Landslide Susceptibility Mapping with GIS in Nagi Dada Area of Panauti Municipality, Kavrepalanchwok District: A Comparison Between AHP and FR Method

Abstract

Landslide Susceptibility Maps (LSM) are useful for both development planning and disaster management. Currently, LSMs are primarily created using GIS and remote sensing techniques. Landslide susceptibility mapping relies heavily on selecting and weighting causative elements based on their impact on slope instability. GIS is useful for calculating static parameters such as slope and aspect, as well as generating landslide susceptibility maps. The different primary data were collected for Kinematic analysis of the study area. The lesser Himalayan rocks are represented by phyllites, pelitic schists, white quartzite, meta carbonates, graphitic schists, laminated quartzite, and garnetiferous schists. This study serves in preparing LSM covering 4 wards of Panauti municipality known as the Nagi Dada area. LSM can produced using various methods using qualitative, hierarchical, and quantitative methods. In this study, 2 methods Analytical Hierarchical Process (AHP) method and the Frequency Ratio (FR) method are used and the efficacy of both methods is compared. The resulting insights hold the potential to inform evidence-based decision-making, empower stakeholders, and pave the way for sustainable urban planning in the Panauti area. The study area is classified as a tourist area with parks, gardens, paragliding, and further infrastructure development underway. The registered landslide areas in the area are ward number 4, 8, 3, and 12 of the Panauti municipality. In this situation, landslide susceptibility mapping is crucial because it identifies the area that is susceptible to landslides by ranging from low to high chances of a landslide occurring in the given area. The landslide susceptibility would serve as the foundation for the Panauti municipality's future planning. ArcGIS Pro is used for calculating static parameters such as slope and aspect, as well as generating landslide susceptibility maps. All together 10 causative factors i.e., slope, slope aspect, curvature, LULC, lithology, distance from River, distance from drainage, distance from the fault, TWI, and precipitation are used in producing LSM. The LSM map was categorized into 5 susceptible indexes i.e., very high, high, moderate, low, and very low. The area is susceptible places for landslides and the scenario of mitigation measure failure was also observed in the area. Kinematics analysis was done in the major three landslides and the failure chances in percentage were calculated. A success rate of 85.2% was achieved with LSM using the FR method whereas 75.4% was achieved using the AHP method which is of very good accuracy.