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Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

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Abstract

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m3 km−2 year−1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m3 km−2 year−1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.

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Authors and Affiliations

  1. Faculty of Civil Engineering, Semnan University, Semnan, Iran

    Hamed Noori, Hojat Karami & Saeed Farzin

  2. Faculty of Civil and Environmental Engineering, Iran University of Science and Technology, Tehran, Iran

    Seyed Mostafa Siadatmousavi & Barat Mojaradi

  3. Faculty of Natural Sciences and Engineering, Ilia State University, Tbilisi, Georgia

    Ozgur Kisi

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  1. Hamed Noori
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  2. Hojat Karami
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  3. Saeed Farzin
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  4. Seyed Mostafa Siadatmousavi
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  5. Barat Mojaradi
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  6. Ozgur Kisi
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Correspondence to Hojat Karami.

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Noori, H., Karami, H., Farzin, S. et al. Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion. Nat Hazards 91, 221–238 (2018). https://doi.org/10.1007/s11069-017-3123-9

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  • DOI: https://doi.org/10.1007/s11069-017-3123-9

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