EXTENDED ABSTRACT
Introduction: Flood is one of the most important natural hazards that has increased in recent years, especially in Iran, and has caused a lot of human and financial losses. Human factors such as construction in flood plains, non-respect of river boundaries, and climate changes have contributed to the aggravation of these damages. Ahar Chai watershed, due to its importance in supplying agricultural products and drinking water, requires careful management of flooding during floods. Therefore, zoning and identifying vulnerable areas is necessary to take appropriate measures
Methodology: In the present study, after determining the control layer or the target of the study, which in the present study is the flood potential of the Ahar Chai watershed, in the next step, the target criteria were determined, and in the present study, 12 criteria are among the factors affecting the phenomenon of flooding, including drainage density, slope, CN, NDVI index, land use, precipitation and runoff with different return periods, land capability, distance from waterways, geology were considere. In the following, different watershed sub-basins that are proposed as options in the present study were selected and in order to weight the criteria and options using network analysis and hierarchical analysis in the environment of Super Decision software version 3.2, which is a decision support software. , was employed. In the following, in order to check the potential of flooding in the position of each piscal in the watershed, the operator and fuzzy functions were used.
Results and Discussion: The current research investigated the risk of flooding in the AharChai watershed. In this study, nine factors affecting flooding were identified and evaluated by weighting the criteria using the network analysis method. This method, unlike the hierarchical analysis of the criteria or options, was also compared to each other for That is why the results of network analysis are preferable. In the present study, the results show that the runoff and the distance from the waterway are known as the main factors affecting the flood potential, although the runoff factor does not have such an effect in the return period of 2 or 10 years, but in the period of higher returns, this factor has a significant effect, which in this research The average face is mentioned. Also, subbasin 3 and 5 were identified as the most risky areas because these watershed subbasin are dependent, meaning they include the upstream runoff. Also, the sensitivity analysis showed that the runoff parameters and curve number have the greatest effect on the model output Due to the fact that in these two criteria, different effective factors of flooding are involved. . In the continuation of the research, taking into account different return periods, 45.6% of the basin area has high to very high flood risk. Also, as the return period increases, the risk of flooding also increases. The results of this research emphasize the effect of various factors on floods and the threats caused by them, and the fuzzy network analysis model shows the potential of floods in this area.
Conclusion: The results showed that the highest weights of the criteria related to runoff, distance from the waterway, and curve number were 0.244, 0.171, 0.140, respectively, and with a total inconsistency rate of 0.09. And the weight of sub-watershed 3 with a value of 0.272 and sub-basin 2 with a value of 0.114 respectively had the highest and lowest weight of flood potential. Also, the criteria of curve number and runoff were identified as the most sensitive factors. . Finally, by integrating these layers according to their weight in the Arc GIS environment, flood potential zoning maps were obtained in a fuzzy manner with a return period of 2, 25, and 50 years. In the 2-year return period, the results showed that 6.45% of the watershed has a high to very high flood risk and 56.57% is in a very low or stable category. While with the return period of 50 years, 22.53% of the area has very high flood potential and 52.77% of the watershed area has very low flood potential.
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