Assessment of earthquake-triggered landslides in Central Nepal

Abstract

Landslides are recurrent in Nepal due to active tectonics, high precipitation, complex topography, geology, and land use practices. Reliable landslide susceptibility maps are crucial for effective disaster management. Ongoing research has improved landslide mapping approaches, while further efforts are needed to assess inventories and enhance susceptibility mapping methods. This thesis aims to evaluate the landslides caused by the Gorkha earthquake in 2015 and develop reliable landslide susceptibility maps using statistical and geospatial techniques. There are four main objectives: (i) proposing clustering-based sampling strategies to increase the efficiency of landslide susceptibility maps over random selection methods, (ii) identifying and delineating effective landslide mapping units, (iii) proposing an innovative framework for comparing inventories and their corresponding susceptibility maps, and (iv) implementing a methodology for landslide-specific susceptibility mapping. Firstly, a comprehensive Gorkha earthquake-induced landslide inventory was initially compiled, and six unsupervised clustering algorithms were employed to generate six distinct training datasets. An additional training dataset was also prepared using a randomised approach. Among the tested algorithms, the Expectation Maximization using the Gaussian Mixture Model (EM/GMM) demonstrated the highest accuracy, confirming the importance of prioritising clustering patterns for training landslide inventory datasets. Secondly, slope units were introduced as an effective mapping unit for assessing landslides, delineating 112,674 slope unit polygons over an approximately 43,000 km2 area in Central Nepal. This is the first instance of generating such comprehensive mapping and making it publicly accessible. Thirdly, a comparison of five post-Gorkha earthquake inventories and susceptibility was conducted, revealing similarities in causative factors and map performance but variations in spatial patterns. Lastly, a rockfall inventory along two significant highways was developed as a landslide-classified inventory, and the rockfall susceptibility was evaluated. A segment-wise map with a 1 to 5 scale indicating low to high susceptibility was published for public use. This thesis proposes new approaches to landslide inventory sampling and earthquake-triggered landslide assessment. It provides publicly accessible databases for Central Nepal's slope unit map and rockfall susceptibility along the major highways. These findings can benefit researchers, planners, and policymakers to enhance risk management practices by advancing landslide assessment, particularly for earthquake-induced landslides in Central Nepal