Citation

Xu, L., Yan, D., Zhao, T. (2021). Probabilistic evaluation of loess landslide impact using multivariate model. Landslides, 18: 1011-1023. Link to paper

Abstract

This paper addresses loess landslides on the Loess Plateau, the largest loess accumulation area in the world. While many methods have been developed to understand landslide mechanisms and identify susceptible regions, quantitative evaluation of the possible impact of potentially unstable slopes remains a gap, which is critical for risk management. This study fills this gap by constructing a comprehensive loess landslide database from field investigation, then developing a multivariate statistical model for loess landslide geometric parameters, including height, width, area, and length, while considering correlations among these parameters. The proposed method was applied to loess landslides in Baoji City, China, for illustration, and results demonstrate that the method works reasonably well. Key equations are provided using results from the multivariate model, allowing geotechnical engineers and decision-makers to evaluate the possible impact of a potentially unstable loess slope with minimal effort. This research provides a practical tool for probabilistic landslide impact assessment, enabling more informed decision-making in landslide risk management and mitigation planning in loess regions.

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