A method for identifying critical displacement threshold of landslide step under combined effects of rainfall and reservoir water level
FENG Yu1，TU Pengfei1，2，ZENG Huaien1，2，3
(1. College of Civil Engineering and Architecture，China Three Gorges University，Yichang，Hubei 443002，China；2. Hubei Key Laboratory of Construction and Management in Hydropower Engineering，China Three Gorges University，Yichang，Hubei 443002，China；3. National Field Observation and Research Station of Landslides in the Three Gorges Reservoir Area of Yangtze River，Yichang，Hubei 443002，China)
Abstract：To overcome the deficiency of the current “step-type” landslide displacement prediction model，a new model is proposed to characterize the features of “step-type” landslides under the combined effects of rainfall and reservoir water level. The model first uses the Nishihara creep model to fit the trend term displacement of the landslide，and then obtains the step displacement through the sliding step identification method based on the adaptive Genetic Algorithm and the step displacement extraction method based on the Moving Average Algorithm. After the step displacement is extracted，the influencing factors of rainfall and reservoir water level are analyzed and selected，and the optimal comprehensive index of rainfall and reservoir water level under the best correlation is obtained utilizing the Particle Swarm Optimization(PSO) algorithm. Finally，the LOF(Local Outlier Factor) Algorithm is utilized to remove outliers of the data set，and the ADASYN(Adaptive Synthetic) Algorithm is utilized for oversampling. After binary classification by the Grasshopper Optimization Algorithm optimized Support Vector Machine(GOA-SVM)，the classification and prediction of landslide step displacement are realized. Taking the Baishuihe landslide as an example of “step-type” landslides，the data of monitoring point ZG118 in the typical step period from June 2003 to August 2009 are selected for research. The prediction results show that the overall prediction accuracy of the data set is 72.73%，the prediction accuracy of the step displacement data set is 100%，and the prediction accuracy of the data set without step displacement is 66.67%，It indicates good prediction performance. When rainfall and reservoir water level become the dominant factors of the occurrence of step-type landslide steps，this model provides new ideas and exploration for the prediction of such landslides.
冯 谕1，涂鹏飞1，2，曾怀恩1，2，3. 降雨及库水位共同作用下滑坡阶跃位移临界面的识别方法[J]. 岩石力学与工程学报, 2023, 42(11): 2788-2805.
FENG Yu1，TU Pengfei1，2，ZENG Huaien1，2，3. A method for identifying critical displacement threshold of landslide step under combined effects of rainfall and reservoir water level. , 2023, 42(11): 2788-2805.
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2023, Vol. 42 
