Hazard Assessment of Debris-Flow along the Baicha River in Heshigten Banner, Inner Mongolia, China

被引:27
作者
Cao, Chen [1 ]
Xu, Peihua [1 ]
Chen, Jianping [1 ]
Zheng, Lianjing [2 ]
Niu, Cencen [1 ]
机构
[1] Jilin Univ, Coll Construct Engn, Changchun 130026, Peoples R China
[2] Changchun Sci Tech Univ, Construct Engn Coll, Changchun 130600, Peoples R China
关键词
3S technologies; cloud model; analytical hierarchy process; entropy method; LOGISTIC-REGRESSION; LANDSLIDE HAZARD; EXTENSION THEORY; RISK-ASSESSMENT; MASS-MOVEMENTS; SUSCEPTIBILITY; MODEL; BASIN; METHODOLOGY; INITIATION;
D O I
10.3390/ijerph14010030
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study focused on a cloud model approach for considering debris-flow hazard assessment, in which the cloud model provided a model for transforming the qualitative and quantitative expressions. Additionally, the entropy method and analytical hierarchy process were united for calculating the parameters weights. The weighting method avoids the disadvantages inherent in using subjective or objective methods alone. Based on the cloud model and component weighting method, a model was established for the analysis of debris-flow hazard assessment. There are 29 debris-flow catchments around the pumped storage power station in the study area located near Zhirui (Inner Mongolia, China). Field survey data and 3S technologies were used for data collection. The results of the cloud model calculation process showed that of the 29 catchments, 25 had low debris-flow hazard assessment, three had moderate hazard assessment, and one had high hazard assessment. The widely used extenics method and field geological surveys were used to validate the proposed approach. This approach shows high potential as a useful tool for debris-flow hazard assessment analysis. Compared with other prediction methods, it avoids the randomness and fuzziness in uncertainty problems, and its prediction results are considered reasonable.
引用
收藏
页数:19
相关论文
共 63 条
[1]  
[Anonymous], 1983, J. Sci. Explor
[2]  
[Anonymous], 1973, MULTIPLE CRITERIA DE
[3]  
[Anonymous], 2015, MATH PROBL ENG, DOI [DOI 10.1155/2015/892549, DOI 10.1155/2015/472917]
[4]  
[Anonymous], 2012, RES J APPL SCI ENG T
[5]   Comparing models of debris-flow susceptibility in the alpine environment [J].
Carrara, Alberto ;
Crosta, Giovanni ;
Frattini, Paolo .
GEOMORPHOLOGY, 2008, 94 (3-4) :353-378
[6]   Landslide hazard and risk mapping at catchment scale in the Arno River basin [J].
Catani, F ;
Casagli, N ;
Ermini, L ;
Righini, G ;
Menduni, G .
LANDSLIDES, 2005, 2 (04) :329-342
[7]   Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments [J].
Cavalli, Marco ;
Trevisani, Sebastiano ;
Comiti, Francesco ;
Marchi, Lorenzo .
GEOMORPHOLOGY, 2013, 188 :31-41
[8]   The application of genetic algorithm in debris flows prediction [J].
Chang, Tung-Chiung ;
Chien, Yue-Hone .
ENVIRONMENTAL GEOLOGY, 2007, 53 (02) :339-347
[9]   Risk degree of debris flow applying neural networks [J].
Chang, Tung-Chiung .
NATURAL HAZARDS, 2007, 42 (01) :209-224
[10]   Application of back-propagation networks in debris flow prediction [J].
Chang, Tung-Chueng ;
Chao, Ru-Jen .
ENGINEERING GEOLOGY, 2006, 85 (3-4) :270-280