DOI: 10.5194/hess-24-4601-2020
论文题名: An uncertainty partition approach for inferring interactive hydrologic risks
作者: Fan Y. ; Huang K. ; Huang G. ; Li Y. ; Wang F.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2020
卷: 24, 期: 9 起始页码: 4601
结束页码: 4624
语种: 英语
Scopus关键词: Flood control
; Floods
; Multivariant analysis
; Risk assessment
; Uncertainty analysis
; Analysis frameworks
; Correlated variables
; Dependence structures
; Failure Probability
; Marginal distribution
; Multivariate threshold
; Parameter uncertainty
; Predictive uncertainty
; Risk analysis
; hydrological modeling
; risk assessment
; runoff
; uncertainty analysis
; watershed
英文摘要: Extensive uncertainties exist in hydrologic risk analysis. Particularly for interdependent hydrometeorological extremes, the random features in individual variables and their dependence structures may lead to bias and uncertainty in future risk inferences. In this study, an iterative factorial copula (IFC) approach is proposed to quantify parameter uncertainties and further reveal their contributions to predictive uncertainties in risk inferences. Specifically, an iterative factorial analysis (IFA) approach is developed to diminish the effect of the sample size and provide reliable characterization for parameters' contributions to the resulting risk inferences. The proposed approach is applied to multivariate flood risk inference for the Wei River basin to demonstrate the applicability of IFC for tracking the major contributors to resulting uncertainty in a multivariate risk analysis framework. In detail, the multivariate risk model associated with flood peak and volume will be established and further introduced into the proposed iterative factorial analysis framework to reveal the individual and interactive effects of parameter uncertainties on the predictive uncertainties in the resulting risk inferences. The results suggest that uncertainties in risk inferences would mainly be attributed to some parameters of the marginal distributions, while the parameter of the dependence structure (i.e. copula function) would not produce noticeable effects. Moreover, compared with traditional factorial analysis (FA), the proposed IFA approach would produce a more reliable visualization for parameters' impacts on risk inferences, while the traditional FA would remarkably overestimate the contribution of parameters' interaction to the failure probability in AND (i.e. all variables would exceed the corresponding thresholds) and at the same time underestimate the contribution of parameters' interaction to the failure probabilities in OR (i.e. one variable would exceed its corresponding threshold) and Kendall (i.e. the correlated variables would exceed a critical multivariate threshold). © Author(s) 2020. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/162590
Appears in Collections: 气候变化与战略
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作者单位: Fan, Y., Department of Civil and Environmental Engineering, Brunel University, London, Uxbridge, Middlesex, UB8 3PH, United Kingdom; Huang, K., Faculty of Engineering and Applied Sciences, University of Regina, Regina, SK S4S0A2, Canada; Huang, G., Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK S4S 0A2, Canada; Li, Y., School of Environment, Beijing Normal University, Beijing, 100875, China; Wang, F., School of Environment, Beijing Normal University, Beijing, 100875, China
Recommended Citation:
Fan Y.,Huang K.,Huang G.,et al. An uncertainty partition approach for inferring interactive hydrologic risks[J]. Hydrology and Earth System Sciences,2020-01-01,24(9)