IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v91y2018i1d10.1007_s11069-017-3123-9.html
   My bibliography  Save this article

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

Author

Listed:
  • Hamed Noori

    (Semnan University)

  • Hojat Karami

    (Semnan University)

  • Saeed Farzin

    (Semnan University)

  • Seyed Mostafa Siadatmousavi

    (Iran University of Science and Technology)

  • Barat Mojaradi

    (Iran University of Science and Technology)

  • Ozgur Kisi

    (Ilia State University)

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.

Suggested Citation

  • Hamed Noori & Hojat Karami & Saeed Farzin & Seyed Mostafa Siadatmousavi & Barat Mojaradi & Ozgur Kisi, 2018. "Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(1), pages 221-238, March.
    • Handle: RePEc:spr:nathaz:v:91:y:2018:i:1:d:10.1007_s11069-017-3123-9
    DOI: 10.1007/s11069-017-3123-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-017-3123-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-017-3123-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jan Blachowski, 2016. "Application of GIS spatial regression methods in assessment of land subsidence in complicated mining conditions: case study of the Walbrzych coal mine (SW Poland)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(2), pages 997-1014, November.
    2. Ion Ionita & Michael Fullen & Wojciech Zgłobicki & Jean Poesen, 2015. "Gully erosion as a natural and human-induced hazard," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(1), pages 1-5, November.
    3. David Byrne & Kevin Horsburgh & Brian Zachry & Paolo Cipollini, 2017. "Using remotely sensed data to modify wind forcing in operational storm surge forecasting," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(1), pages 275-293, October.
    4. V. Prasannakumar & H. Vijith & N. Geetha & R. Shiny, 2011. "Regional Scale Erosion Assessment of a Sub-tropical Highland Segment in the Western Ghats of Kerala, South India," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(14), pages 3715-3727, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali M. Rajabi & A. Yavari & A. Cheshomi, 2022. "Sediment yield and soil erosion assessment by using empirical models for Shazand watershed, a semi-arid area in center of Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(2), pages 1685-1704, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sandipta Debanshi & Swades Pal, 2020. "Assessing gully erosion susceptibility in Mayurakshi river basin of eastern India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 883-914, February.
    2. E. Molina-Navarro & S. Martínez-Pérez & A. Sastre-Merlín & R. Bienes-Allas, 2014. "Catchment Erosion and Sediment Delivery in a Limno-Reservoir Basin Using a Simple Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2129-2143, June.
    3. Xue Jin & Xiaoxia Shi & Jintian Gao & Tongbin Xu & Kedong Yin, 2018. "Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups," IJERPH, MDPI, vol. 15(4), pages 1-19, March.
    4. Yulei Ma & Xiangzhou Xu & Peiqing Xiao & Qiao Yan & Chao Zhao, 2021. "Geomorphic natural hazard on loess terrain: expansion on the gully sidewall," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(3), pages 2535-2555, December.
    5. Zhiheng Yang & Chenxi Li & Yongheng Fang, 2020. "Driving Factors of the Industrial Land Transfer Price Based on a Geographically Weighted Regression Model: Evidence from a Rural Land System Reform Pilot in China," Land, MDPI, vol. 9(1), pages 1-21, January.
    6. Xiaobing Liu & Hao Li & Shengmin Zhang & Richard M. Cruse & Xingyi Zhang, 2019. "Gully Erosion Control Practices in Northeast China: A Review," Sustainability, MDPI, vol. 11(18), pages 1-16, September.
    7. V. Chowdary & D. Chakraborthy & A. Jeyaram & Y. Murthy & J. Sharma & V. Dadhwal, 2013. "Multi-Criteria Decision Making Approach for Watershed Prioritization Using Analytic Hierarchy Process Technique and GIS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3555-3571, August.
    8. Elham Hosseinzadeh & Sara Anamaghi & Massoud Behboudian & Zahra Kalantari, 2024. "Evaluating Machine Learning-Based Approaches in Land Subsidence Susceptibility Mapping," Land, MDPI, vol. 13(3), pages 1-27, March.
    9. Amit Kumar & Mamta Devi & Benidhar Deshmukh, 2014. "Integrated Remote Sensing and Geographic Information System Based RUSLE Modelling for Estimation of Soil Loss in Western Himalaya, India," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3307-3317, August.
    10. Shixian Xu & Xinjun Wang & Xiaofei Ma & Shenghan Gao, 2023. "Risk Assessment and Prediction of Soil Water Erosion on the Middle Northern Slope of Tianshan Mountain," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    11. Xunan Liu & Yao Zhang & Chenbin Liang & Yayu Yang & Wanru Huang & Ning Jia & Bo Cheng, 2022. "Storm surge damage interpretation by satellite imagery: case review," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 349-365, May.
    12. I. Gaubi & A. Chaabani & A. Ben Mammou & M. H. Hamza, 2017. "A GIS-based soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) (Lebna watershed, Cap Bon, Tunisia)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 219-239, March.
    13. Chenxi Li & Kening Wu, 2017. "Driving forces of the villages hollowing based on geographically weighted regression model: a case study of Longde County, the Ningxia Hui Autonomous Region, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1059-1079, December.
    14. Selamawit Amare & Saskia Keesstra & Martine van der Ploeg & Eddy Langendoen & Tammo Steenhuis & Seifu Tilahun, 2019. "Causes and Controlling Factors of Valley Bottom Gullies," Land, MDPI, vol. 8(9), pages 1-21, September.
    15. Y. M. R. Hernandez & L. A. P. Bacellar & J. A. Araujo Junior, 2022. "Groundwater-induced seasonal slumps in gullies of the Bação Complex, Southeastern Brazil," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3061-3081, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:91:y:2018:i:1:d:10.1007_s11069-017-3123-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.