the same soil measurements well, leading to a non-uniqueness problem. To address this issue, this study used groundwater level, stream flow, and tile drainage measurements along with soil moisture data to constraint soil drainage estimation through a coupled soil and groundwater modeling framework in the Cross River watershed in Prince Edward Island, Canada. A 1D Richards equation model, LEACHM, was developed to predict soil drainage and calibrated using soil moisture data. A 3D watershed-scale MODFLOW model was built and calibrated against groundwater level data. The two models were loosely coupled using the soil drainage predicted by LEACHM as recharge. Forward coupled LEACHM and MODFLOW simulations were performed until simulated daily soil moisture, groundwater level, baseflow, and tile drainage values simultaneously matched the 2011–2014 observed values within prescribed error ranges by fine tuning the hydraulic parameters in coupled models. The coupled models were then verified using 2015–2016 data. The resulting LEACHM simulations matched the soil moisture data with less than 15% error, and MODFLOW simulations matched the groundwater level and base flow data, except for a few short periods when LEACHM overestimated soil drainage under deep snow cover. Although the timing of simulated soil drainage corresponded with the occurrence of tile drainage, the simulated soil drainage was generally higher than the tile drainage, which is considered reasonable because tiles intercept only a portion of the overall soil drainage. This exercise demonstrates that the coupled modeling respected multiple hydrological data sources instead of soil moisture alone, and thus enhanced soil moisture estimation.

How to cite: Jiang, Y. and the Yefang Jiang: Using multiple hydrological data sources to reduce uncertainty in soil drainage modeling, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-30, https://doi.org/10.5194/egusphere-gc8-hydro-30, 2023.

In the view of global freshwater availability and an increasing water demand in agriculture to secure world nutrition, efficient water use is a key factor for sustainable irrigation management. Irrigation decision support systems often show a lack of awareness on intra-site and variety-specific optimum ranges of plant available water content, which enhances the ineffective use of irrigation water. In potato production, all phenological stages are sensitive to insufficient water supply, with optimum soil water contents ranging between 40% and 90% plant available water content. Hence, observations and simulations of soil moisture dynamics are crucial information for irrigation management. In a study to be presented we aim (i) to assess the optimum irrigation level for starch potatoes in terms of plant available water dynamics, and (ii) to compare the suitability of three different model environments for simulating soil moisture dynamics.

Four test plots (each 172 m x 72 m) were installed during the growing seasons 2021 and 2022 on two loamy sands (27 ha and 35 ha) in Mecklenburg-Western Pomerania, Germany, within one gun sprinkler irrigation lane. In each test plot, one irrigation level was applied: the longtime used irrigation level of the local farmer (100%), two deficit irrigation levels (80%, 90%), and one abundant irrigation level (120%). The 100% irrigation level was 119.2 mm in 2021 and 132.8 mm in 2022. The soil hydraulic properties determined in laboratory are typical for a loamy sand with soil moisture of 0.196 m³ m^-3 at field capacity and 0.038 m³ m^-3 at permanent wilting point. Hourly and daily simulations of root-zone (0-60 cm) soil moisture dynamics were performed using the evapotranspiration-based “Agrarmeteorologisches Modell zur Berechnung der aktuellen Verdunstung” (AMBAV) model and the soil hydraulic properties-based HYDRUS-1D and HYDRUS-2D model environments. In-situ soil moisture measurements, observed in three-time replicates per test plot in 10 cm increments up to a depth of 60 cm, were used for validation.

Field measurements confirmed that all irrigation levels impacted plant available water contents. They ranged between 25% and 65% at the 80% irrigation level, between 42% and 94% at the 90% irrigation level, between 50% and field capacity at the 100% irrigation level and between 64% and 109% at the 120% irrigation level. All three model environments provide reliable simulation results at all irrigation levels, with an average coefficient of determination (R²) of 70.13% (AMBAV), 76.62% (HYDRUS-1D) and 81.13% (HYDRUS-2D). Simulated soil moisture dynamics varied stronger in topsoil than in subsoil layers, mainly due to the soil hydraulic properties of a potato dam and the effects of evapotranspiration.

The in-situ measured soil moisture dynamics confirm the capability of a 90% irrigation level for starch potatoes. AMBAV´s lower input parameter requirements ensure a greater dispersion of simulated soil moisture dynamics, when compared to more precise estimations by both HYDRUS environments. The inclusion of soil hydraulic properties in irrigation scheduling provides practice-relevant information, e.g., the actual irrigation demand of a specific crop, and enables the use of hydrological models for irrigation scheduling instead of in-situ measurements.

How to cite: Wenzel, J. L., Conrad, C., Piernicke, T., Haßelbusch, K., Böttcher, F., and Pöhlitz, J.: Observing soil moisture dynamics on starch potato fields for improving irrigation management based on hydrological simulations, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-87, https://doi.org/10.5194/egusphere-gc8-hydro-87, 2023.

Urban and metropolitan settlements, due to the growing impacts of climate change, are highly at risk from critical hydro-meteorological hazards (HMHs), such us floods and heatwaves.
Future climate change scenarios require the implementation of resilient design solutions taking into account the climate projections, as well as vulnerability and exposure. In this context, we propose a GIS-based framework aimed at supporting decision-makers in designing long-term climate adaptive design solutions. The framework is developed starting from input data assimilation; then, using AI machine learning and decision-making techniques, are executed aggregations and classifications of urban physical features in order to assess the spatial distribution of vulnerability and risk indicators.
In particular, it is proposed a method to verify the resilient efficacy of nature-based solutions in reducing potential economic damages produced by coastal floods events, and simultaneously improving the open spaces heatwave vulnerability.

How to cite: Miraglia, V., Clemente, M. F., D'Ambrosio, V., and Di Martino, F.: GIS-based Framework and AI Approaches to support Decision Makers in Implementation of Climate-adaptive Design Solutions, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-68, https://doi.org/10.5194/egusphere-gc8-hydro-68, 2023.

Accurate estimation of the partitioning of actual evapotranspiration (ETa) into plant transpiration (Tr) and soil evaporation (E) is difficult but important for assessing biomass production and the allocation of increasingly scarce water resources. This work aims to evaluate the performance of the AquaCrop model to estimate actual crop ETa and its components (Tr and E) over drip irrigated wheat fields in the semi-arid region of Morocco. Field experiments were carried out during 2016-2017 season on an irrigated winter wheat field in semi-arid region of Morocco. Wheat ETa and its partitioning components (Tr and E) were measured by using the eddy covariance (EC) system and the sap flow system (SF). The obtained results showed that the AquaCrop model adequately simulated canopy cover (CC), ETa and wheat biomass. The coefficient of determination (R²) between observed and measured CC, ETa and biomass were 0.98, 0.72 and 0.98 respectively. With regard to the ETa partitioning, the results indicate that the estimate of Tr using the AquaCrop model is well consistent with those of the in-situ measurements with SF. The Root mean square error (RMSE) between the observed and simulated Tr was about 0.60 mm.day^-1. This work demonstrates that the AquaCrop model has reliable accuracy in simulating wheat growth, production and ETa partitioning. As a result, this model provides a technical means of application to formulate optimal irrigation schedules.

How to cite: Bouras, E. H., Amazirh, A., Rafi, Z., Jarlan, L., Khabba, S., Merlin, O., and Er-Raki, S.: Evapotranspiration partitioning over irrigated wheat in a semi-arid region using in-situ measurements and AquaCrop model., A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-62, https://doi.org/10.5194/egusphere-gc8-hydro-62, 2023.

MOSES (Modular Observation Solutions for Earth Systems) is a research initiative comprising nine Helmholtz research centres which are part of the research field “Earth and Environment”. MOSES focuses on 4 research areas covering Ocean Eddies, Permafrost Thaw, Heat Waves, and Hydrological Extremes. Highly flexible and mobile observing systems, combining the expertise of the involved Helmholtz Institutes, were developed to study effects along full event chains in highly dynamic situations (such as floods or droughts) as well as the long-term trends in environmental systems.

To study Hydrological Extremes, the Elbe river basin in Germany was selected as investigation area during the implementation phase of MOSES. The measurements in headwater catchments of the Elbe river includes several campaigns, coordinated by the Karlsruhe Institute of Technology (KIT). These campaigns took place in the Mueglitz Valley in the Eastern Ore Mountains, Germany, aiming at the investigation of the effects of extreme rainfall events along an entire process chain from the origination in the atmosphere, over the land-surface and the subsurface including their storage dynamics, up to flood generation in the contributing sub-catchments. The Institute for Meteorology and Climate Research - Department Tropospheric Research (IMK-TRO) of KIT provides essential data on the formation and evolution of heavy precipitation events, as well as high resolution measurements of precipitation distributions and evaporation. The Research Centre Jülich (FZJ) study the handover of water vapour and trace substances into the upper troposphere and even into the lower stratosphere.

The Helmholtz Centre for Environmental Research (UFZ) and the German Research Centre for Geosciences (GFZ) studies the catchment storage dynamics and runoff generation during flood and drought events by absolute and relative gravimeters, soil moisture monitoring with wireless sensor networks as well as with stationary and roving Cosmic Ray measurements, and river water level and discharge monitoring.

The presentation will explain the research questions and introduce the field and monitoring set up and the methods applied.

How to cite: Wieser, A., Ködel, U., Güntner, A., Rolf, C., Blume, T., Dietrich, P., Handwerker, J., Khordakova, D., Kohler, M., Nixdorf, E., Reich, M., and Thoss, H.: MOSES Campaigns to Study the Evolution of Hydrological Extremes in the Mueglitz Valley, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-4, https://doi.org/10.5194/egusphere-gc8-hydro-4, 2023.

The ongoing intensification of the hydrological cycle calls for the identification and assessment of factors controlling catchment resilience to climate change. Stable isotopes of O and H in streams and precipitation are cardinal tools in this respect – notably for investigating questions related to water source, flowpaths and transit times. However, the spatial and temporal variability of these tracers remain largely unknown – essentially due to the limited availability of long historical time series of O-H isotope signatures in stream water, as opposed to the multi-decadal records in precipitation of the IAEA’s GNIP database (https://www.iaea.org/services/networks/gnip).

Based on their quality as natural archives of in-stream environmental conditions, freshwater mussels have been recently used for complementing stream water δ¹⁸O isotope records. With an average life span of ca. 10 years (up to 200 years for the freshwater pearl mussel), their potential is significant, considering the fact that nearly 1200 freshwater bivalve species inhabit a large variety of river systems and lakes around the globe (Pfister et al., 2018). Our proof-of-concept work has shown that δ¹⁸O values extracted from their shells closely mirror the variance of the measured stream water δ¹⁸O – both showing a strong damping of the precipitation signal. In our follow-up study, we leverage prior work by Schöne et al. (2020) on potential links between the NAO index, precipitation isotope signatures and subsequent interdecadal variabilities in reconstructed stream water δ¹⁸O signals for three catchments located in Sweden. Using freshwater bivalve shell δ¹⁸O as a proxy of stream water δ¹⁸O signatures, we hypothesize that interdecadal shifts in atmospheric circulation patterns translate into modifications of δ¹⁸O isotope signatures in precipitation and subsequent stream water δ¹⁸O signals – the latter potentially revealing changes in young stream water fractions related to fast flow paths. In parallel, we stipulate that the long-term δ¹⁸O signal in precipitation can be retrieved from historic records and reanalysis data of climate variables, as well as from synoptic atmospheric circulation classifications.

Here we focus on findings gained from a unique dataset of 5 years-worth of sub-daily precipitation O-H isotope data from the Belvaux (L) meteorological station, comprising 1443 rainfall samples. We investigated the links between local climate variables, the rainfall amount, atmospheric circulation patterns, and the precipitation δ¹⁸O signal. Our results show (i) an anticipated strong temperature-induced seasonality of the δ¹⁸O signal, characteristic for semi-continental sites, (ii) a weak but significant amount effect, (iii) a circulation type-dependant influence of local climate variables on the δ¹⁸O signal, and (iv) a high variability at the event-scale – indicating the influence of complex frontal systems and moisture recycling. We leveraged these findings for building a multiple linear regression model, explaining up to 50 percent of the variability of the δ¹⁸O signal at sub-daily resolution and closely matching the isotopic signal when applying moving averages over periods within a monthly range.

How to cite: Guilhem, T., Pfister, L., Schöne, B., Gey, C., Thielen, F., Hissler, C., Barnich, F., and Léonard, L.: Reconstructing the history of flowing waters from freshwater mussels in the context of interdecadal climate variability, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-13, https://doi.org/10.5194/egusphere-gc8-hydro-13, 2023.

A holistic understanding of ecohydrological processes that regulate the variability of tree water use, water flow pathways through the soil and to groundwater and the stream, and the transit time of water at the catchment scale is still challenging. In this work, we rely on an integrated dataset of isotope tracers and hydrometric data to show new evidence on the main ecohydrological processes and their controls that link runoff origin, sources of tree water uptake, and water transit time in a small mountain, forested catchment in central Italy.

The Re della Pietra experimental catchment is located in the Tuscan Apennines. The catchment is 2 km² in size and ranges in elevations between 650 and 1280 m a.s.l.. Forests cover more than 95% of the area, and the main tree species are beech and oak trees, with a much smaller proportion of conifers. Mean annual precipitation is around 950 mm. We collected water samples from April 2019 to January 2023 from precipitation, throughfall, soil, groundwater, springs, stream at different sections, and xylem of beech trees, and determined their isotopic composition. Weather data, streamflow, soil moisture, groundwater level, and throughfall were monitored in a 0.3 km² headwater sub-catchment. Stream stage and electrical conductivity as additional tracer were measured in three stream sections from the headwater sub-catchment down to the Re della Pietra outlet. Streamflow, groundwater, spring flow, and soil moisture are characterized by a marked seasonality, reflecting the strong seasonal variability in the meteorological forcing, typical of the Mediterranean climate.

Based on field observations and preliminary data analysis, we aim to test the following hypotheses:

• i) Trees growing along a steep hillslope in the headwater sub-catchment use different water sources (soil water vs. shallow groundwater) as a function of their topographic position.
• ii) Hillslope soil water is an important contributor to streamflow only during wet conditions (i.e., in winter, late fall, and early spring).
• iii) Spring water flows through shallow pathways and is a negligible contributor to streamflow, especially during dry conditions.
• iv) Water transit time increases as a function of increasing catchment size (i.e., increasing drainage area).

The results will contribute to the conceptualization of the interrelated ecohydrological processes driving water fluxes in Mediterranean forested catchments.

How to cite: Penna, D., Brighenti, S., Borga, M., Comiti, F., Dani, A., Fabiani, G., Klaus, J., Manca di Villahermosa, F. S., Marchina, C., Pfister, L., Preti, F., Trucchi, P., Verdone, M., Zuecco, G., and Kaffas, K.: Flow pathways, transit time, and tree water sources: linking ecohydrological processes with stable isotopes in a small forested catchment, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-81, https://doi.org/10.5194/egusphere-gc8-hydro-81, 2023.

Comprehension of the hydrological process and accurate estimation of major water balance components are substantial for a prosperous hydrologic model application. Analyses of changes in the stable hydrogen and oxygen isotope composition of surface water and groundwater can be employed to estimate evaporation losses and to define the origin of water and the way it moves in a specific region. This study aims at a better understanding of the water cycle of lowland lakes (Groß Glienicker See, Sacrower See) in Berlin-Brandenburg state, Germany, using stable water isotopes (oxygen-18, deuterium). To get that done, an isotopic mass balance model (HydroCalculator) was applied to compute the evaporative losses over inflow from the lakes’ water bodies under a steady-state hydrologic regime condition. The isotopic signatures of precipitation, water samples from eight observation wells, and from different depths of the lakes’ water within the time period of September 2022 to Jan 2023 classify the lakes into flow-through types which are fed by shallow groundwater. The estimated fractional water loss by evaporation is slightly higher in Groß Glienicker See (35%) in comparison to Sacrower See (33%). This is due to the different depths and areas of their water bodies.

How to cite: Mahmoodi, N., Merz, C., and Schneider, M.: Application of the stable isotope compositions of water for quantifying evaporative losses, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-94, https://doi.org/10.5194/egusphere-gc8-hydro-94, 2023.

As communities prepare for the impacts of climate change, policy makers and stakeholders increasingly require locally-resolved projections of future climate. Statistical downscaling uses low-resolution outputs from climate models and historical observations to both enhance the spatial resolution and correct for systematic biases. By examining the downscaled rainfall over land, we show that although bias corrections are effective in reducing biases in the current climate, they do not reduce the intermodel spread in future rainfall projections. This failure stems from the strong dependence of future rainfall change upon the current climatological rainfall patterns. Even after bias corrections are applied, the downscaled projections of precipitation change retain this dependence upon their native climatology. However, we show that this dependence can be exploited; even very simple methods to sub-set models according to their ability to resolve the observed rainfall climatology can substantially reduce the intermodel spread in rainfall projections.

How to cite: soden, B. and Zhang, B.: Constraining Climate Model Projections of Regional Precipitation Change, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-9, https://doi.org/10.5194/egusphere-gc8-hydro-9, 2023.

Many operational drought indices use precipitation and temperature data together with vegetation conditions obtained with advanced remote sensing technologies. However, there are only a few indices that use actual evapotranspiration (ET) but still do not address the effect of precipitation. In this work, we brought actual ET using enhanced complementary relationship method to include precipitation and vegetation conditions when depicting drought conditions.  We compared the proposed drought index with the U.S. Drought Monitor (USDM) which is widely used within the United States. The results of this study showed that the drought patterns from the proposed drought index are consistent with USDM, and the use of an accurate ET method improved its performance as a drought index. The key strengths of this study are that the proposed index can serve as an indicator of rapid droughts developing over a few weeks, and uniquely describes the drought conditions with vegetation conditions which have large impacts on predictions compared to other drought indices.

How to cite: Kim, H. and Kaluarachchi, J.: Drought Monitoring using the Enhanced Complementary Relationship of Evapotranspiration and Remote Sensing, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-29, https://doi.org/10.5194/egusphere-gc8-hydro-29, 2023.

The frequency, intensity and duration of drought events are expected to increase during the coming years. Hence, the resilience against climate changes and water deficit would be of concerns to ensure agro-food and energy safety. To address this issue, the outputs of general circulation models (GCM) under various emission scenarios are used to generate two meteorological and hydrological drought indices for a number of meteorological stations scattered in three major basins namely Buyuk Menderes, Kucuk Menderes, and Gediz located in the western Turkey (the Aegean Region). The biases in the outputs of GCMs were corrected using linear scaling method with respect to the reference period (1990-2020). The results were assessed in two 30-years period as mid-time future (2041-2070) and late future (2071-2100). Afterward, the well-known standard precipitation index (SPI) together with the streamflow drought index (SDI) are determined based on the outputs of the climate scenarios for the allocated time periods. The results of the study showed a significant increase in the number and severity of the drought events by the end of the century under all emission scenarios.  

How to cite: Safari, M. J. S., Nuri Balov, M., and Vaheddoost, B.: A Climate Based-Projection of Future Drought in Aegean Region of Turkey, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-35, https://doi.org/10.5194/egusphere-gc8-hydro-35, 2023.

This communication is dedicated to the Mediterranean agro-hydrological observatory OMERE (Mediterranean Observatory of Rural Environment and Water). It aims to explain the observation strategy and to highlight how this strategy and the associated research have contributed to a better understanding of the impact of agricultural and land management on water and soil resources in Mediterranean catchments.

OMERE is a Franco-Tunisian observatory based on two agricultural catchments, one in northern Tunisia and the other in southern France, representing the diversity of agricultural and ecosystem situations in hilly Mediterranean regions. The observatory was created more than twenty years ago to answer key scientific questions concerning the impact of global changes on soil and water resources (Voltz and Albergel, 2002). More specifically, the motivation has been to study how hydrological processes involved in water cycles and in the mass transport, such as contaminants and sediments, are affected by changes in farming practices and landscape management . The processes underlying these changes may be slow, such as in land use or contaminant dynamics, or infrequent over time, such as erosion. Understanding these processes and their relationship requires long-term observations to capture slow dynamics or infrequent events, which motivated the OMERE observatory.

The OMERE observatory belongs to the French national network OZCAR, dedicated to the observation of the critical zone. The observation strategy is motivated by monitoring the flow of water, sediments and contaminants and hydrological and climatic variables at different spatial scales from cultivated plots and landscape elements to the catchment scale (Molénat et al., 2018). These measurements were made with fine temporal resolution on a long-term scale and examining land use, agricultural practices and soil surface characteristics. The long-term observation strategy aims to support multidisciplinary integrative research to elucidate the conditions that improve soil and water management and the provision of ecosystem services in the Mediterranean context of rain-fed agriculture. The observatory helped to address three scientific questions: (i) better understand water flows, erosion and contaminants, in particular pesticides, and their natural and anthropogenic factors in the short and long term; (ii) analyze the overall effects of agriculture and land management on mass flows at different scales, from the plot to the watershed or the landscape; and (iii) develop new scenarios for sustainable agricultural management and better delivery of ecosystem services. Some of the main scientific advances of research conducted using the observatory obtained through OMERE are presented. The main perspectives in matter of the observation strategy are also drawn.

References

Molénat, J., Raclot, D., Zitouna R., ...., Albergel, J., and Voltz M., 2018, OMERE: A Long-Term Observatory of Soil and Water Resources, in Interaction with Agricultural and Land Management in Mediterranean Hilly Catchments, Vadose Zone J., 17:180086. doi:10.2136/vzj2018.04.0086

Voltz, M., and A. Albergel. 2002. OMERE: Observatoire Méditerranéen de l’Environnement Rural et de l’Eau- Impact des actions anthropiques sur les transferts de masse dans les hydrosystèmes méditerranéens ruraux. Proposition d’Observatoire de Recherche en Environnement. Minist. Français Rech., Paris

more information at : www.obs-omere.org

How to cite: Molénat, J., Raclot, D., Zitouna, R., Albergel, J., and Voltz, M. and the OMERE Team: OMERE: A Long-Term Observatory of Soil and Water Resources, in Interaction with Agricultural and Land Management in Mediterranean Hilly Catchments, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-41, https://doi.org/10.5194/egusphere-gc8-hydro-41, 2023.

In Mediterranean climates during the winter months much of the precipitation recharges sub-surface and surface reservoirs. However, in the late winter and early spring, when vegetation growth conditions are favorable, much of the precipitation can be depleted by transpiration and, furthermore, runoff reduced directly by the increased vegetation cover. In the Mediterranean regions there is the evident effect of climate changes that it is causing several problems on the water resources availability. Several scientists have shown a strong decreasing trend in winter precipitation amounts and an evident shift in how the precipitation is distributed across the winter and spring months. Considering that most of the runoff to surface reservoirs occurs in the winter months and that spring hydrologic response is likely to be influenced strongly by vegetation, these precipitation changes can be considered hydrologically important. Case study is the Flumendosa basin (Sardinia), which is one of the case studies of the ALTOS European project, characterized by a reservoir system that supplies water to the main city of Sardinia, Cagliari. Data are from 42 rain gauges stations (1922-2021 period) over the entire basin and data of runoff are available for the same period. In the Flumendosa reservoir system the average annual input from stream discharge in the latter part of the 20th century was less than half the historic average rate, while the precipitation over the Flumendosa basin has decreased, but not at such a drastic rate as the discharge, suggesting a marked non-linear response of discharge to precipitation changes. We developed and calibrated a distributed hydrological model at basin scale which predicts runoff, soil water storage, evapotranspiration and grass and tree leaf area index (LAI). Hydrometeorological variables provided by the future climate scenarios predicted by Global Climate Model (CMPI-6 MPI-ESM1-2-LR downscaled) have been used as input in the model to predict soil water balance and vegetation dynamics under the future hydrometeorological landcover scenarios. The historical observations highlighted strong negative trends in precipitation series and in the number of wet days (examined using the Mann-Kendall trend test). The results from model application showed that tree dynamics are strongly influenced by the inter-annual variability of atmospheric forcing, with tree density changing according to seasonal rainfall. At the same time the tree dynamics affected the soil water balance. We demonstrated that future warmer scenarios would impact the forest, which could be not able to adapt to the increasing droughts. In addition,  future scenarios predict a reduction of the runoff, which is crucial for the dam reservoir recharge. The water resources system planning needs to carefully takes into account the effect of future climate change on water resources and vegetation dynamics.

How to cite: Corona, R., Sirigu, S., and Montaldo, N.: Historical and future changes on water resources in the Flumendosa basin, Sardinia., A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-74, https://doi.org/10.5194/egusphere-gc8-hydro-74, 2023.

Floods and droughts are widespread emergency event (EE) issues in Central Asian (CA) countries. Water sustainability and efficient use of water resources are connected to complicated problems in CA. SustDrain (https://www.susdrain.org/ )  will be reasonable to expand in an application for the proper water management, collection, and efficient use of flood water. We are working on the potential expansion in applications of the TERESA project for CA, https://teresa.inowas.com/about/. TERESA is a nature-based solution for urban catchments by combining the advantages of sustainable urban drainage (SUDS) and MAR systems. The vulnerability to flooding and the growing demand for drinkable water are complicated issues for CA regions. Integrated water management, which integrates surface water management (stormwater catchment, flood protection) and groundwater management, is required to address both issues simultaneously (recharge measures, recovery for different uses). The development of multifunctional solutions should reduce stormwater runoff and increase groundwater recharge for the mitigation of flooding and protection of groundwater-dependent ecosystems. Some of the complexities to expanding the TERESA project applications are related to the acceptance of this approach with the expansion of the connected TVET (technical and vocational education and training) programs among the CA communities. The current customs, community attitude, and legislation system will be reasonable to update in combination with water efficiency technologies, modeling, and prediction analysis. For example, snow in urban Kazakhstan areas is categorized as “ waste”, and municipalities usually collect snow and damp snow by moving out by the big tracks in the garbage collection sites, without proper localized SusDrain MAR approach, as the TERESA project implementation program suggests. The current status of the TVET SUDS MAR activities for CA communities will be presented during the conference

How to cite: Amanzholova, R., Stefan, Dr. C., Sallwey, Dr. J., Ongdas, M. Sc. N., Sarbassov, D., Sailaubek, A., and Sagin, Dr. J.: TVET SUDS MAR opportunities for water sustainability , A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-80, https://doi.org/10.5194/egusphere-gc8-hydro-80, 2023.

In the last few years, several studies have detected changes in the rainfall regime which may have an impact on hydrological extremes and water resources availability. In addition, the lack of continuous observations as well as the significant transformations of river basins limits our ability to fully characterize hydrological response. Therefore, it is urgent to update current methods and tools in order to shed light on the expected hydrological changes.

In the present study, we try to construct a detailed description of extreme flow patterns in Southern Italy in the period 1920-2020. For this reason, the dataset of annual maximum discharges was constructed using all available records and extended using indirect measurements (e.g., daily discharge and water levels). The data before 1980 were collected in the SIMN Special Publication No. 17 and in the SIMN Hydrological Yearbooks, which provide the annual maximum flow rates and the annual rating curves. Hydrological observatory have been transferred to the regional Department of Civil Protection, but only water level observations are available for the most recent period.

Dataset from different sources requires a significant effort to reconstruct reliable timeseries. In order to extend the historical series of floods annual maxima, we tried to transform mean daily maxima into peak flow values by means of a conversion factor proposed by Taguas et al. (2008). Additionally, the database was also integrated with the most recent data converting water level measurements in annual floods by using the annual maxima flow rating curve. Such rating curve turned out to be quite stable over time as demonstrated by Claps et al. (2010) and it was verified using also hydraulic numerical models.

The present study results complement the outcomes of the recent study by Blöschl et al. (2017), who investigated flood trends over the last five decades in Europe. This study provided a clear overview on the recent tendencies in Europe except for southern Italy because of the limited and discontinuous data availability. Therefore, the study allowed to reconstruct a relevant number of timeseries representative of the entire southern Italy. The homogeneity of the reconstructed data have been verified using the Kolmogorov-Smirnov test. Then, the obtained series were analysed in order to detect possible trends by using the Mann-Kendall non-parametric test. Results highlights the dynamics of flood production over the entire southern Italy.

References

Blöschl G., Hall J., Parajka J., Perdigão R.A.P., Merz B, Arheimer B., Aronica G.T., Bilibashi A., Bonacci O., [...], Živković N. (2017). Changing climate shifts timing of European floods. Science, 357, pp. 588-59.

Claps P., Ganora D., Laio F., and Radice R. (2010) Riesame ed integrazione di serie di portate al colmo mediante scale di deflusso di piena, Atti del XXXII Convegno Nazionale di Idraulica e Costruzioni Idrauliche, Idraulica e Costruzioni Idrauliche, Palermo, 14-17 settembre 2010.

Taguas E.V., Ayuso J.L., Pena A., Yuan Y., Sanchez M.C., Giraldez J.V., and Pérez R. (2008) Testing the relationship between instantaneous peak flow and mean daily flow in a Mediterranean Area Southeast Spain, Catena, 75, pp. 129-137. https://doi.org/10.1016/j.catena.2008.04.015

How to cite: Messina, M., Manfreda, S., Avino, A., Pizzolla, T., and Naeem Sarwar, A.: Reconstruction of annual flood series in Southern Italy, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-110, https://doi.org/10.5194/egusphere-gc8-hydro-110, 2023.

Remote sensing is recognized as the most feasible means to provide regional information on land surfaces and monitor soil parameters such as soil moisture and evapotranspiration. The use of satellite-derived products can be crucial for groundwater resources in karst aquifers, particularly in regions, such as southern Italy, where groundwater availability drives economic and social development and there is a lack of monitored data. This study aims to expand the classical hydrogeological approach, used for the estimation of groundwater recharge of karst aquifers, to the understanding of the hydrological role of soil coverings by the integration of field monitoring and products derived by remotely sensed data. The research was conducted on the representative Mts. Soprano-Vesole-Chianello karst aquifer (Campania, southern Italy). Copernicus Global Land Services Soil Water Index (SWI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Evapotranspiration products were explored to assess soil water content and evapotranspiration regimes. The analysis included time series gathered by a monitoring network consisting of 5 soil moisture multi-profile probes, working since 2021. The SWI1km provides daily soil water content information at 1 km resolution. Depending on the uncertain calculation, not considering evapotranspiration and soil texture, the SWI1km product provides 8-SWI estimations and the related quality factor values. Instead, the MOD16A2 is based on MODIS data and provides 8-day evapotranspiration estimation at 0.5 km resolution. The product collection is based on the logic of the Penman-Monteith equation, which integrates inputs of daily meteorological re-analysis data along with products derived by (MODIS) including vegetation property dynamics, albedo, and land cover.

Both products showed zones of no-data occurring across the mountain areas of the karst aquifers. This limitation is related to the algorithms that consider several parameters such as topography (slope aspect and angle) and occurrence of clouds for product generation.

The primary outcome of this study was the extraction of SWI values and the calculation of a mean value for the 8-SWI values, weighted by the related quality factor (SWI_w). SWI_w showed a constant difference of about -20% in comparison to the daily average values obtained by field monitoring. Despite this discrepancy, the annual trend of the SWI_w was found being very consistent with the soil moisture probe measurements (corr. > 0.68) and displaying a good response to rainfall events.

Moreover, the MODIS ET data displayed the expected pattern of evapotranspiration with a temporal resolution not achievable in other ways considering the lack of local meteorological data.

In order to cope with missing data across the mountain areas of the karst aquifer, a spatial interpolation of SWI_w and MODIS ET was carried out by different geostatistical techniques.

The findings suggest that SWI1km and MODIS16A2 are useful in monitoring soil water content and evapotranspiration of soils covering karst aquifers and controlling groundwater recharge. Although there are limitations due to missing data, both products can be still effectively utilized if properly interpolated. Therefore, they can be considered fundamental for assessing patterns of groundwater recharge in karst aquifers, especially in areas which are not extensively monitored as in the case of southern Italy.

How to cite: Lepore, D., Conrad, C., Allocca, V., Cusano, D., Löw, J., El-Hokayem, L., and De Vita, P.: Integration of remotely sensed and field monitoring data for characterizing the hydrological regime of soils covering karst aquifers and assessing groundwater recharge, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-65, https://doi.org/10.5194/egusphere-gc8-hydro-65, 2023.

The importance of mapping Research Infrastructures (RIs) is widely recognized, there are numerous and diverse observatories and research infrastructures dealing with water challenges, both at local, national and European levels.

With the aim to create a network, since 2013, a lot of work has already been done within the Water JPI, an intergovernmental initiative whose mission is to strengthen water RDI collaboration amongst Member States in order to spur Europe’s leadership and competitiveness in the water sector. 

A Water JPI Infrastructures Platform was developed with the aim to support and facilitate the dissemination of information, assessing the existing RIs, to promote active collaboration among institutions and to provide access to world-leading research infrastructures that will enable excellent interdisciplinary research in water topic.

Today, the new European Partnership Water4All - Water Security for the Planet, is making great efforts to continue pursuing this goal: a first mapping report has been produced for assessing possible gaps and identifying synergies between existing structures. One of the main objectives of this mapping is the facilitation of sharing and accessing large-scale and long-term environmental data, in order to cooperate with relevant EU and national actors for developing observation data, their distribution and services for broadening implementation and to enhance the European observing capacity and predicting capabilities of the water cycle at global, regional and basin scales and its impacts on ecosystems.

In parallel, Water4All is developing a platform and a toolbox for water related data by integrating various existing databases and data collected and developed in the research projects funded by Water4All. The objective is to manage water related data thus providing a platform for a more efficient use of the information collected in Water4All following the FAIR (Findability, Accessibility, Interoperability and Reuse) principles.

How to cite: Sole, M. C. and Lotti, A.: The importance of networks of observatories and research infrastructures in hydrological data collection: the example of Water JPI and Water4All, A European vision for hydrological observations and experimentation, Naples, Italy, 12–15 Jun 2023, GC8-Hydro-86, https://doi.org/10.5194/egusphere-gc8-hydro-86, 2023.