Articles | Volume 24, issue 4
https://doi.org/10.5194/hess-24-2017-2020
https://doi.org/10.5194/hess-24-2017-2020
Research article
 | 
23 Apr 2020
Research article |  | 23 Apr 2020

A crash-testing framework for predictive uncertainty assessment when forecasting high flows in an extrapolation context

Lionel Berthet, François Bourgin, Charles Perrin, Julie Viatgé, Renaud Marty, and Olivier Piotte

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Latest update: 28 Mar 2024
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Short summary
An increasing number of flood forecasting services assess and communicate the uncertainty associated with their forecasts. We present a crash-testing framework that evaluates the quality of hydrological forecasts in an extrapolation context. Overall, the results highlight the challenge of uncertainty quantification when forecasting high flows. They show a significant drop in reliability when forecasting high flows and considerable variability among catchments and across lead times.