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Poultry Terminology::
Abstract
Identification and prioritization of basins based on their potential for flooding are essential in integrated watershed management and reducing flood damages. However, the lack of flood discharge of watersheds has led to difficulty in estimating the coefficient of flooding. Therefore, the use of multi-criteria decision-making methods such as fuzzy AHP in weighting influential factors in flooding can be an efficient and effective solution for estimating the coefficient of flooding, especially at sub-basin outlets without hydrometric station. For this purpose, in the present study, fuzzy AHP method has been used to determine the flooding potential of sub-basins in Khezrabad watershed. Moreover, flooding is a phenomenon influenced by many factors, all of which cannot be measured due to time and cost limitations. As the watersheds and the drainage network are fractal phenomena in which fractal patterns can be found, the fractal geometry has also been used to investigate the potential for flood occurrence. In the present research, the criteria for weighting include area, graviolus coefficient, bifurcation ratio, curve number, main drainage length, Qp100/2, concentration time, rectangular equivalent length, rectangular equivalent width, and 24-hour rainfall in fuzzy AHP method. These criteria have resulted from the factor analysis conducted on 21 factors. The results showed that five criteria of Qp100/2, curve number, 24-hour precipitation, area, and slope with relative weights of 0.26, 0.19, 0.13, 0.11, and 0.1 were the most influential factors in the flooding potential of Khezrabad watershed. Also, the final results obtained from integrating the weight of criteria and sub-criteria revealed that the studied watershed belonged to three classes with flooding coefficient of 0.3, 0.3-0.4, and 0.4. The sub-catchments of E4, F3, D3, and E1 respectively had a higher potential for flood occurrence than others. The comparison among sub-catchments for flooding coefficients and fractal dimension values of the drainage network also showed that the fractal dimension values follow a specific pattern in the classes. With an increase in the coefficient of flooding, the fractal dimension values are increased. The values of fractal dimension in the three classes were respectively obtained 1.2, 1.2-1.35, and 1.4. Hence, it can be claimed that the fractal dimension analysis of the drainage network is a key determinant of the potential and priority of catchments in flood occurrence.
Keywords: Fuzzy analytic hierarchical process, flooding potential, Multi-criteria decision making, Khezrabad watershed.
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