Data-driven modelling of hydraulic-head time series: results and lessons learned from the 2022 Groundwater Time Series Modelling Challenge

<p>This paper presents the results of the 2022 Groundwater Time Series Modelling Challenge, where 15 teams from different institutes applied various data-driven models to simulate hydraulic-head time series at four monitoring wells. Three of the wells were located in Europe and one was located...

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Main Authors:	R. A. Collenteur, E. Haaf, M. Bakker, T. Liesch, A. Wunsch, J. Soonthornrangsan, J. White, N. Martin, R. Hugman, E. de Sousa, D. Vanden Berghe, X. Fan, T. J. Peterson, J. Bikše, A. Di Ciacca, X. Wang, Y. Zheng, M. Nölscher, J. Koch, R. Schneider, N. Benavides Höglund, S. Krishna Reddy Chidepudi, A. Henriot, N. Massei, A. Jardani, M. G. Rudolph, A. Rouhani, J. J. Gómez-Hernández, S. Jomaa, A. Pölz, T. Franken, M. Behbooei, J. Lin, R. Meysami
Format:	Article
Language:	English
Published:	Copernicus Publications 2024-12-01
Series:	Hydrology and Earth System Sciences
Online Access:	https://hess.copernicus.org/articles/28/5193/2024/hess-28-5193-2024.pdf
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Data-driven modelling of hydraulic-head time series: results and lessons learned from the 2022 Groundwater Time Series Modelling Challenge

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