Flood Analysis of Subbasins Using WASPAS Model (Case Study: Aland Chai Basin, Northwest of Iran)

SWARA Multi-Criteria Decision Analysis model was used to weight the parameters. The Step-wise weight assessment ratio analysis (SWARA) model was developed by Keršuliene et al (2010). WASPAS multi-criteria decision-making model was used to prioritize sub-basins in terms of flood sensitivity. The Weighted Aggregated Sum Product Assessment (WASPAS) method is proposed by Zavadskas et al in 2012. The WASPAS method consists of two aggregated parts: 1- The Weighted Sum Model (WSM) and 2- The Weighted Product Model (WPM). According to a comparison between 22 parameters using the SWARA method, it was specified that Drainage texture, Texture ratio, and Drainage density (weighted as 0.273, 0.273 and 0.156) have the highest impacts on Flood occurrence in study area. On the contrary, Rho Coefficient, Constant of channel maintenance, Infiltration Number, and Length of overland flow show the lowest weight.Sub-basins prioritization results using WASPAS model showed that sub-basin 1 with 0.907778 coefficients, sub-basin 3 with a coefficient of 0.858988 and sub-basin 2 with a coefficient of 0.818645 have high sensitivity to flooding. The results also showed that sub-basins 4, 7, 11 and 15 in high class, sub-basins 8 and 9 in moderate class, sub-basins 5, 10, 12 and 14 in low class and sub-basins 6 and 13 in the very low class of In terms of flood sensitivity. The total area of sub-basins in the high and very high class of flood is 656.72 km2, which comprises 57.24% of the total Aland Chai basin.