부산대학교 도서관

Debris flow disasters occur frequently in Nyingchi City, Tibet. There is an urgent need to establish an early warning model to predict the possible areas of debris flow disasters in Nyingchi City and reduce the losses caused by those disasters. This paper presented an early warning model based on raster runoff simulation in Nyingchi City, which can simulate the water depth at each location in the watershed and improve the spatial pertinence of debris flow early warning. In this model, the disaster factors of debris flow are divided into background factor and excitation factor. The probability of debris flow disaster in Nyingchi City is obtained by logistic regression of many factors such as bare rock rate, vertical slope of riverbed and so on, which is used as the background factor. The raster runoff simulation model is introduced to simulate the predicted water depth at each position of the basin during the early warning period by importing the precipitation and snow water equivalent data. Using binary logistic regression method to calculate the weight of background factor and excitation factor, the final model is obtained. 18 historical disasters from 2011 to 2020 were used to verify the model. The disaster points falling into the early warning area accounted for 64.4%, which has certain guiding significance for the early warning of debris flow disaster in Nyingchi City.