Estimation of Shallow Landslides Caused by Heavy Rainfall Using Two Conceptual Models

Abstract

In this study, two indices were used to examine the influence of rainstorms on landslides. The first was a soil water index (SWI) derived from the three-layer tank model that has been applied to the actual evacuation warning system in Japan since 2007. The second was a potential landslide area index (PLAI) derived by combining SWI and a distributed-landslide conceptual model consisting of groundwater table calculation and infinite-slope stability analyses. These two methods were applied to the Utsunomiya University Forest in Funyu, Tochigi, Japan. In August 1998, a heavy rainfall event caused many shallow landslides in the study area, whereas other heavy rainfall events in 1979-2011 did not cause severe landslides. For 26 heavy rainfall events from 1979 to 2011 detected based on the value of SWI, the two indices were used to discriminate between rainstorms with and without landslides. The responses of the two indices to rainfall events showed similar trends, confirming the commonality of the two indices. However, comparing values from both indices between heavy rainfall events with and without landslides showed that PLAI had better sensitivity, suggesting the superiority of this index.

Identification and evaluation of the risk induced by landslides based on G.I.S. models of spatial analysis. Case study: Bicazu Ardelean, Romania

“…They represent one of the most destructive and dangerous natural hazards Representing one of the objectives of this study, the deterministic model focuses on shaping reality as faithfully as possible, by knowing the input data sets, knowing the analysis and the steps involved in its realization, and knowing the structure of the output data sets. Therefore, this type of model is rightly called deterministic, because the entire process of collecting, processing, and defining information is known from start to finish (Shuin et al, 2014;Dahal, 2017;Ma et al, 2017).…”