Prioritization of Ghezel Owzan-Sefidrud sub-basins for identification of the erosion-sensitive basins, based on morphometry, erosion rate, and vegetation

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Abstract:

Prioritization of watershed basins includes classification of sub-basins on the basis of the existing conditions and erosion intensity, which ultimately leads to protective operations and watershed management in more significant and susceptible sub-basins. In this research, in order to prioritize Ghezel Owzan-Sefidrud sub-basins against sensitivity to erosion, linear and form-based morphometric parameters are applied as physiographic factors involved in erosion of basins, and on the other side, erosion and vegetation factors are used as external and protective dynamic factors. In order to estimate the morphometric parameters, SRTM digital elevation model with a 30-m land resolution was utilized; furthermore, to prepare the vegetation map, a MODIS image frame of the maximum vegetation time, together with the NDVI index was used. In order to approximate the erosion rate of the basins spatially, the rainfall data of TRMM satellite along with the Fornier index were utilized; also, the CP method of ranking was applied for prioritization. The prioritization results on the basis of morphometric parameters indicated that the sub-basins are categorized into two classes including the high-priority type with 45.46% and medium-priority type with 54.54% of the basin area. The prioritization based on the erosion rate and vegetation demonstrated that the studied sub-basins are more diverse than morphometric-based one; accordingly, 9.1% of the land belongs to very high susceptibility class, 63.63% to high susceptibility class, 18.17% to medium susceptibility class, and 9.1% to low susceptibility class. The integrative prioritization on the basis of all three factors showed that 45.45% of the sub-basins are in high susceptibility class as the following order: Goltappeh, Taleghan, Mahneshan, Ghorveh and Divandarreh basins; they need protective activities. As well, the rest 54.55% of them belongs to the middle class.

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Journal title

volume 9  issue 33

pages  69- 82

publication date 2018-10

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