Abstract
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.
Highlights
Landslide risk has increased all over the world during recent decades, because of the uncontrolled urban sprawl by fast population growth and accelerated economic development
This paper presents the results of a recent study on rainfall thresholds for shallow landslides at a regional scale to overcome the aforementioned difficulties
Most of the shallow landslides are located in the mountainous region, which always occurred in rainy season every year, but some are located in the plain areas where usually rive banks are
Summary
Landslide risk has increased all over the world during recent decades, because of the uncontrolled urban sprawl by fast population growth and accelerated economic development. When working over larger areas, the method used in early warning systems to forecast shallow landslide occurrence is frequently based on statistical and empirical models relying on one or two parameters from the rainfall events, e.g., rainfall intensity and duration, or antecedent precipitation. For Tuscany, Italy, Segoni et al (2014) presented a mosaic of several local rainfall thresholds instead of a single regional one They established a relation between the threshold parameters and the prevailing lithology, which significantly enhances the effectiveness of an early warning system. All these critical thresholds and equations strongly depend on the local physiographic, hydrological, and meteorological conditions (Guzzetti et al, 2007a). The paper contains (i) the description of a method to calculate rainfall thresholds from limited available data and time; (ii) the application and improvement of the rainfall threshold for landslide early warning in a case study
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