Abstract
An early warning system can effectively reduce the damage caused by landslides. To study the change law of hydrological indexes with the evolution process, a rainfall-induced landslide model test was carried out. The changes of volumetric moisture content, matrix suction, and pore water pressure with time were obtained. It was shown that the volumetric moisture content maintained the maximum value before failure, and the pore water pressure increased; at the same time, the failure was accompanied by a sudden change of volumetric moisture content. Pore water pressure and volumetric moisture content are usually used as indicators for landslide early warnings. In many cases, a slope stability model based on pore water pressure is better than that based on volumetric moisture content. However, heavy rainfall sometimes causes failure after a small amount of positive pore water pressure forms. It is difficult to explain this instability using a traditional slope stability model; therefore, we established a model that focused on volumetric moisture content and its variation over time and early warning thresholds for two landslides with different permeabilities. The early warning model proposed in this study can be applied reliably for landslides not triggered by positive pore water pressure and provide early warning for slope instabilities triggered in saturated conditions or with low pore water pressure.
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Funding
This work was financed by the China Geological Survey (No. DD20190716 and No. 377 0001212020CC60002), the 111 Project of Hubei Province (Grant Number 2021EJD026), the Open Fund of Badong National Observation and Research Station of Geohazards (No. BNORSG-202207) and the National Foundation of China (No. 42107489, U21A2031). The first author received financial support for this research from the Research Fund for Excellent Dissertation, China’s Three Gorges University (No. 2021BSPY006).
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Zhan, Q., Wang, S., Guo, F. et al. Early warning model and model test verification of rainfall-induced shallow landslide. Bull Eng Geol Environ 81, 318 (2022). https://doi.org/10.1007/s10064-022-02827-4
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DOI: https://doi.org/10.1007/s10064-022-02827-4