Abstract
Abstract
Landslides are among the most significant natural hazards in the Himalayan region of India, causing substantial damage to infrastructure, natural resources, and local communities. This study presents an integrated hydro-geotechnical approach for regional landslide susceptibility assessment by combining statistical susceptibility mapping with slope stability evaluation. The proposed framework considers the influence of key hydrologic factors, including rainfall, drainage density, topographic wetness, and groundwater conditions, together with geotechnical properties to better explain the mechanisms controlling slope failure. Five bivariate statistical models, namely, frequency ratio (FR), information value (IV), weight of evidence (WoE), certainty factor (CF), and Shannon entropy (SE), were applied to produce landslide susceptibility maps. Their performance was evaluated using the area under the curve (AUC) and landslide density index (LDI). Among the evaluated models, SE achieved the highest predictive accuracy (
AUC
=
87.17
%
), followed closely by FR (87.06%). The results indicate that steep slopes (
>
30
°
), weak lithological formations, high drainage density, and groundwater conditions are the main factors controlling landslide occurrence in the study area. Slope stability was further evaluated using laboratory-derived geotechnical parameters and circular failure charts (CFC), providing an independent assessment of slope conditions under different groundwater scenarios. The combined use of statistical modeling, hydrologic factors, and geotechnical verification improves the reliability of landslide susceptibility assessment and provides a practical framework that can be applied in other mountainous regions affected by rainfall-induced landslides.