Journal
ADVANCES IN WATER RESOURCES
Volume 88, Issue -, Pages 170-185Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.advwatres.2015.12.017
Keywords
Flood risk; Copula; Flood frequency analysis; Distribution; Conditional distribution; Gaussian mixture model
Categories
Funding
- Natural Sciences Foundation [51190095, 51225904]
- 111 Project [B14008]
- Natural Science and Engineering Research Council of Canada
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In this study, a bivariate hydrologic risk framework is proposed through coupling Gaussian mixtures into copulas, leading to a coupled GMM-copula method. In the coupled GMM-Copula method, the marginal distributions of flood peak, volume and duration are quantified through Gaussian mixture models and the joint probability distributions of flood peak-volume, peak-duration and volume-duration are established through copulas. The bivariate hydrologic risk is then derived based on the joint return period of flood variable pairs. The proposed method is applied to the risk analysis for the Yichang station on the main stream of the Yangtze River, China. The results indicate that (i) the bivariate risk for flood peak-volume would keep constant for the flood volume less than 1.0 x 10(5) m(3)/s day, but present a significant decreasing trend for the flood volume larger than 1.7 x 10(5) m(3)/s day; and (ii) the bivariate risk for flood peak-duration would not change significantly for the flood duration less than S days, and then decrease significantly as duration value become larger. The probability density functions (pdfs) of the flood volume and duration conditional on flood peak can also be generated through the fitted copulas. The results indicate that the conditional pdfs of flood volume and duration follow bimodal distributions, with the occurrence frequency of the first vertex decreasing and the latter one increasing as the increase of flood peak. The obtained conclusions from the bivariate hydrologic analysis can provide decision support for flood control and mitigation. (C) 2015 Elsevier Ltd. All rights reserved.
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