Soil moisture is an essential climate variable and the main driver for water exchanges between the land surface and the atmosphere. An accurate knowledge of the soil moisture conditions is also crucial to estimate the amount of water needed or used for agricultural purposes.

As human demand for water is increasing along with extreme drought events, an optimal agricultural management is paramount to cope with a drier and warmer future, e.g. in Mediterranean regions. Thus, the knowledge of soil moisture is central for monitoring agricultural drought, optimizing agricultural water uses (i.e., irrigation) and improving the water cycle and land-atmosphere processes understanding. Nevertheless, the point-based nature and limited spatial coverage of in situ soil moisture observations in conjunction with the poor parameterization of human processes in earth system models (i.e., unmodelled or wrongly modelled irrigation), undermine the ability to accurately monitor and forecast drought events as well as the capacity to safely manage water resources.

Remote sensing observations offer a unique opportunity to fill these gaps as they can directly observe the processes of the plant-soil continuum. Here we provide insights on the value of satellite-based soil moisture and soil moisture-related measurements (i.e, radar backscatter) for land surface models and for agricultural drought research. We will show the utility of both classical coarse-scale and new high resolution observations for a number of applications that span from irrigation estimation, crop yield analysis, improvement of water cycle processes to estimation of small scale soil moisture variability across agricultural and mountaineous European pilot sites.

How to cite: Modanesi, S., De Lannoy, G. J. M., Bechtold, M., Brocca, L., Dari, J., Busschaert, L., Natali, M., and Massari, C.: Combining land surface modelling and Earth observations: the key role of soil moisture data to improve estimates of agricultural water uses, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2784, https://doi.org/10.5194/egusphere-egu23-2784, 2023.

Accurate measurements and estimates of evapotranspiration (ET) and soil moisture are essential for efficient crop management and understanding of hydrological processes in agricultural catchments. In this study, we used satellite imagery for a small catchment (Nučice, Czech Republic) to retrieve vegetative indices (VIs, including NDVI, SAVI and EVI), hence to analyse their spatial and temporal variability. Furthermore, we investigated the relationship between vegetative indices (VIs), measured evapotranspiration (ET), and soil water storage (SWS). Also, for each variable, we aggregated weekly data at the seasonal temporal resolution, being able to study the trends of each variable’s statistical moments. Moreover, we employed the Normalized Nash-Sutcliffe Efficiency (NNSE) index to study the error and the bias between normalized variables within the same seasonality. We found linear relationships between VIs, ET, and SWS when they exceeded a certain threshold. We were able to estimate the ET by exploiting its linear relationships with VIs and SWS, thus bridging the measurement gap. Our results suggest ET prediction based on VIs can be used during the growing season but may give inaccurate results after harvest (when VIs have low values). SWS can provide a reasonable estimate of the ET when no vegetation is present. Furthermore, the good correspondence between the seasonal NNSE indices and the trends of statistical moments of ET, VIs, and SWS suggest that subsurface processes might be inferred from seasonal vegetation cover. Therefore, this allows us to anticipate the likelihood of seasonal correlations across surrogate variables, further studying the spatial variations of SWS throughout the catchment in connection to ET and VIs.

This research has been supported by the Grant Agency of the Czech Technical University in Prague, Grant No. SGS20/156/OHK1/3T/11 and TUdi project, EU Horizon 2020 Grant Agreement No 101000224.

How to cite: Li, T., Schiavo, M., and Zumr, D.: Mutual relationships between evapotranspiration and soil water storage in a small agricultural catchment and their consistency from a statistical viewpoint, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3298, https://doi.org/10.5194/egusphere-egu23-3298, 2023.

Comparative analysis of the hydrological response at the catchment scale across different climates is critical to understand possible similarities in runoff generation processes. In this work, we relied on high-resolution soil moisture measurements in three European forested catchments to characterize hydrological responses during different wetness conditions. The study sites include Ressi, Italy (2.4 ha), Weierbach, Luxembourg (42 ha), and Can Vila, Spain (56 ha). We analyzed the seasonal variability in the difference between soil moisture at a relatively shallow (10–15 cm) and deep (45–60 cm) location within soil profiles in each catchment in the period 2017–2021, which included a wide range of meteorological conditions. We found contrasting soil moisture patterns across the investigated catchments. In the most humid site, Ressi, which receives over 2000 mm of precipitation per year, we often found similar soil moisture at the two soil depths, and soil moisture at the shallow depth was rarely higher than that at the deeper layer, suggesting very frequent vertical connectivity in this site. In Weierbach, which receives around 1000 mm of precipitation per year, soil moisture in the shallow sensor was consistently higher than in the deeper soil except during wet conditions when water content was similar across the entire soil profile. During dry conditions, evaporation of shallow water resulted in consistently higher soil moisture in the deeper layers. We infer that in Weierbach vertical connectivity between deep and shallow soil layers develops only during wet conditions. Despite similar total precipitation amount between Can Vila and Weierbach, soil moisture patterns were very different. In Can Vila, soil moisture was consistently higher in the deeper layer compared to the shallow one irrespectively of the season. This difference could be driven by very high evaporation of shallow water or a significant contribution of groundwater that promotes vertical connectivity. Our approach provides a relatively simple and inexpensive method to assess differences in hydrological behavior solely based on soil moisture data, opening the possibility for further analysis and comparisons across multiple catchments.

How to cite: Penna, D., Segura, C., Borga, M., Hissler, C., Latron, J., Llorens, P., Marchina, C., Martìnez-Carreras, N., and Zuecco, G.: Soil moisture response as a tool to understand hydrological processes across forested catchments in different climates, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11410, https://doi.org/10.5194/egusphere-egu23-11410, 2023.

Root-zone soil moisture is decisive in partitioning the water fluxes at the land surface, e.g. between evapotranspiration and groundwater recharge. Field-scale estimates of these time variant recharge rates can be derived from 1D soil hydrologic models, if the soil moisture product represents the respective scales and dynamics, and lateral fluxes can be neglected. Measured soil moisture time series can be used to calibrate these models by optimizing soil hydrologic properties (SHPs) and in this way increase confidence in simulated downward flux from a soil column (potential groundwater recharge). To obtain indirectly and non-invasively measure soil moisture at the field scale, Cosmic-ray neutron sensing (CRNS) has gained increasing attention in the last years. However, the variable penetration depth of the sensor and its decreasing sensitivity with depth and distance from the sensor complicate the interpretation of the soil moisture product and limit direct comparison to simulated soil moisture.

Within this study a two-layered Hydrus-1D model (up to 1.5 m depth) has been set up at an agricultural field site for one cropping season and calibrated using different soil moisture products to derive potential groundwater recharge estimates. While the use of point soil moisture sensor network data (SN) in the optimization is straightforward, different options to use CRNS data are evaluated: i) the COSMIC operator (simulates neutron count rates) ii) weighting simulated soil moisture according to CRNS vertical sensitivity, iii) applying a soil moisture profile correction on measured CRNS soil moisture before comparison.

Optimizing the SHPs did result in very good model performance for the SN as well as for the CRNS options (KGE > 0.86). While the SN delivers information down to a depth of 90 cm, using CRNS data that considers the vertical sensitivity (option i) and ii)) can result in difficulties informing the bottom layer of the model, which shows in optimized SHPs hitting the previously determined parameter bounds. Compared to that, using CRNS option (iii) leads to slightly reduced performance measures in the optimization but better informs the SHPs of the bottom layer when averaging modeled soil moisture over a fixed depth. For the successful optimizations, regardless of the method, recharge rates vary little and are comparable to independently estimated water flux at the field site.

Results of the study confirm the ability of the profile correction to increase CRNS information content to the main rooting zone and the validity of assuming a fixed integration depth, although this is expected to vary between field sites. This encourages also the use of CRNS soil moisture for non-experts of the method for soil hydrologic and landscape models as well as water balance calculations targeting downward fluxes.

How to cite: Scheiffele, L. M., Munz, M., Francke, T., Baroni, G., and Oswald, S. E.: Constraining groundwater recharge estimates at the field scale using soil hydrologic modelling and measured root zone soil moisture: how to deal with the vertical sensitivity of cosmic-ray measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15330, https://doi.org/10.5194/egusphere-egu23-15330, 2023.

Local heavy precipitation regularly causes great damage resulting from flash floods in smaller catchments. Appropriate discharge records are usually unavailable to derive an extreme value statistics and regionalization approaches predicting peak discharge from discharge records of larger basins cannot include the small-scale effects and local processes. In addition, forecasting flash floods from rainfall forecast requires to identify the initial soil moisture conditions under which a catchment is most prone to trigger flash floods. In this respect, soil moisture affects runoff at the local scale during runoff generation (infiltration), but also at the catchment scale during runoff concentration with possible infiltration of overland flow (run-on infiltration) along the flow path.

Our proposed framework to study the role of soil moisture on flash floods includes three steps: (1) to validate long-term hydrological simulations with in-situ soil moisture data to derive typical probability distributions of initial soil moisture depending on soil properties, vegetation and land cover, groundwater influences, etc; (2) to derive the sensitivity of runoff generation to soil moisture at the local and catchment scale by combining different probabilities for rainfall amount, duration and initial soil moisture resulting in the same joint probability and (3) to include the effect of soil moisture on run-on infiltration by linking a distributed hydrological and 2D-hydraulic model to simulate runoff hydrographs with and without run-on infiltration. The final set of simulations with the distributed, process-based rainfall-runoff model RoGeR for different temporal (event to long-term) and spatial scale (plots to submeter scale) allows us for a given catchment to derive the role of soil moisture on different hydrological processes (runoff generation and runoff concentration). We developed a spatial explicit method, which combines the joint probability of soil moisture and rainfall for runoff formation with hydraulic assumptions to determine runoff concentration and thus the corresponding hydrographs and the specific conditions in a catchment that can trigger flash floods. These simulations are compared in different test catchments with discharge records to validate out model chain. Finally, a comparison among different catchments with different characteristics (soil, geology, land-use, geomorphology, etc) enables us to derive a flood generation soil moisture sensitivity which should help to improve hydrological models to include all relevant processes and to focus our future in-situ soil moisture observations in the sensitive catchments to allow for a better prediction of flash floods by including observed soil moisture instead of simulated values. 

How to cite: Weiler, M., Leistert, H., Schmit, M., and Steinbrich, A.: Linking in-situ and simulated soil moisture data for flood prediction: the advantage of joint probabilities of initial soil moisture and rainfall characteristic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16866, https://doi.org/10.5194/egusphere-egu23-16866, 2023.

Soil moisture measurements are very popular. Yet they provide a very incomplete picture about the state of the partially saturated zone and the capillary binding of soil water. Here we propose that the free energy of the soil water stock offers a superior perspective on storage dynamics, as it combines soil water content, gravity potential and matric potential data. Based on this new state variable, we show that the partially saturated zone is characterized by a system-specific balance of storage and release corresponding to local state of minimum free energy. The latter depends on the soil water retention curve and topography/depth to groundwater. In the absence of an external rainfall or radiative forcing, the system will thus naturally relax back to and persist in this equilibrium. Hydrological systems are however not isolated, they are frequently forced out of their equilibrium either by rainfall or by radiation driven evaporation. Here we show that the corresponding storage dynamics manifests as deviations of the free energy from and relaxations back the local equilibrium and that the latter separates two different regimes, which are either associated with a storage excess and overshoot of potential energy or a storage deficit and overshoot of capillary binding energy. We demonstrate that these pseudo oscillations are distinctly different in different hydrological landscapes. As the free energy state of the soil water stock, the storage equilibrium and the ranges of both storage regimes depend jointly on depth to groundwater and the soil water retention curve, we combine both controls into a hydrological system characteristics we call the ‘energy state function’ of the soil. We show that the latter allows an insightful inter-comparison of storage dynamics with in different hydrological landscapes, and a priory estimate of depth to groundwater, based on available soil moisture and matric potential data. Finally, we demonstrate a threshold-like relation between the free energy of soil water in the riparian zone and streamflow generation, where the tipping points coincides with the transition from a storage deficit to a storage excess.

How to cite: Zehe, E., Hoffmeister, S., and Loritz, R.: Free energy of soil water – a superior perspective on storage dynamics and its sensitivity to soil hydraulic properties and topography, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6735, https://doi.org/10.5194/egusphere-egu23-6735, 2023.

Soil moisture is recognized as an Essential Climate Variable (ECV), because it is crucial to assess water availability for plants and hence food production. Having long time series of freely available and interoperable soil moisture data with global coverage enables scientists, farmers and decision makers to detect trends, assess the impacts of climate change and develop adaptation strategies.

The collection, harmonization and archiving of in situ soil moisture data was the motivation to establish the International Soil Moisture Network (ISMN) at the Vienna University of Technology in 2009 as a community effort. Based on several project funding periods by the European Space Agency (ESA), the ISMN became an essential means for validating and improving global land surface satellite products, climate and hydrological models.

Permanent funding for the ISMN operations was secured through the German Government (Ministry of Digital and Transport) and therefore the ISMN has successfully migrated at the end of 2022 to its new host the International Centre for Water Resources and Global Change (ICWRGC) and the German Federal Institute of Hydrology (BfG). Furthermore, the ISMN was recognized by WMO in their latest State of Global Water Resources report.

To improve the data service delivery, ISMN users can now benefit from a newly developed dataviewer which features functionalities such as data archives and advanced filter options (e.g. for climate and landcover types, for data quality) developed in synergies with the ESA project Fiducial Reference Measurements for Soil Moisture (FRM4SM). This presentation aims at showcasing these latest upgrades as well as new network contributions to the ISMN.

How to cite: Böhmer, F., Olarinoye, T., Korres, W., Kramer, K., Dietrich, S., Zink, M., Himmelbauer, I., Schremmer, L., Petrakovic, I., Aberer, D., Sabia, R., Crapolicchio, R., Goryl, P., Scipal, K., and Dorigo, W.: The International Soil Moisture Network - a global interoperable data center for in situ soil moisture observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4973, https://doi.org/10.5194/egusphere-egu23-4973, 2023.

Whether subsurface flow is relatively young or old when it passes by the catchment outlet is a strong indicator of weathering processes, nutrient availability, pollution susceptibility and the hydrologic response of a catchment. It depends not only on individual catchment, climate, event and vegetation properties, it is also the result of a multitude of interactions between different processes and catchment states within the hydrologic system.

In order to begin to disentangle the cause-effect chains (or better even: webs), we employed the physically-based, spatially explicit 3D model HydroGeoSphere in a virtual catchment running 100 scenarios with different combinations of catchment, climate and vegetation properties. One result showed, e.g., that streamflow in forested areas appeared to become older on average compared to a non-vegetated site. Upon closer inspection, this was not necessarily only caused by subsurface runoff becoming slower/older due to lower hydraulic conductivities of drier soils when there was active root water uptake. Another component of this increase in stream water age was the different partitioning of precipitation into subsurface runoff and groundwater flow. Relatively more water was transported in the slower groundwater domain and less within the soil at the bedrock-soil interface.

This is to show that, in order to make meaningful predictions about the age of hydrologic fluxes, it may not be the best approach to single out specific catchment and climate properties. Instead, it can be extremely helpful to look at the individual properties and the processes they control, their potential interactions and interdependencies, in a bottom-up approach within the framework of a hydrologic model.

How to cite: Heidbüchel, I., Yang, J., and Fleckenstein, J. H.: Modeling the age of subsurface runoff at the catchment scale – what makes it younger or older?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17088, https://doi.org/10.5194/egusphere-egu23-17088, 2023.

Calibration of subsurface runoff models in a catchment scale requires lots of observation sites/wells due to their scale difference. An observation site could fail to receive the required data due to variations in flow paths in rainfall events.  Therefore, establishing an effective monitoring site for subsurface runoff is a challenging task in hydrology studies. An alternative choice of monitoring equipment for subsurface runoff is using a terrestrial gravimeter. A terrestrial gravimeter has a broader sensible region than a monitoring well or several ERT (Electrical Resistivity Tomography) profiles. In addition, it takes the water(mass) itself as a tracer rather than using biogeochemical proxies and thus the quantity of runoff is estimated through observed gravity changes accordingly. Due to such advantages, in this presentation, we demonstrate the possibility of using gravimetry to monitor subsurface runoff in Taiwan. In one of the study sites at a proximal fan, our studies cover hourly, daily, weekly and monthly time spans, which encounter different intensities of rainfall over 1.5 years. The infiltration coefficient and percolation rate over 30 m length around our study site were determined in a severe rain event. In another study where we placed an absolute gravimeter in land subsidence regions, we estimated water storage changes at different sites after a wet season and rank their capability for being an artificial recharge pond. This presentation demonstrates the possibility of terrain gravimetry used in calibrating subsurface runoff models. We can picture that when quantum gravimeters are well-developed, high-temporal gravity measurements can assist to build a more accurate subsurface runoff model.

How to cite: Chen, K. and Hwang, C.: Monitoring of subsurface runoff using absolute gravimetry in Taiwan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12302, https://doi.org/10.5194/egusphere-egu23-12302, 2023.

Understanding the way in which a water budget is distributed within a hydrological system is imperative in the prediction of the systems behaviour when this water budget has changed. A complex interaction of variable flow rates, residence times and reactive transport, controls the available streamflow of a river system not only over seasonal changes, but under longer term climate fluctuations as well. Hydrological modelling techniques have been instrumental in predicting these changes by monitoring/simulating rainfall, river and groundwater contributions but are dependent on robust data collection through the maintenance of old infrastructure and the creation of new infrastructure. South Africa is a pertinent example of the decline of gauging infrastructure and a prime use case for novel stable isotope techniques as an accessory to traditional hydrological modelling in semi-gauged watersheds. Furthermore, to constrain contributions in modified systems, that include reservoirs and land use changes, isotopes present an opportunity to assess unpredictable water mobilisation in the streamflow system. In this study, stable isotope measurements of rainwater, groundwater and stream water (δ²H and δ¹⁸O), together with a tertiary mixing model were used to develop an isotope-enabled version of the JAMS/J2000 rainfall-runoff model, named J2000iso. The application was applied to the upper Berg River catchment, a catchment impacted by recent drought, but important for regional water supply. Compared to the base version, the J2000iso had 13% more simulated interflow, with 56% less variance in the ensemble results and less overall process uncertainty. The J2000iso was also more robust than the base version during a subsequent validation. The isotope-enabled models provided a means to constrain the proportion of surface runoff, interflow and baseflow considering the streamflow signal changes due to upstream reservoir operations. As many catchments in South Africa are still ungauged or impacted by upstream reservoirs, the J2000iso model provides a means to simulate hydrological processes, given the appropriate collection of isotope and auxiliary data.

How to cite: van Rooyen, J., Watson, A., Vystavna, Y., and Miller, J.: Stable isotopes as a tool for improving rainfall-runoff modelling in South Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11353, https://doi.org/10.5194/egusphere-egu23-11353, 2023.

Numerical simulations of coupled groundwater flow, heat and mass transport have been carried out for better understanding of cryo-hydrogeological system behavior under climate change.

Simulations are based on conceptual models of two well-monitored field sites at Umiujaq and Salluit, in Nunavik, (northern Quebec), Canada. The Umiujaq site contains discontinuous permafrost as discrete mounds within a marine silt bounded by unconfined and confined sand aquifers, while the Salluit site includes a bedrock river-talik system within continuous permafrost.

All simulations are run with the finite element HEATFLOW/SMOKER code which includes density-dependent groundwater flow, advective-conductive heat transport and advective-dispersive microparticle transport. Water-ice phase change, latent heat, ice-fraction dependent relative permeability and temperature-dependent thermal parameters are integrated in the solution. The thermal-hydraulic system is driven by ground surface recharge/discharge conditions which depend on the thermal state of the shallow subsurface (frozen or thawed), and by coupling with air-ground temperature gradients. Microparticle transport includes thaw-dependent particle suspension and velocity-dependent downgradient retention in heterogeneous porous media.

At the Umiujaq site, the two-dimensional vertical-plane simulations through a permafrost mound show how supra- and sub-permafrost groundwater flow can affect permafrost thaw which can lead to the release of microparticles, contributing to increased groundwater turbidity. At the Salluit site, supported by cross-sections of electrical resistivity tomography, the simulated 3D river-talik system follows the river meanders and responds dynamically to seasonal changes in air temperature and groundwater pumping.  The groundwater pumping rate needs to be managed for sustainable use, especially in winter when the talik is hydraulically disconnected from the river bed.

How to cite: Molson, J., Pedchenko, O., Khadhraoui, M., Fortier, R., and Lemieux, J.-M.: Numerical modelling of integrated processes in cryo-hydrogeological systems: Applications in Nunavik, Quebec, Canada, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10678, https://doi.org/10.5194/egusphere-egu23-10678, 2023.

Braided rivers are an important source of groundwater recharge in New Zealand. They consist of multiple temporary channels in a gravel environment and, as a consequence, their interactions with groundwater are complex and highly variable in space and time at different scales. Recently, the gravels of the contemporary braidplain of these rivers have been described and referred to as the ‘braidplain aquifer’. It is within this aquifer that hyporheic and parafluvial flows occur. In these systems, the groundwater recharge to the deeper regional aquifer is actually the water exchange between the braidplain and the regional aquifers. Some of these braided rivers are perched above the regional water level in their main losing section, which means that an unsaturated zone exists between the braidplain and regional aquifer. This complexity calls for the use of 3D fully integrated hydrological models to represent groundwater – surface water interactions in these environments. However, these complex models are very computationally intensive, which strongly limits their use in parameter inference and uncertainty quantification schemes as well as their applicability to regional scale problems.

We present a modelling framework that includes a 3D fully coupled HydroGeoSphere (HGS) model and several 2D cross-sectional HYDRUS-2D models (with 1, 2 and 3 layers). This framework aims at simplifying the model while ensuring the appropriate simulation of the groundwater recharge. We demonstrate our modelling approach on the relatively small Selwyn River. Piezometric data and groundwater recharge estimates derived from satellite photography were available for this river. First, stochastic simulations were performed using the 2D cross-sectional models and compared to observations in order to explore the validity of different subsurface conceptualizations and parameter values. Second, the selected conceptualization and parameter values were used to parameterize the 3D fully coupled HGS model. Third, the groundwater recharge simulated by the 3D and the 2D models were compared. Our results demonstrate that the observations can only be reproduced with a minimum of 3 distinct layers, with a lower permeability layer in the middle. Furthermore, this modelling exercise revealed the primary importance of the width and thickness of the braidplain aquifer as they determine the infiltration front width and the pressure head applied to the braidplain aquifer bottom, respectively. This shows that the properties, dimensions and water level in the subsurface are controlling the groundwater recharge from the perched braided river rather than the river characteristics. Moreover, we show that a 2D cross-sectional model can effectively replace the 3D fully coupled model to simulate groundwater recharge from the perched braided river and that this reduces the model run time by 3 orders of magnitude. Finally, some analytical equations, which can be easily implemented in regional groundwater models, were tested as a further simplification of the 2D model.

How to cite: Di Ciacca, A., Wilson, S., and Wöhling, T.: Model simplification to simulate groundwater recharge from perched gravel-bed braided rivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9868, https://doi.org/10.5194/egusphere-egu23-9868, 2023.

Coastal aquifers supply freshwater to nearly half of the world's population, and their importance for sustainable development in coastal areas is immense. Due to the proximity to the ocean, salinization is typically the biggest risk for coastal groundwater resources. Furthermore, the interactions between groundwater and surface water during coastal flooding often result in surface instabilities arising from elevated groundwater heads. Here, integrated hydrologic modeling is used to examine the effect of groundwater-surface water interactions on the salinity distribution in aquifers and on the stability of beach surfaces. The processes considered include multi-scale fluctuations in sea level (tides, storm surges, and glacial cycles). Results show that modern salt distributions may change even if the current conditions remain stable, when considering short- and long-term cyclical processes that aquifers are likely still responding to. It is also found that during coastal flooding, critical hydraulic gradients may develop, potentially destabilizing the beach surface. The distribution of these critical gradients depends on beach topography, with a non-trivial relationship between surface elevation and the location of critical gradients. These results mean that the interactions between groundwater and surface water likely play a pivotal role in the hydrologic state of coastal systems, with important implications for water resources management and for natural hazard mitigation.

How to cite: Paldor, A., Frederiks, R. S., Housego, R., Raubenheimer, B., Elgar, S., Stark, N., and Michael, H. A.: Harnessing integrated hydrologic modeling to analyze the coastal impacts of groundwater-surface water interactions on beach surface stability and freshwater availability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3658, https://doi.org/10.5194/egusphere-egu23-3658, 2023.

For water managers, extreme weather events such as droughts and heavy rainfall can pose severe challenges. Both sudden and longer term surpluses or shortages of water are operationally challenging to deal with. Investigating the effects of extreme hydrological events at the catchment scale requires the development of hydrological models capable of simulating such events. The present study is focused on developing such a model for an agricultural catchment using the integrated surface-subsurface hydrological flow model (ISSHM) HydroGeoSphere. For robust simulation of the impact of heavy rainfall and drought events on water availability and crops, an accurate representation of the spatially highly variable soil hydraulic properties has been identified as crucial. To identify effective soil hydraulic properties at the catchment scale, we propose a method combining real time observations of soil moisture, groundwater levels and catchment outflow with an ISSHM of the catchment via pilot point-based model inversion. The applicability of the method is demonstrated on a 17 km² tributary agricultural catchment of the Odra River located 20 km north of Wrocław, Poland. The validation data for the approach consist of soil samples analysed both before and after the vegetation period.

How to cite: Głogowski, A., Fiałkiewicz, W., Schilling, O., and Brunner, P.: Inverse identification of soil properties at catchment scale via pilot point calibration of an integrated surface-subsurface hydrological model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8815, https://doi.org/10.5194/egusphere-egu23-8815, 2023.

Agricultural areas are often artificially drained, especially in temperate and flat landscapes. This also applies to Denmark, where approximately half of the agricultural area is artificially drained, mostly with tile drains. The generated drain flow has significant impacts on various aspects of the hydrologic cycle such as groundwater recharge, flow paths and transport times. Consequently, drain flow is a major control on the transport of nutrients such as nitrogen. Yet, detailed knowledge of spatial and temporal variability of drain flow is inadequate due to insufficient observations of drain flow, lacking knowledge of drain infrastructure and issues of scale and hydrogeologic heterogeneity.

The objective was to improve the simulation of both the spatial and temporal variability of drain flow in a large-scale hydrological model used to map nitrate transport. This model is a physically-based, distributed groundwater-surface water model of all of Denmark. It is a major challenge to simulate drain flow distribution in space and time with the national model due to its coarse horizontal resolution (500m or 100m), and the lack of drain flow observations at relevant scale. Hence, to achieve the objective, we gathered existing field-scale drain flow observations from all over Denmark. For these drain catchments, fine-scale (10m) physically based hydrological models were setup and calibrated against the drain flow observations. After successful calibration, the resulting simulated distributions of drain fraction (drain flow relative to precipitation) were regionalized to applicable areas across all of Denmark. The regionalization was performed using decision tree machine learning algorithms, and a set of topographic and geologic covariates available nationally at fine resolution. An analysis of spatial transferability of the machine learning algorithm allowed to limit predictions to applicable areas. Finally, these estimates of drain fraction are used in the calibration of the large-scale national hydrologic model, amongst other objective functions such as streamflow and groundwater heads.

How to cite: Schneider, R., Noordujin, S., Mahmood, H., Stisen, S., and Højberg, A. L.: Improving drain flow simulations in a national hydrologic model with machine learning estimates of drain fraction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11474, https://doi.org/10.5194/egusphere-egu23-11474, 2023.