Articles | Volume 15, issue 12
Nat. Hazards Earth Syst. Sci., 15, 2715–2723, 2015
https://doi.org/10.5194/nhess-15-2715-2015

Special issue: Landslide Prediction & Forecasting

Nat. Hazards Earth Syst. Sci., 15, 2715–2723, 2015
https://doi.org/10.5194/nhess-15-2715-2015

Research article 21 Dec 2015

Research article | 21 Dec 2015

Determination of rainfall thresholds for shallow landslides by a probabilistic and empirical method

J. Huang, N. P. Ju, Y. J. Liao, and D. D. Liu J. Huang et al.
  • State Key Laboratory of Geohazard Prevention and Geo-environment Protection, Chengdu University of Technology, Chengdu, Sichuan 610059, China

Abstract. Rainfall-induced landslides not only cause property loss, but also kill and injure large numbers of people every year in mountainous areas in China. These losses and casualties may be avoided to some extent with rainfall threshold values used in an early warning system at a regional scale for the occurrence of landslides. However, the limited availability of data always causes difficulties. In this paper we present a method to calculate rainfall threshold values with limited data sets for two rainfall parameters: hourly rainfall intensity and accumulated precipitation. The method has been applied to the Huangshan region, in the province of Anhui, China. Four early warning levels (zero, outlook, attention, and warning) have been adopted and the corresponding rainfall threshold values have been defined by probability lines. A validation procedure showed that this method can significantly enhance the effectiveness of a warning system, and finally reduce and mitigate the risk of shallow landslides in mountainous regions.

Download
Short summary
In this paper we present a method to calculate rainfall threshold values with limited data sets based on two rainfall parameters: hourly rainfall intensity and accumulated precipitation. The method has been applied to the Huangshan region, in the province of Anhui, China. A validation procedure showed that this method can significantly enhance the effectiveness of a warning system, and finally reduce and mitigate the risk of shallow landslides in mountainous regions.
Altmetrics
Final-revised paper
Preprint