TY - JOUR ID - 16747 TI - GIS-Based Flood Risk Zoning Based On Data-Driven Models JO - Journal of Hydraulic Structures JA - JHS LA - en SN - 2345-413X AU - Eslaminezhad, Seyed Ahmad AU - Eftekhari, Mobin AU - Akbari, Mohammad AD - Department of surveying and Geomatics Engineering, College of Engineering, University of Tehran, Tehran, Iran AD - Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran. AD - Department of Civil Engineering, University of Birjand, Birjand, Iran. Y1 - 2020 PY - 2020 VL - 6 IS - 4 SP - 75 EP - 98 KW - Flood risk KW - geographically weighted regression KW - Artificial neural network KW - binary particle swarm optimization algorithm DO - 10.22055/jhs.2021.36629.1163 N2 - Increasing the occurrence of floods, especially in cities, and the risks to human, financial, and environmental risks due to its, make flood risk zoning of great importance. The purpose of this study is to estimate the flood risk of the Maneh and Samalghan based on determining effective criteria and spatial and non-spatial data-driven models. The criteria used in this research include Modified Fournier Index, Topographic Position Index, Curve Number, Flow Accumulation, Slope, Digital elevation model, Topographic Wetness Index, Vertical Overland Flow Distance, Horizontal Overland Flow Distance, and Normalized difference vegetation index. The novelty of this study is to present new combination approaches to determine the effective criteria in flood risk zoning (Maneh and Samalghan). In this regard, the geographically weighted regression (GWR) with exponential and bi-square kernels and artificial neural network (ANN) combined with a binary particle swarm optimization algorithm (BPSO). The best value of the fitness function (1-R2) for ANN, GWR with the exponential kernel, and GWR with bi-square kernel was obtained 0.1757, 0.0461, and 0.0097, respectively, Which indicates higher compatibility of the bi-square kernel than the other models. It was also found that the criteria used have a significant effect on the rate of flooding in the study area. UR - https://jhs.scu.ac.ir/article_16747.html L1 - https://jhs.scu.ac.ir/article_16747_0bb7301d9e9d2a70bc6962954b1f912c.pdf ER -