Rapid prediction of landslide dam stability using the logistic regression method
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Yibo Shan I Shengshui Chen I Qiming Zhong
Rapid prediction of landslide dam stability using the logistic regression method
Abstract The accurate and rapid prediction of landslide dam stability is of great significance for emergency response planning. However, current rapid prediction methods for the landslide dam cannot quantitatively consider the influence of landslide debris grain size distribution. A database was established based on 1434 documented historical landslide dams, including formed-unstable and formed-stable cases from around the world. The logistic regression method was utilized to develop new methods for the rapid prediction of landslide dam stability, which can consider the morphological characteristics and particle composition of the landslide dams as well as the hydrodynamic conditions of the upstream dammed lake. According to the available information on landslide debris particle composition, the newly proposed rapid prediction methods were classified as either detailed or simplified based on 27 and 150 cases, respectively. Based on the database, several typical methods for the rapid prediction of landslide dam stability were chosen to compare with the newly proposed methods. The performances of each method testify to the rationality of the new methods. Keywords Landslide dam . Rapid prediction method . Stability . Database . Particle composition . Verification . Comparison Introduction Landslide dams, a common geological feature in earthquake- or storm-prone mountainous areas, are generally formed by largescale landslides or rock avalanches blocking a river (Costa and Schuster 1988; Chang and Zhang 2010; Zhong et al. 2018). Landslide dam failure poses a significant threat to the people and property in the risk area (Korup 2002; Alexander 2010). Based on the investigation of the longevity of 73 landslide dams, Costa and Schuster (1988) reported that 85% of landslide dams lasted less than 1 year, 80% lasted less than 6 months, 56% lasted less than 1 month, 41% lasted less than 1 week, and 27% lasted less than 1 day. Peng and Zhang (2012) presented similar conclusions based on 204 documented cases. Although landslide dam failures would pose tremendous risk to human beings, some landslide dams are naturally stable for several thousand years (Chai et al. 1995; Stephen et al. 2011; Safran et al. 2015; Stefanelli et al. 2015). In general, a landslide dam with a longevity of more than 10 years or several decades is assigned the “stable” status class (Perrin and Hancox 1992; Korup 2004). According to Korup (2004), former landslide-dammed lakes that have been infilled are taken as an indication for a stable dam. Since landslide dams generally form in mountainous area and are rarely accessible to people, they are prone to burst naturally in a relatively short time period; therefore, a rapid and accurate prediction method for landslide dam stability has great significance for emergency response planning as well as disaster prevention and reduction. In order to rapidly predict landslide dam stability, a se
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