SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
Keywords: Rainfall debris flow, Analytic Hierarchy Process, Binary Logistic Regression, Random Forest, Certainty factor model, Susceptibility
Abstract. The lower reaches of the Yajiang River are high in the east and low in the west, with abundant rainfall, and contain a large amount of hydropower resources that have not been exploited and utilized. Nonetheless, due to the unique geographical environment in southeast Tibet, rainfall debris flow is one of the frequent geological disasters in this area. In this research, 42 debris flow points were collected, ten disaster-causing factors were selected, and satellite elevation data were analyzed to evaluate the disaster susceptibility of the study area. The disaster-causing factors information is extracted from Arcgis. The certainty factor model (CF) was used to calculate the coefficient of certainty of 10 factors including fault distance, elevation, normalized difference vegetation index (NDVI), average annual rainfall, profile curvature, relief, silt content, TWI, SPI, and slope aspect. The Analytic Hierarchy Process (AHP), Binary Logistic Regression (LR), Random Forest (RF) and CF model were used to analyze and predict the possibility of debris flow occurrence. The results show that the accuracy of the CF-LR model is the highest under the verification of the ROC curve. In the prediction model, the high-risk areas of debris flow are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. After bringing the data of different annual rainfall into the model, it is found that the saturation critical value of debris flow water source in the study area is within the range of 600–700mm annual rainfall.