Articles | Volume 26, issue 22
Hydrol. Earth Syst. Sci., 26, 5859–5877, 2022
Hydrol. Earth Syst. Sci., 26, 5859–5877, 2022
Research article
23 Nov 2022
Research article | 23 Nov 2022

Machine-learning-based downscaling of modelled climate change impacts on groundwater table depth

Raphael Schneider et al.

Related authors

A robust objective function for calibration of groundwater models in light of deficiencies of model structure and observations
Raphael Schneider, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci. Discuss.,,, 2020
Revised manuscript not accepted
Short summary
Application of CryoSat-2 altimetry data for river analysis and modelling
Raphael Schneider, Peter Nygaard Godiksen, Heidi Villadsen, Henrik Madsen, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 21, 751–764,,, 2017
Short summary

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
Shouchuan Zhang, Zheming Shi, Guangcai Wang, Zuochen Zhang, and Huaming Guo
Hydrol. Earth Syst. Sci., 27, 401–415,,, 2023
Short summary
Advance prediction of coastal groundwater levels with temporal convolutional and long short-term memory networks
Xiaoying Zhang, Fan Dong, Guangquan Chen, and Zhenxue Dai
Hydrol. Earth Syst. Sci., 27, 83–96,,, 2023
Short summary
Three-dimensional hydrogeological parametrization using sparse piezometric data
Dimitri Rambourg, Raphaël Di Chiara, and Philippe Ackerer
Hydrol. Earth Syst. Sci., 26, 6147–6162,,, 2022
Short summary
Frequency domain water table fluctuations reveal impacts of intense rainfall and vadose zone thickness on groundwater recharge
Luca Guillaumot, Laurent Longuevergne, Jean Marçais, Nicolas Lavenant, and Olivier Bour
Hydrol. Earth Syst. Sci., 26, 5697–5720,,, 2022
Short summary
Characterizing groundwater heat transport in a complex lowland aquifer using paleo-temperature reconstruction, satellite data, temperature–depth profiles, and numerical models
Alberto Casillas-Trasvina, Bart Rogiers, Koen Beerten, Laurent Wouters, and Kristine Walraevens
Hydrol. Earth Syst. Sci., 26, 5577–5604,,, 2022
Short summary

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,, 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,, 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,<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,, 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. 
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.