Landslide susceptibility mapping by using GIS along the China–Pakistan economic corridor (Karakoram Highway), Pakistan

Abstract

Abstract. The Karakoram Highway (KKH), as part of the China-Pakistan Economic Corridor (CPEC), connects Northern Pakistan with Western China. KKH passes through the actively rising mountain ranges of Himalaya, Karakoram and Hindu Kush, forming the junction between the Indian and Eurasian plates, including Kohistan Island Arc. The area is characterized by fractured and weathered rockmass, diverse lithologies (igneous, metamorphic, and sedimentary), high seismicity, deep gorges, high relief, arid to Monsoon climate and locally high rates of tectonic activity. These conditions make the study area a unique geohazards laboratory. Starting with its construction in 1979, KKH's stability has been endangered by a variety of geohazards. In that regard, landslides constitute an appreciable threat, having blocked KKH for several times. Therefore, landslide susceptibility mapping was carried out in this study, to support highway authorities in maintaining smooth and hazard free travelling. Geological and geomorphological data were collected and processed using Arc GIS 10.3. Different conditioning and triggering factors for landslide occurrences were considered for preparation of the susceptibility map. These factors include lithology, seismicity, rainfall intensity, faults, elevation, slope angle, aspect, curvature, land cover and hydrology. According to spatial and statistical analyses, active faults, seismicity and slope angle mainly control the spatial distribution of landslides. Each controlling parameter was assigned a numerical weight by utilizing the Analytic Hierarchy Process (AHP) method. Additionally, the weighted overlay method (WOL) was employed to determine landslide susceptibility indices. As a final result, the landslide susceptibility map was produced. In the map, KKH was subdivided into four different susceptibility zones. Some sections of the highway fall into high to very high susceptibility zones. According to results, active faults, slope gradient, seismicity and lithology have a strong influence on landslide events. Credibility of the map was validated by landslide density analysis (LDA) and receiver operator characteristics (ROC), yielding a predictive accuracy of 72 % which is rated sufficient for mitigation planning.