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Evaluation of risk of hydrological droughts by the trivariate Plackett copula in the East River basin (China)

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  • Yongqin Chen
  • Qiang Zhang
  • Mingzhong Xiao
  • Vijay Singh

Abstract

East River, one of the major tributaries of Pearl River, is the major source of water supply for mega-cites within and in the vicinity of the Pearl River Delta, China. The availability and variability of water resources of the East River basin are therefore of practical importance. This study aims to investigate the probabilistic behavior of hydrological droughts in the East River basin using the trivariate Plackett copula. Daily streamflow data for the period of 1975–2009 from 3 hydrological stations in the East River basin are analyzed. Defining hydrological droughts by drought severity, duration, and minimum flow, secondary return periods are computed. Results show that the Plackett copula satisfactorily models bivariate and trivariate probability distributions of correlated drought variables. Results of risk evaluation show an increasing drought risk from the upper to the lower East River basin. This result is important for basin-scale water resources management in the East River basin. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Yongqin Chen & Qiang Zhang & Mingzhong Xiao & Vijay Singh, 2013. "Evaluation of risk of hydrological droughts by the trivariate Plackett copula in the East River basin (China)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 68(2), pages 529-547, September.
    • Handle: RePEc:spr:nathaz:v:68:y:2013:i:2:p:529-547
    DOI: 10.1007/s11069-013-0628-8
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    References listed on IDEAS

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    1. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    2. Christian Genest & Jean‐François Quessy & Bruno Rémillard, 2006. "Goodness‐of‐fit Procedures for Copula Models Based on the Probability Integral Transformation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(2), pages 337-366, June.
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    2. Elaheh Motevali Bashi Naeini & Ali Mohammad Akhoond-Ali & Fereydoun Radmanesh & Jahangir Abedi Koupai & Shahrokh Soltaninia, 2021. "Comparison of the Calculated Drought Return Periods Using Tri-variate and Bivariate Copula Functions Under Climate Change Condition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4855-4875, November.
    3. Giovana Cristina Santos Medeiros & Adelena Gonçalves Maia & Joana Darc Freire Medeiros, 2019. "Assessment of Two Different Methods in Predicting Hydrological Drought from the Perspective of Water Demand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(5), pages 1851-1865, March.
    4. Chao Zhang & Changming Ji & Yi Wang & Qian Xiao, 2022. "Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 1339-1360, January.
    5. Jinping Zhang & Hang Zhang & Hongyuan Fang, 2022. "Study on Urban Rainstorms Design Based on Multivariate Secondary Return Period," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2293-2307, May.

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