Data-driven modeling of hydraulic head time series: results and lessons learned from the 2022 groundwater modeling challenge
Preprint, 2024
The models were evaluated on their performance to simulate the heads in the calibration period and the validation period. Different metrics were used to assess performance including metrics for average relative fit, average absolute fit, fit of extreme (high or low) heads, and the coverage of the uncertainty interval. For all wells, reasonable performance was obtained by at least one team from each of the three groups. However, the performance was not consistent across submissions within each groups, which implies that application of each method to individual sites requires significant effort and experience. Especially estimates of the uncertainty interval varied widely between teams, although some teams submitted confidence intervals rather than prediction intervals. There was not one team, let alone one method, that performed best for all wells and all performance metrics. Lumped-parameter models generally performed as well as artificial intelligence models, except for the well in the USA, where the lumped-parameter models did not use (or use to the full benefit) the provided river stage data, which was crucial for obtaining a good model. In conclusion, the challenge was a successful initiative to compare different models and learn from each other. Future challenges are needed to investigate, e.g., the performance of models in more variable climatic settings, to simulate head series with significant gaps, or to estimate the effect of drought periods.
Author
Raoul Collenteur
Eawag - Swiss Federal Institute of Aquatic Science and Technology
Ezra Haaf
Chalmers, Architecture and Civil Engineering, Geology and Geotechnics
Mark Bakker
Delft University of Technology
Tanja Liesch
Karlsruhe Institute of Technology (KIT)
A. Wunsch
Subject Categories
Other Computer and Information Science
Water Engineering
Geology
Oceanography, Hydrology, Water Resources
Driving Forces
Sustainable development
DOI
10.5194/hess-2024-111