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.
Research article
| 
22 Sep 2020
Research article |
| 22 Sep 2020
| 22 Sep 2020
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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Cited
20 citations as recorded by crossref.
- Impact of the number of donor catchments and the efficiency threshold on regionalization performance of hydrological models W. Qi et al. https://doi.org/10.1016/j.jhydrol.2021.126680
- Towards reliable uncertainty quantification for hydrologic predictions, part II: Characterizing impacts of uncertain factors through an iterative factorial data assimilation framework Y. Fan et al. https://doi.org/10.1016/j.jhydrol.2022.128136
- Regional Copula Modeling of Rainfall Duration and Intensity: Derivation and Validation of IDF Curves in the Kastoria Basin E. Leivadiotis et al. https://doi.org/10.3390/hydrology13040117
- Development of clustered polynomial chaos expansion model for stochastic hydrological prediction F. Wang et al. https://doi.org/10.1016/j.jhydrol.2021.126022
- Uncertainty quantification and partition for multivariate risk inferences through a factorial multimodel Bayesian copula (FMBC) system Y. Fan et al. https://doi.org/10.1016/j.jhydrol.2021.126406
- Hydrologic risk from consecutive dry and wet extremes at the global scale M. Rashid & T. Wahl https://doi.org/10.1088/2515-7620/ac77de
- A factorial inexact copula stochastic programming (FICSP) approach for water-energy- food nexus system management Y. Wang et al. https://doi.org/10.1016/j.agwat.2022.108069
- Multivariate Hydrologic Risk Analysis for River Thames R. Gabriel & Y. Fan https://doi.org/10.3390/w14030384
- Composite copula adaptive metropolis for joint parameter estimation in hydrological models F. Wang et al. https://doi.org/10.1016/j.jhydrol.2026.135733
- Tracing design flood hydrograph uncertainty in reservoir flood control system A. Guo et al. https://doi.org/10.1016/j.apm.2021.09.012
- Development of a disaggregated multi-level factorial hydrologic data assimilation model F. Wang et al. https://doi.org/10.1016/j.jhydrol.2022.127802
- Impacts of climate variations on non-stationarity of streamflow over Canada F. Wang et al. https://doi.org/10.1016/j.envres.2021.111118
- Multi-level factorial analysis for ensemble data-driven hydrological prediction F. Wang et al. https://doi.org/10.1016/j.advwatres.2021.103948
- Tracing Uncertainty Contributors in the Multi‐Hazard Risk Analysis for Compound Extremes Y. Fan et al. https://doi.org/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. https://doi.org/10.1016/j.scitotenv.2022.153198
- Partition of one-dimensional river flood routing uncertainty due to boundary conditions and riverbed roughness J. Wang et al. https://doi.org/10.1016/j.jhydrol.2022.127660
- Bivariate hydrologic risk analysis for the Xiangxi River in Three Gorges Reservoir Area, China Y. Fan https://doi.org/10.1186/s40068-022-00264-6
- A Statistical Hydrological Model for Yangtze River Watershed Based on Stepwise Cluster Analysis F. Wang et al. https://doi.org/10.3389/feart.2021.742331
- Copulas for hydroclimatic analysis: A practice‐oriented overview F. Tootoonchi et al. https://doi.org/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. https://doi.org/10.1029/2021WR031557
20 citations as recorded by crossref.
- Impact of the number of donor catchments and the efficiency threshold on regionalization performance of hydrological models W. Qi et al. https://doi.org/10.1016/j.jhydrol.2021.126680
- Towards reliable uncertainty quantification for hydrologic predictions, part II: Characterizing impacts of uncertain factors through an iterative factorial data assimilation framework Y. Fan et al. https://doi.org/10.1016/j.jhydrol.2022.128136
- Regional Copula Modeling of Rainfall Duration and Intensity: Derivation and Validation of IDF Curves in the Kastoria Basin E. Leivadiotis et al. https://doi.org/10.3390/hydrology13040117
- Development of clustered polynomial chaos expansion model for stochastic hydrological prediction F. Wang et al. https://doi.org/10.1016/j.jhydrol.2021.126022
- Uncertainty quantification and partition for multivariate risk inferences through a factorial multimodel Bayesian copula (FMBC) system Y. Fan et al. https://doi.org/10.1016/j.jhydrol.2021.126406
- Hydrologic risk from consecutive dry and wet extremes at the global scale M. Rashid & T. Wahl https://doi.org/10.1088/2515-7620/ac77de
- A factorial inexact copula stochastic programming (FICSP) approach for water-energy- food nexus system management Y. Wang et al. https://doi.org/10.1016/j.agwat.2022.108069
- Multivariate Hydrologic Risk Analysis for River Thames R. Gabriel & Y. Fan https://doi.org/10.3390/w14030384
- Composite copula adaptive metropolis for joint parameter estimation in hydrological models F. Wang et al. https://doi.org/10.1016/j.jhydrol.2026.135733
- Tracing design flood hydrograph uncertainty in reservoir flood control system A. Guo et al. https://doi.org/10.1016/j.apm.2021.09.012
- Development of a disaggregated multi-level factorial hydrologic data assimilation model F. Wang et al. https://doi.org/10.1016/j.jhydrol.2022.127802
- Impacts of climate variations on non-stationarity of streamflow over Canada F. Wang et al. https://doi.org/10.1016/j.envres.2021.111118
- Multi-level factorial analysis for ensemble data-driven hydrological prediction F. Wang et al. https://doi.org/10.1016/j.advwatres.2021.103948
- Tracing Uncertainty Contributors in the Multi‐Hazard Risk Analysis for Compound Extremes Y. Fan et al. https://doi.org/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. https://doi.org/10.1016/j.scitotenv.2022.153198
- Partition of one-dimensional river flood routing uncertainty due to boundary conditions and riverbed roughness J. Wang et al. https://doi.org/10.1016/j.jhydrol.2022.127660
- Bivariate hydrologic risk analysis for the Xiangxi River in Three Gorges Reservoir Area, China Y. Fan https://doi.org/10.1186/s40068-022-00264-6
- A Statistical Hydrological Model for Yangtze River Watershed Based on Stepwise Cluster Analysis F. Wang et al. https://doi.org/10.3389/feart.2021.742331
- Copulas for hydroclimatic analysis: A practice‐oriented overview F. Tootoonchi et al. https://doi.org/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. https://doi.org/10.1029/2021WR031557
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