A study on the early-warning technique concerning debris flow disasters

作     者：ZHOU Jinxing, WANG Lixian, XIE Baoyuan, FEI Shimin, WANG Xilin (1. Inst. of Forestry Research, Chinese Academy of Forestry Science, Beijing 100091, China 2. College of Resource & Environment, Beijing Forestry University, Beijing 100083, China) 

作者机构：Inst of Forestry Research Chinese Academy of Forestry Science 北京 100091 College of Resource & Environment Beijing Forestry University 北京 100083 

出 版 物：《Journal of Geographical Sciences》 (地理学报（英文版）)

年 卷 期：2002年第12卷第3期

页      面：363-370页

核心收录：

学科分类：08[工学] 0837[工学-安全科学与工程] 

基　　金：Fund by the Ministry of Science and Technology, No.2002BA516A17 Foundation of Chinese Academy of Forestry Science, No.200114 

主　　题：debris flows disaster early-warning technique torrent classification mapping of the hazard zones 

摘      要：According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN) real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system’s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type