ABSTRACT Landslides require timely prediction to minimize losses. However, predicting first‐time slope failures remains difficult as the associated hazards are often unknown. This study investigates the Bwasni landslide, a first‐time slope failure triggered by extreme rainfall on 14 August 2023 in the Solan district of Himachal Pradesh, India. This landslide affected an area of 2.83 × 10 5 m 2 and occurred in an area previously mapped as low susceptible terrain. Therefore, to understand the causes of this unexpected failure and its post‐event behavior, copula based probabilistic slope stability modeling and time‐series Interferometric Synthetic Aperture Radar (InSAR) analysis with wavelet methods have been applied. The slope stability results show that the mean Probability of Failure ( P f ) increased from 0.06 under dry conditions to 0.21 under saturated conditions. The results also indicate multiple localized failures within the landslide, where extreme rainfall mobilized the displaced debris and destroyed approximately 40 houses along the runout path. Likewise, wavelet analysis shows that pre‐failure deformation was largely controlled by antecedent rainfall. Although, time‐series InSAR results reveal ongoing post‐failure deformation with a mean velocity of 22 mm per year. These findings show that prolonged rainfall can initiate slope instability, whereas extreme rainfall events can act as the trigger. Thus, the study underscores the importance of accounting for both rainfall accumulation and extreme events in landslide hazard assessment, and highlights the need for continuous deformation monitoring to minimize future risks.
Das et al. (Tue,) studied this question.