Towards the construction of representative regional hydro(geo)logical numerical models: Modelling the upper Danube basin as a starting point

Introduction: Pressure on groundwater resources is increasing rapidly by population growth and climate change effects. Thus, it is urgent to quantify their availability and determine their dynamics at a global scale to assess the impacts of climate change or anthropogenically induced pressure, and to support water management strategies. In this context, regional hydrogeological numerical models become essential to simulate the behavior of groundwater resources. However, the construction of global hydrogeological models faces a lot of challenges that affect their accuracy.Methods: In this work, using the German portion of the Upper Danube Basin (∼43,000 km2) we outline common challenges encountered in parameterizing a regional-scale groundwater model, and provide an innovative approach to efficiently tackle such challenges. The hydrogeological model of the Danube consists of the groundwater finite element code OpenGeoSys forced by the groundwater recharge of the surface hydrological model mHM.Results: The main novelties of the suggested approach are 1) the use of spectral analyses of the river baseflow and a steady state calibration taking as reference the topography to constraint the hydraulic parameters and facilitate the calibration process, and 2) the calibration of the hydraulic parameters for a transient state model by considering parameters derived from the piezometric head evolution.Discussion/conclusion: The results show that the proposed methodology is useful to build a reliable large-scale groundwater model. Finally, the suggested approach is compared with the standard one used by other authors for the construction of global models. The comparison shows that the proposed approach allows for obtaining more reliable results, especially in mountainous areas

Solute transport in aquifers with evolving scale heterogeneity

Transport processes in groundwater systems with spatially heterogeneous properties often exhibit anomalous behavior. Using first-order approximations in velocity fluctuations we show that anomalous superdiffusive behavior may result if velocity fields are modeled as superpositions of random space functions with correlation structures consisting of linear combinations of short-range correlations. In particular, this corresponds to the superposition of independent random velocity fields with increasing integral scales proposed as model for evolving scale heterogeneity of natural porous media [Gelhar, L. W. Water Resour. Res. 22 (1986), 135S-145S]. Monte Carlo simulations of transport in such multi-scale fields support the theoretical results and demonstrate the approach to superdiffusive behavior as the number of superposed scales increases.publishedVersio

Ecological Sustainability Assessment of Water Distribution for the Maintenance of Ecosystems, their Services and Biodiversity

Water provision and distribution are subject to conflicts between users worldwide, with agriculture as a major driver of discords. Water sensitive ecosystems and their services are often impaired by man-made water shortage. Nevertheless, they are not sufficiently included in sustainability or risk assessments and neglected when it comes to distribution of available water resources. The herein presented contribution to the Sustainable Development Goals Clean Water and Sanitation (SDG 6) and Life on Land (SDG 15) is the Ecological Sustainability Assessment of Water distribution (ESAW-tool). The ESAW-tool introduces a watershed sustainability assessment that evaluates the sustainability of the water supply-demand ratio on basin level, where domestic water use and the water requirements of ecosystems are considered as most important water users. An ecological risk assessment estimates potential impacts of agricultural depletion of renewable water resources on (ground)water-dependent ecosystems. The ESAW-tool works in standard GIS applications and is applicable in basins worldwide with a set of broadly available input data. The ESAW-tool is tested in the Danube river basin through combination of high-resolution hydro-agroecological model data (hydrological land surface process model PROMET and groundwater model OpenGeoSys) and further freely available data (water use, biodiversity and wetlands maps). Based on the results, measures for more sustainable water management can be deduced, such as increase of rainfed agriculture near vulnerable ecosystems or change of certain crops. The tool can support decision making of authorities from local to national level as well as private enterprises who want to improve the sustainability of their supply chains. © 2022, The Author(s)

Disparate Seasonal Nitrate Export from Nested Heterogeneous Subcatchments Revealed with StorAge Selection Functions

Understanding catchment controls on catchment solute export is a prerequisite for water quality management. StorAge Selection (SAS) functions encapsulate essential information about catchment functioning in terms of discharge selection preference and solute export dynamics. However, they lack information on the spatial origin of solutes when applied at the catchment scale, thereby limiting our understanding of the internal (subcatchment) functioning. Here, we parameterized SAS functions in a spatially explicit way to understand the internal catchment responses and transport dynamics of reactive dissolved nitrate (N-NO<sub>3</sub>). The model was applied in a nested mesoscale catchment (457 km²), consisting of a mountainous partly forested, partly agricultural subcatchment, a middle-reach forested subcatchment, and a lowland agricultural subcatchment. The model captured flow and nitrate concentration dynamics not only at the catchment outlet but also at internal gauging stations. Results reveal disparate subsurface mixing dynamics and nitrate export among headwater and lowland subcatchments. The headwater subcatchment has high seasonal variation in subsurface mixing schemes and younger water in discharge, while the lowland subcatchment has less pronounced seasonality in subsurface mixing and much older water in discharge. Consequently, nitrate concentration in discharge from the headwater subcatchment shows strong seasonality, whereas that from the lowland subcatchment is stable in time. The temporally varying responses of headwater and lowland subcatchments alternates the dominant contribution to nitrate export in high and low-flow periods between subcatchments. Overall, our results demonstrate that the spatially explicit SAS modeling provides useful information about internal catchment functioning, helping to develop or evaluate spatial management practices

Deep learning integrating scale conversion and pedo-transfer function to avoid potential errors in cross-scale transfer

Pedo-transfer functions (PTFs) relate soil/landscape static properties to a wide range of model inputs (e.g., soil hydraulic parameters) that are essential to soil hydrological modeling. Combining PTFs and hydrological models is a powerful strategy allowing the use of soil/landscape static properties for the generalization of large-scale modeling. However, since the spatial scales of soil hydraulic parameters required for model inputs and soil/landscape static properties are often not identical, cross-scale transfer is required, which can be a significant source of errors. Here, we investigate uncertainties in cross-scale transfer and develop an approach that avoids them. The proposed method uses the convolutional neural network (CNN) as a cross-scale transfer approach to directly map soil/landscape static properties to soil hydraulic parameters across different spatial scales. The proposed CNN approach is applied under two different estimation strategies to invert the hydraulic parameters of a soil-water balance model and subsequently the quality of the parameters is assessed. Both synthetical and real-world results around the conterminous United States indicate that in general the employed end-to-end strategy is superior to the two-step strategy. The CNN-based integrated model successfully reduces potential errors in cross-scale transfer and can be applied to other areas lacking information on hydraulic parameters or observations. The proposed method can be extended to improve parameter estimation in earth system models and enhance our understanding of key hydrological processes

High-resolution drought simulations and comparison to soil moisture observations in Germany

Germany\u27s 2018–2020 consecutive drought events resulted in multiple sectors – including agriculture, forestry, water management, energy production, and transport – being impacted. High-resolution information systems are key to preparedness for such extreme drought events. This study evaluates the new setup of the one-kilometer German drought monitor (GDM), which is based on daily soil moisture (SM) simulations from the mesoscale hydrological model (mHM). The simulated SM is compared against a set of diverse observations from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations, and lysimeters at 40 sites in Germany. Our results show that the agreement of simulated and observed SM dynamics in the upper soil (0–25 cm) are especially high in the vegetative active period (0.84 median correlation R) and lower in winter (0.59 median R). The lower agreement in winter results from methodological uncertainties in both simulations and observations. Moderate but significant improvements between the coarser 4 km resolution setup and the ≈ 1.2 km resolution GDM in the agreement to observed SM dynamics is observed in autumn (+0.07 median R) and winter (+0.12 median R). Both model setups display similar correlations to observations in the dry anomaly spectrum, with higher overall agreement of simulations to observations with a larger spatial footprint. The higher resolution of the second GDM version allows for a more detailed representation of the spatial variability of SM, which is particularly beneficial for local risk assessments. Furthermore, the results underline that nationwide drought information systems depend both on appropriate simulations of the water cycle and a broad, high-quality, observational soil moisture database

Baseflow statistics in aggregated catchments

This paper employs stochastic analysis to investigate the combined effect of temporal and spatial variability on the temporal variance of baseflow in large catchments. The study makes use of the well-known aggregated reservoir model, representing the catchment as a network of parallel linear reservoirs. Each reservoir models a sub-catchment as an independent unit whose discharge temporal variation is characterized by a response time. By treating the rainfall-generated recharge and the sub-catchment response times as random variables, the statistical temporal moments of total baseflow are quantified. Comparisons are made between the temporal variance of baseflow in the aggregated reservoir model and that of a single homogeneous reservoir to define an upscaled response time. The analysis of the statistical moments of the random baseflow reveals that the number of reservoirs N has a weak impact on baseflow variance, with ergodic conditions achieved even with a small number of reservoirs. The study highlights that the ratio between the recharge correlation time and the geometric mean of the sub-catchment response times plays a critical role in baseflow damping and the upscaled response. The results indicate that the dynamics of baseflow generation depend not only on the catchment hydro-geological structure but also on the variability of the input signal. This research underscores the importance of understanding the combined influences of hydro-geological factors and recharge input variability for baseflow prediction under uncertainty. The present study should be regarded as a first step, setting the theoretical framework for future research toward incorporating field data

The Pilot Lab Exascale Earth System Modelling

The Pilot Lab Exascale Earth System Modelling (PL-ExaESM) is a “Helmholtz-Inkubator Information & Data Science” project and explores specific concepts to enable exascale readiness of Earth System models and associated work flows in Earth System science. PL-ExaESM provides a new platform for scientists of the Helmholtz Association to develop scientific and technological concepts for future generation Earth System models and data analysis systems