Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and...Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.展开更多
The assessment of rainfall-induced shallow landslide hazards is a significant issue in the Three Gorges Reservoir area in China due to the rapid development of land in the past two decades. In this study, a probabilis...The assessment of rainfall-induced shallow landslide hazards is a significant issue in the Three Gorges Reservoir area in China due to the rapid development of land in the past two decades. In this study, a probabilistic analysis method that combines TRIGRS and the point-estimate method for evaluating the hazards of shallow landslides have been proposed under the condition of rainfall over a large area. TRIGRS provides the transient infiltration model to analyze the pore water pressure during a rainfall. The point-estimate method is used to analyze the uncertainty of the soil parameters, which is performed in the geographic information system(GIS). In this paper, we use this method to evaluate the hazards of shallow landslides in Badong County,Three Gorges Reservoir, under two different types of rainfall intensity, and the results are compared with the field investigation. The results showed that the distribution of the hazard map is consistent with the observed landslides. To some extent, the distributionof the hazard map reflects the spatial and temporal distribution of the shallow landslide caused by rainfall.展开更多
Landslides are increasing since the 1980s in Xi'an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of ste...Landslides are increasing since the 1980s in Xi'an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall(IR) and antecedent effective rainfall(AER). Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; "A" region is safe, "B" region is on watch alert, "C" region is on warning alert and "D" region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi'an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi'an region.展开更多
文摘Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang–Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping(LSM) of this region was carried out using frequency ratio(FR) and weights-of-evidence(W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226(70%) were randomly selected for model training and the remaining 106(30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified andcompared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region(W of E model(success rate = 83.39%, prediction rate = 79.59%); FR model(success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.
基金The National Natural Science Foundation of China(SN:41572292)the follow-up work of geological disaster prevention projects in Three Gorges Reservoir supported the research in thispaper(SN:0001212015CC60005)
文摘The assessment of rainfall-induced shallow landslide hazards is a significant issue in the Three Gorges Reservoir area in China due to the rapid development of land in the past two decades. In this study, a probabilistic analysis method that combines TRIGRS and the point-estimate method for evaluating the hazards of shallow landslides have been proposed under the condition of rainfall over a large area. TRIGRS provides the transient infiltration model to analyze the pore water pressure during a rainfall. The point-estimate method is used to analyze the uncertainty of the soil parameters, which is performed in the geographic information system(GIS). In this paper, we use this method to evaluate the hazards of shallow landslides in Badong County,Three Gorges Reservoir, under two different types of rainfall intensity, and the results are compared with the field investigation. The results showed that the distribution of the hazard map is consistent with the observed landslides. To some extent, the distributionof the hazard map reflects the spatial and temporal distribution of the shallow landslide caused by rainfall.
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 41130753 and 41202244)the National Key Fundamental Research Program of China (973) (Grant No. 2014CB744703)China Postdoctoral Science Foundation (Grant No. 2012M521728)
文摘Landslides are increasing since the 1980s in Xi'an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall(IR) and antecedent effective rainfall(AER). Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; "A" region is safe, "B" region is on watch alert, "C" region is on warning alert and "D" region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi'an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi'an region.
