JWSS - Journal of Water and Soil Science

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Shirani K, Chavoshi S. Prioritization of Catchments Prone to Flooding by Morphometric Analysis. jwss 2019; 22 (4) :59-72
URL: http://jstnar.iut.ac.ir/article-1-3544-en.html

Catchment prioritization in terms of natural disaster intensity as well as prevention and control practices plays a main role in the natural resources and watershed management. In this study, a total of 24 sub-catchments in the Zohreh-Jarrahi basin were prioritized according to their morphometric parameters and using the mixed model of TOPSIS-Multivariate regression. A total of 12 morphometric parameters including constant component of channel maintenance, drainage density, ruggedness number, infiltration index, stream power index, stream frequency, slope, drainage texture rate, relief rate, form factor, bifurcation ratio and topography wetness index, in addition to rainfall, were studied and scored. Parameters were weighted by using multivariate regression and the spatial distribution of the observed flood events. TOPSIS model was used for the prioritization process. The results obtained from the weighting analysis showed that the ruggedness number, slope and rainfall had the highest effect on flooding in the study area with the score of 0.068, 0.024, and 0.016, respectively. According to the prioritization results, sub-catchments of Seidoon, Emamzadeh Jafar, and Takht Deraz, which had the minimum distance to the positive optimum (0.0028, 0.0029, and 0.0029, respectively) and the maximum distance to the negative optimum (0.0097, 0.0098 and 0.0095, respectively), showed the highest flooding intensity with the score of 0.7745, 0.7690 and 0.7625, respectively. In order to validate the results, prioritization results were compared to the observed flood events. Validation results also indicated the efficiency of the mixed model in delineation of catchments prone to flooding. Three sub-catchments of Seidoon, Emamzadeh Jafar and Takht Deraz were observed to have the highest number of observed flood events, thereby showing the high effectiveness of the model and also, the role of the morphometric parameters in flooding.