The influence of extreme rainfall on crime: Spatiotemporal dynamics in Hunan Province, China

Dongshui Zhang, Yanlu Xiao, Yongshun Han, Tongsheng Li, Xiuquan Li, Xinbao Chen, Jun Fang, Pin Zhong and Zhe Ning

PLOS ONE, 2026, vol. 21, issue 4, 1-16

Abstract: The influence of extreme weather events on social stability is increasingly acknowledged as a critical and pressing concern. Utilizing data on the criminal offenses, extreme climate conditions, and socio-economic indicators from counties and cities in Hunan Province for the period 2014–2018, this study systematically examines the impact of extreme heavy rainfall events on crime. By integrating a standardized crime intensity index, spatial autocorrelation analysis, grey correlation analysis, and a panel data model, the research comprehensively analyzes the underlying mechanisms and spatiotemporal dynamics of this relationship. The main conclusions are as follows: (1) Heavy rainfall exerts a discernible influence on the spatial distribution of crime, especially in agricultural regions such as Ningxiang and Dongkou. In these areas, the interruption of farming activities caused by intense precipitation appears to increase susceptibility to criminal incidents. (2) Extended rainfall events are associated with elevated crime rates, increasing by approximately 0.374 percent for each 1 percent increase in storm duration. In contrast, variations in rainfall intensity show no substantial influence on crime incidence. (3) Socio-economic conditions, including population mobility, GDP per capita, and the proportion of tertiary industry, further complicate this relationship by amplifying the influence of rainfall under specific contextual settings. The findings provide tailored strategies for preventing crime in regions that are particularly vulnerable to disruptions in agricultural production.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0345811

DOI: 10.1371/journal.pone.0345811

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