Abstract Landslides are one of the common geological hazards in the hilly regions throughout the world. Other than geological, morphological and anthropogenic causes, precipitation is the most common triggering factor for the occurrence of landslides. Rainfall-induced landslides are the result of the combined action of precipitation on topography, geology, soil and vegetation. Soil moisture and rainfall are intervened with each other. Forecasting landslides based on soil moisture is very difficult because mainly other geological and geomorphological parameters play quite a dominant role. However, in this study we analyse the soil moisture before and during landslides at three places (Solan, Shimla, Mandi) in Himachal Pradesh, India, which happened on 14 august 2023 after heavy rainfall. This study compares the various models, observations and reanalysis datasets available and assesses the various components of hydro-meteorological factors leading towards potential prediction of landslides. Model forecast is predicting an increase in soil moisture for the day when landslide occurred; therefore soil moisture forecast can be used in landslide early warning system.
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Fatima et al. (2024) studied this question.
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