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HS2.5.3

Understanding groundwater processes across large domains – recent advances in models, theory, and data from regional to global scales

Groundwater provides about 40% of all human water abstractions and is an essential water source for freshwater biota in rivers, lakes, and wetlands. Aquifers may span political and natural boundaries, but our large-scale understanding of groundwater processes and their interconnection to surface water is still limited.
Increasingly global-scale groundwater models are being developed, and big-data assessments of groundwater wells have been conducted to push the boundaries of our large-scale understanding of groundwater processes. Similar to the catchment scale, knowledge of the exchange between surface and subsurface waters is essential for determining the hydrological water balance at larger scales. Furthermore, surface and subsurface waters exchanges, as well as inter-catchment groundwater flow, affect water, pollutant and nutrient fluxes, bio-organisms in streams, and the groundwater itself. Additionally, human activities (e.g., pumping/irrigation) could alter the natural conditions for the groundwater flow processes and exchange between surface and subsurface.
In this session, we want to highlight the increasing interest in the large-scale study of groundwater availability and processes while discussing current obstacles related to data availability and model design. Therefore, we seek contributions addressing issues including:
• Regional to global groundwater-related datasets and big-data assessments
• Transboundary and inter-catchment assessments of groundwater processes
• Surface-subsurface water exchange at the catchment to global scales from both observational and modeling aspects
• Effects of surface-subsurface water exchange on hydrological extremes (drought/flood), water availability, and solute and pollutant transport under climate change
• Implications of large-scale groundwater understanding on monitoring design and integrated water management beyond the catchment scale
• Variation of controls on groundwater processes across large domains

Convener: Robert ReineckeECSECS | Co-conveners: Yan LiuECSECS, Fanny SarrazinECSECS, Andreas Hartmann, Thorsten Wagener
Presentations
| Wed, 25 May, 17:00–18:30 (CEST)
 
Room 2.17

Wed, 25 May, 17:00–18:30

Chairpersons: Robert Reinecke, Yan Liu, Fanny Sarrazin

17:00–17:02
Introduction

17:02–17:12
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EGU22-8739
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solicited
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Virtual presentation
Laura Condon et al.

It is well established that groundwater is an important buffer to hydrologic systems; stabilizing water supplies across spatial scales and long time frames. However, groundwater surface water interactions are non-linear and can vary greatly based on climate and hydrogeologic setting.  This challenge is exacerbated in changing systems where shifting land cover, extreme droughts and floods can significantly change groundwater storage, discharge and recharge dynamics. Observations of groundwater levels and the hydrogeologic properties that govern flow are sparse both in space and time.  As a result, we rely heavily on physically based numerical models to help us understand this critical component of the hydrologic cycle. There are an increasing number of national to global scale groundwater models that take a variety of numerical approaches and simplify the system to varying degrees.  One of the challenges we face is that the integrated models best suited to capture changing dynamics, are also by far the most computationally expensive. This creates a trade-off between the physical complexity we can represent and the size of the ensembles we can explore (another critical dimension in highly uncertain systems). 

            Here we will explore the potential for machine learning emulators to help accelerate solutions while maintaining physically rigorous solutions in changing systems. First, we present progress in the development of the next generation high resolution (1km2) ParFlow model of the contiguous US (ParFlow-CONUS).  Next, we explore a range of machine learning architectures that have been developed to emulate the national model. Here we focus on solutions that can emulate the full 3D subsurface system as this allows for the most flexibility in hydrologic applications.  Specifically, we explore 3D convolutional neural networks, recursive neural networks and LSTM approaches.  For every approach we evaluate the fidelity with which the machine learning model can emulate the physics-based model. We focus specifically on performance for extreme hydrologic conditions both when the ML emulator is provided training data on these cases and when the ML model is applied to out of sample scenarios.  One of the key strengths of physically based hydrologic models is their ability to represent scenarios that we haven’t seen in the past. This can be a large challenge for purely data driven ML approaches which can provide erroneous results on conditions that fall outside historical behavior.  

How to cite: Condon, L., Bennett, A., Tran, H., Horowitz, B., Leonarduzzi, E., Melchior, P., and Maxwell, R.: Accelerating large scale groundwater simulation with machine learning: modeling approaches and science implications for changing systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8739, https://doi.org/10.5194/egusphere-egu22-8739, 2022.

17:12–17:18
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EGU22-2543
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ECS
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On-site presentation
Maximilian Nölscher et al.

The application of machine learning in geosciences began several decades ago and is, especially in the advent of increasing and affordable computational power, continuously gaining popularity. However, in some specific areas such as hydrogeology, where processes are partly or fully subsurface, the application of machine learning is still limited due to either missing or noisy data, such as in mapping hydrogeochemical parameters of aquifer properties. The presented dataset EU-MOHP v013.1.0 partly closes this gap. It provides cross-scale information on the multiorder hydrologic position (MOHP) of a geographic point within its respective river network and catchment as gridded maps. More precisely, it comprises the three measures “lateral position” (LP) as a relative measure of the position between the stream and the catchment divide, “divide stream distance” (DSD) as sum of the distances to the nearest stream and divide and “stream distance” (SD) as an absolute measure of the distance to the nearest stream. These three measures are calculated for several hydrologic orders to reflect different spatial scales. Its spatial extent covers major parts of the European Economic Area (EEA39), which also largely coincides with physiographical Europe. Although there might be many potential use cases, this dataset serves predominantly as valuable static environmental predictor variable for hydrogeological and hydrological modelling such as mapping or regionalization tasks using machine learning. The concept is strongly inspired by Belitz et al. (2019), who generated this dataset for conterminous USA.

How to cite: Nölscher, M., Mutz, M., and Broda, S.: Multiorder Hydrologic Position for Europe (EU-MOHP) as a Set of Environmental Predictor Variables for Hydrologic Modelling and Groundwater Mapping with Focus on the Application of Machine Learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2543, https://doi.org/10.5194/egusphere-egu22-2543, 2022.

17:18–17:24
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EGU22-288
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ECS
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On-site presentation
Simulating the contribution of groundwater to crop growth at the global scale
(withdrawn)
Inge de Graaf et al.
17:24–17:30
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EGU22-989
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On-site presentation
Marc Bierkens et al.

The increasing population numbers and demand for food has greatly increased the dependence of irrigated crops on groundwater resources. This has resulted in a steep rise of groundwater withdrawal for irrigation around the globe, with a decline of groundwater levels and the potential economic depletion of aquifers as a result. In this presentation we revisit the classic problem of determining economically optimal groundwater withdrawal rates for irrigation. The novelty compared to previous mathematical analyses is the inclusion of non-linear groundwater-surface water interaction that allows for including the impact of capture and the application of this framework at the global scale.

We base our analysis on a recently published analytical framework of groundwater-surface water interaction subject to groundwater pumping (Bierkens et al., 2021). This framework distinguishes between two regimes: 1. a physically stable withdrawal regime, for which groundwater withdrawal q is smaller than a critical withdrawal rate qcrit. Here, groundwater level decline reaches an equilibrium and all groundwater withdrawal eventually comes out of capture; 2. a physically non-stable regime (q > qcrit) where groundwater withdrawal is larger than maximum capture and leads to persistent groundwater level decline. Using a simple hydroeconomic model based on competition of resources, we derive an equation for the optimal withdrawal rate under the stable regime. Similarly, we use the hydroeconomic model to derive economically optimal withdrawal and depletion trajectories for the non-stable regime assuming either full competition or optimal control (intertemporal efficiency). The expressions derived for optimal depletion trajectories under the non-stable regime are a generalization of the work of Gisser and Sánchez (1980), by including (non-linear) groundwater-surface water interaction.

We apply the hydroeconomic framework at the global scale, limited to regions with significant groundwater use for irrigation. For the regions with stable groundwater withdrawal (q<qcrit) we determine the optimal withdrawal rate qopt and check whether it is attainable in the stable regime (qopt < qcrit). We also assess the economic gain that can be achieved when the current withdrawal is set equal to qopt. For regions with non-stable groundwater withdrawal (q>qcrit) we estimate the final groundwater level decline and associated net present value (NPV) of accumulated profits over time, and compare these between competition and optimal control. This allows us to assess, at first order, globally where the so-called Gisser-Sánchez effect olds, in that competition and optimal control lead to similar depletion rates and economic value. Finally, we use the hydroeconomic framework to assess for regions with non-stable groundwater withdrawal (q>qcrit) whether it is more profitable (in the long run) to pursue controlled depletion or reduce withdrawal rates to the stable regime.

How to cite: Bierkens, M., van Beek, R. L. P. H., and Wanders, N.: Revisiting optimal groundwater withdrawal under irrigation: including groundwater-surface water interaction and global analyses, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-989, https://doi.org/10.5194/egusphere-egu22-989, 2022.

17:30–17:36
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EGU22-9196
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ECS
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Virtual presentation
Nahed Ben-Salem et al.

Growing water demands in the Mediterranean region have increased groundwater exploitation, imposing urgent and efficient groundwater management. Sustainable management requires a proper understanding of groundwater status and accurate estimates of groundwater levels with less uncertainty. In this context, large-scale modelling has been shown to assess groundwater resources under changing conditions, especially in regions known for data scarcity. This study aims to quantify the steady-state groundwater levels at continental scales using a model ensemble and in-situ groundwater observations. To test the models' applicability and validity, we utilize one of the most monitored groundwater systems in the Mediterranean region, the Iberian Peninsula. Outputs of three global gradient-based groundwater models (Reinecke et al. (2019), de Graaf et al. (2017), and Fan et al. (2013)) were compared to observations from long-term groundwater monitoring network. The model ensemble showed reasonable performance in replicating the groundwater levels for shallow groundwater, but performance deteriorated with increased elevation.

In this study, we argue that we can develop continental scale groundwater maps for groundwater assessment by combining model results with in-situ data. Historical groundwater levels were used to test, train and validate the different combination methods. Here we present the outcomes and discuss the accuracy of the final product. We see this study as a benchmark approach of using multi-model ensemble and observations to deliver better groundwater steady-state conditions as a baseline for groundwater users and managers in the Mediterranean region.

This work was supported by the German Federal Ministry of Education and Research (BMBF, Germany, Grant 01DH19015) under the Project Sustain-COAST, co-funded by EU PRIMA 2018 programmes.

How to cite: Ben-Salem, N., Reinecke, R., P. Karatzas, G., Rode, M., and Jomaa, S.: Combining a global groundwater model ensemble with in-situ data for groundwater assessment in the Mediterranean region , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9196, https://doi.org/10.5194/egusphere-egu22-9196, 2022.

17:36–17:42
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EGU22-7057
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On-site presentation
Daniel Kretschmer et al.

Groundwater is the primary drinking water supply of billions of people worldwide. While groundwater is under pressure globally due to extensive water abstractions, proximity to coasts amplifies these pressures due to potential sea water intrusion that can endanger groundwater quality. It is unclear how climate change (changing potential groundwater recharge), as well as rising sea levels, will alter coastal groundwater dynamics, i.e., submarine groundwater discharge and seawater intrusion.

Various factors impact coastal groundwater dynamics, including groundwater recharge & extraction, hydraulic gradients, permeabilities, water densities, and oceanic activity (e.g., tidal pumping and wave setup). It is currently unclear how much these different factors control submarine fluxes along global coastlines. We developed perceptual models of coastal groundwater fluxes based on a literature review of regional and global models. Here we present our perceptual model and discuss it in the context of currently available global data, uncertainties, climate change, and whether it can be implemented with an existing Open Source global groundwater modeling framework (G³M-f).

How to cite: Kretschmer, D., Reinecke, R., Moosdorf, N., Michael, H., and Wagener, T.: Understanding coastal groundwater processes in a changing climate: A perceptual model of global-scale coastal groundwater dynamics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7057, https://doi.org/10.5194/egusphere-egu22-7057, 2022.

17:42–17:48
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EGU22-1659
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ECS
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On-site presentation
Ehsan Sharifi and Andreas Güntner and the G3P team

The Global Gravity-based Groundwater Product (G3P) aims at developing a satellite-based groundwater storage (GW) data set as a new product for the EU Copernicus Climate Change Service. As the world’s largest distributed freshwater storage, GW is a key resource for mankind, industrial, and agricultural demands. In Copernicus, there is no service available yet to deliver data on this fundamental resource, nor is there any other data source worldwide that operationally provides information on changing groundwater resources in a consistent way, observation-based, and with global coverage. Therefore, G3P develops an operational global groundwater service as a cross-cutting extension of the existing Copernicus portfolio. G3P capitalizes from the unique capability of GRACE and GRACE-FO satellite gravimetry as the only remote sensing technology to monitor subsurface mass variations, and from other satellite-based water storage products to provide a data set of groundwater storage change for large areas with global coverage. G3P is obtained by using a mass balance approach, i.e., by subtracting satellite-based water storage compartments (WSCs) such as snow water equivalent, root-zone soil moisture, glacier mass, and surface water storage from GRACE/GRACE-FO monthly terrestrial water storage anomalies (TWSA). For a consistent subtraction of all individual WSCs from GRACE-TWSA, the individual WSCs are filtered in a similar way as GRACE-TWSA, where optimal filter types were derived by analyses of spatial correlation patterns. G3P groundwater variations are provided for almost two decades (from 2002 to the present), with the monthly resolution, and at a 0.5-degree spatial resolution globally. In this contribution, we also illustrate preliminary results of the G3P data set and of its uncertainties, as well as its evaluation by independent groundwater data.

This study has received funding from the European Union’s Horizon 2020 research and innovation programme for G3P (Global Gravity-based Groundwater Product) under grant agreement nº 870353.

How to cite: Sharifi, E. and Güntner, A. and the G3P team: The Global Gravity-based Groundwater Product (G3P): first results , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1659, https://doi.org/10.5194/egusphere-egu22-1659, 2022.

17:48–17:54
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EGU22-2495
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ECS
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On-site presentation
Mohamed Akl et al.

Abstract:
Accurate estimation of groundwater storage is hindered by the lack of direct observations of groundwater over space and time. Gravity Recovery and Climate Experiment (GRACE) satellite observes total water storage, thus presenting issues in applying water budget approaches to extract GRACE-derived groundwater storage. This is especially true in regions with complicated hydrology, ranging from numerous small lakes/reservoirs, elevation variation, and changes in active layer thickness in regions with frozen ground. While the objective of many GRACE studies is to disaggregate total water storage budget, to separately estimate groundwater storage changes, the influence of reservoir storage change within a basin is generally ignored. Extraction of groundwater time series from GRACE, using hydrologic and land surface model output, fails to capture storage changes caused by changes in lake and reservoir storage. In significant surface water areas, reservoir storage may alter water storage changes by increasing leakage errors, and offsetting seasonal variability, leading to accumulation of errors in groundwater estimates. Here, we conducted data-driven experiments to understand the spatial influence of lake and reservoirs on GRACE-derived groundwater storage estimation, using independent information of recorded lake/reservoir water level. The study included comparisons with in-situ groundwater observations throughout Canada to validate our GRACE-derived groundwater storage signal. Accounting for reservoir storage combined with GRACE, improved out estimate of GRACE-derived groundwater storage changes for most basins. Identifying what factors did or did not influence goodness of fit will be addressed.

Acknowledgement: The researcher, Mohamed Akl, is funded by a full scholarship from the Ministry of Higher Education of the Arab Republic of Egypt.

How to cite: Akl, M., Thomas, B., and Mills, J.: GRACE-derived groundwater storage estimation: Lake/Reservoir storage controls across Canada, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2495, https://doi.org/10.5194/egusphere-egu22-2495, 2022.

17:54–18:00
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EGU22-7127
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ECS
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Virtual presentation
Kuei-Hua Hsu et al.

The German Research Unit GlobalCDA has the goal to improve the predictive skills of hydrological models by combining remote sensing information using a calibration/data assimilation (C/DA) approach. In order to validate model results and to assess the success of the C/DA efforts, independent data sets are crucially needed, such as in-situ groundwater observations to assess the ability of the model to describe groundwater storage changes. The main challenge arising from such comparisons is to capture basin-scale groundwater storage from a set of in-situ GW observations settled in highly heterogeneous lithologies with irregular & non-homogeneous sampling. Furthermore, the conversion from groundwater (GW) level measurements to storage variations requires information on specific yield, ideally given site-specific for each monitoring well. However, this information is largely not available and difficult to estimate in areas with highly heterogeneous geology.

In our study we use a data set of groundwater level observations at about 3000 groundwater monitoring wells in France. Based on a high-resolution hydro-geological information system provided by the French geological survey (BRGM) and water authorities (BDLISA), we assign the borehole data to individual hydro-geological units. For the upscaling to river basin averages, we (i) aggregate the measurements that originate from the same unit and (ii) account for the areal fractions of the hydro-geological units within the river basin. For the interpretation of GW level variations to GW storage changes, we tested several approaches to estimate specific yield values for the individual hydro-geological units. Wherever possible, we use the specific yield values explicitly provided in the BDLISA data base, mostly estimated from pumping test analysis. When not available, we assign literature-based specific yield values based on the detailed lithological information provided for each unit. This method is compared to global porosity information provided by low resolution geological data from GHYLMPS (Gleeson et al., 2014)

Besides presenting the methodological approach, this presentation shows the resulting groundwater storage time series, averaged for individual river basins in France and for individual 0.5° grid cells. Additionally, comparisons to simulated groundwater storage variations of the WaterGAP Global Hydrology Model (WGHM) will be presented. We discuss the sensitivity of basin averaged GW storage time series to different choices of specific yield for individual boreholes.

How to cite: Hsu, K.-H., Eicker, A., Hasan, M., Güntner, A., and Longuevergne, L.: Estimating groundwater storage changes for major river basins in France using a regional groundwater data set , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7127, https://doi.org/10.5194/egusphere-egu22-7127, 2022.

18:00–18:06
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EGU22-7966
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ECS
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On-site presentation
Rafael Chavez Garcia Silva et al.

The Mediterranean region is undergoing increasing climatic and anthropogenic pressures that challenge water security. Groundwater is a strategic resource for agriculture and water supply in the region, buffering climate change impacts. While previous studies have focused on specific aquifers' water budgets and trends at plot scales, regional dynamics remain unclear. One of the challenges for assessment is the uneven distribution of access to groundwater level monitoring data, as it's not centralized and publicly accessible in most Mediterranean countries. Here we present results that focused on analyzing the groundwater level trends in the countries with the most available groundwater level information: France, Portugal, and Spain. This study contributes to our understanding of groundwater dynamics under varying drivers and groundwater-depletion mitigation options.

As a system with 'memory,' analyzing decades of time series is essential to understand the changes, vulnerability, and resilience. For 1985-1994, 1995-2004, and 2005-2014, a trend analysis was performed on the groundwater levels for piezometers (n=844) covering these periods with considerable completeness. We identified clusters of similar groundwater level developments and categorized them into nine aquifer archetypes, for example: stable water table depth, continued depletion, groundwater level recovery, and local gaining or depleting water levels occurring in each of the three decades. Furthermore, the influence of climate and geological variables on these temporal evolutions were analyzed. Overall, about a third of the studied piezometers showed trends in at least one of the periods. Increasing depths were observed more abundantly in the first period (1985-1994), while decreasing depths were more abundant in the last period.

This work was developed in the scope of the InTheMED project. InTheMED is part of the PRIMA programme supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No 1923.

How to cite: Chavez Garcia Silva, R., Reinecke, R., Varouchakis, E., Gómez-Hernández, J., Rode, M., and Jomaa, S.: Identification of large-scale aquifer behavior across three decades of groundwater storage change in the western Mediterranean region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7966, https://doi.org/10.5194/egusphere-egu22-7966, 2022.

18:06–18:12
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EGU22-1009
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ECS
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On-site presentation
Wouter Berghuijs et al.

How much precipitation recharges groundwaters varies enormously across Earth's surface, but recharge rates are uncertain because field observations are sparse and modeled global estimates remain largely unvalidated. Here we show that annual recharge is predictable as a simple function of climatic aridity — the ratio of long-term potential evapotranspiration to precipitation — using a global synthesis of measured recharge of 5237 sites across six continents. We use this relationship to estimate long-term recharge globally outside of permafrost regions. Our estimates double previous global hydrological model estimates and are more consistent with empirical field observations. These revised higher estimates of global groundwater recharge imply that groundwater contributes more actively to evapotranspiration and streamflow than previously represented in global water cycle depictions or global hydrological and Earth system models. In addition, we quantify the sensitivity of groundwater recharge to changes in aridity using the empirical relationship between groundwater recharge rates and climatic aridity. This analysis indicates that recharge is most sensitive to climate aridity in mesic regions, where changes in the replenishment of aquifers will be amplified relative to projected changes in precipitation. Global hydrological models seem to underestimate changes in recharge with climate aridity. Thus, the impacts of climatic changes on the replenishment of Earth's largest liquid freshwater stores may be larger than previously anticipated.

How to cite: Berghuijs, W., Allen, S., Jasechko, S., Moeck, C., Luijendijk, E., and van der Velde, Y.: A more active role for groundwater in the land water cycle, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1009, https://doi.org/10.5194/egusphere-egu22-1009, 2022.

18:12–18:18
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EGU22-2374
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ECS
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Virtual presentation
Li Han et al.

In permafrost environments, groundwater recharge and groundwater flow are strongly affected by seasonal thawing and freezing cycles, the depth of the active layer, and the spatial coverage of permafrost. In such areas, groundwater is an important supply to the regional water resources, especially during the cold season when the frozen ground strongly restricts the water flows close to the ground and the runoff in rivers. However, due to absent or very limited groundwater observations in the permafrost domain, in combination with remoteness and harsh environments such as in Siberia, key processes and factors that control the subsurface dynamics on the large scale are not well understood yet. In a warming climate, the storage and movement of water in the subsurface system are expected to be altered through degrading permafrost and changing underground connections. However, due to the lack of corresponding studies, assumptions in this regard are very speculative.

Based on long-term daily river flow records (1950-2010) of large southern Siberian catchments (about 1,600,000 km² in total) with different permafrost conditions, we investigate the historical variations in magnitude, timing, and duration of low flow (as an indicator of groundwater dynamics) during the winter period. Our results show that the magnitude of low flow in the catchments has increased during 1950-2010, with the most considerable rise being noticed in the late 30-years period since 1980. Furthermore, we also found that the occurrence of the minflow (i.e., the minimum value of low flow) fluctuates between early and late winter in the catchments with sparse permafrost coverage. In contrast, in the catchments where continuous permafrost prevails, the minflow always occurs in late winter. Finally, for the catchments underlain by discontinuous permafrost, the timing of minflow shows relatively stable conditions in the earlier 30-year period. However, it starts fluctuating between early and late winter during the latter 30 years when a significant rise in low flow is observed. Given the unprecedented warming over the last decades in southern Siberia, these significant changes in both the magnitude and timing of low flow could be induced by the altered surface water-groundwater interactions that are triggered by the degrading permafrost. Overall, our results provide insights into the potential evolutions in the large-scale groundwater dynamics over varied temporal and spatial distributions of permafrost under a warming climate.

How to cite: Han, L., Park, H., and Menzel, L.: How does thawing permafrost change groundwater discharge? A case study from southern Siberia , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2374, https://doi.org/10.5194/egusphere-egu22-2374, 2022.

18:18–18:24
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EGU22-4158
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On-site presentation
Simon Stisen et al.

Groundwater recharge quantification is essential for sustainable groundwater resources management, but typically limited to local and regional scale estimates. A high-resolution (1 km x 1 km) dataset consisting of long-term average actual evapotranspiration, effective precipitation, a groundwater recharge coefficient, and the resulting groundwater recharge map has been created for all of Europe using a variety of pan-European datasets and seven national gridded recharge estimates. As an initial step, the approach developed for continental scale mapping consists of a merged estimate of actual evapotranspiration originating from satellite data and the vegetation controlled Budyko approach to subsequently estimate effective precipitation.  Secondly, a machine learning model based on the Random Forest regressor was developed for mapping groundwater recharge coefficients, using a range of covariates related to geology, soil, topography and climate. A common feature of the approach is the validation and training against effective precipitation, recharge coefficients and groundwater recharge from seven national gridded datasets covering the UK, Ireland, Finland, Denmark, the Netherlands, France and Spain, representing a wide range of climatic and hydrogeological conditions across Europe.  The groundwater recharge map provides harmonised high-resolution estimates across Europe and locally relevant estimates for areas where this information is otherwise not available, while being consistent with the existing national gridded estimates. The Pan-European groundwater recharge pattern compares well with results from the global hydrological model PCR-GLOBWB 2. At country scale, the results were compared to a German recharge map showing great similarity. The full dataset of long-term average actual evapotranspiration, effective precipitation, recharge coefficients and groundwater recharge is available through the EuroGeoSurveys’ open access European Geological Data Infrastructure (EGDI).

How to cite: Stisen, S., Martinsen, G., Bessiere, H., Caballero, Y., Koch, J., Juan Collados-Lara, A., Mansour, M., Sallasmaa, O., Pulido Velázquez, D., Hunter Williams, N., and Jan Zaadnoordijk, W.: Pan-European high-resolution groundwater recharge mapping – combining satellite data and national survey data using machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4158, https://doi.org/10.5194/egusphere-egu22-4158, 2022.

18:24–18:30
Discussion