A Landslide Probability Model Based on a Long-Term Landslide Inventory and Rainfall Factors

Abstract

The prediction and advanced warning of landslide hazards in large-scale areas must deal with a large amount of uncertainty, therefore a growing number of studies are using stochastic models to analyze the probability of landslide occurrences. In this study, we used a modified Thiessen’s polygon method to divide the research area into several rain gauge control areas, and divided the control areas into slope units reflecting the topographic characteristics to enhance the spatial resolution of a landslide probability model. We used a 2000–2015 long-term landslide inventory, daily rainfall, and effective accumulated rainfall to estimate the rainfall threshold that can trigger landslides. We then employed a Poisson probability model and historical rainfall data from 1987 to 2016 to calculate the exceedance probability that rainfall events will exceed the threshold value. We calculated the number of landslides occurring from the events when rainfall exceeds the threshold value in the slope units to estimate the probability that a landslide will occur in this situation. Lastly, we employed the concept of conditional probability by multiplying this probability with the exceedance probability of rainfall events exceeding the threshold value, which yielded the probability that a landslide will occur in each slope unit for one year. The results indicated the slope units with high probability that at least one rainfall event will exceed the threshold value at the same time that one landslide will occur within any one year are largely located in the southwestern part of the Taipei Water Source Domain, and the highest probability is 0.26. These slope units are located in parts of the study area with relatively weak lithology, high elevations, and steep slopes. Compared with probability models based solely on landslide inventories, our proposed landslide probability model, combined with a long-term landslide inventory and rainfall factors, can avoid problems resulting from an incomplete landslide inventory, and can also be used to estimate landslide occurrence probability based on future potential changes in rainfall.

The optimal rainfall thresholds and probabilistic rainfall conditions for a landslide early warning system for Chuncheon, Republic of Korea

“…Gariano et al (2015) utilized a validation method using a contingency table and skill score of rainfall-induced landslide thresholds, and this method was later used in the research of Piciullo et al (2017) and Lee and Kim (2017). The basic concepts of contingencies include whether the event occurs or not and whether the model predictions are correct or wrong (Wilks 2011;Accadia et al 2003;Frattini et al 2010;Staley et al 2012) [TNs]) can be obtained based on the rainfall conditions, which are either lower or higher than the rainfall thresholds, and whether a landslide occurred or did not occur ( Table 1). The definition of the contingencies is as follows.…”

Stability Analysis of Expansive Soil Slope Considering Seepage Softening and Moistening Expansion Deformation

“…Under the action of rainfall and dry-wet cycles, the landslide first appeared in the shallow part of the slope foot, and then the upper soil mass was caused to slide. According to the existing research [23,24], the expansive soil landslide is mainly shallow traction landslide, which is different from the circular sliding surface of ordinary cohesive soil [25,26]. Under the condition of heavy rainfall, the sliding surface of expansive soil tends to be shallower.…”

CHILDA – Czech Historical Landslide Database

“…The first works on landsliding in Czechia are dated to the eighteenth century (e.g. Strnad, 1790), followed by works emerging as of the end of the nineteenth century (Zahálka, 1890;Dědina, 1896;Woldřich, 1899) and at the beginning of the twentieth century (Čermák, 1912;Dědina, 1916). More systematic landslide research started, however, in the 1920s with the work of Záruba (1922Záruba ( , 1923Záruba ( , 1926Záruba ( , 1938.…”