Belt and Road Initiative(BRI) is a Chinese national strategy which calls for cooperative economic, political and cultural exchange at the global level along the ancient Silk Road. The overwhelming natural hazards loca...Belt and Road Initiative(BRI) is a Chinese national strategy which calls for cooperative economic, political and cultural exchange at the global level along the ancient Silk Road. The overwhelming natural hazards located along the belt and road bring great challenges to the success of BRI. In this framework, a 5-year international program was launched to address issues related to hazards assessment and disaster risk reduction(DRR). The first workshop of this program was held in Beijing with international experts from over 15 countries. Risk conditions on Belt and Road Countries(BRCs) have been shared and science and technology advancements on DRR have been disseminated during the workshop. Under this program, six task forces have been setup to carry out collaborative research works and three prioritized study areas have been established. This workshop announced the launching of this program which involved partners from different countries including Pakistan, Nepal, Russia, Italy, United Kingdom, Sri Lanka and Tajikistan. The program adopted the objectives of Sendai Framework for Disaster Risk Reduction 2015-2030 and United Nation Sustainable Development Goals 2030 and was implemented to assess disaster risk in BRCs and to propose suitable measures for disaster control which can be appropriate both for an individual country and for specific sites. This paper deals with the outcomes of the workshop and points out opportunities for the near future international cooperation on this matter.展开更多
Nepal was hit by a 7.8 magnitude earthquake on 25^(th) April,2015.The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal.We have developed a landslide susceptibility...Nepal was hit by a 7.8 magnitude earthquake on 25^(th) April,2015.The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal.We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork,using bivariate statistical model with different landslide causative factors.From the investigation,it is observed that most of the coseismic landslides are independent of previous landslides.Out of 3,716 mapped landslides,we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model.A total of 11 different landslide-influencing parameters were considered.These include slope gradient,slope aspect,plan curvature,elevation,relative relief,Peak Ground Acceleration(PGA),distance from epicenters of the mainshock and major aftershocks,lithology,distance of the landslide from the fault,fold,and drainage line.The success rate of 87.66% and the prediction rate of86.87% indicate that the model is in good agreement between the developed susceptibility map and theexisting landslides data.PGA,lithology,slope angle and elevation have played a major role in triggering the coseismic mass movements.This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.展开更多
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
基金supported by the International partnership program (Grant No.131551KYSB20160002)National Natural Science Foundation Major International (Regional) Joint Research Project (Grant No.41520104002)Science and Technology Service Network Initiative of Chinese Academy of Science (Grant No.KFJSTS-ZDTP-015)
文摘Belt and Road Initiative(BRI) is a Chinese national strategy which calls for cooperative economic, political and cultural exchange at the global level along the ancient Silk Road. The overwhelming natural hazards located along the belt and road bring great challenges to the success of BRI. In this framework, a 5-year international program was launched to address issues related to hazards assessment and disaster risk reduction(DRR). The first workshop of this program was held in Beijing with international experts from over 15 countries. Risk conditions on Belt and Road Countries(BRCs) have been shared and science and technology advancements on DRR have been disseminated during the workshop. Under this program, six task forces have been setup to carry out collaborative research works and three prioritized study areas have been established. This workshop announced the launching of this program which involved partners from different countries including Pakistan, Nepal, Russia, Italy, United Kingdom, Sri Lanka and Tajikistan. The program adopted the objectives of Sendai Framework for Disaster Risk Reduction 2015-2030 and United Nation Sustainable Development Goals 2030 and was implemented to assess disaster risk in BRCs and to propose suitable measures for disaster control which can be appropriate both for an individual country and for specific sites. This paper deals with the outcomes of the workshop and points out opportunities for the near future international cooperation on this matter.
基金the Chinese Academy of Sciences Presidents International Fellowship Initiative(Grant No.2015PEO23)External Cooperation Program of BIC,15 Chinese Academy of Sciences(Grant No.131551KYSB20150009)hundred talents program of Chinese Academy of Sciences(Su Lijun)for supporting for this research
文摘Nepal was hit by a 7.8 magnitude earthquake on 25^(th) April,2015.The main shock and many large aftershocks generated a large number of coseismic landslips in central Nepal.We have developed a landslide susceptibility map of the affected region based on the coseismic landslides collected from remotely sensed data and fieldwork,using bivariate statistical model with different landslide causative factors.From the investigation,it is observed that most of the coseismic landslides are independent of previous landslides.Out of 3,716 mapped landslides,we used 80% of them to develop a susceptibility map and the remaining 20% were taken for validating the model.A total of 11 different landslide-influencing parameters were considered.These include slope gradient,slope aspect,plan curvature,elevation,relative relief,Peak Ground Acceleration(PGA),distance from epicenters of the mainshock and major aftershocks,lithology,distance of the landslide from the fault,fold,and drainage line.The success rate of 87.66% and the prediction rate of86.87% indicate that the model is in good agreement between the developed susceptibility map and theexisting landslides data.PGA,lithology,slope angle and elevation have played a major role in triggering the coseismic mass movements.This susceptibility map can be used for relocating the people in the affected regions as well as for future land development.
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.