Articles | Volume 27, issue 1
https://doi.org/10.5194/hess-27-83-2023
© Author(s) 2023. 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-27-83-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jan 2023
Research article |
| 02 Jan 2023
| 02 Jan 2023
Advance prediction of coastal groundwater levels with temporal convolutional and long short-term memory networks
Xiaoying Zhang
Institute of Intelligent Simulation and Early Warning for
Subsurface Environment, Jilin University, Changchun, China
College of Construction Engineering, Jilin University, Changchun,
China
Fan Dong
Institute of Intelligent Simulation and Early Warning for
Subsurface Environment, Jilin University, Changchun, China
College of Construction Engineering, Jilin University, Changchun,
China
Guangquan Chen
Key Laboratory of Marine Sedimentology and Environmental Geology,
First Institute of Oceanography, State Oceanic Administration, Qingdao, China
Zhenxue Dai
CORRESPONDING AUTHOR
Institute of Intelligent Simulation and Early Warning for
Subsurface Environment, Jilin University, Changchun, China
College of Construction Engineering, Jilin University, Changchun,
China
Related authors
Guoxiao Wei, Xiaoying Zhang, Ming Ye, Ning Yue, and Fei Kan
Hydrol. Earth Syst. Sci., 23, 2877–2895, https://doi.org/10.5194/hess-23-2877-2019, https://doi.org/10.5194/hess-23-2877-2019, 2019
Short summary
Short summary
Accurately evaluating evapotranspiration (ET) is a critical challenge in improving hydrological process modeling. Here we evaluated four ET models (PM, SW, PT–FC, and AA) under the Bayesian framework. Our results reveal that the SW model has the best performance. This is in part because the SW model captures the main physical mechanism in ET; the other part is that the key parameters, such as the extinction factor, could be well constrained with observation data.
Huijun Li, Lin Zhu, Gaoxuan Guo, Yan Zhang, Zhenxue Dai, Xiaojuan Li, Linzhen Chang, and Pietro Teatini
Nat. Hazards Earth Syst. Sci., 21, 823–835, https://doi.org/10.5194/nhess-21-823-2021, https://doi.org/10.5194/nhess-21-823-2021, 2021
Short summary
Short summary
We propose a method that integrates fuzzy set theory and a weighted Bayesian model to evaluate the hazard probability of land subsidence based on Interferometric Synthetic Aperture Radar technology. The proposed model can represent the uncertainty and ambiguity in the evaluation process, and results can be compared to traditional qualitative methods.
Guoxiao Wei, Xiaoying Zhang, Ming Ye, Ning Yue, and Fei Kan
Hydrol. Earth Syst. Sci., 23, 2877–2895, https://doi.org/10.5194/hess-23-2877-2019, https://doi.org/10.5194/hess-23-2877-2019, 2019
Short summary
Short summary
Accurately evaluating evapotranspiration (ET) is a critical challenge in improving hydrological process modeling. Here we evaluated four ET models (PM, SW, PT–FC, and AA) under the Bayesian framework. Our results reveal that the SW model has the best performance. This is in part because the SW model captures the main physical mechanism in ET; the other part is that the key parameters, such as the extinction factor, could be well constrained with observation data.
Related subject area
Subject: Groundwater hydrology | Techniques and Approaches: Modelling approaches
The origin of hydrological responses following earthquakes in a confined aquifer: insight from water level, flow rate, and temperature observations
Three-dimensional hydrogeological parametrization using sparse piezometric data
Machine-learning-based downscaling of modelled climate change impacts on groundwater table depth
Frequency domain water table fluctuations reveal impacts of intense rainfall and vadose zone thickness on groundwater recharge
Characterizing groundwater heat transport in a complex lowland aquifer using paleo-temperature reconstruction, satellite data, temperature–depth profiles, and numerical models
Karst spring recession and classification: efficient, automated methods for both fast- and slow-flow components
Exploring river–aquifer interactions and hydrological system response using baseflow separation, impulse response modeling, and time series analysis in three temperate lowland catchments
Experimental study of non-Darcy flow characteristics in permeable stones
Karst spring discharge modeling based on deep learning using spatially distributed input data
HESS Opinions: Chemical transport modeling in subsurface hydrological systems – space, time, and the “holy grail” of “upscaling”
Spatiotemporal variations in water sources and mixing spots in a riparian zone
Delineation of discrete conduit networks in karst aquifers via combined analysis of tracer tests and geophysical data
Reactive transport modeling for supporting climate resilience at groundwater contamination sites
Improved understanding of regional groundwater drought development through time series modelling: the 2018–2019 drought in the Netherlands
Simulation of long-term spatiotemporal variations in regional-scale groundwater recharge: contributions of a water budget approach in cold and humid climates
Feedback mechanisms between precipitation and dissolution reactions across randomly heterogeneous conductivity fields
Taking theory to the field: streamflow generation mechanisms in an intermittent Mediterranean catchment
Coupling saturated and unsaturated flow: comparing the iterative and the non-iterative approach
Time lags of nitrate, chloride, and tritium in streams assessed by dynamic groundwater flow tracking in a lowland landscape
Using Long Short-Term Memory networks to connect water table depth anomalies to precipitation anomalies over Europe
Estimation of groundwater recharge from groundwater levels using nonlinear transfer function noise models and comparison to lysimeter data
Early hypogenic carbonic acid speleogenesis in unconfined limestone aquifers by upwelling deep-seated waters with high CO2 concentration: a modelling approach
Impacts of climate change on groundwater flooding and ecohydrology in lowland karst
How daily groundwater table drawdown affects the diel rhythm of hyporheic exchange
Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exogenous input (NARX)
Groundwater and baseflow drought responses to synthetic recharge stress tests
Determination of vadose zone and saturated zone nitrate lag times using long-term groundwater monitoring data and statistical machine learning
Modelling the hydrological interactions between a fissured granite aquifer and a valley mire in the Massif Central, France
A new criterion for determining the representative elementary volume of translucent porous media and inner contaminant
Physics-inspired integrated space–time artificial neural networks for regional groundwater flow modeling
Hydraulic and geochemical impact of occasional saltwater intrusions through a submarine spring in a karst and thermal aquifer (Balaruc peninsula near Montpellier, France)
Calibration of a lumped karst system model and application to the Qachqouch karst spring (Lebanon) under climate change conditions
Sensitivity of hydrologic and geologic parameters on recharge processes in a highly heterogeneous, semi-confined aquifer system
Basin-scale multi-objective simulation-optimization modeling for conjunctive use of surface water and groundwater in northwest China
Assessing the response of groundwater quantity and travel time distribution to 1.5, 2, and 3 °C global warming in a mesoscale central German basin
Groundwater mean residence times of a subtropical barrier sand island
On the conceptual complexity of non-point source management: impact of spatial variability
The millennium-old hydrogeology textbook The Extraction of Hidden Waters by the Persian mathematician and engineer Abubakr Mohammad Karaji (953 CE–1029 CE)
Modeling groundwater responses to climate change in the Prairie Pothole Region
A multi-environmental tracer study to determine groundwater residence times and recharge in a structurally complex multi-aquifer system
A three-dimensional palaeohydrogeological reconstruction of the groundwater salinity distribution in the Nile Delta Aquifer
Modelling of the shallow water table at high spatial resolution using random forests
An extended trajectory-mechanics approach for calculating the path of a pressure transient: travel-time tomography
Global sensitivity analysis and adaptive stochastic sampling of a subsurface-flow model using active subspaces
A comprehensive quasi-3-D model for regional-scale unsaturated–saturated water flow
Decomposition technique for contributions to groundwater heads from inside and outside of an arbitrary boundary: application to Guantao County, North China Plain
High-resolution paleovalley classification from airborne electromagnetic imaging and deep neural network training using digital elevation model data
A partially coupled hydro-mechanical analysis of the Bengal Aquifer System under hydrological loading
Reactive transport with wellbore storages in a single-well push–pull test
Dynamics of wormhole formation in fractured limestones
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Raphael Schneider, Julian Koch, Lars Troldborg, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci., 26, 5859–5877, https://doi.org/10.5194/hess-26-5859-2022, https://doi.org/10.5194/hess-26-5859-2022, 2022
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Stephen R. Maples, Laura Foglia, Graham E. Fogg, and Reed M. Maxwell
Hydrol. Earth Syst. Sci., 24, 2437–2456, https://doi.org/10.5194/hess-24-2437-2020, https://doi.org/10.5194/hess-24-2437-2020, 2020
Short summary
Short summary
In this study, we use a combination of local- and global-sensitivity analyses to evaluate the relative importance of (1) the configuration of subsurface alluvial geology and (2) the hydraulic properties of geologic facies on recharge processes. Results show that there is a large variation of recharge rates possible in a typical alluvial aquifer system and that the configuration proportion of sand and gravel deposits in the subsurface have a large impact on recharge rates.
Jian Song, Yun Yang, Xiaomin Sun, Jin Lin, Ming Wu, Jianfeng Wu, and Jichun Wu
Hydrol. Earth Syst. Sci., 24, 2323–2341, https://doi.org/10.5194/hess-24-2323-2020, https://doi.org/10.5194/hess-24-2323-2020, 2020
Short summary
Short summary
We proposed a novel many-objective simulation-optimization framework for conjunctive use of surface water and groundwater in Yanqi Basin, northwest China. The management model involving socioeconomic and environmental objectives was constructed to explore optimal water-use schemes. Three runoff scenarios were then specified to quantify the effect of runoff reduction related to climate change on water management. Results provide Pareto-optimal solutions for basin-scale water management.
Miao Jing, Rohini Kumar, Falk Heße, Stephan Thober, Oldrich Rakovec, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 24, 1511–1526, https://doi.org/10.5194/hess-24-1511-2020, https://doi.org/10.5194/hess-24-1511-2020, 2020
Short summary
Short summary
This study investigates the response of regional groundwater system to the climate change under three global warming levels (1.5, 2, and 3 °C) in a central German basin. A comprehensive uncertainty analysis is also presented. This study indicates that the variability of responses increases with the amount of global warming, which might affect the cost of managing the groundwater system.
Harald Hofmann, Dean Newborn, Ian Cartwright, Dioni I. Cendón, and Matthias Raiber
Hydrol. Earth Syst. Sci., 24, 1293–1318, https://doi.org/10.5194/hess-24-1293-2020, https://doi.org/10.5194/hess-24-1293-2020, 2020
Short summary
Short summary
Fresh groundwater (GW) on barrier islands is affected by GW use and precipitation variability. Mean residence times (MRTs) of GW on a sand barrier island were determined. They ranged from 37 years to more than 150 years for tritium and had a much larger range (modern to 5000 years) for carbon-14. Perched aquifer systems in the unsaturated zone and peat formations around wetlands are the most likely cause of longer MRTs, as they have a significant impact on regional recharge and flow diversion.
Christopher Vincent Henri, Thomas Harter, and Efstathios Diamantopoulos
Hydrol. Earth Syst. Sci., 24, 1189–1209, https://doi.org/10.5194/hess-24-1189-2020, https://doi.org/10.5194/hess-24-1189-2020, 2020
Short summary
Short summary
Non-point source contaminations of aquifers are complex to model, predict and manage. This study uses numerical and stochastic methods to address the importance of key sources of spatial variability. We show that heterogeneity in recharge and contaminant loading does not significantly impact management metrics and could be simplified. Also, homogenizing physical properties has more impact on predictions, but can provide useful information on concentration statistics in a regional analysis.
Behzad Ataie-Ashtiani and Craig T. Simmons
Hydrol. Earth Syst. Sci., 24, 761–769, https://doi.org/10.5194/hess-24-761-2020, https://doi.org/10.5194/hess-24-761-2020, 2020
Short summary
Short summary
We revisit and shed light on the textbook The Extraction of Hidden Waters by the Persian mathematician and engineer Abubakr Mohammad Karaji. Ground-breaking ideas and descriptions of hydrological and hydrogeological perceptions such as components of the hydrological cycle, groundwater quality and driving factors for groundwater flow were presented in the book. We speculate that Karaji's book is the first of its kind to provide a construction and maintenance manual for an engineering project.
Zhe Zhang, Yanping Li, Michael Barlage, Fei Chen, Gonzalo Miguez-Macho, Andrew Ireson, and Zhenhua Li
Hydrol. Earth Syst. Sci., 24, 655–672, https://doi.org/10.5194/hess-24-655-2020, https://doi.org/10.5194/hess-24-655-2020, 2020
Short summary
Short summary
The groundwater regime in cold regions is strongly impacted by the soil freeze–thaw processes and semiarid climatic conditions. In this paper, we incorporate groundwater dynamics in the Noah-MP land surface model to simulate the water exchange between the unsaturated soil zone and an unconfined aquifer in the Prairie Pothole Region. The water table dynamics are reasonably simulated. The water budget of groundwater aquifer under current and future climate are also investigated.
Cornelia Wilske, Axel Suckow, Ulf Mallast, Christiane Meier, Silke Merchel, Broder Merkel, Stefan Pavetich, Tino Rödiger, Georg Rugel, Agnes Sachse, Stephan M. Weise, and Christian Siebert
Hydrol. Earth Syst. Sci., 24, 249–267, https://doi.org/10.5194/hess-24-249-2020, https://doi.org/10.5194/hess-24-249-2020, 2020
Short summary
Short summary
Despite feeding several million people, the flow system and inter-aquifer communication within one of the major aquifer systems in Israel and the West Bank is still poorly understood. Applying a combination of inorganic elements, anthropogenic organic trace substances and classical environmental age-dating tracers like 3H, CFCs, SF6 and 36Cl / Cl, groundwater flow patterns, mixing end-members, transport times and recharge estimates have been obtained despite very limited data.
Joeri van Engelen, Jarno Verkaik, Jude King, Eman R. Nofal, Marc F. P. Bierkens, and Gualbert H. P. Oude Essink
Hydrol. Earth Syst. Sci., 23, 5175–5198, https://doi.org/10.5194/hess-23-5175-2019, https://doi.org/10.5194/hess-23-5175-2019, 2019
Short summary
Short summary
The Nile Delta is an important agricultural area with a fast-growing population, relying increasingly on groundwater. However, saline groundwater extends far land-inward, rendering groundwater close to the coastal zone useless for consumption or agriculture. It normally is assumed that this is caused by mixing due to velocity differences, but here we show that it might also be caused by the coastline being located more land-inward 8000 years ago.
Julian Koch, Helen Berger, Hans Jørgen Henriksen, and Torben Obel Sonnenborg
Hydrol. Earth Syst. Sci., 23, 4603–4619, https://doi.org/10.5194/hess-23-4603-2019, https://doi.org/10.5194/hess-23-4603-2019, 2019
Short summary
Short summary
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.
Donald W. Vasco, Joseph Doetsch, and Ralf Brauchler
Hydrol. Earth Syst. Sci., 23, 4541–4560, https://doi.org/10.5194/hess-23-4541-2019, https://doi.org/10.5194/hess-23-4541-2019, 2019
Short summary
Short summary
This paper presents the application of a new approach for calculating the path of a pressure transient in a heterogeneous porous medium containing a slightly compressible fluid. Unlike previous asymptotic approaches, the expressions for the path and travel time are valid in the presence of rapid variations in material properties. The technique is applied to both synthetic transient pressure variations from a test example and actual field data from a field experiment in Widen, Switzerland.
Daniel Erdal and Olaf A. Cirpka
Hydrol. Earth Syst. Sci., 23, 3787–3805, https://doi.org/10.5194/hess-23-3787-2019, https://doi.org/10.5194/hess-23-3787-2019, 2019
Short summary
Short summary
Assessing how sensitive uncertain model parameters are to observed data can be done by analyzing an ensemble of model simulations in which the parameters are varied. In subsurface modeling, this involves running heavy models. To reduce time wasted simulating models which show poor behavior, we use a fast polynomial model based on a simple parameter decomposition to approximate the behavior prior to
full-model simulation. This largely reduces the cost for the global sensitivity analysis.
Wei Mao, Yan Zhu, Heng Dai, Ming Ye, Jinzhong Yang, and Jingwei Wu
Hydrol. Earth Syst. Sci., 23, 3481–3502, https://doi.org/10.5194/hess-23-3481-2019, https://doi.org/10.5194/hess-23-3481-2019, 2019
Short summary
Short summary
A new quasi-3-D model was developed by coupling a soil water balance model with MODFLOW iteratively for regional-scale water flow modeling. The model was tested to be effective and efficient with well-maintained mass balance. A modeling framework was developed to organize the coupling scheme and to handle the pre- and post-processing information. The model is then used to evaluate groundwater recharge in a real-world application, which shows the model practicability in regional-scale problems.
Ning Li, Wolfgang Kinzelbach, Haitao Li, Wenpeng Li, and Fei Chen
Hydrol. Earth Syst. Sci., 23, 2823–2840, https://doi.org/10.5194/hess-23-2823-2019, https://doi.org/10.5194/hess-23-2823-2019, 2019
Short summary
Short summary
Groundwater heads within an administrative unit are influenced not only by inside drivers, but also by outside drivers. To assess the efficiency of groundwater management of the administrative unit, we propose the decomposition of groundwater heads within the unit into inside and outside contributions by using three numerical groundwater models. The method is successfully demonstrated using Guantao County, China.
Zhenjiao Jiang, Dirk Mallants, Luk Peeters, Lei Gao, Camilla Soerensen, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 23, 2561–2580, https://doi.org/10.5194/hess-23-2561-2019, https://doi.org/10.5194/hess-23-2561-2019, 2019
Short summary
Short summary
Paleovalleys often form productive aquifers in the semiarid and arid areas. A methodology based on deep learning is introduced to automatically generate high-resolution 3-D paleovalley maps from low-resolution electrical conductivity data derived from airborne geophysical surveys. It is validated by borehole logs and the surface valley indices that the proposed method in this study provides an effective tool for regional-scale paleovalley mapping and groundwater exploration.
Nicholas D. Woodman, William G. Burgess, Kazi Matin Ahmed, and Anwar Zahid
Hydrol. Earth Syst. Sci., 23, 2461–2479, https://doi.org/10.5194/hess-23-2461-2019, https://doi.org/10.5194/hess-23-2461-2019, 2019
Short summary
Short summary
We show that a conventional hydraulic understanding of groundwater level fluctuation is too simplistic for the extensive floodplains of Bangladesh and West Bengal. This is crucial because 150 million people of the region rely on groundwater for drinking and irrigation. We describe a more complex situation: the coupled hydro-mechanical action of surface water coming and going as the seasons change. Our model results will assist sustainable management of groundwater resources across the region.
Quanrong Wang and Hongbin Zhan
Hydrol. Earth Syst. Sci., 23, 2207–2223, https://doi.org/10.5194/hess-23-2207-2019, https://doi.org/10.5194/hess-23-2207-2019, 2019
Short summary
Short summary
New multi-species reactive models of the four-phase SWPP test were presented considering the wellbore storages for both groundwater flow and solute transport and a finite-aquifer hydraulic diffusivity, which were ignored in previous studies. The models of the wellbore storage for solute transport were proposed based on the mass balance, and the sensitivity analysis and uniqueness analysis were employed to investigate the assumptions used in previous studies on the parameter estimation.
Wolfgang Dreybrodt and Franci Gabrovšek
Hydrol. Earth Syst. Sci., 23, 1995–2014, https://doi.org/10.5194/hess-23-1995-2019, https://doi.org/10.5194/hess-23-1995-2019, 2019
Short summary
Short summary
Numerical models of wormhole formation in fractured porous media provide basic insights on the evolution of complex conduit systems in karst aquifers. In this work we use a time-propagating reactive flow model to explore the evolution of wormholes in a 2-D grid of fractures. We demonstrate physically meaningful mechanisms leading to the formation of individual wormholes and the competition between a set of evolving wormholes.
Cited articles
Abdalla, O. A. and Al-Rawahi, A. S.: Groundwater recharge dams in arid areas as tools for aquifer replenishment and mitigating seawater intrusion: example of AlKhod, Oman, Environ. Earth Sci., 69, 1951–1962, 2013.
Afaq, S. and Rao, S.: Significance of epochs on training a neural network,
Int. J. Scient. Technol. Res., 9, 485–488, 2020.
Baena-Ruiz, L., Pulido-Velazquez, D., Collados-Lara, A.-J., Renau-Pruñonosa, A., and Morell, I.: Global assessment of seawater intrusion problems (status and vulnerability), Water Resour. Manage., 32,
2681–2700, 2018.
Bai, S., Kolter, J. Z., and Koltun, V.: An empirical evaluation of generic
convolutional and recurrent networks for sequence modeling, arXiv preprint
arXiv:1803.01271, https://doi.org/10.48550/arXiv.1803.01271, 2018.
Barlow, P. M. and Reichard, E. G.: Saltwater intrusion in coastal regions of
North America, Hydrogeol. J., 18, 247–260, 2010.
Batelaan, O., De Smedt, F., and Triest, L.: Regional groundwater discharge:
phreatophyte mapping, groundwater modelling and impact analysis of land-use
change, J. Hydrol., 275, 86–108, 2003.
Bengio, Y., Simard, P., and Frasconi, P.: Learning long-term dependencies
with gradient descent is difficult, IEEE T. Neural Netw., 5, 157–166, 1994.
Borovykh, A., Bohte, S., and Oosterlee, C. W.: Dilated convolutional neural
networks for time series forecasting, J. Comput. Financ., 22, 73–101, https://doi.org/10.21314/JCF.2019.358, 2018.
Cannas, B., Fanni, A., See, L., and Sias, G.: Data preprocessing for river
flow forecasting using neural networks: wavelet transforms and data
partitioning, Phys. Chem. Earth, 31, 1164–1171, 2006.
Cao, Y., Ding, Y., Jia, M., and Tian, R.: A novel temporal convolutional
network with residual self-attention mechanism for remaining useful life
prediction of rolling bearings, Reliab. Eng. Syst. Safe., 215, 107813, https://doi.org/10.1016/j.ress.2021.107813, 2021.
Chen, Y., Kang, Y., Chen, Y., and Wang, Z.: Probabilistic forecasting with
temporal convolutional neural network, Neurocomputing, 399, 491–501, 2020.
Coulibaly, P., Anctil, F., Aravena, R., and Bobée, B.: Artificial neural
network modeling of water table depth fluctuations, Water Resour. Res., 37,
885–896, 2001.
Dai, Z. and Samper, J.: Inverse modeling of water flow and multicomponent
reactive transport in coastal aquifer systems, J. Hydrol., 327, 447–461, 2006.
Dai, Z., Xu, L., Xiao, T., McPherson, B., Zhang, X., Zheng, L., Dong, S.,
Yang, Z., Soltanian, M. R., and Yang, C.: Reactive chemical transport simulations of geologic carbon sequestration: Methods and applications,
Earth-Sci. Rev., 208, 103265, https://doi.org/10.1016/j.earscirev.2020.103265, 2020.
Dubey, A. K., Kumar, A., García-Díaz, V., Sharma, A. K., and Kanhaiya, K.: Study and analysis of SARIMA and LSTM in forecasting time series data, Sustain. Energ. Technol. Assess., 47, 101474, https://doi.org/10.1016/j.seta.2021.101474, 2021.
Ergen, T. and Kozat, S. S.: Efficient online learning algorithms based on
LSTM neural networks, IEEE T. Neural Netw. Learn. Syst., 29, 3772–3783, 2017.
Feng, N., Geng, X., and Qin, L.: Study on MRI medical image segmentation
technology based on CNN-CRF model, IEEE Access, 8, 60505–60514, 2020.
Fischer, T. and Krauss, C.: Deep learning with long short-term memory networks for financial market predictions, Eur. J. Oper. Res., 270, 654–669,
2018.
Gan, Z., Li, C., Zhou, J., and Tang, G.: Temporal convolutional networks
interval prediction model for wind speed forecasting, Elect. Power Syst. Res., 191, 106865, https://doi.org/10.1016/j.epsr.2020.106865, 2021.
Garza-Díaz, L. E., DeVincentis, A. J., Sandoval-Solis, S., Azizipour, M., Ortiz-Partida, J. P., Mahlknecht, J., Cahn, M., Medellín-Azuara, J., Zaccaria, D., and Kisekka, I.: Land-use optimization for sustainable agricultural water management in Pajaro Valley, California, J. Water Resour.
Pl. Manage.-ASCE, 145, 05019018, https://doi.org/10.1061/(ASCE)WR.1943-5452.0001117, 2019.
Gorgij, A. D., Kisi, O., and Moghaddam, A. A.: Groundwater budget forecasting, using hybrid wavelet-ANN-GP modelling: a case study of Azarshahr Plain, East Azerbaijan, Iran, Hydrol. Res., 48, 455–467, 2017.
Han, D., Kohfahl, C., Song, X., Xiao, G., and Yang, J.: Geochemical and
isotopic evidence for palaeo-seawater intrusion into the south coast aquifer of Laizhou Bay, China, Appl. Geochem., 26, 863–883, 2011.
Han, D., Song, X., Currell, M. J., Yang, J., and Xiao, G.: Chemical and
isotopic constraints on evolution of groundwater salinization in the coastal
plain aquifer of Laizhou Bay, China, J. Hydrol., 508, 12–27, 2014.
He, K., Zhang, X., Ren, S., and Sun, J.: Deep residual learning for image
recognition, Proc. IEEE, 770–778, 2016.
Huang, F.-K., Chuang, M.-H., Wang, G. S., and Yeh, H.-D.: Tide-induced
groundwater level fluctuation in a U-shaped coastal aquifer, J. Hydrol.,
530, 291–305, 2015.
Jiang, Y., Zhao, M., Zhao, W., Qin, H., Qi, H., Wang, K., and Wang, C.:
Prediction of sea temperature using temporal convolutional network and LSTM-GRU network, Complex Eng. Syst., 1, 9, https://doi.org/10.20517/ces.2021.03, 2021.
Ketabchi, H. and Ataie-Ashtiani, B.: Evolutionary algorithms for the optimal
management of coastal groundwater: A comparative study toward future
challenges, J. Hydrol., 520, 193–213, 2015.
Kingma, D. P. and Ba, J: Adam: A method for stochastic optimization, in: International Conference on Learning Representations (ICLR), ICLR 2015, 7–9 May 2015, San Diego, CA, USA, https://doi.org/10.48550/arXiv.1412.6980, 2015.
Kratzert, F., Herrnegger, M., Klotz, D., Hochreiter, S., and Klambauer, G.:
NeuralHydrology–interpreting LSTMs in hydrology, in: Explainable AI:
Interpreting, explaining and visualizing deep learning, Springer, 347–362,
https://doi.org/10.1007/978-3-030-28954-6_19, 2019.
Kreyenberg, P. J., Bauser, H. H., and Roth, K.: Velocity field estimation on
density-driven solute transport with a convolutional neural network, Water
Resour. Res., 55, 7275–7293, 2019.
Lara-Benítez, P., Carranza-García, M., Luna-Romera, J. M., and Riquelme, J. C.: Temporal convolutional networks applied to energy-related
time series forecasting, Appl. Sci., 10, 2322, https://doi.org/10.3390/app10072322, 2020.
Lea, C., Vidal, R., Reiter, A., and Hager, G. D.: Temporal convolutional networks: A unified approach to action segmentation, in: Computer Vision – ECCV 2016 Workshops, Lecture Notes in Computer Science, edited by: Hua, G. and Jégou, H., Springer, Cham, https://doi.org/10.1007/978-3-319-49409-8_7, 2016.
Lea, C., Flynn, M. D., Vidal, R., Reiter, A., and Hager, G. D.: Temporal Convolutional Networks for Action Segmentation and Detection, in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 21–26 July 2017, Honolulu, HI, USA, 1003–1012, https://doi.org/10.1109/CVPR.2017.113,
2017.
LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P.: Gradient-based learning
applied to document recognition, Proc. IEEE, 86, 2278–2324, 1998.
Li, H., Jiao, J. J., Luk, M., and Cheung, K.: Tide-induced groundwater level
fluctuation in coastal aquifers bounded by L-shaped coastlines, Water Resour. Res., 38, 6-1–6-8, 2002.
Long, J., Shelhamer, E., and Darrell, T.: Fully convolutional networks for semantic segmentation, in: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7–12 June 2015, Boston, MA, USA, 3431–3440, https://doi.org/10.1109/CVPR.2015.7298965, 2015.
Lu, C., Werner, A. D., and Simmons, C. T.: Threats to coastal aquifers, Nat. Clim. Change, 3, 605–605, 2013.
Lu, C., Cao, H., Ma, J., Shi, W., Rathore, S. S., Wu, J., and Luo, J.: A
proof-of-concept study of using a less permeable slice along the shoreline to increase fresh groundwater storage of oceanic islands: Analytical and experimental validation, Water Resour. Res., 55, 6450–6463, 2019.
Maier, H. R. and Dandy, G. C.: Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and
applications, Environ. Model. Softw., 15, 101–124, 2000.
Mehr, A. D. and Nourani, V.: A Pareto-optimal moving average-multigene genetic programming model for rainfall-runoff modelling, Environ. Model.
Softw., 92, 239–251, 2017.
Mei, Y., Tan, G., and Liu, Z.: An improved brain-inspired emotional learning
algorithm for fast classification, Algorithms, 10, 70, https://doi.org/10.3390/a10020070, 2017.
Nair, V. and Hinton, G. E.: Rectified linear units improve restricted boltzmann machines, in: Proceedings of the 27th International Conference on Machine Learning (ICML-10), 21–24 June 2010, Haifa, Israel, 807–814,
https://doi.org/10.5555/3104322.3104425, 2010.
Park, Y., Lee, J.-Y., Kim, J.-H., and Song, S.-H.: National scale evaluation
of groundwater chemistry in Korea coastal aquifers: evidences of seawater
intrusion, Environ. Earth Sci., 66, 707–718, 2012.
Pascanu, R., Mikolov, T., and Bengio, Y.: On the difficulty of training recurrent neural networks, in: International conference on machine learning, in: Proceedings of the 30th International Conference on Machine Learning (PMLR), 16–21 June 2013, Atlanta, GA, USA, 1310–1318, https://doi.org/10.48550/arXiv.1211.5063, 2013.
Pratheepa, V., Ramesh, S., Sukumaran, N., and Murugesan, A.: Identification
of the sources for groundwater salinization in the coastal aquifers of
Southern Tamil Nadu, India, Environ. Earth Sci., 74, 2819–2829, 2015.
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., and
Carvalhais, N.: Deep learning and process understanding for data-driven
Earth system science, Nature, 566, 195–204, 2019.
Rumelhart, D. E., Hinton, G. E., and Williams, R. J.: Learning representations by back-propagating errors, Nature, 323, 533–536, 1986.
Sahoo, S., Russo, T., Elliott, J., and Foster, I.: Machine learning algorithms for modeling groundwater level changes in agricultural regions of
the US, Water Resour. Res., 53, 3878–3895, 2017.
Salimans, T. and Kingma, D. P.: Weight normalization: A simple reparameterization to accelerate training of deep neural networks, Adv.
Neural Inform. Process. Syst., 29, 901–909, 2016.
Senthil Kumar, A., Sudheer, K., Jain, S., and Agarwal, P.: Rainfall-runoff
modelling using artificial neural networks: comparison of network types, Hydrol. Process., 19, 1277–1291, 2005.
Seo, Y., Kim, S., Kisi, O., and Singh, V. P.: Daily water level forecasting
using wavelet decomposition and artificial intelligence techniques, J.
Hydrol., 520, 224–243, 2015.
Solgi, R., Loáiciga, H. A., and Kram, M.: Long short-term memory neural
network (LSTM-NN) for aquifer level time series forecasting using in-situ
piezometric observations, J. Hydrol., 601, 126800, https://doi.org/10.1016/j.jhydrol.2021.126800, 2021.
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., and Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting, J. Mach. Learn. Res., 15, 1929–1958, 2014.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, 2001.
Torres, J. F., Troncoso, A., Koprinska, I., Wang, Z., and Martínez-Álvarez, F.: Deep learning for big data time series forecasting applied to solar power, in: Proceedings of the international joint conference SOCO'18-CISIS'18-ICEUTE'18, Springer International Publishing, Cham, 123–133, https://doi.org/10.1007/978-3-319-94120-2_12, 2018.
Wan, R., Mei, S., Wang, J., Liu, M., and Yang, F.: Multivariate temporal
convolutional network: A deep neural networks approach for multivariate time
series forecasting, Electronics, 8, 876, https://doi.org/10.3390/electronics8080876, 2019.
Wunsch, A., Liesch, T., and Broda, S.: Groundwater level forecasting with artificial neural networks: a comparison of long short-term memory (LSTM), convolutional neural networks (CNNs), and non-linear autoregressive networks with exogenous input (NARX), Hydrol. Earth Syst. Sci., 25, 1671–1687, https://doi.org/10.5194/hess-25-1671-2021, 2021.
Xu, Z. and Hu, B. X.: Development of a discrete-continuum VDFST-CFP numerical model for simulating seawater intrusion to a coastal karst aquifer with a conduit system, Water Resour. Res., 53, 688–711, 2017.
Xue, Y., Wu, J., Ye, S., and Zhang, Y.: Hydrogeological and hydrogeochemical
studies for salt water intrusion on the south coast of Laizhou Bay, China,
Groundwater, 38, 38–45, 2000.
Yan, J., Mu, L., Wang, L., Ranjan, R., and Zomaya, A. Y.: Temporal convolutional networks for the advance prediction of ENSO, Sci. Rep., 10,
1–15, 2020.
Zeng, X., Wu, J., Wang, D., and Zhu, X.: Assessing the pollution risk of a
groundwater source field at western Laizhou Bay under seawater intrusion,
Environ. Res., 148, 586–594, 2016.
Zhan, C., Dai, Z., Soltanian, M. R., and Zhang, X.: Stage-wise stochastic
deep learning inversion framework for subsurface sedimentary structure
identification, Geophys. Res. Lett., 49, e2021GL095823, https://doi.org/10.1029/2021GL095823, 2022.
Zhang, D., Lin, J., Peng, Q., Wang, D., Yang, T., Sorooshian, S., Liu, X.,
and Zhuang, J.: Modeling and simulating of reservoir operation using the
artificial neural network, support vector regression, deep learning algorithm, J. Hydrol., 565, 720–736, 2018.
Zhang, J., Zhu, Y., Zhang, X., Ye, M., and Yang, J.: Developing a Long
Short-Term Memory (LSTM) based model for predicting water table depth in
agricultural areas, J. Hydrol., 561, 918–929, 2018.
Zhang, J., Zhang, X., Niu, J., Hu, B. X., Soltanian, M. R., Qiu, H., and
Yang, L.: Prediction of groundwater level in seashore reclaimed land using
wavelet and artificial neural network-based hybrid model, J. Hydrol., 577,
123948, https://doi.org/10.1016/j.jhydrol.2019.123948, 2019.
Zhang, X., Miao, J., Hu, B. X., Liu, H., Zhang, H., and Ma, Z.: Hydrogeochemical characterization and groundwater quality assessment in
intruded coastal brine aquifers (Laizhou Bay, China), Environ. Sci. Pollut.
Res., 24, 21073–21090, 2017.
Zhang, X., Dong, F., Dai, H., Hu, B. X., Qin, G., Li, D., Lv, X., Dai, Z.,
and Soltanian, M. R.: Influence of lunar semidiurnal tides on groundwater
dynamics in estuarine aquifers, Hydrogeol. J., 28, 1419–1429, 2020.
Short summary
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.
In a data-driven framework, groundwater levels can generally only be calculated 1 time step...
