# Influence of Earthquakes on Landslide Susceptibility in a Seismic Prone Catchment in Central Asia
## 1 Introduction  
As one of the greatest natural hazards in the world, landslides occur frequently due to the downslope movement of rock, debris, or soil, and have caused huge property damages, personal injuries, and even loss of human lives [1, 2]. In total, landslides account forabout 9% of the past world's disasters [3], and the damages of landslides to society and environment are expected to increase in the future [2; 4]. The factors that can potentially trigger landslides are numerous and interdependent, comprising both natural events (e.g., earthquakes, droughts, intensive rainfalls, rapid snow melting, volcanic activities, groundwater pressure, geomorphological processes, and wildfire) [5; 6; 7] and anthropogenic activities (e.g., deforestation, agricultural cultivation, quarries, mines, and infrastructural development) [8; 9; 10]. To minimise the loss of lives and damage to properties, the landslide susceptibility assessment is usually the first step [11; 12] and has been playing an important role in the past, for instance, for safe and economic planning, especially for the selection of safe localities of infrastructure [11; 13]. By showing the probability of landslides in an area, a landslide susceptibility map can be used to determine spaces with potential landslide risks [8; 14]. However, in engineering practice, the potential volume of landslide (VOL), which refers to the volume of material between the ground surface and the potential failure surface [15], is more frequently required because (1) it is the best way to indicate the magnitude and the realistic size of each individual landslide [16; 17; 18]; (2) with the knowledge of volume, engineers can develop precise mitigation plans and relevant budget measures [19; 20]; and (3) it is a fundamental indicator to estimate secondary hazards (e.g., formation and break of landslide dams, amount and duration of debris flows, isolated districts due to traffic disruption, and long-term degradation of mountainous vegetation) [21; 22; 23]. However, due to the complicated process of volume simulation and the lack of soil information related to potential failure surface, the majority of previous studies related to landslides focuses on either landslide susceptibility maps or the volume estimation of the occurred landslides in the past [8; 16], and only very few studies have attempted to predict the potential VOL [15]. In total, five types of methods have been developed for the volume estimation: field surveys (e.g., trenching and drilling boreholes for direct measurements of the position and geometry of geologic discontinuities), geometrical estimation (e.g., ellipsoids based on surface displacement and morphology), empirical modelling (e.g., the California and USGS methods for the estimation of landslide displacements), multi-temporal DEM (digital elevation model) analysis (e.g., the differed-time analysis of past movements and the records of recent slope movements), and physically-based modelling [1; 8; 16; 24]. Among them, the physically-based modelling has been recently widely used [20]. By integrating terrain data (e.g., DEM), soil parameters (e.g., layer depth, cohesion, angle of internal friction, and specific gravity), and hydrological parameters (e.g., pore water pressure), the physically-based models can mimic the underground situation. Based on the mimicked underground situations, the physically-based models can simulate the unstable slopes and further calculate the slope stabilities (i.e., landslide susceptibility index or LSI) and VOL [15; 25]. Currently, two types of principles have been adopted in the physically-based models for the slope stability analysis: limit equilibrium method (LEM) and finite element method (FEM) [26; 27]. LEM predefines the failure surfaces for slopes and analyses the stabilities of those predefined failure surfaces [28; 29]. In contrast to LEM, FEM does not predefine failure surfaces [26; 27]. It should be noted that most of the physically-based models adopt LEM to carry out the slope stability analysis [15; 29].