Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway
China–Nepal Highway is an important international passage connecting China and Nepal. Owing to its location in a complex mountainous area in the Qinghai– Tibet Plateau, the Shigatse section of the China–Nepal Highway is often impacted and troubled by mudflow. In order to effectively conduct road con...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2020-03-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2020-0004 |
| _version_ | 1818652902289309696 |
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| author | Xiao Liming Zhang Yonghong Ge Taotao Wang Chen Wei Ming |
| author_facet | Xiao Liming Zhang Yonghong Ge Taotao Wang Chen Wei Ming |
| author_sort | Xiao Liming |
| collection | DOAJ |
| description | China–Nepal Highway is an important international passage connecting China and Nepal. Owing to its location in a complex mountainous area in the Qinghai– Tibet Plateau, the Shigatse section of the China–Nepal Highway is often impacted and troubled by mudflow. In order to effectively conduct road construction and maintenance and improve early disaster-warning capability, the relationship between various hazard factors and disaster points was analysed. It is found that four factors such as slope, precipitation, soil type and digital elevation have the strongest correlation with the occurrence of the disasters. From the distribution of disaster points, it is observed that the disaster point is closely related to the slope, its local correlation with precipitation is good and the its local correlation with the soil type and Digital Elevation Model (DEM) data is significant. In order to quantitatively evaluate the susceptibility of mudflow disasters in the Shigatse region, this paper uses the analytic hierarchy process (AHP) as the main analysis method supplemented by the fuzzy clustering method. The results show that the slope, when accompanied by heavy rainfall, is the most important factor among four factors. In this paper, the neural network method is used to establish the identification and early warning model of mudflow susceptibility. When the recognition rate reaches 66% or above, it can be used as an early-warning threshold for mudflow disasters. This study has conducted a useful exploration of the research, assessment and early warning of mudflow disasters along the Shigatse section of the China–Nepal Highway. |
| first_indexed | 2024-12-17T02:29:23Z |
| format | Article |
| id | doaj.art-60bbf519a3a94017b16849f1a22cb08d |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-12-17T02:29:23Z |
| publishDate | 2020-03-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-60bbf519a3a94017b16849f1a22cb08d2022-12-21T22:07:00ZengDe GruyterOpen Geosciences2391-54472020-03-01121445810.1515/geo-2020-0004geo-2020-0004Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal HighwayXiao Liming0Zhang Yonghong1Ge Taotao2Wang Chen3Wei Ming4School of Automation, Nanjing University of Information Science and Technology, 210044Nanjing, ChinaSchool of Automation, Nanjing University of Information Science and Technology, 210044Nanjing, ChinaSchool of Automation, Nanjing University of Information Science and Technology, 210044Nanjing, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044Nanjing, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, 210044Nanjing, ChinaChina–Nepal Highway is an important international passage connecting China and Nepal. Owing to its location in a complex mountainous area in the Qinghai– Tibet Plateau, the Shigatse section of the China–Nepal Highway is often impacted and troubled by mudflow. In order to effectively conduct road construction and maintenance and improve early disaster-warning capability, the relationship between various hazard factors and disaster points was analysed. It is found that four factors such as slope, precipitation, soil type and digital elevation have the strongest correlation with the occurrence of the disasters. From the distribution of disaster points, it is observed that the disaster point is closely related to the slope, its local correlation with precipitation is good and the its local correlation with the soil type and Digital Elevation Model (DEM) data is significant. In order to quantitatively evaluate the susceptibility of mudflow disasters in the Shigatse region, this paper uses the analytic hierarchy process (AHP) as the main analysis method supplemented by the fuzzy clustering method. The results show that the slope, when accompanied by heavy rainfall, is the most important factor among four factors. In this paper, the neural network method is used to establish the identification and early warning model of mudflow susceptibility. When the recognition rate reaches 66% or above, it can be used as an early-warning threshold for mudflow disasters. This study has conducted a useful exploration of the research, assessment and early warning of mudflow disasters along the Shigatse section of the China–Nepal Highway.https://doi.org/10.1515/geo-2020-0004shigatse section of the china–nepal highwaymudflowdisaster analysisrisk assessmentearly warning model |
| spellingShingle | Xiao Liming Zhang Yonghong Ge Taotao Wang Chen Wei Ming Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway Open Geosciences shigatse section of the china–nepal highway mudflow disaster analysis risk assessment early warning model |
| title | Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway |
| title_full | Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway |
| title_fullStr | Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway |
| title_full_unstemmed | Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway |
| title_short | Analysis, Assessment and Early Warning of Mudflow Disasters along the Shigatse Section of the China–Nepal Highway |
| title_sort | analysis assessment and early warning of mudflow disasters along the shigatse section of the china nepal highway |
| topic | shigatse section of the china–nepal highway mudflow disaster analysis risk assessment early warning model |
| url | https://doi.org/10.1515/geo-2020-0004 |
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