Journal ArticleDOI
Flood susceptibility mapping using frequency ratio and weights-of-evidence models in the Golastan Province, Iran
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In this article, the authors investigated the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran.Abstract:
Flood is one of the most devastating natural disasters with socio-economic and environmental consequences. Thus, comprehensive flood management is essential to reduce the flood effects on human lives and livelihoods. The main goal of this study was to investigate the application of the frequency ratio (FR) and weights-of-evidence (WofE) models for flood susceptibility mapping in the Golestan Province, Iran. At first, a flood inventory map was prepared using Iranian Water Resources Department and extensive field surveys. In total, 144 flood locations were identified in the study area. Of these, 101 (70%) floods were randomly selected as training data and the remaining 43 (30%) cases were used for the validation purposes. In the next step, flood conditioning factors such as lithology, land-use, distance from rivers, soil texture, slope angle, slope aspect, plan curvature, topographic wetness index (TWI) and altitude were prepared from the spatial database. Subsequently, the receiver operating characteristic...read more
Citations
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Journal ArticleDOI
A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.
Khabat Khosravi,Binh Thai Pham,Kamran Chapi,Ataollah Shirzadi,Himan Shahabi,Inge Revhaug,Indra Prakash,Dieu Tien Bui +7 more
TL;DR: Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively.
Journal ArticleDOI
An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines
Bahram Choubin,Bahram Choubin,Ehsan Moradi,Mohammad Golshan,Jan Adamowski,Farzaneh Sajedi-Hosseini,Amir Mosavi +6 more
TL;DR: In this paper, the authors employed two new algorithms for the first time in flood susceptibility analysis, namely multivariate discriminant analysis (MDA), and classification and regression trees (CART), incorporated with a widely used algorithm, the support vector machine (SVM), to create a flood susceptibility map using an ensemble modeling approach.
Journal ArticleDOI
Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms.
Seyed Vahid Razavi Termeh,Aiding Kornejady,Hamid Reza Pourghasemi,Saskia Keesstra,Saskia Keesstra +4 more
TL;DR: The ANFIS-PSO was found to be the most practical model in term of producing the highly focused flood susceptibility map with lesser spatial distribution related to highly susceptible classes, and was introduced as the premier model in the study area.
Journal ArticleDOI
A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making technique
TL;DR: In this paper, the authors used four models, namely frequency ratio (FR), weights-of-evidence (WofE), analytical hierarchy process (AHP), and ensemble of frequency ratio with AHP (FR-AHP) to compare them at Haraz Watershed in Mazandaran Province, Iran.
Journal ArticleDOI
Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.
Haoyuan Hong,Haoyuan Hong,Mahdi Panahi,Ataollah Shirzadi,Tianwu Ma,Tianwu Ma,Junzhi Liu,Junzhi Liu,A-Xing Zhu,A-Xing Zhu,Wei Chen,Ioannis Kougias,Nerantzis Kazakis +12 more
TL;DR: This paper addresses the development of a flood susceptibility assessment that uses intelligent techniques and GIS and an adaptive neuro-fuzzy inference system (ANFIS) was coupled with a genetic algorithm and differential evolution for flood spatial modelling.
References
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