Flood susceptibility mapping using an improved analytic network process with statistical models

被引:55
作者
Yariyan, Peyman [1 ]
Avand, Mohammadtaghi [2 ]
Abbaspour, Rahim Ali [3 ]
Torabi Haghighi, Ali [4 ]
Costache, Romulus [5 ,6 ]
Ghorbanzadeh, Omid [7 ]
Janizadeh, Saeid [2 ]
Blaschke, Thomas [7 ]
机构
[1] Islamic Azad Univ, Saghez Branch, Dept Surveying Engn, Saghez, Iran
[2] Tarbiat Modares Univ, Coll Nat Resources, Dept Watershed Management Engn, Tehran, Iran
[3] Univ Tehran, Coll Engn, Sch Surveying & Geospatial Engn, Tehran, Iran
[4] Univ Oulu, Water Resources & Environm Engn, Oulu, Finland
[5] Univ Bucharest, Res Inst, Bucharest, Romania
[6] Natl Inst Hydrol & Water Management, Bucharest, Romania
[7] Univ Salzburg, Dept Geoinformat Z GIS, Salzburg, Austria
基金
奥地利科学基金会;
关键词
Flood mapping; analytic network process (ANP); statistical models; Saqqez City; MULTICRITERIA DECISION-MAKING; GEOGRAPHIC INFORMATION-SYSTEM; MACHINE LEARNING-METHODS; SPATIAL PREDICTION; RIVER MORPHOLOGY; HYBRID APPROACH; NATIONAL SCALE; HUGLI DISTRICT; WEST-BENGAL; RISK;
D O I
10.1080/19475705.2020.1836036
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Flooding is a natural disaster that causes considerable damage to different sectors and severely affects economic and social activities. The city of Saqqez in Iran is susceptible to flooding due to its specific environmental characteristics. Therefore, susceptibility and vulnerability mapping are essential for comprehensive management to reduce the harmful effects of flooding. The primary purpose of this study is to combine the Analytic Network Process (ANP) decision-making method and the statistical models of Frequency Ratio (FR), Evidential Belief Function (EBF), and Ordered Weight Average (OWA) for flood susceptibility mapping in Saqqez City in Kurdistan Province, Iran. The frequency ratio method was used instead of expert opinions to weight the criteria in the ANP. The ten factors influencing flood susceptibility in the study area are slope, rainfall, slope length, topographic wetness index, slope aspect, altitude, curvature, distance from river, geology, and land use/land cover. We identified 42 flood points in the area, 70% of which was used for modelling, and the remaining 30% was used to validate the models. The Receiver Operating Characteristic (ROC) curve was used to evaluate the results. The area under the curve obtained from the ROC curve indicates a superior performance of the ANP and EBF hybrid model (ANP-EBF) with 95.1% efficiency compared to the combination of ANP and FR (ANP-FR) with 91% and ANP and OWA (ANP-OWA) with 89.6% efficiency.
引用
收藏
页码:2282 / 2314
页数:33
相关论文
共 91 条
[31]   Forest Fire Susceptibility and Risk Mapping Using Social/Infrastructural Vulnerability and Environmental Variables [J].
Ghorbanzadeh, Omid ;
Blaschke, Thomas ;
Gholamnia, Khalil ;
Aryal, Jagannath .
FIRE-SWITZERLAND, 2019, 2 (03) :1-27
[32]   Spatial Prediction of Wildfire Susceptibility Using Field Survey GPS Data and Machine Learning Approaches [J].
Ghorbanzadeh, Omid ;
Kamran, Khalil Valizadeh ;
Blaschke, Thomas ;
Aryal, Jagannath ;
Naboureh, Amin ;
Einali, Jamshid ;
Bian, Jinhu .
FIRE-SWITZERLAND, 2019, 2 (03) :1-23
[33]   Sustainable Urban Transport Planning Considering Different Stakeholder Groups by an Interval-AHP Decision Support Model [J].
Ghorbanzadeh, Omid ;
Moslem, Sarbast ;
Blaschke, Thomas ;
Duleba, Szabolcs .
SUSTAINABILITY, 2019, 11 (01)
[34]   An interval matrix method used to optimize the decision matrix in AHP technique for land subsidence susceptibility mapping [J].
Ghorbanzadeh, Omid ;
Feizizadeh, Bakhtiar ;
Blaschke, Thomas .
ENVIRONMENTAL EARTH SCIENCES, 2018, 77 (16)
[35]   Multi-criteria risk evaluation by integrating an analytical network process approach into GIS-based sensitivity and uncertainty analyses [J].
Ghorbanzadeh, Omid ;
Feizizadeh, Bakhtiar ;
Blaschke, Thomas .
GEOMATICS NATURAL HAZARDS & RISK, 2018, 9 (01) :127-151
[36]  
Ha MH, 2017, ASIAN J SHIPPING LOG, V33, P105, DOI 10.1016/j.ajsl.2017.09.001
[37]  
Hölting B, 2019, SPR TXT EAR SCI GEOG, P33, DOI 10.1007/978-3-662-56375-5_5
[38]   Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China [J].
Hong, Haoyuan ;
Tsangaratos, Paraskevas ;
Ilia, Ioanna ;
Liu, Junzhi ;
Zhu, A-Xing ;
Chen, Wei .
SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 625 :575-588
[39]   Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran [J].
Janizadeh, Saeid ;
Avand, Mohammadtaghi ;
Jaafari, Abolfazl ;
Tran Van Phong ;
Bayat, Mahmoud ;
Ahmadisharaf, Ebrahim ;
Prakash, Indra ;
Binh Thai Pham ;
Lee, Saro .
SUSTAINABILITY, 2019, 11 (19)
[40]   A new approach to flood susceptibility assessment in data-scarce and ungauged regions based on GIS-based hybrid multi criteria decision-making method [J].
Kanani-Sadat, Yousef ;
Arabsheibani, Reza ;
Karimipour, Farid ;
Nasseri, Mohsen .
JOURNAL OF HYDROLOGY, 2019, 572 :17-31