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

Yuqing Peng, Zengchuan Dong (), Tianyan Zhang, Can Cui, Shengnan Zhu, Shujun Wu, Zhuozheng Li and Xun Cui
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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

Sustainability, 2024, vol. 16, issue 24, 1-15

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.

Keywords: extreme precipitation; large-scale climate indicators; remote correlation; Copula; Zishui River Basin (ZRB) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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