Sub-Basins Prioritization Using Morphometric Analysis-Remote Sensing Technique and GIS-Golestan-Iran

Amani, Mohamad; Safaviyan, Arezoo

doi:10.18052/www.scipress.com/ILNS.38.56

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Sub-Basins Prioritization Using Morphometric Analysis-Remote Sensing Technique and GIS-Golestan-Iran

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Abstract:

Sub-basins prioritization is one of the most important resolutions of development sustainability and natural resources comprehended management. In this study, 11 sub-basins of Lohender in east Golstan province about 272/63cm Prioritized using computation and morphometric analysis and using GIS and RS techniques. Erosion mode in each sub-basin specified through Sediment Yield Index approximation. In morphometric analysis, parameters like canal length, bifurcation ratio, discharge density, sub-basins shape coefficient, round coefficient, stretch coefficient and compressive coefficients were computed thus these parameters divided to two classifications: linear coefficients and figurative coefficient. In order to study annual sediment index, from fields applied maps, land coverage, slope, soil type and topographic map scale 1:50000 were used. Finally, each sub-basin Priority determined due to Sediment Yield Index (SYI) and total average of morphometric parameters. According to morphometric parameters, the BS sub-basin and according to SYI parameter, A5 sub-basin showed more critical mode and combination of both showed that B2 sub-basin showed the worst situation.

Info:

Periodical:

International Letters of Natural Sciences (Volume 38)

Pages:

56-65

DOI:

https://doi.org/10.18052/www.scipress.com/ILNS.38.56

Citation:

M. Amani and A. Safaviyan, "Sub-Basins Prioritization Using Morphometric Analysis-Remote Sensing Technique and GIS-Golestan-Iran", International Letters of Natural Sciences, Vol. 38, pp. 56-65, 2015

Online since:

May 2015

Authors:

Mohamad Amani, Arezoo Safaviyan

Keywords:

Erodibility, Lohender Basin, Morphometric, Prioritization, SYI

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Distribution:

Open Access

This work is licensed under a
Creative Commons Attribution 4.0 International License

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[1] S. Mandal, S. Mondal, Geoinformatics and Modelling of Landslide Susceptibility and Risk, p. 49, 2019

DOI: https://doi.org/10.1007/978-3-030-10495-5_3