Abstract
Slope units is an effective mapping unit for rainfall landslides prediction at regional scale. At present, slope units extracted by hydrology and morphological method report very different morphological feature and boundaries. In order to investigate the effect of morphological difference on the prediction performance, this paper presents a general landslide probability analysis model for slope units. Monte Carlo method was used to describe the spatial uncertainties of soil mechanical parameters within slope units, and random search technique was performed to obtain the minimum safety factor; transient hydrological processes simulation was used to provide key hydrological parameters required by the model, thereby achieving landslide prediction driven by quantitative precipitation estimation and forecasting data. The prediction performance of conventional slope units (CSUs) and homogeneous slope units (HSUs) were analyzed in three case studies from Fengjie County, China. The results indicate that the mean missing alarm rate of CSUs and HSUs are 31.4% and 10.6%, respectively. Receiver Operating Characteristics (ROC) analysis also reveals that HSUs is capable of improving the overall prediction performance, and may be used further for rainfall-induced landslide prediction at regional scale.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant No. 42271013) and the Chongqing Municipal Bureau of Land, Resources and Housing Administration (Grant No. KJ-2022033), the Young Scholar Training Program of Zhongyuan University of technology (Grant No. 2020XQG13), the strength improvement plan of the advantageous disciplines of Zhongyuan University of Technology (Grant No. SD202231), Natural Science Foundation Project of Zhongyuan University of Technology (Grant No. K2023QN008) and the Science and Technology Support Program of Sichuan Province (2021YFG0258). This work was also supported by the funding of the National Natural Science Foundation of China (Grant No. 41972292), the Innovation Capability Support Program of Shaanxi Province (Grant No. 2021TD-54), the Key Research and Development Program of Shaanxi Province (Grant No. 2022ZDLSF06-03).
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Wang, K., Zhang, Sj., Xie, Wl. et al. Prediction of the instability probability for rainfall induced landslides: the effect of morphological differences in geomorphology within mapping units. J. Mt. Sci. 20, 1249–1265 (2023). https://doi.org/10.1007/s11629-022-7789-4
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DOI: https://doi.org/10.1007/s11629-022-7789-4