| Debris flow is a common geological disaster in mountainous areas. Debris flows are widely distributed all over the world and they are frequently seen in China. The population density is high in the mountainous area of Beijing and the local residents’ life and property safety is under serious threat of debris flow disasters. The prediction and early warning research of debris flow of Nanjiao can provide early warning information for local residents and visitors. Therefore, the prediction and early warning research of debris flow is of great academic significance and practical value.In this paper, we took Nanjiao watershed in Fangshan District as the research object. On the basis of field survey, we studied the type of debris flow, disaster ability, development stages and prone degree of debris flow. In this study we chose eleven factors for debris flow hazard analysis. Analytic hierarchy process(AHP) and entropy method were performed to obtain subjective and objective weighting of the factors, respectively. Game theory was carried out to determine the combination weighting since it provides analytical tools to model interactions among factors. An improved fuzzy C-means clustering analysis was applied to determine the susceptibility level of debris flows. This method is based on a Gravitational Search algorithm, which is an evolutionary algorithm that can achieve global optimization, and is not sensitive to the initial cluster centers. Finally we acquired the debris flow hazard classification results for main tributaries of Nanjiao catchment. Base on Arc GIS, we also carried out hazards zoning, vulnerability zoning, and risk zoning. Medium and long term prediction for debris flows in the main tributaries of Nanjiao catchment includes field geological description, debris flow feature evaluation, debris flow hazard assessment and debris flow’s risk zoning.Debris flow short-term and impending warning system was put forward in this study. This system includes short-term warning and impending warning. Short-term warning is a warning to the deterioration of the weather conditions, and the impending warning refers to the beginning of the rain fall until the warning is relieved. In view of the complex process of rainfall, the concept of "a process of rainfall" was proposed. By recording the rainfall data, calculating the total amount of the total rainfall in a certain area, we can acquire continuous warning model with a precision at 1 min. We calculated the antecedent effective rainfall by using the improved antecedent rainfall attenuation function. Then historical rainfall data and debris flow disaster data were used to establish the total amount of rainfall critical line. To gain more time for target users, we drawn four levels(red, orange, yellow and blue) of warning line under the critical line. Through the wireless sensor network monitoring platform, real-time data of rainfall, typical source water content, pore water pressure, debris flow infrasound signals, mud depth information, debris flow video images and other data of Nanjiao catchment were obtained. During "a process of rainfall", the total amount of antecedent effective rainfall and short-term rainfall were calculated. The warning system can publish corresponding level of warning information basing on the location of the coordinates point on the chart of total rainfall critical line.The main conclusions of this paper are as follows:1. Human activity intensity of Nanjiao watershed is high. In the basin, it is visible of material caving of road slope, small landslides caused by terrace disrepair, as well as a large number of coal gangue. In view of this characteristic, the method considering newly increased source of slope, terrace, and coal gangue’s quantity was proposed. Through the debris flow characteristics of discrimination, we get the mainstream and main tributaries comprehensive activity intensity: weak ~ strong, disaster-causing capacity: weak ~ strong, development stage: recession, and debris flow prone degrees belong to mild prone level.2. This study chose eleven factors for debris flow hazard analysis. Analytic hierarchy process(AHP) and entropy method were performed to obtain subjective and objective weighting of the factors, respectively. Game theory was carried out to determine the combination weighting. An GSA improved fuzzy C-means clustering analysis was applied to determine the susceptibility level of debris flows. Results showed that the hazard levels for Beian and Zuozhigoutwo debris flow catchments were high, Zuozhigouone and Sanhecun catchments were moderate, and Maoershan, Nangang, and Shuiyu catchments were low. Basing on Arc GIS, we carried out risk zoning of Nanjiao catchment. Results showed that, the risks of the regions away from mainstream were low, while both sides of the mainstream were vulnerable to the debris flows, and the risk of the village was higher.3. In view of the complex process of rainfall, the concept of "a process of rainfall" was proposed. The antecedent effective rainfall was calculated by using the improved antecedent rainfall attenuation function. Historical rainfall data and debris flow disaster data were used to establish the total amount of rainfall critical line. To gain more time for target users, we drawn red, orange, yellow and blue, totally four levels of warning lines under the critical line. By recording the rainfall data, calculating the total amount of the total rainfall in a certain area, we can acquire a continuous warning model. Through the wireless sensor network monitoring platform, rainfall, typical source water content, pore water pressure, debris flow infrasound signals, mud depth information, debris flow video images and other data of Nanjiao catchment were obtained. We can acquire the goal of building a warning system which can stepwisely response for debris flow, from the short-term warning referring to deterioration of the weather condition, to the impending warning referring to total rainfall critical line and auxiliary equipment. |
PDF Full Text Request