Physically-based landslide prediction over a large region
Scaling low-resolution hydrological model results for high-resolution slope stability assessment
Sheng Wang (Hohai University, TU Delft - Water Resources)
Ke Zhang (Hohai University)
Rens Van Beek (Universiteit Utrecht)
X. Tian (TU Delft - Water Resources)
T.A. Bogaard (TU Delft - Water Resources)
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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.