Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment

Sheng Wang, Ke Zhang, Ludovicus P.H. van Beek, Xin Tian, Thom A. Bogaard

Research output: Contribution to journalArticleScientificpeer-review

29 Citations (Scopus)
12 Downloads (Pure)

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.

Original languageEnglish
Article number104607
Number of pages14
JournalEnvironmental Modelling and Software
Volume124
DOIs
Publication statusPublished - 2020

Keywords

  • Hydrological model
  • Infinite slope model
  • Landslide prediction
  • Scaling

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