Spatiotemporal Characteristics and Driving Force Analysis of Flash Floods in Fujian Province

• Main Authors: Junnan Xiong, Quan Pang, Chunkun Fan, Weiming Cheng, Chongchong Ye, Yunliang Zhao, Yuanrong He, Yifan Cao
• Format: Article
• Language: English
• Published: MDPI AG 2020-02-01
• Series: ISPRS International Journal of Geo-Information
• Subjects: flash flood; spatiotemporal patterns; driving forces; geomorphic regionalization; sensitivity; fujian province
• Online Access: https://www.mdpi.com/2220-9964/9/2/133

Flash floods are one of the most destructive natural disasters. The comprehensive identification of the spatiotemporal characteristics and driving factors of a flash flood is the basis for the scientific understanding of the formation mechanism and the distribution characteristics of flash floods. In this study, we explored the spatiotemporal patterns of flash floods in Fujian Province from 1951 to 2015. Then, we analyzed the driving forces of flash floods in geomorphic regions with three different grades based on three methods, namely, geographical detector, principal component analysis, and multiple linear regression. Finally, the sensitivity of flash floods to the gross domestic product, village point density, annual maximum one-day precipitation (Rx1day), and annual total precipitation from days > 95th percentile (R95p) was analyzed. The analytical results indicated that (1) The counts of flash floods rose sharply from 1988, and the spatial distribution of flash floods mainly extended from the coastal low mountains, hills, and plain regions of Fujian (IIA2) to the low-middle mountains, hills, and valley regions in the Wuyi mountains (IIA4) from 1951 to 2015. (2) From IIA2 to IIA4, the impact of human activities on flash floods was gradually weakened, while the contribution of precipitation indicators gradually strengthened. (3) The sensitivity analysis results revealed that the hazard factors of flash floods in different periods and regions had significant differences in Fujian Province. Based on the above results, it is necessary to accurately forecast extreme precipitation and improve the economic development model of the IIA2 region.