Earth, Atmosphere & Environment Sciences

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Landslides are significant natural disasters causing significant loss of life and property. Kerala has experienced the highest number of landslides in India over the past seven years. Climate change may alter precipitation type and frequency. Landslide hazard assessments can be performed by evaluating spatial and temporal probabilities of landslide occurrences. This research project aims to develop landslide hazard maps of different locations in Kerala by integrating LSMs and LP in a non-stationary framework. The project also aims to develop a ready reference hazard assessment tool.

This study proposes a novel framework for developing landslide hazard maps in the Western Ghats of Kerala, India, considering non-stationarity in rainfall due to climate change and multisite rainfall information. The methodology includes developing a landslide susceptibility map using machine learning, creating a landslide hazard map using stationary and non-stationary analysis, and determining the probability of landslide occurrence using the Copula technique. The methodology is aligned with different objectives and provides a flow chart for the overall proposal.

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