Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment. (February 2020) - Wang, Sheng; Zhang, Ke; van Beek, Ludovicus P.H.; Tian, Xin; Bogaard, Thom A.
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 <20% and >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. Highlights: Downscaling soil moisture using topographical attributes. Coupling hydrological model and slope stability model with different spatial resolutions. Developed a useful and efficient method to conduct landslide hazard prediction. The coupled model is more robust than the conventional rainfall threshold method.