Articles | Volume 26, issue 22
https://doi.org/10.5194/hess-26-5859-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-5859-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Nov 2022
Research article |
| 23 Nov 2022
| 23 Nov 2022
Machine-learning-based downscaling of modelled climate change impacts on groundwater table depth
Department of Hydrology, Geological Survey of Denmark and Greenland
(GEUS), 1350 Copenhagen K, Denmark
Julian Koch
Department of Hydrology, Geological Survey of Denmark and Greenland
(GEUS), 1350 Copenhagen K, Denmark
Lars Troldborg
Department of Hydrology, Geological Survey of Denmark and Greenland
(GEUS), 1350 Copenhagen K, Denmark
Hans Jørgen Henriksen
Department of Hydrology, Geological Survey of Denmark and Greenland
(GEUS), 1350 Copenhagen K, Denmark
Simon Stisen
Department of Hydrology, Geological Survey of Denmark and Greenland
(GEUS), 1350 Copenhagen K, Denmark
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Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-235, https://doi.org/10.5194/hess-2023-235, 2023
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We developed hybrid schemes to enhance national scale streamflow predictions, combining LSTM with a physically based hydrological model (PBM). A comprehensive evaluation of the hybrid setups across all of Denmark indicates that LSTM forced only by climate data and catchment attributes perform well in many regions but face challenges in groundwater-dependent basins. The hybrid schemes supported by PBM possess higher performance in reproducing long-term streamflow behavior and extreme events.
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Temporal drain flow dynamics and understanding of their underlying controlling factors are important for water resource management in tile-drained agricultural areas. This study examine whether simpler, more efficient machine learning (ML) models can provide acceptable solutions compared to traditional physics based models. We predicted drain flow time series in multiple catchments subject to a range of climatic and landscape conditions.
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Raphael Schneider, Peter Nygaard Godiksen, Heidi Villadsen, Henrik Madsen, and Peter Bauer-Gottwein
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We use water level observations from the CryoSat-2 satellite in combination with a river model of the Brahmaputra River, extracting satellite data over a dynamic river mask derived from Landsat imagery. The novelty of this work is the use of the CryoSat-2 water level observations, collected using a complex spatio-temporal sampling scheme, to calibrate a hydrodynamic river model. The resulting model accurately reproduces water levels, without precise knowledge of river bathymetry.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
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This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
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We developed hybrid schemes to enhance national scale streamflow predictions, combining LSTM with a physically based hydrological model (PBM). A comprehensive evaluation of the hybrid setups across all of Denmark indicates that LSTM forced only by climate data and catchment attributes perform well in many regions but face challenges in groundwater-dependent basins. The hybrid schemes supported by PBM possess higher performance in reproducing long-term streamflow behavior and extreme events.
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Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
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This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
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Biogeosciences, 20, 2387–2403, https://doi.org/10.5194/bg-20-2387-2023, https://doi.org/10.5194/bg-20-2387-2023, 2023
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Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The emissions are triggered by lowering the water table, which is a necessary step in order to make peatlands arable. Many countries aim at reducing their emissions by restoring peatlands, which can be achieved by stopping agricultural activities and thereby raising the water table. We estimate a total emission of 2.6 Mt CO2-eq for organic-rich peatlands in Denmark and a potential reduction of 77 %.
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Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-68, https://doi.org/10.5194/nhess-2023-68, 2023
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In this study, we examine how future climate change may affect activity in landslides in Denmark using publicly available data. Our findings show that climate change will increase groundwater table depth, which will lead to increased landslide activity. During past events of extremely wet winters in this region, landslides caused damage to buildings and infrastructure.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
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Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms
Hydrol. Earth Syst. Sci., 26, 3337–3357, https://doi.org/10.5194/hess-26-3337-2022, https://doi.org/10.5194/hess-26-3337-2022, 2022
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The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
Raphael Schneider, Hans Jørgen Henriksen, and Simon Stisen
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Julian Koch, Helen Berger, Hans Jørgen Henriksen, and Torben Obel Sonnenborg
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This study explores novel modelling avenues using machine learning in combination with process-based models to predict the shallow water table at high spatial resolution. Due to climate change and anthropogenic impacts, the shallow groundwater is rising in many parts of the world. In order to adapt to risks induced by groundwater flooding, new modelling tools need to emerge. In this study, we found that machine learning is capable of reaching the required accuracy and resolution.
Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen
Geosci. Model Dev., 11, 1873–1886, https://doi.org/10.5194/gmd-11-1873-2018, https://doi.org/10.5194/gmd-11-1873-2018, 2018
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Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
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Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
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Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Gorka Mendiguren, Julian Koch, and Simon Stisen
Hydrol. Earth Syst. Sci., 21, 5987–6005, https://doi.org/10.5194/hess-21-5987-2017, https://doi.org/10.5194/hess-21-5987-2017, 2017
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The present study is focused on the spatial pattern evaluation of two models and describes the similarities and dissimilarities. It also discusses the factors that generate these patterns and proposes similar new approaches to minimize the differences. The study points towards a new approach in which the spatial component of the hydrological model is also calibrated and taken into account.
Raphael Schneider, Peter Nygaard Godiksen, Heidi Villadsen, Henrik Madsen, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 21, 751–764, https://doi.org/10.5194/hess-21-751-2017, https://doi.org/10.5194/hess-21-751-2017, 2017
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We use water level observations from the CryoSat-2 satellite in combination with a river model of the Brahmaputra River, extracting satellite data over a dynamic river mask derived from Landsat imagery. The novelty of this work is the use of the CryoSat-2 water level observations, collected using a complex spatio-temporal sampling scheme, to calibrate a hydrodynamic river model. The resulting model accurately reproduces water levels, without precise knowledge of river bathymetry.
R. Guzinski, H. Nieto, S. Stisen, and R. Fensholt
Hydrol. Earth Syst. Sci., 19, 2017–2036, https://doi.org/10.5194/hess-19-2017-2015, https://doi.org/10.5194/hess-19-2017-2015, 2015
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The study compared evapotranspiration (ET) modelled by two remote sensing models and one hydrological model in a river catchment in Denmark. The results show that the spatial patterns of ET produced by the remote sensing models are more similar to each other than to the fluxes produced by the hydrological model. This indicates potential benefits to the hydrological modelling community from integrating spatial information derived through remote sensing methodology into the hydrological models.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
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A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
J. Koch, X. He, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 18, 2907–2923, https://doi.org/10.5194/hess-18-2907-2014, https://doi.org/10.5194/hess-18-2907-2014, 2014
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Hydrol. Earth Syst. Sci., 28, 525–543, https://doi.org/10.5194/hess-28-525-2024, https://doi.org/10.5194/hess-28-525-2024, 2024
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We build a neural network to predict groundwater levels from monitoring wells. We predict all wells at the same time, by learning the differences between wells with static features, making it an entity-aware global model. This works, but we also test different static features and find that the model does not use them to learn exactly how the wells are different, but only to uniquely identify them. As this model class is not actually entity aware, we suggest further steps to make it so.
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In this study, we demonstrate an approach to evaluate the interpretation uncertainty within a manually interpreted geological model in a groundwater model. Using qualitative estimates of uncertainties, several geological realizations are developed and implemented in groundwater models. We confirm existing evidence that if the conceptual model is well defined, interpretation uncertainties within the conceptual model have limited impact on groundwater model predictions.
Yong Zhang, Graham E. Fogg, HongGuang Sun, Donald M. Reeves, Roseanna M. Neupauer, and Wei Wei
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Pollutant release history and source identification are helpful for managing water resources, but it remains a challenge to reliably identify such information for real-world, complex transport processes in rivers and aquifers. In this study, we filled this knowledge gap by deriving a general backward governing equation and developing the efficient solver. Field applications showed that this model and solver are applicable for a broad range of flow systems, dimensions, and spatiotemporal scales.
Mennatullah T. Elrashidy, Andrew M. Ireson, and Saman Razavi
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Wetlands are important ecosystems that store carbon and play a vital role in the water cycle. However, hydrological computer models do not always represent wetlands and their interaction with groundwater accurately. We tested different possible ways to include groundwater–wetland interactions in these models. We found that the optimal method to include wetlands and groundwater in the models is reliant on the intended use of the models and the characteristics of the land and soil being studied.
Andreas Wunsch, Tanja Liesch, and Nico Goldscheider
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-284, https://doi.org/10.5194/hess-2023-284, 2023
Revised manuscript accepted for HESS
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Seasons have a strong influence on groundwater levels, but relationships are complex and partly unknown. Using data from wells in Germany and an explainable machine learning approach, we showed that summer precipitation is the key factor that controls the severeness of a low-water period in fall, high summer temperatures do not per-se cause stronger decreases. Preceding winters have only minor influence on such low-water periods, in general.
Conny Tschritter, Christopher J. Daughney, Sapthala Karalliyadda, Brioch Hemmings, Uwe Morgenstern, and Catherine Moore
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Understanding groundwater travel time (groundwater age) is crucial for tracking flow and contaminants. While groundwater age is usually inferred from age tracers, this study utilised two machine learning techniques with common groundwater chemistry data. The results of both methods correspond to traditional approaches. They are useful where hydrochemistry data exist but age tracer data are limited. These methods could help enhance our knowledge, aiding in sustainable freshwater management.
Jose M. Bastias Espejo, Chris Turnadge, Russell S. Crosbie, Philipp Blum, and Gabriel C. Rau
Hydrol. Earth Syst. Sci., 27, 3447–3462, https://doi.org/10.5194/hess-27-3447-2023, https://doi.org/10.5194/hess-27-3447-2023, 2023
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Analytical models estimate subsurface properties from subsurface–tidal load interactions. However, they have limited accuracy in representing subsurface physics and parameter estimation. We derived a new analytical solution which models flow to wells due to atmospheric tides. We applied it to field data and compared our findings with subsurface knowledge. Our results enhance understanding of subsurface systems, providing valuable information on their behavior.
Ronan Abhervé, Clément Roques, Alexandre Gauvain, Laurent Longuevergne, Stéphane Louaisil, Luc Aquilina, and Jean-Raynald de Dreuzy
Hydrol. Earth Syst. Sci., 27, 3221–3239, https://doi.org/10.5194/hess-27-3221-2023, https://doi.org/10.5194/hess-27-3221-2023, 2023
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We propose a model calibration method constraining groundwater seepage in the hydrographic network. The method assesses the hydraulic properties of aquifers in regions where perennial streams are directly fed by groundwater. The estimated hydraulic conductivity appear to be highly sensitive to the spatial extent and density of streams. Such an approach improving subsurface characterization from surface information is particularly interesting for ungauged basins.
Amanda Triplett and Laura E. Condon
Hydrol. Earth Syst. Sci., 27, 2763–2785, https://doi.org/10.5194/hess-27-2763-2023, https://doi.org/10.5194/hess-27-2763-2023, 2023
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Accelerated melting in mountains is a global phenomenon. The Heihe River basin depends on upstream mountains for its water supply. We built a hydrologic model to examine how shifts in streamflow and warming will impact ground and surface water interactions. The results indicate that degrading permafrost has a larger effect than melting glaciers. Additionally, warming temperatures tend to have more impact than changes to streamflow. These results can inform other mountain–valley system studies.
Guillaume Cinkus, Andreas Wunsch, Naomi Mazzilli, Tanja Liesch, Zhao Chen, Nataša Ravbar, Joanna Doummar, Jaime Fernández-Ortega, Juan Antonio Barberá, Bartolomé Andreo, Nico Goldscheider, and Hervé Jourde
Hydrol. Earth Syst. Sci., 27, 1961–1985, https://doi.org/10.5194/hess-27-1961-2023, https://doi.org/10.5194/hess-27-1961-2023, 2023
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Numerous modelling approaches can be used for studying karst water resources, which can make it difficult for a stakeholder or researcher to choose the appropriate method. We conduct a comparison of two widely used karst modelling approaches: artificial neural networks (ANNs) and reservoir models. Results show that ANN models are very flexible and seem great for reproducing high flows. Reservoir models can work with relatively short time series and seem to accurately reproduce low flows.
Wenguang Shi, Quanrong Wang, Hongbin Zhan, Renjie Zhou, and Haitao Yan
Hydrol. Earth Syst. Sci., 27, 1891–1908, https://doi.org/10.5194/hess-27-1891-2023, https://doi.org/10.5194/hess-27-1891-2023, 2023
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The mechanism of radial dispersion is important for understanding reactive transport in the subsurface and for estimating aquifer parameters required in the optimization design of remediation strategies. A general model and associated analytical solutions are developed in this study. The new model represents the most recent advancement on radial dispersion studies and incorporates a host of important processes that are not taken into consideration in previous investigations.
Vanja Travaš, Luka Zaharija, Davor Stipanić, and Siniša Družeta
Hydrol. Earth Syst. Sci., 27, 1343–1359, https://doi.org/10.5194/hess-27-1343-2023, https://doi.org/10.5194/hess-27-1343-2023, 2023
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In order to model groundwater flow in karst aquifers, it is necessary to approximate the influence of the unknown and irregular structure of the karst conduits. For this purpose, a procedure based on inverse modeling is adopted. Moreover, in order to reconstruct the functional dependencies related to groundwater flow, the particle swarm method was used, through which the optimal solution of unknown functions is found by imitating the movement of ants in search of food.
Shouchuan Zhang, Zheming Shi, Guangcai Wang, Zuochen Zhang, and Huaming Guo
Hydrol. Earth Syst. Sci., 27, 401–415, https://doi.org/10.5194/hess-27-401-2023, https://doi.org/10.5194/hess-27-401-2023, 2023
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We documented the step-like increases of water level, flow rate, and water temperatures in a confined aquifer following multiple earthquakes. By employing tidal analysis and a coupled temperature and flow rate model, we find that post-seismic vertical permeability changes and recharge model could explain the co-seismic response. And co-seismic temperature changes are caused by mixing of different volumes of water, with the mixing ratio varying according to each earthquake.
Xiaoying Zhang, Fan Dong, Guangquan Chen, and Zhenxue Dai
Hydrol. Earth Syst. Sci., 27, 83–96, https://doi.org/10.5194/hess-27-83-2023, https://doi.org/10.5194/hess-27-83-2023, 2023
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In a data-driven framework, groundwater levels can generally only be calculated 1 time step ahead. We discuss the advance prediction with longer forecast periods rather than single time steps by constructing a model based on a temporal convolutional network. Model accuracy and efficiency were further compared with an LSTM-based model. The two models derived in this study can help people cope with the uncertainty of what might occur in hydrological scenarios under the threat of climate change.
Dimitri Rambourg, Raphaël Di Chiara, and Philippe Ackerer
Hydrol. Earth Syst. Sci., 26, 6147–6162, https://doi.org/10.5194/hess-26-6147-2022, https://doi.org/10.5194/hess-26-6147-2022, 2022
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The reproduction of flows and contaminations underground requires a good estimation of the parameters of the geological environment (mainly permeability and porosity), in three dimensions. While most researchers rely on geophysical methods, which are costly and difficult to implement in the field, this study proposes an alternative using data that are already widely available: piezometric records (monitoring of the water table) and the lithological description of the piezometric wells.
Luca Guillaumot, Laurent Longuevergne, Jean Marçais, Nicolas Lavenant, and Olivier Bour
Hydrol. Earth Syst. Sci., 26, 5697–5720, https://doi.org/10.5194/hess-26-5697-2022, https://doi.org/10.5194/hess-26-5697-2022, 2022
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Recharge, defining the renewal rate of groundwater resources, is difficult to estimate at basin scale. Here, recharge variations are inferred from water table variations recorded in boreholes. First, results show that aquifer-scale properties controlling these variations can be inferred from boreholes. Second, groundwater is recharged by both intense and seasonal rainfall. Third, the short-term contribution appears overestimated in recharge models and depends on the unsaturated zone thickness.
Alberto Casillas-Trasvina, Bart Rogiers, Koen Beerten, Laurent Wouters, and Kristine Walraevens
Hydrol. Earth Syst. Sci., 26, 5577–5604, https://doi.org/10.5194/hess-26-5577-2022, https://doi.org/10.5194/hess-26-5577-2022, 2022
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Heat in the subsurface can be used to characterize aquifer flow behaviour. The temperature data obtained can be useful for understanding the groundwater flow, which is of particular importance in waste disposal studies. Satellite images of surface temperature and a temperature–time curve were implemented in a heat transport model. Results indicate that conduction plays a major role in the aquifer and support the usefulness of temperature measurements.
Tunde Olarinoye, Tom Gleeson, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 26, 5431–5447, https://doi.org/10.5194/hess-26-5431-2022, https://doi.org/10.5194/hess-26-5431-2022, 2022
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Analysis of karst spring recession is essential for management of groundwater. In karst, recession is dominated by slow and fast components; separating these components is by manual and subjective approaches. In our study, we tested the applicability of automated streamflow recession extraction procedures for a karst spring. Results showed that, by simple modification, streamflow extraction methods can identify slow and fast components: derived recession parameters are within reasonable ranges.
Min Lu, Bart Rogiers, Koen Beerten, Matej Gedeon, and Marijke Huysmans
Hydrol. Earth Syst. Sci., 26, 3629–3649, https://doi.org/10.5194/hess-26-3629-2022, https://doi.org/10.5194/hess-26-3629-2022, 2022
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Lowland rivers and shallow aquifers are closely coupled. We study their interactions here using a combination of impulse response modeling and hydrological data analysis. The results show that the lowland catchments are groundwater dominated and that the hydrological system from precipitation impulse to groundwater inflow response is a very fast response regime. This study also provides an alternative method to estimate groundwater inflow to rivers from the perspective of groundwater level.
Zhongxia Li, Junwei Wan, Tao Xiong, Hongbin Zhan, Linqing He, and Kun Huang
Hydrol. Earth Syst. Sci., 26, 3359–3375, https://doi.org/10.5194/hess-26-3359-2022, https://doi.org/10.5194/hess-26-3359-2022, 2022
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Four permeable rocks with different pore sizes were considered to provide experimental evidence of Forchheimer flow and the transition between different flow regimes. The mercury injection technique was used to measure the pore size distribution, which is an essential factor for determining the flow regime, for four permeable stones. Finally, the influences of porosity and particle size on the Forchheimer coefficients were discussed.
Andreas Wunsch, Tanja Liesch, Guillaume Cinkus, Nataša Ravbar, Zhao Chen, Naomi Mazzilli, Hervé Jourde, and Nico Goldscheider
Hydrol. Earth Syst. Sci., 26, 2405–2430, https://doi.org/10.5194/hess-26-2405-2022, https://doi.org/10.5194/hess-26-2405-2022, 2022
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Modeling complex karst water resources is difficult enough, but often there are no or too few climate stations available within or close to the catchment to deliver input data for modeling purposes. We apply image recognition algorithms to time-distributed, spatially gridded meteorological data to simulate karst spring discharge. Our models can also learn the approximate catchment location of a spring independently.
Brian Berkowitz
Hydrol. Earth Syst. Sci., 26, 2161–2180, https://doi.org/10.5194/hess-26-2161-2022, https://doi.org/10.5194/hess-26-2161-2022, 2022
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Extensive efforts have focused on quantifying conservative chemical transport in geological formations. We assert that an explicit accounting of temporal information, under uncertainty, in addition to spatial information, is fundamental to an effective modeling formulation. We further assert that efforts to apply chemical transport equations at large length scales, based on measurements and model parameter values relevant to significantly smaller length scales, are an unattainable
holy grail.
Guilherme E. H. Nogueira, Christian Schmidt, Daniel Partington, Philip Brunner, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 26, 1883–1905, https://doi.org/10.5194/hess-26-1883-2022, https://doi.org/10.5194/hess-26-1883-2022, 2022
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In near-stream aquifers, mixing between stream water and ambient groundwater can lead to dilution and the removal of substances that can be harmful to the water ecosystem at high concentrations. We used a numerical model to track the spatiotemporal evolution of different water sources and their mixing around a stream, which are rather difficult in the field. Results show that mixing mainly develops as narrow spots, varying In time and space, and is affected by magnitudes of discharge events.
Jacques Bodin, Gilles Porel, Benoît Nauleau, and Denis Paquet
Hydrol. Earth Syst. Sci., 26, 1713–1726, https://doi.org/10.5194/hess-26-1713-2022, https://doi.org/10.5194/hess-26-1713-2022, 2022
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Assessment of the karst network geometry is an important challenge in the accurate modeling of karst aquifers. In this study, we propose an approach for the identification of effective three-dimensional discrete karst conduit networks conditioned on tracer tests and geophysical data. The applicability of the proposed approach is illustrated through a case study at the Hydrogeological Experimental Site in Poitiers, France.
Zexuan Xu, Rebecca Serata, Haruko Wainwright, Miles Denham, Sergi Molins, Hansell Gonzalez-Raymat, Konstantin Lipnikov, J. David Moulton, and Carol Eddy-Dilek
Hydrol. Earth Syst. Sci., 26, 755–773, https://doi.org/10.5194/hess-26-755-2022, https://doi.org/10.5194/hess-26-755-2022, 2022
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Climate change could change the groundwater system and threaten water supply. To quantitatively evaluate its impact on water quality, numerical simulations with chemical and reaction processes are required. With the climate projection dataset, we used the newly developed hydrological and chemical model to investigate the movement of contaminants and assist the management of contamination sites.
Esther Brakkee, Marjolein H. J. van Huijgevoort, and Ruud P. Bartholomeus
Hydrol. Earth Syst. Sci., 26, 551–569, https://doi.org/10.5194/hess-26-551-2022, https://doi.org/10.5194/hess-26-551-2022, 2022
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Periods of drought often lead to groundwater shortages in large regions, which cause damage to nature and the economy. To take measures, we need a good understanding of where and when groundwater shortage occurs. In this study, we have tested a method that can combine large amounts of groundwater measurements in an automated way and provide detailed maps of how groundwater shortages develop during a drought period. This information can help water managers to limit future groundwater shortages.
Emmanuel Dubois, Marie Larocque, Sylvain Gagné, and Guillaume Meyzonnat
Hydrol. Earth Syst. Sci., 25, 6567–6589, https://doi.org/10.5194/hess-25-6567-2021, https://doi.org/10.5194/hess-25-6567-2021, 2021
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This work demonstrates the relevance of using a water budget model to understand long-term transient and regional-scale groundwater recharge (GWR) in cold and humid climates where groundwater observations are scarce. Monthly GWR is simulated for 57 years on 500 m x 500 m cells in Canada (36 000 km2 area) with limited uncertainty due to a robust automatic calibration method. The increases in precipitation and temperature since the 1960s have not yet produced significant changes in annual GWR.
Yaniv Edery, Martin Stolar, Giovanni Porta, and Alberto Guadagnini
Hydrol. Earth Syst. Sci., 25, 5905–5915, https://doi.org/10.5194/hess-25-5905-2021, https://doi.org/10.5194/hess-25-5905-2021, 2021
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The interplay between dissolution, precipitation and transport is widely encountered in porous media, from CO2 storage to cave formation in carbonate rocks. We show that dissolution occurs along preferential flow paths with high hydraulic conductivity, while precipitation occurs at locations close to yet separated from these flow paths, thus further funneling the flow and changing the probability density function of the transport, as measured on the altered conductivity field at various times.
Karina Y. Gutierrez-Jurado, Daniel Partington, and Margaret Shanafield
Hydrol. Earth Syst. Sci., 25, 4299–4317, https://doi.org/10.5194/hess-25-4299-2021, https://doi.org/10.5194/hess-25-4299-2021, 2021
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Understanding the hydrologic cycle in semi-arid landscapes includes knowing the physical processes that govern where and why rivers flow and dry within a given catchment. To gain this understanding, we put together a conceptual model of what processes we think are important and then tested that model with numerical analysis. The results broadly confirmed our hypothesis that there are three distinct regions in our study catchment that contribute to streamflow generation in quite different ways.
Natascha Brandhorst, Daniel Erdal, and Insa Neuweiler
Hydrol. Earth Syst. Sci., 25, 4041–4059, https://doi.org/10.5194/hess-25-4041-2021, https://doi.org/10.5194/hess-25-4041-2021, 2021
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We compare two approaches for coupling a 2D groundwater model with multiple 1D models for the unsaturated zone. One is non-iterative and very fast. The other one is iterative and involves a new way of treating the specific yield, which is crucial for obtaining a consistent solution in both model compartments. Tested on different scenarios, this new method turns out to be slower than the non-iterative approach but more accurate and still very efficient compared to fully integrated 3D model runs.
Vince P. Kaandorp, Hans Peter Broers, Ype van der Velde, Joachim Rozemeijer, and Perry G. B. de Louw
Hydrol. Earth Syst. Sci., 25, 3691–3711, https://doi.org/10.5194/hess-25-3691-2021, https://doi.org/10.5194/hess-25-3691-2021, 2021
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We reconstructed historical and present-day tritium, chloride, and nitrate concentrations in stream water of a catchment using
land-use-based input curves and calculated travel times of groundwater. Parameters such as the unsaturated zone thickness, mean travel time, and input patterns determine time lags between inputs and in-stream concentrations. The timescale of the breakthrough of pollutants in streams is dependent on the location of pollution in a catchment.
Yueling Ma, Carsten Montzka, Bagher Bayat, and Stefan Kollet
Hydrol. Earth Syst. Sci., 25, 3555–3575, https://doi.org/10.5194/hess-25-3555-2021, https://doi.org/10.5194/hess-25-3555-2021, 2021
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This study utilized spatiotemporally continuous precipitation anomaly (pra) and water table depth anomaly (wtda) data from integrated hydrologic simulation results over Europe in combination with Long Short-Term Memory (LSTM) networks to capture the time-varying and time-lagged relationship between pra and wtda in order to obtain reliable models to estimate wtda at the individual pixel level.
Raoul A. Collenteur, Mark Bakker, Gernot Klammler, and Steffen Birk
Hydrol. Earth Syst. Sci., 25, 2931–2949, https://doi.org/10.5194/hess-25-2931-2021, https://doi.org/10.5194/hess-25-2931-2021, 2021
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This study explores the use of nonlinear transfer function noise (TFN) models to simulate groundwater levels and estimate groundwater recharge from observed groundwater levels. A nonlinear recharge model is implemented in a TFN model to compute the recharge. The estimated recharge rates are shown to be in good agreement with the recharge observed with a lysimeter present at the case study site in Austria. The method can be used to obtain groundwater recharge rates at
sub-yearly timescales.
Franci Gabrovšek and Wolfgang Dreybrodt
Hydrol. Earth Syst. Sci., 25, 2895–2913, https://doi.org/10.5194/hess-25-2895-2021, https://doi.org/10.5194/hess-25-2895-2021, 2021
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The evolution of karst aquifers is often governed by solutions gaining their aggressiveness in depth. Although the principles of
hypogene speleogenesisare known, modelling studies based on reactive flow in fracture networks are missing. We present a model where dissolution at depth is triggered by the mixing of waters of different origin and chemistry. We show how the initial position of the mixing zone and flow instabilities therein determine the position and shape of the final conduits.
Patrick Morrissey, Paul Nolan, Ted McCormack, Paul Johnston, Owen Naughton, Saheba Bhatnagar, and Laurence Gill
Hydrol. Earth Syst. Sci., 25, 1923–1941, https://doi.org/10.5194/hess-25-1923-2021, https://doi.org/10.5194/hess-25-1923-2021, 2021
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Lowland karst aquifers provide important wetland habitat resulting from seasonal flooding on the land surface. This flooding is controlled by surcharging of the karst system, which is very sensitive to changes in rainfall. This study investigates the predicted impacts of climate change on a lowland karst catchment in Ireland and highlights the relative vulnerability to future changing climate conditions of karst systems and any associated wetland habitats.
Liwen Wu, Jesus D. Gomez-Velez, Stefan Krause, Anders Wörman, Tanu Singh, Gunnar Nützmann, and Jörg Lewandowski
Hydrol. Earth Syst. Sci., 25, 1905–1921, https://doi.org/10.5194/hess-25-1905-2021, https://doi.org/10.5194/hess-25-1905-2021, 2021
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With a physically based model that couples flow and heat transport in hyporheic zones, the present study provides the first insights into the dynamics of hyporheic responses to the impacts of daily groundwater withdrawal and river temperature fluctuations, allowing for a better understanding of transient hyporheic exchange processes and hence an improved pumping operational scheme.
Andreas Wunsch, Tanja Liesch, and Stefan Broda
Hydrol. Earth Syst. Sci., 25, 1671–1687, https://doi.org/10.5194/hess-25-1671-2021, https://doi.org/10.5194/hess-25-1671-2021, 2021
Jost Hellwig, Michael Stoelzle, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 25, 1053–1068, https://doi.org/10.5194/hess-25-1053-2021, https://doi.org/10.5194/hess-25-1053-2021, 2021
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Potential future groundwater and baseflow drought hazards depend on systems' sensitivity to altered recharge conditions. With three generic scenarios, we found different sensitivities across Germany driven by hydrogeology. While changes in drought hazard due to seasonal recharge shifts will be rather low, a lengthening of dry spells could cause stronger responses in regions with slow groundwater response to precipitation, urging local water management to prepare for more severe droughts.
Martin J. Wells, Troy E. Gilmore, Natalie Nelson, Aaron Mittelstet, and John K. Böhlke
Hydrol. Earth Syst. Sci., 25, 811–829, https://doi.org/10.5194/hess-25-811-2021, https://doi.org/10.5194/hess-25-811-2021, 2021
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Groundwater in many agricultural areas contains high levels of nitrate, which is a concern for drinking water supplies. The rate at which nitrate moves through the subsurface is a critical piece of information for predicting how quickly groundwater nitrate levels may improve after agricultural producers change their approach to managing crop water and fertilizers. In this study, we explored a new statistical modeling approach to determine rates at which nitrate moves into and through an aquifer.
Arnaud Duranel, Julian R. Thompson, Helene Burningham, Philippe Durepaire, Stéphane Garambois, Robert Wyns, and Hervé Cubizolle
Hydrol. Earth Syst. Sci., 25, 291–319, https://doi.org/10.5194/hess-25-291-2021, https://doi.org/10.5194/hess-25-291-2021, 2021
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Peat-forming wetlands (mires) provide multiple ecosystem services, which depend on peat remaining waterlogged. Using hydrological modelling, we show that, contrary to a common assumption, groundwater inflow can be a quantitatively important and functionally critical element of the water balance of mires in hard-rock upland and mountain areas. This influence is such that patterns of groundwater upwelling and seepage explain the spatial distribution of mires in the landscape.
Ming Wu, Jianfeng Wu, Jichun Wu, and Bill X. Hu
Hydrol. Earth Syst. Sci., 24, 5903–5917, https://doi.org/10.5194/hess-24-5903-2020, https://doi.org/10.5194/hess-24-5903-2020, 2020
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A new criterion (χi) is proposed to estimate representative elementary volume (REV) of a translucent material based on light transmission techniques. This study is essential for quantitative investigation of the scale effect of porous media and contaminant transformation. The fluid and contaminant migration and transform in porous media can be simulated accurately according to the REV estimation results using the light transmission technique and the appropriate criterion χi.
Ali Ghaseminejad and Venkatesh Uddameri
Hydrol. Earth Syst. Sci., 24, 5759–5779, https://doi.org/10.5194/hess-24-5759-2020, https://doi.org/10.5194/hess-24-5759-2020, 2020
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While artificial neural networks (ANNs) have been used to forecast groundwater levels at single wells, they have not been constructed to forecast hydraulic heads in both space and time. This seminal study presents a modeling framework, guided by the governing physical laws, for building an integrated space–time ANN (IST–ANN) model for regional groundwater level predictions. IST–ANN shows promise for parsimoniously modeling regional-scale groundwater levels using available surrogate information.
Marie-Amélie Pétré, Bernard Ladouche, Jean-Luc Seidel, Romain Hemelsdaël, Véronique de Montety, Christelle Batiot-Guilhe, and Claudine Lamotte
Hydrol. Earth Syst. Sci., 24, 5655–5672, https://doi.org/10.5194/hess-24-5655-2020, https://doi.org/10.5194/hess-24-5655-2020, 2020
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We studied the impact of occasional saltwater intrusions into the karst aquifer of the Balaruc peninsula (France). Using hydrogeological and geochemical data, this study shows that the hydraulic impact on the aquifer is rapid and of regional extent, whereas the geochemical impact is observed at the local scale and is temporally persistent. This research supports groundwater management by providing a better understanding of the hydrodynamics and recovery of the aquifer after saltwater intrusions.
Emmanuel Dubois, Joanna Doummar, Séverin Pistre, and Marie Larocque
Hydrol. Earth Syst. Sci., 24, 4275–4290, https://doi.org/10.5194/hess-24-4275-2020, https://doi.org/10.5194/hess-24-4275-2020, 2020
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The simulation of flow in a karst aquifer in a Mediterranean region using a semi-distributed linear reservoir model (geometry and parameterization) is calibrated and validated based on the analysis of high-resolution time series. The model is used to predict the effect of climatic variation. Although the spring is highly sensitive to rainfall variations, it is also resilient to warming temperature. Finally, this integrated conceptual method is reproducible for karst in semiarid regions.
Cited articles
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and
Rasmussen, J.: An introduction to the European Hydrological System –
Systeme Hydrologique Europeen, “SHE”, 1: History and philosophy of a
physically-based, distributed modelling system, J. Hydrol., 87, 45–59,
https://doi.org/10.1016/0022-1694(86)90114-9, 1986.
Addor, N., Nearing, G., Prieto, C., Newman, A. J., Le Vine, N., and Clark,
M. P.: A Ranking of Hydrological Signatures Based on Their Predictability in
Space, Water Resour. Res., 54, 8792–8812, https://doi.org/10.1029/2018WR022606, 2018.
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Torn, R. D., Kustas, W.
P., and Basara, J. B.: A Multiscale Remote Sensing Model for Disaggregating
Regional Fluxes to Micrometeorological Scales, J. Hydrometeorol., 5,
343–363, https://doi.org/10.1175/1525-7541(2004)005<0343:AMRSMF>2.0.CO;2, 2004.
Anderson, M. C., Yang, Y., Xue, J., Knipper, K. R., Yang, Y., Gao, F., Hain,
C. R., Kustas, W. P., Cawse-Nicholson, K., Hulley, G., Fisher, J. B.,
Alfieri, J. G., Meyers, T. P., Prueger, J., Baldocchi, D. D., and
Rey-Sanchez, C.: Interoperability of ECOSTRESS and Landsat for mapping
evapotranspiration time series at sub-field scales, Remote Sens. Environ.,
252, 112189, https://doi.org/10.1016/j.rse.2020.112189, 2021.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing
area model of basin hydrology, Hydrol. Sci. Sci. Hydrol., 24, 43–69, 1979.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324, 2001.
Cheng, J., Kuang, Q., Shen, C., Liu, J., Tan, X., and Liu, W.: ResLap:
Generating High-Resolution Climate Prediction through Image
Super-Resolution, IEEE Access, 8, 39623–39634,
https://doi.org/10.1109/ACCESS.2020.2974785, 2020.
DHI: MIKE SHE – User Guide and Reference Manual,
https://manuals.mikepoweredbydhi.help/2020/Water_Resources/MIKE_SHE_Print.pdf (last access: 17 November 2022), 2020.
Doherty, J.: Calibration and Uncertainty Analysis for Complex Environmental
Models, Watermark Numerical Computing, Brisbane, Australia, ISBN 978-0-9943786-0-6 (electronic), 2015.
Fan, Y., Li, H., and Miguez-Macho, G.: Global Patterns of Groundwater Table Depth, Science, 339, 940–943,
https://doi.org/10.1126/science.1229881, 2013.
Ghiggi, G., Humphrey, V., Seneviratne, S. I., and Gudmundsson, L.: GRUN: an observation-based global gridded runoff dataset from 1902 to 2014, Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, 2019.
Gleeson, T., Befus, K. M., Jasechko, S., Luijendijk, E., and Cardenas, M.
B.: The global volume and distribution of modern groundwater, Nat. Geosci.,
9, 161–164, https://doi.org/10.1038/ngeo2590, 2016.
Gonzalez, R. Q. and Arsanjani, J. J.: Prediction of Groundwater Level
Variations in a Changing Climate: A Danish Case Study, ISPRS Int. J.
Geo-Information, 10, 792, https://doi.org/10.3390/ijgi10110792, 2021.
Guzinski, R. and Nieto, H.: Evaluating the feasibility of using Sentinel-2
and Sentinel-3 satellites for high-resolution evapotranspiration
estimations, Remote Sens. Environ., 221, 157–172,
https://doi.org/10.1016/j.rse.2018.11.019, 2019.
Halsnæs, K., Larsen, M. A. D., and Drenck, K. L.: Samfundsøkonomiske
konsekvenser af oversvømmelser og investeringer i klimatilpasning, 56
pp., DTU, Department of Management Engineering, Kgs. Lyngby, Denmark, https://backend.orbit.dtu.dk/ws/portalfiles/portal/268507361/Samfunds_konomiske_konsekvenser_af_oversv_mmelser_og_investeringer_i_klimatilpasning_final_reduced.pdf, last access: 17 November 2022.
Henriksen, H. J., Troldborg, L., Nyegaard, P., Sonnenborg, T. O., Refsgaard,
J. C., and Madsen, B.: Methodology for construction, calibration and
validation of a national hydrological model for Denmark, J. Hydrol., 280,
52–71, https://doi.org/10.1016/S0022-1694(03)00186-0, 2003.
Henriksen, H. J., Kragh, S. J., Gotfredsen, J., Ondracek, M., van Til, M.,
Jakobsen, A., Schneider, R. J. M., Koch, J., Troldborg, L., Rasmussen, P.,
Pasten-Zapata, E., and Stisen, S.: Dokumentationsrapport vedr.
modelleverancer til Hydrologisk Informations- og Prognosesystem, GEUS, https://doi.org/10.22008/gpub/38113, 2020a.
Henriksen, H. J., Kragh, S. J., Gotfredsen, J., Ondracek, M., van Til, M.,
Jakobsen, A., Schneider, R. J. M., Koch, J., Troldborg, L., Rasmussen, P.,
Pasten-Zapata, E., and Stisen, S.: Sammenfatningsrapport vedr.
modelleverancer til Hydrologisk Informations- og Prognosesystem, GEUS, https://doi.org/10.22008/gpub/38112, 2020b.
Højberg, A. L., Troldborg, L., Stisen, S., Christensen, B. B. S., and
Henriksen, H. J.: Stakeholder driven update and improvement of a national
water resources model, Environ. Model. Softw., 40, 202–213,
https://doi.org/10.1016/j.envsoft.2012.09.010, 2013.
Im, J., Park, S., Rhee, J., Baik, J., and Choi, M.: Downscaling of AMSR-E
soil moisture with MODIS products using machine learning approaches,
Environ. Earth Sci., 75, 1120, https://doi.org/10.1007/s12665-016-5917-6,
2016.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer,
L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G.,
Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A.,
Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N.,
Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C.,
Pfeifer, S., Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D.,
Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J. F., Teichmann, C.,
Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: New
high-resolution climate change projections for European impact research,
Reg. Environ. Chang., 14, 563–578,
https://doi.org/10.1007/s10113-013-0499-2, 2014.
Jakobsen, P. R., Hermansen, B., and Tougaard, L.: Danmarks digitale
jordartskort 1:25000 – Version 4.0, GEUS, https://doi.org/10.22008/gpub/30680, 2015.
Koch, J. and Schneider, R.: Long short-term memory networks enhance
rainfall-runoff modelling at the national scale of Denmark, GEUS Bull., 49,
8292, https://doi.org/10.34194/geusb.v49.8292, 2022.
Koch, J., Stisen, S., Refsgaard, J. C., Ernstsen, V., Jakobsen, P. R., and
Højberg, A. L.: Modeling Depth of the Redox Interface at High Resolution
at National Scale Using Random Forest and Residual Gaussian Simulation,
Water Resour. Res., 55, 1451–1469, https://doi.org/10.1029/2018WR023939,
2019a.
Koch, J., Berger, H., Henriksen, H. J., and Sonnenborg, T. O.: Modelling of the shallow water table at high spatial resolution using random forests, Hydrol. Earth Syst. Sci., 23, 4603–4619, https://doi.org/10.5194/hess-23-4603-2019, 2019b.
Koch, J., Gotfredsen, J., Schneider, R., Troldborg, L., Stisen, S., and
Henriksen, H. J.: High Resolution Water Table Modeling of the Shallow
Groundwater Using a Knowledge-Guided Gradient Boosting Decision Tree Model,
Front. Water, 3, 701726, https://doi.org/10.3389/frwa.2021.701726, 2021.
Mai, J., Tolson, B. A., Shen, H., Gaborit, É., Fortin, V., Gasset, N.,
Awoye, H., Stadnyk, T. A., Fry, L. M., Bradley, E. A., Seglenieks, F.,
Temgoua, A. G. T., Princz, D. G., Gharari, S., Haghnegahdar, A., Elshamy, M.
E., Razavi, S., Gauch, M., Lin, J., Ni, X., Yuan, Y., McLeod, M., Basu, N.
B., Kumar, R., Rakovec, O., Samaniego, L., Attinger, S., Shrestha, N. K.,
Daggupati, P., Roy, T., Wi, S., Hunter, T., Craig, J. R., and Pietroniro,
A.: Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E),
J. Hydrol. Eng., 26, 05021020,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0002097, 2021.
Meyer, H. and Pebesma, E.: Predicting into unknown space? Estimating the
area of applicability of spatial prediction models, Methods Ecol. Evol., 12,
1620–1633, https://doi.org/10.1111/2041-210X.13650, 2021.
Møller, A. B., Beucher, A., Iversen, B. V., and Greve, M. H.: Predicting
artificially drained areas by means of a selective model ensemble, Geoderma,
320, 30–42, https://doi.org/10.1016/j.geoderma.2018.01.018, 2018.
Motarjemi, S. K., Møller, A. B., Plauborg, F., and Iversen, B. V.:
Predicting national-scale tile drainage discharge in Denmark using machine
learning algorithms, J. Hydrol. Reg. Stud., 36, 100839,
https://doi.org/10.1016/j.ejrh.2021.100839, 2021.
Nearing, G. S., Kratzert, F., Sampson, A. K., Pelissier, C. S., Klotz, D.,
Frame, J. M., Prieto, C., and Gupta, H. V.: What Role Does Hydrological
Science Play in the Age of Machine Learning?, Water Resour. Res., 57, e2020WR028091, https://doi.org/10.1029/2020WR028091, 2021.
Nijzink, R. C., Samaniego, L., Mai, J., Kumar, R., Thober, S., Zink, M., Schäfer, D., Savenije, H. H. G., and Hrachowitz, M.: The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models, Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, 2016.
Noorduijn, S. L., Refsgaard, J. C., Petersen, R. J., and Højberg, A. L.:
Downscaling a national hydrological model to subgrid scale, J. Hydrol., 603, 126796, https://doi.org/10.1016/j.jhydrol.2021.126796, 2021.
Olesen, S. E.: Kortlægning af potentielt dræningsbehov på
landbrugsarealer opdelt efter landskabselement, geologi, jordklasse,
geologisk region samt høj/lavbund, 30 pp., Aarhus Universitet, Det Jordbrugsvidenskabelige Fakultet, https://pure.au.dk/portal/en/publications/kortlaegning-af-potentielt-draeningsbehov-paa-landbrugsarealer-opdelt-efter-landskabselement-geologi-jordklasse-geologisk-region-samt-hoejlavbund(db364720-183e-11de-a378-000ea68e967b).html (last access: 17 November 2022), 2009.
Pasten-Zapata, E., Sonnenborg, T. O., and Refsgaard, J. C.: Climate change:
Sources of uncertainty in precipitation and temperature projections for
Denmark, GEUS Bull., 43, e2019430102-01,
https://doi.org/10.34194/GEUSB-201943-01-02, 2019.
Read, J. S., Jia, X., Willard, J., Appling, A. P., Zwart, J. A., Oliver, S.
K., Karpatne, A., Hansen, G. J. A., Hanson, P. C., Watkins, W., Steinbach,
M., and Kumar, V.: Process-Guided Deep Learning Predictions of Lake Water
Temperature, Water Resour. Res., 55, 9173–9190,
https://doi.org/10.1029/2019WR024922, 2019.
Refsgaard, J. C., Sonnenborg, T. O., Butts, M. B., Christensen, J. H.,
Christensen, S., Drews, M., Jensen, K. H., Jørgensen, F., Jørgensen,
L. F., Larsen, M. A. D., Rasmussen, S. H., Seaby, L. P., Seifert, D., and
Vilhelmsen, T. N.: Climate change impacts on groundwater hydrology – where
are the main uncertainties and can they be reduced?, Hydrol. Sci. J., 61,
2312–2324, https://doi.org/10.1080/02626667.2015.1131899, 2016.
Rodell, M., Famiglietti, J. S., Wiese, D. N., Reager, J. T., Beaudoing, H.
K., Landerer, F. W., and Lo, M. H.: Emerging trends in global freshwater
availability, Nature, 557, 651–659,
https://doi.org/10.1038/s41586-018-0123-1, 2018.
Rodriguez-Galiano, V., Mendes, M. P., Garcia-Soldado, M. J., Chica-Olmo, M.,
and Ribeiro, L.: Predictive modeling of groundwater nitrate pollution using
Random Forest and multisource variables related to intrinsic and specific
vulnerability: A case study in an agricultural setting (Southern Spain),
Sci. Total Environ., 476–477, 189–206,
https://doi.org/10.1016/j.scitotenv.2014.01.001, 2014.
Samaniego, L., Thober, S., Wanders, N., Pan, M., Rakovec, O., Sheffield, J.,
Wood, E. F., Prudhomme, C., Rees, G., Houghton-Carr, H., Fry, M., Smith, K.,
Watts, G., Hisdal, H., Estrela, T., Buontempo, C., Marx, A., and Kumar, R.:
Hydrological Forecasts and Projections for Improved Decision-Making in the
Water Sector in Europe, B. Am. Meteorol. Soc., 100, 2451–2472,
https://doi.org/10.1175/BAMS-D-17-0274.1, 2019.
Scharling, M.: Klimagrid Danmark – Nedbør, lufttemperatur og potentiel
fordampning 20X20 & 40 × 40 km – Metodebeskrivelse, Danish Meteorological
Institute, ISSN 1399-1388 (Technical Report 99-12), https://www.dmi.dk/fileadmin/user_upload/Rapporter/TR/1999/tr99-12.pdf (last access: 17 November 2022), 1999a.
Scharling, M.: Klimagrid Danmark Nedbør 10 × 10 km (ver. 2) –
Metodebeskrivelse, Danish Meteorological Institute, ISSN 1399-1388 (Technical Report 99-15), https://www.dmi.dk/fileadmin/user_upload/Rapporter/TR/1999/tr99-15.pdf (last access: 17 November 2022), 1999b.
Schneider, R., Stisen, S., and Højberg, A. L.: Hunting for Information in
Streamflow Signatures to Improve Modelled Drainage, 14, 110, https://doi.org/10.3390/w14010110, 2022.
Soltani, M., Bjerre, E., Koch, J., and Stisen, S.: Integrating remote
sensing data in optimization of a national water resources model to improve
the spatial pattern performance of evapotranspiration, J. Hydrol., 603,
127026, https://doi.org/10.1016/j.jhydrol.2021.127026, 2021.
Soylu, M. E. and Bras, R. L.: Global Shallow Groundwater Patterns from Soil
Moisture Satellite Retrievals, IEEE J. Sel. Top. Appl. Earth Obs. Remote
Sens., 15, 89–101, https://doi.org/10.1109/JSTARS.2021.3124892, 2022.
Stisen, S., Sonnenborg, T. O., Højberg, A. L., Troldborg, L., and
Refsgaard, J. C.: Evaluation of Climate Input Biases and Water Balance
Issues Using a Coupled Surface-Subsurface Model, Vadose Zo. J., 10, 37–53,
https://doi.org/10.2136/vzj2010.0001, 2011.
Stisen, S., Schneider, R., Ondracek, M., and Henriksen, H. J.: Modellering
af terrænnært grundvand, vandstand i vandløb og vand på
terræn for Storå og Odense Å. Slutrapport (FODS 6.1 Fasttrack
metodeudvikling), 1–170 pp., https://doi.org/10.22008/gpub/32582, 2018.
Stisen, S., Ondracek, M., Troldborg, L., Schneider, R. J. M., and van Til,
M. J.: National Vandressource Model – Modelopstilling og kalibrering af
DK-model 2019, https://doi.org/10.22008/gpub/32631, 2019.
Sun, A. Y. and Tang, G.: Downscaling Satellite and Reanalysis Precipitation
Products Using Attention-Based Deep Convolutional Neural Nets, Front. Water,
2, 536743, https://doi.org/10.3389/frwa.2020.536743, 2020.
Tesoriero, A. J., Gronberg, J. A., Juckem, P. F., Miller, M. P., and Austin,
B. P.: Predicting redox-sensitive contaminant concentrations in groundwater
using random forest classification, Water Resour. Res., 53, 7316–7331,
https://doi.org/10.1002/2016WR020197, 2017.
The Danish Agency for Data Supply and Infrastructure (SDFI): HIP – Hydrologisk Informations- og Prognosesystem, https://hip.dataforsyningen.dk/ (last access: 17 November 2022), 2021.
Thejll, P., Boberg, F., Schmith, T., Christiansen, B., Christensen, O. B.,
Madsen, M. S., Su, J., Andree, E., Olsen, S., Langen, P. L., Skovgaard, K.
M., Olesen, M., Pedersen, R. A., and Payne, M. R.: Methods used in the
Danish Climate Atlas, 67 pp., Danish Meteorological Institute, ISBN 978-87-7478-690-0, 2021.
Tran, H., Leonarduzzi, E., De la Fuente, L., Hull, R. B., Bansal, V.,
Chennault, C., Gentine, P., Melchior, P., Condon, L. E., and Maxwell, R. M.:
Development of a Deep Learning Emulator for a Distributed
Groundwater–Surface Water Model: ParFlow-ML, Water, 13, 3393,
https://doi.org/10.3390/w13233393, 2021.
Tyralis, H., Papacharalampous, G., and Langousis, A.: A Brief Review of
Random Forests for Water Scientists and Practitioners and Their Recent
History in Water Resources, Water, 11, 910, https://doi.org/10.3390/w11050910,
2019.
van Roosmalen, L., Christensen, B. S. B., and Sonnenborg, T. O.: Regional
Differences in Climate Change Impacts on Groundwater and Stream Discharge in
Denmark, Vadose Zo. J., 6, 554–571, https://doi.org/10.2136/vzj2006.0093,
2007.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A.,
Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T.,
Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The
representative concentration pathways: an overview, Clim. Change, 109,
5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Wood, E. F., Roundy, J. K., Troy, T. J., van Beek, L. P. H., Bierkens, M. F.
P., Blyth, E., de Roo, A., Döll, P., Ek, M., Famiglietti, J., Gochis,
D., van de Giesen, N., Houser, P., Jaffé, P. R., Kollet, S., Lehner, B.,
Lettenmaier, D. P., Peters-Lidard, C., Sivapalan, M., Sheffield, J., Wade,
A., and Whitehead, P.: Hyperresolution global land surface modeling: Meeting
a grand challenge for monitoring Earth's terrestrial water, Water Resour.
Res., 47, 1–10, https://doi.org/10.1029/2010WR010090, 2011.
Wunsch, A., Liesch, T., and Broda, S.: Deep learning shows declining
groundwater levels in Germany until 2100 due to climate change, Nat.
Commun., 13, 1–13, https://doi.org/10.1038/s41467-022-28770-2, 2022.
Yang, Y., Cao, C., Pan, X., Li, X., and Zhu, X.: Downscaling Land Surface
Temperature in an Arid Area by Using Multiple Remote Sensing Indices with
Random Forest Regression, Remote Sens., 9, 789, https://doi.org/10.3390/rs9080789,
2017.
Zhang, J., Liu, K., and Wang, M.: Downscaling Groundwater Storage Data in
China to a 1-km Resolution Using Machine Learning Methods, Remote Sens., 13,
523, https://doi.org/10.3390/rs13030523, 2021.
Short summary
Hydrological models at high spatial resolution are computationally expensive. However, outputs from such models, such as the depth of the groundwater table, are often desired in high resolution. We developed a downscaling algorithm based on machine learning that allows us to increase spatial resolution of hydrological model outputs, alleviating computational burden. We successfully applied the downscaling algorithm to the climate-change-induced impacts on the groundwater table across Denmark.
Hydrological models at high spatial resolution are computationally expensive. However, outputs...
