Multi-level factorial analysis for ensemble data-driven hydrological prediction-Reference-Cited by-同舟云学术

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Multi-level factorial analysis for ensemble data-driven hydrological prediction

Published:2021-07 Issue: Volume:153 Page:103948
ISSN:0309-1708
Container-title:Advances in Water Resources
language:en
Short-container-title:Advances in Water Resources

Author:

Wang Feng,Huang Guohe,Cheng Guanhui,Li Yongping

Funder

Natural Sciences and Engineering Research Council of Canada

Beijing Normal University

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference52 articles.

1. Topographic, pedologic and climatic interactions influencing streamflow generation at multiple catchment scales;Ali;Hydrol. Process.,2012

2. Sensitivity analysis and multi-response, multi-criteria evaluation of a physically based distributed model;Anderton;Hydrol. Process.,2002

3. The relative importance of different flood-generating mechanisms across Europe;Berghuijs;Water Resour. Res.,2019

4. Quantifying local rainfall dynamics and uncertain boundary conditions into a nested regional-local flood modeling system;Bermúdez;Water Resour. Res.,2017

5. Seasonal hydrologic forecasting: do multimodel ensemble averages always yield improvements in forecast skill?;Bohn;J. Hydrometeorol.,2010

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