Mapping the susceptibility of rainfall and earthquake triggered landslides along China–Nepal highways

Abstract

The 2015 Gorkha earthquake (Mw = 7.8) caused significant earthquake triggered landslides (ETL) in a landscape that is heavily intervened by rainfall triggered landslides (RTL). China’s Belt and Road Initiative plan to boost South-Asian regional trade and mobility through two key highway corridors, i.e. 1) Longmu–Rasuwa–Kathmandu (LRK) and 2) Nyalam–Tatopani–Kathmandu (NTK) route, that dissect the Himalayas through this geologically unstable region. To understand the spatial characteristics and susceptibility of these ETL and RTL, we delineate the landslides by means of time variant satellite imageries, assess their spatial distribution and model their susceptibilities along the highway slopes. We use a coupled frequency ratio (FR) – analytical hierarchy process (AHP) model by considering nine landslide determinants, e.g. geomorphic type (slope, aspect, curvature, elevation), hydrologic type (erosive potential of gullies, i.e. stream power index and distance to streams), normalized difference vegetation index, lithology and civil structure type (i.e. distance to roads). The results demonstrate that elevation and slope predominantly control both these landslide occurrences. The model predicts locations of ETL with higher accuracy than RTL. On comparison, NTK was safer with 133.5 km2 of high RTL or ETL (or both) landslide susceptible areas, whereas LRK has 216.04 km2. For mapping the extent of these landslides, we constricted it to the slope units of highways to reduce the computational effort, but this technique successfully achieved an acceptable threefold average model prediction rate of 82.75% in ETL and 77.9% in RTL. These landslide susceptibility maps and route comparisons would provide guidance towards further planning, monitoring, and implementing landslide risk mitigation measures for the governments.