Driving Force Analysis of the Temporal and Spatial Distribution of Flash Floods in Sichuan Province

Yesen Liu, Ximin Yuan, Liang Guo, Yaohuan Huang and Xiaolei Zhang
Additional contact information
Yesen Liu: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China
Ximin Yuan: State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China
Liang Guo: China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Yaohuan Huang: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiaolei Zhang: China Institute of Water Resources and Hydropower Research, Beijing 100038, China

Sustainability, 2017, vol. 9, issue 9, 1-17

Abstract: Flash floods are important natural disasters in China that can result in casualties and property losses. In this paper, we present a quantitative approach to examine the driving factors of the spatiotemporal distribution of flash floods based on a geographical detector. The environmental background condition (elevation, slope, etc.), precipitation, and human activity factors, as well as changes in these factors, are investigated in Sichuan Province via a driving force analysis. The results show that heavy precipitation is the most important driver, with power of determinant ( PD ) values of 0.71 and 0.77 for the spatial distributions of flash floods from 1995 to 2004 and from 2005 to 2014, respectively. The PD s of population density are 0.65 and 0.78 in the same two periods, while those of elevation are 0.59 and 0.73. Precipitation variability is the most important driver of the spatiotemporal variability of flash floods, followed by GDP density and population density, with PD s of 0.48, 0.29, and 0.27, respectively. The results show that human activities and precipitation are the primary driving forces of the spatiotemporal variability of flash floods and should be the focus of flash flood prevention and forecasting.

Keywords: flash flood; geographical detector; driving force; human activity; Sichuan Province (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/2071-1050/9/9/1527/pdf (application/pdf)
https://www.mdpi.com/2071-1050/9/9/1527/ (text/html)

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:gam:jsusta:v:9:y:2017:i:9:p:1527-:d:110077

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().