Abstract

We present an index-based shallow landsliding susceptibility model which allows explicit incorporation of local heavy rainfall statistical properties. The model, called Quasi-Dynamic Shallow Landsliding Model (QD-SLaM), is developed upon a theory for coupled shallow subsurface flow and landsliding of the soil mantle. The model uses a ‘quasi-dynamic’ wetness index to predict the spatial distribution of soil saturation in response to a rainfall of specified duration, and can take into account the spatial variability of soil properties. The rainfall predicted to cause instability in each topographic element is characterized by intensity and duration. The incorporation of a scaling model for the rainfall frequency–duration relationship provides a parsimonious and robust way to include heavy rainfall statistical properties into shallow landsliding modeling. The model is used to determine the return period of the critical rainfall needed to cause instability for each topographic element. The model is validated over six different study sites, where detailed inventories of shallow landslides are available. Two study sites are located in the north of Taiwan, and four are located in the Italian Alps. The sites are characterized by different climates and by different duration of the landslide-triggering storms. Model results are evaluated against the surveyed landslides and compared to those obtained by using a steady-state model, resembling SHALSTAB. It is shown that QD-SLaM improves significantly over the steady-state approach in predicting existing landslides as represented in the considered landslide inventory. Moreover, the improvement is higher for the cases where the landslide-triggering storm duration is short with respect to the length of time required for every point on a catchment to reach subsurface drainage equilibrium. The results of our work highlight the capability of the model to incorporate a robust description of the heavy rainfall properties in the analysis and mapping of shallow landsliding susceptibility by using an index-style approach.

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