Articles | Volume 26, issue 9
Hydrol. Earth Syst. Sci., 26, 2405–2430, 2022
https://doi.org/10.5194/hess-26-2405-2022
Hydrol. Earth Syst. Sci., 26, 2405–2430, 2022
https://doi.org/10.5194/hess-26-2405-2022
Research article
09 May 2022
Research article | 09 May 2022

Karst spring discharge modeling based on deep learning using spatially distributed input data

Andreas Wunsch et al.

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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.