Reservoir-landslide is mainly caused by changes in hydrodynamic conditions of slope interior at the time of water storage or discharge. The current study mainly focuses on the typical reservoirlandslide, but the sudde...Reservoir-landslide is mainly caused by changes in hydrodynamic conditions of slope interior at the time of water storage or discharge. The current study mainly focuses on the typical reservoirlandslide, but the sudden occurrence of some unknown landslides brought a lot of difficulties for hazards prevention. Therefore, we proposed a method to evaluate the regional scale reservoir-landslide hazard. We took Wanzhou section of Three Gorges Reservoir(China) as the study area and systemically and synthetically carried out the reservoir-landslide hazard evaluation under the condition of water level regulation. Firstly, we made reservoir-landslide susceptibility assessment by using the methods of spatial analysis and statistics based on geological and geomorphological materials and field survey data, and then, analyzed the regional-scale slope stability based on the infinite slope model used to analyze the bank slope stability change under the condition of water fluctuation, finally, developed a reservoir-landslide hazard evaluation model based on the results of susceptibility and stability. The hazard evaluation model was used to predict and evaluate the hazard change under the role of water level regulation. The results showed that the landslide hazard of the whole region decreased during water storage, landslide hazards increased during water discharge. The faster the regulation speed, the greater the slope hazard. The results can provide the basis for hazard management and regional land-use planning.展开更多
Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification techniq...Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan＇an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves（AUC） in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.展开更多
基金supported by the International Cooperation Program of the Ministry of Science and Technology of China (Grant No. 2013DFA21720)the National Science & Technology Support Program during the Twelfth Five-Year Plan Period (Grant No. 2011BAK12B01)
文摘Reservoir-landslide is mainly caused by changes in hydrodynamic conditions of slope interior at the time of water storage or discharge. The current study mainly focuses on the typical reservoirlandslide, but the sudden occurrence of some unknown landslides brought a lot of difficulties for hazards prevention. Therefore, we proposed a method to evaluate the regional scale reservoir-landslide hazard. We took Wanzhou section of Three Gorges Reservoir(China) as the study area and systemically and synthetically carried out the reservoir-landslide hazard evaluation under the condition of water level regulation. Firstly, we made reservoir-landslide susceptibility assessment by using the methods of spatial analysis and statistics based on geological and geomorphological materials and field survey data, and then, analyzed the regional-scale slope stability based on the infinite slope model used to analyze the bank slope stability change under the condition of water fluctuation, finally, developed a reservoir-landslide hazard evaluation model based on the results of susceptibility and stability. The hazard evaluation model was used to predict and evaluate the hazard change under the role of water level regulation. The results showed that the landslide hazard of the whole region decreased during water storage, landslide hazards increased during water discharge. The faster the regulation speed, the greater the slope hazard. The results can provide the basis for hazard management and regional land-use planning.
基金Projects(41362015,51164012) supported by the National Natural Science Foundation of ChinaProject(2012AA061901) supported by the National High-tech Research and Development Program of China
文摘Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan＇an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves（AUC） in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.
