Articles | Volume 24, issue 9
https://doi.org/10.5194/hess-24-4601-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-4601-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An uncertainty partition approach for inferring interactive hydrologic risks
Department of Civil and Environmental Engineering, Brunel University, London, Uxbridge, Middlesex, UB8 3PH, United Kingdom
Kai Huang
Faculty of Engineering and Applied Sciences, University of Regina,
Regina, SK, S4S0A2, Canada
Guohe Huang
CORRESPONDING AUTHOR
Institute for Energy, Environment and Sustainable Communities,
University of Regina, Regina,SK, S4S 0A2, Canada
Yongping Li
School of Environment, Beijing Normal University, Beijing 100875,
China
Feng Wang
School of Environment, Beijing Normal University, Beijing 100875,
China
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- Tracing Uncertainty Contributors in the Multi‐Hazard Risk Analysis for Compound Extremes Y. Fan et al. 10.1029/2021EF002280
- An optimization model for water resources allocation in Dongjiang River Basin of Guangdong-Hong Kong-Macao Greater Bay Area under multiple complexities Y. Huang et al. 10.1016/j.scitotenv.2022.153198
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- Bivariate hydrologic risk analysis for the Xiangxi River in Three Gorges Reservoir Area, China Y. Fan 10.1186/s40068-022-00264-6
- A Statistical Hydrological Model for Yangtze River Watershed Based on Stepwise Cluster Analysis F. Wang et al. 10.3389/feart.2021.742331
- Copulas for hydroclimatic analysis: A practice‐oriented overview F. Tootoonchi et al. 10.1002/wat2.1579
- Development of a Joint Probabilistic Rainfall‐Runoff Model for High‐to‐Extreme Flow Projections Under Changing Climatic Conditions K. Li et al. 10.1029/2021WR031557
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Latest update: 22 Nov 2024