Landslide risk assessment based on susceptibility and vulnerability

被引:16
作者
Mosaffaie, Jamal [1 ]
Jam, Amin Salehpour [1 ]
Sarfaraz, Faramarz [2 ]
机构
[1] Agr Res Educ & Extens Org AREEO, Soil Conservat & Watershed Management Res Inst SCW, 10Th Km,Karaj Special Rd,Shahid Asheri St,Shahid S, Tehran, Iran
[2] Qazvin Agr & Nat Resources Res & Educ Ctr, Tehran, Iran
关键词
Landslide risk; Zonation; Density ratio; Quality sum; Alamut; FREQUENCY RATIO; FUZZY; GIS; MANAGEMENT;
D O I
10.1007/s10668-023-03093-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The aim of this study was to map the landslide risk at the Alamut watershed based on relative vulnerability and susceptibility. The potential of damage to the resources was considered landslide vulnerability. The fuzzy gamma operators were also used to assess landslide susceptibility. Thematic layers of 10 causal factors including slope, aspect, altitude, land use, lithology, distance to road, distance to stream, distance to fault, peak ground acceleration and mean annual precipitation were prepared. The landslide inventory map comprising 40 landslides covering 1417 hectares was partitioned into two subsets including 70% for training and 30% for testing. The Dr and Qs indices were applied to compare the validity of the landslide susceptibility maps. The spatial landslide risk was obtained by multiplying the landslide susceptibility and landslide vulnerability. The results show that the LSM derived by gamma of 0.95 has the most validity with Qs equal to 1.93. The ascending trend of the Dr index for low to high classes implies the correct classification of the LSM. The most important role in the occurrence of landslides has been related to lithology and land use factors. Although residential areas cover a small area of the watershed, 84.35% of the very high-risk class and 91.21% of the high-risk class are located in these areas. These results imply that in the Alamut watershed, the principles of land use planning have not been considered for landslide management. Therefore, the results of this study can be very useful for landslide risk management in the region.
引用
收藏
页码:9285 / 9303
页数:19
相关论文
共 50 条
[31]   Comparison of GIS-based methodologies for the landslide susceptibility assessment [J].
Magliulo, Paolo ;
Di Lisio, Antonio ;
Russo, Filippo .
GEOINFORMATICA, 2009, 13 (03) :253-265
[32]   A frequency ratio–based sampling strategy for landslide susceptibility assessment [J].
Lei-Lei Liu ;
Yi-Li Zhang ;
Ting Xiao ;
Can Yang .
Bulletin of Engineering Geology and the Environment, 2022, 81
[33]   Landslide susceptibility assessment on the left side of the Izvorul Muntelui Lake bank, Romania [J].
Codru, Ionut-Costel ;
Niacsu, Lilian .
PRESENT ENVIRONMENT AND SUSTAINABLE DEVELOPMENT, 2022, 16 (01) :5-21
[34]   Comparison of GIS-based methodologies for the landslide susceptibility assessment [J].
Paolo Magliulo ;
Antonio Di Lisio ;
Filippo Russo .
GeoInformatica, 2009, 13 :253-265
[35]   Landslide susceptibility assessment using Information Value Method in parts of the Darjeeling Himalayas [J].
Sarkar, Shraban ;
Roy, Archana K. ;
Martha, Tapas R. .
JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA, 2013, 82 (04) :351-362
[36]   A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment [J].
Ba, Qianqian ;
Chen, Yumin ;
Deng, Susu ;
Yang, Jiaxin ;
Li, Huifang .
EARTH SCIENCE INFORMATICS, 2018, 11 (03) :373-388
[37]   Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment [J].
Sameen, Maher Ibrahim ;
Pradhan, Biswajeet ;
Lee, Saro .
CATENA, 2020, 186
[38]   Evaluation of neural network models for landslide susceptibility assessment [J].
Yi, Yaning ;
Zhang, Wanchang ;
Xu, Xiwei ;
Zhang, Zhijie ;
Wu, Xuan .
INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2022, 15 (01) :934-953
[39]   Quantitative assessment of landslide susceptibility on the Loess Plateau in China [J].
Ma, Shuyue ;
Qiu, Haijun ;
Hu, Sheng ;
Pei, Yanqian ;
Yang, Wenlu ;
Yang, Dongdong ;
Cao, Mingming .
PHYSICAL GEOGRAPHY, 2020, 41 (06) :489-516
[40]   The application of DInSAR and Bayesian statistics for the assessment of landslide susceptibility [J].
Kouhartsiouk, Dimitris ;
Perdikou, Skevi .
NATURAL HAZARDS, 2021, 105 (03) :2957-2985