Improving the structure of a hydrological model to forecast catchment response to intense rainfall-Reference-Cited by-同舟云学术

Improving the structure of a hydrological model to forecast catchment response to intense rainfall

Published:2024-05-07 Issue: Volume: Page:
ISSN:2767-8490
Container-title:LHB
language:en
Short-container-title:LHB

Author:

Astagneau Paul C.¹²³⁴^ORCID,Bourgin François¹^ORCID,Andréassian Vazken¹^ORCID,Perrin Charles¹^ORCID

Affiliation:

1. Université Paris-Saclay, INRAE, HYCAR Research Unit, Antony, France

2. WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland

3. Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

4. Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Davos Dorf, Switzerland

Funder

French Ministry of Environment

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/27678490.2024.2341027

Reference32 articles.

1. When does a parsimonious model fail to simulate floods? Learning from the seasonality of model bias

2. Catchment response to intense rainfall: Evaluating modelling hypotheses

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

4. Challenges in modeling and predicting floods and droughts: A review

5. Coron L. Delaigue O. Thirel G. Dorchies D. Perrin C. & Michel C. (2020). airGR: Suite of GR Hydrological models for precipitation-runoff modelling. R package version 1.6.9.27. https://cran.r-project.org/web/packages/airGR/index.html

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