Next Article in Journal
Irrigation-Induced Changes in Evapotranspiration Demand of Awati Irrigation District, Northwest China: Weakening the Effects of Water Saving?
Next Article in Special Issue
Model to Assess the Quality of Magmatic Rocks for Reliable and Sustainable Constructions
Previous Article in Journal
Deteriorated Water Quality of Agricultural Catchments in South China by Net Anthropogenic Phosphorus Inputs
Previous Article in Special Issue
Risk Indicators and Road Accident Analysis for the Period 2012–2016
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Sustainability 2017, 9(9), 1527; doi:10.3390/su9091527

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

State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China
China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Author to whom correspondence should be addressed.
Received: 8 June 2017 / Revised: 21 August 2017 / Accepted: 24 August 2017 / Published: 28 August 2017
(This article belongs to the Special Issue Risk Assessment and Management)
View Full-Text   |   Download PDF [3871 KB, uploaded 28 August 2017]   |  


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 PDs 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 PDs 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. View Full-Text
Keywords: flash flood; geographical detector; driving force; human activity; Sichuan Province flash flood; geographical detector; driving force; human activity; Sichuan Province

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Liu, Y.; Yuan, X.; Guo, L.; Huang, Y.; Zhang, X. Driving Force Analysis of the Temporal and Spatial Distribution of Flash Floods in Sichuan Province. Sustainability 2017, 9, 1527.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top