Physically based landslide prediction over a large region: Scaling low resolution hydrological model results for high resolution slope stability assessment
Abstract Rainfall triggered shallow landslides are widespread natural hazards around the world, causing many damages to human lives and property. In this study, we focused on predicting landslides in a large region by coupling a 1 km resolution hydrological model and a 90 m resolution slope stability model, where a downscaling method for soil moisture via topographic wetness index was applied. The modeled hydrological processes show generally good agreements with the observed discharges: relative biases and correlation coefficients at three validation stations are all 0.60, respectively. The derived scaling law for soil moisture allows for near conservative downscaling of the original 1 km soil moisture to 90 m resolution for slope stability assessment. For landslide prediction, the global accuracy and true positive rate are 97.2% and 66.9% respectively. This study provides an effective and computationally efficient coupling method to predict landslides over large regions in which fine scale topographical information is incorporated.
Environ. Model. Softw.