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Assessment of Teleconnections of Extreme Precipitation with Large-Scale Climate Indices: A Case Study of the Zishui River Basin, China

Author

Listed:
  • Yuqing Peng

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Zengchuan Dong

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Tianyan Zhang

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Can Cui

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Shengnan Zhu

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Shujun Wu

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Zhuozheng Li

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

  • Xun Cui

    (College of Hydrology and Water Resource, Hohai University, Nanjing 210098, China)

Abstract

With global climate change, the frequency of extreme precipitation events in the Zishui River Basin (ZRB) is increasing, presenting significant challenges for water resource management. This study focuses on analyzing the evolution of extreme precipitation trends during the flood season from 1979 to 2018 and investigating their remote correlations with 18 large-scale climate indicators (LCIs) using three-dimensional (3D) Vine Copula. The results indicate a significant downward trend in the sustained wetness index (CWD) during the flood season, while trends in other extreme precipitation indices (EPIs) are not significant. Notably, a significant correlation exists between Maximum Precipitation for One Day (RX1day) and the Pacific Decadal Oscillation (PDO), Pacific North American pattern (PNO), and Sustained Drought Index (CDD), as well as between Atlantic Multi-decadal Oscillation (AMO) and PDO. Excluding the optimal marginal distribution of PDO, which follows a Laplace distribution, the optimal marginal distributions of the other indices conform to a Beta distribution. The C-Vine Copula function was employed to establish the functional relationships among RX1day, PDO, PNO, CDD, and AMO, allowing for an analysis of the impact of model fitting on EPIs under different LCI scenarios. The findings of this study are significant for the ZRB and other inland monsoon climate zones, providing a scientific foundation for addressing climate extremes and enhancing flood monitoring and prediction capabilities in the region.

Suggested Citation

  • Yuqing Peng & Zengchuan Dong & Tianyan Zhang & Can Cui & Shengnan Zhu & Shujun Wu & Zhuozheng Li & Xun Cui, 2024. "Assessment of Teleconnections of Extreme Precipitation with Large-Scale Climate Indices: A Case Study of the Zishui River Basin, China," Sustainability, MDPI, vol. 16(24), pages 1-15, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:11235-:d:1549322
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    References listed on IDEAS

    as
    1. Aiguo Dai, 2013. "Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(1), pages 52-58, January.
    2. Steffen Grønneberg & Nils Lid Hjort, 2014. "The Copula Information Criteria," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 436-459, June.
    3. Aiguo Dai, 2013. "Erratum: Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(2), pages 171-171, February.
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