Flood zoning using fuzzy analysis (case study: Sari city)

Every year we see natural disasters causing major financial and human losses to human societies, and unfortunately, our country also has a bitter taste of it every now and then. Floods, earthquakes, droughts, frostbites, storms, and so on ... There are a lot of financial and financial losses to the country, which will require measures to reduce the damage caused by these disasters. Definitely, the first step is to understand and understand these phenomena. The development of the process of urbanization and degradation of vegetation, soil erosion, and global climate change has already paid attention to the importance of addressing the issue of the urban flood. This research was carried out to determine the risk of flooding in Sari using multi-criteria decision-making techniques. Using nine criteria, the distance from the river, runoff coefficient, CN coefficient, population density, residential density, slope, land use, the age of the building and outdoor space were developed. By preparing the required layers, determining the weight of each layer based on their importance in the occurrence of a flood. After the final weighing, the layers were compared in two to two by Expert Choice software and the matrices derived from these comparisons were transferred to Idrisi software and the final coefficient was determined for each layer. Finally, by applying these coefficients, ArcGIS software provided a flood risk zoning map in the city of Sari. The results show that flood risk in the center and south of the city has been the highest. Flood risk zoning map shows that 12.24% of the map area is in a very high danger zone and 37.05% in very low-risk zoning. To reduce the risk of retrofitting buildings around the river to reduce flood damage.