Flood coincidence analysis of Poyang Lake and Yangtze River: risk and influencing factors

Published

Journal Article (Review)

© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. We build copula function-based joint distribution models for the annual maximum flood peaks of the Yangtze River and Poyang Lake, to analyze the coincidence probabilities, using scenarios that combine with the impoundment of three Gorges, define influencing indexes and relative contribution rates on flood coincidence at varying frequencies. The study shows the probabilities for coincidence of floods with 1000, 100, and 10-year return periods in both Yangtze main stem and Poyang Lake are respectively 0.02, 0.19 and 2.87%, with higher coincidence probabilities for shorter return periods; when 1000-year flood occurs in the Yangtze, the probabilities for Poyang Lake to encounter flood of the 1000, 100, or 10-year magnitude are higher than 16.08, 42.48 or 74.77% respectively; Poyang–Yangtze flood coincidence is affected by operation of the hydraulic engineering. The lowering of flood peaks caused by the Three Gorges impoundment and regulation of the lake have respectively reduced the probabilities of Poyang–Yangtze flood coincidence by about 7.0 and 1.97%, with average relative contribution rates − 33.82 and − 17.1%; influenced by hydrological projects in Poyang basin, variations in Poyang’s inflow flood have displayed an average contribution rate of 20.4% for the negative effect on extreme (P OpenSPiltSPi 5% or P CloseSPigtSPi 90%) flood coincidence, while having a positive contribution rate of 38.2% on floods of other return periods. The results can help increase our understanding of flood coincidence, and support flood control efforts in Poyang Lake; its analytical approach may also be useful to other applications of copula functions.

Full Text

Duke Authors

Cited Authors

  • Jianping, B; Pengxin, D; Xiang, Z; Sunyun, L; Marani, M; Yi, X

Published Date

  • April 1, 2018

Published In

Volume / Issue

  • 32 / 4

Start / End Page

  • 879 - 891

Electronic International Standard Serial Number (EISSN)

  • 1436-3259

International Standard Serial Number (ISSN)

  • 1436-3240

Digital Object Identifier (DOI)

  • 10.1007/s00477-018-1514-4

Citation Source

  • Scopus