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Peer-reviewed

River flooding mechanisms and their changes in Europe revealed by explainable machine learning

Shijie Jiang, Emanuele Bevacqua, Jakob Zscheischler

Hydrology and earth system sciences · 2022

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Summary

Abstract. Climate change may systematically impact hydrometeorological processes and their interactions, resulting in changes in flooding mechanisms. Identifying such changes is important for flood forecasting and projection. Currently, there is a lack of observational evidence regarding trends in flooding mechanisms in Europe, which requires reliable methods to disentangle emerging patterns from the complex interactions between flood drivers. Recently, numerous studies have demonstrated the skill of machine learning (ML) for predictions in hydrology, e.g., for predicting river discharge based on its relationship with meteorological drivers. The relationship, if explained properly, may provide us with new insights into hydrological processes. Here, by using a novel explainable ML framework

Source type
Peer-reviewed study
DOI
10.5194/hess-26-6339-2022
Catalogue ID
SNmokeh4rf-3ln823
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