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Soil Erosion Hazard Mapping in Central Zab Basin Using Epm Model in GIS Environment

Author

Listed:
  • Himan Shahabi
  • Mamand Salari
  • Baharin Bin Ahmad
  • Ayub Mohammadi

Abstract

Soil losses and erosion are the primary concerns that decrease soil fertility, deposition materials in waterways, flooding, environmental pollution, and declining dam capacity. The aim of this study is zonation of soil erosion hazard and sediment yield in central Zab basin in southwest of West-Azerbaijan province in Iran. The Sardasht dam construction is established on its main branches that estimate amount of soil erosion and sedimentation of behind the dam is necessary. Hence EPM model have been used to soil erosion hazard mapping using series of GIS data, Landsat ETM+ satellite images, aerial photos in GIS environment. Required layers information was used in this research including slope, aspect, lithology, soil, land use, rainfall, and river erosion. Hence, GIS databases and their weighting of each map layers were extracted according to the hydrologic units. Also, GIS database was prepared based on EPM model to extract of erosion and sedimentation maps The obtained result using EPM model showed that south and southwest parts of central Zab basin near the Sardasht Dam construction are very highly eroded due to their soil erosion and lithology while the northern parts of case study are moderately eroded because of the intensive land cover.

Suggested Citation

  • Himan Shahabi & Mamand Salari & Baharin Bin Ahmad & Ayub Mohammadi, 2016. "Soil Erosion Hazard Mapping in Central Zab Basin Using Epm Model in GIS Environment," International Journal of Geography and Geology, Conscientia Beam, vol. 5(11), pages 224-235.
    • Handle: RePEc:pkp:ijogag:v:5:y:2016:i:11:p:224-235:id:1967
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    Cited by:

    1. Viet-Ha Nhu & Ayub Mohammadi & Himan Shahabi & Baharin Bin Ahmad & Nadhir Al-Ansari & Ataollah Shirzadi & John J. Clague & Abolfazl Jaafari & Wei Chen & Hoang Nguyen, 2020. "Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment," IJERPH, MDPI, vol. 17(14), pages 1-23, July.

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