Spatial risk occurrence of extreme precipitation in China under historical and future scenarios

Haoyu Jin, Ruida Zhong, Moyang Liu, Changxin Ye and Xiaohong Chen ()
Additional contact information
Haoyu Jin: Sun Yat-Sen University
Ruida Zhong: Sun Yat-Sen University
Moyang Liu: The Australian National University (ANU)
Changxin Ye: Sun Yat-Sen University
Xiaohong Chen: Sun Yat-Sen University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 119, issue 3, No 37, 2033-2062

Abstract: Abstract In recent years, extreme precipitation events have shown a significant increasing trend in both intensity and amount. Therefore, it is urgent to delineate the areas vulnerable to extreme precipitation and formulate more reasonable measures to reduce the risk of extreme precipitation. In this study, we selected gross domestic product, population, nighttime light, normalized difference vegetation index, runoff depth, and relief degree of land surface data to comprehensively characterize surface vulnerability. We selected the 90, 95, and 99% precipitation quantiles and their occurrence frequencies in the historical and future periods as hazard factors, and calculated the extreme precipitation risks faced by different regions of China based on a risk calculation formula. The results indicate that the Qinghai-Tibet Plateau and urbanized regions such as the Yangtze River Delta are high-risk areas affected by extreme precipitation. The precipitation simulated by the Beijing Climate Center climate system model version 2 (BCC-CSM2-MR) global climate model selected in this study is relatively smaller than the historical precipitation, but it can basically reflect the actual spatial distribution characteristics of precipitation. Under four future climate scenarios, the joint occurrence probability of extreme precipitation will decrease, while high-risk areas of extreme precipitation will still be located in the Qinghai-Tibet Plateau and densely urbanized areas. This study systematically analyzed the spatial distribution characteristics of extreme precipitation risk under historical and future scenarios, providing theoretical support for the formulation of more reasonable measures to prevent extreme precipitation risk.

Keywords: Extreme precipitation; Continuous precipitation; Joint probability; GCM; Risk analysis (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-023-06177-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:119:y:2023:i:3:d:10.1007_s11069-023-06177-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-023-06177-6

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().