IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i1d10.1007_s10668-022-02705-9.html
   My bibliography  Save this article

Estimation of soil erosion and sediment yield concentrations in Dudhganga watershed of Kashmir Valley using RUSLE & SDR model

Author

Listed:
  • Wani Suhail Ahmad

    (University of Ladakh)

  • Saleha Jamal

    (Aligarh Muslim University)

  • Mohd Taqi

    (University of Ladakh)

  • Hazem T. Abd El-Hamid

    (National Institute of Oceanography and Fisheries)

  • Jigmat Norboo

    (University of Ladakh)

Abstract

A systematic method, incorporating the statistical RUSLE & SDR model, remote sensing and GIS, was used to estimate the annual soil loss and to display spatial distribution of potential erosion risk in Dudhganga watershed. The RUSLE was used in this study in GIS platform based on erosional factors. The spatial and temporal trend of soil erosion in the watershed was obtained by integrating input variables of RUSLE, such as R-factor, K-factor, LS-factor, C-factor and P-factor, into a grid-based GIS method. The estimated rainfall erosivity factor of the watershed ranges from 560.93 to 342.68 MJ mm ha−1 h−1 yr−1 from the year 2000–2020, respectively. The anticipated annual amount of soil loss in the watershed varies in between 6682.37 and 0 t ha−1 yr−1 for the year 2000. Similarly, the values corresponding to annual soil loss increased to 9879.912 t ha−1 yr−1 for the year 2010. Again, in the year 2020 it marked an increase where it recorded the soil loss values of 11,825.98 t ha−1 yr−1 with mean annual soil loss estimates to be 126.89 t ha−1 yr−1, respectively. The findings of the study revealed that the barren land is the main precarious source exposed to the process of soil erosion and has the upper hand in the rate of soil loss and sediment yield. The results of the study divulged that the most affected part of the watershed is the southwestern side where the majority of the area is occupied by barren land, and consequently, the high soil loss in the upper reaches of the watershed exhibits a close correlation to LS and K factor. It has been found in the study that anthropogenic nuisances like rapid deforestation and reckless unplanned urbanization are the principle drivers responsible for the land change systems in the study region. In the long haul, the outcome of these changes will eventually gear up the soil loss activities in the wetland catchments which in turn will lead to the generation of sediment yield and thereby give rise to sedimentation and siltation of waterbodies and, consequently, will affect their overall water holding capacity.

Suggested Citation

  • Wani Suhail Ahmad & Saleha Jamal & Mohd Taqi & Hazem T. Abd El-Hamid & Jigmat Norboo, 2024. "Estimation of soil erosion and sediment yield concentrations in Dudhganga watershed of Kashmir Valley using RUSLE & SDR model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(1), pages 215-238, January.
  • Handle: RePEc:spr:endesu:v:26:y:2024:i:1:d:10.1007_s10668-022-02705-9
    DOI: 10.1007/s10668-022-02705-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-022-02705-9
    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/s10668-022-02705-9?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. 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.
    2. Rahman, Md. Rejaur & Shi, Z.H. & Chongfa, Cai, 2009. "Soil erosion hazard evaluation—An integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies," Ecological Modelling, Elsevier, vol. 220(13), pages 1724-1734.
    3. Manoj Jain & Debjyoti Das, 2010. "Estimation of Sediment Yield and Areas of Soil Erosion and Deposition for Watershed Prioritization using GIS and Remote Sensing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(10), pages 2091-2112, August.
    4. Krishna Bhandari & Jagannath Aryal & Rotchanatch Darnsawasdi, 2015. "A geospatial approach to assessing soil erosion in a watershed by integrating socio-economic determinants and the RUSLE model," 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. 75(1), pages 321-342, January.
    Full references (including those not matched with items on IDEAS)

    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. Shifa Chen & Xuan Zha, 2016. "Evaluation of soil erosion vulnerability in the Zhuxi watershed, Fujian Province, 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. 82(3), pages 1589-1607, July.
    2. Sumedh R. Kashiwar & Manik Chandra Kundu & Usha R. Dongarwar, 2022. "Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS," 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. 110(2), pages 937-959, January.
    3. Ranghu Wang & Shuwen Zhang & Jiuchun Yang & Luoman Pu & Chaobin Yang & Lingxue Yu & Liping Chang & Kun Bu, 2016. "Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China," Sustainability, MDPI, vol. 8(4), pages 1-20, March.
    4. 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.
    5. Arun Mondal & Deepak Khare & Sananda Kundu, 2016. "Impact assessment of climate change on future soil erosion and SOC loss," 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. 82(3), pages 1515-1539, July.
    6. Chuhong Shen & Kangning Xiong & Tian Shu, 2022. "Dynamic Evolution and Quantitative Attribution of Soil Erosion Based on Slope Units: A Case Study of a Karst Plateau-Gorge Area in SW China," Land, MDPI, vol. 11(8), pages 1-18, July.
    7. Demetris Zarris & Marianna Vlastara & Dionysia Panagoulia, 2011. "Sediment Delivery Assessment for a Transboundary Mediterranean Catchment: The Example of Nestos River Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(14), pages 3785-3803, November.
    8. Nektarios N. Kourgialas & Georgios C. Koubouris & George P. Karatzas & Ioannis Metzidakis, 2016. "Assessing water erosion in Mediterranean tree crops using GIS techniques and field measurements: the effect of climate change," 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. 83(1), pages 65-81, October.
    9. Vesna Đukić & Zoran Radić, 2014. "GIS Based Estimation of Sediment Discharge and Areas of Soil Erosion and Deposition for the Torrential Lukovska River Catchment in Serbia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4567-4581, October.
    10. Hadi Eskandari Damaneh & Hassan Khosravi & Khalil Habashi & Hamed Eskandari Damaneh & John P. Tiefenbacher, 2022. "The impact of land use and land cover changes on soil erosion in western 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. 110(3), pages 2185-2205, February.
    11. Ching-Nuo Chen & Chih-Heng Tsai & Chang-Tai Tsai, 2011. "Simulation of Runoff and Suspended Sediment Transport Rate in a Basin with Multiple Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(3), pages 793-816, February.
    12. Hamed Ahmadpour & Ommolbanin Bazrafshan & Elham Rafiei-Sardooi & Hossein Zamani & Thomas Panagopoulos, 2021. "Gully Erosion Susceptibility Assessment in the Kondoran Watershed Using Machine Learning Algorithms and the Boruta Feature Selection," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
    13. Zahra Ebrahimi Gatgash & Seyed Hamidreza Sadeghi, 2023. "Prioritization-based management of the watershed using health assessment analysis at sub-watershed scale," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9673-9702, September.
    14. Giorgos Mallinis & Ioannis Z. Gitas & Georgios Tasionas & Fotis Maris, 2016. "Multitemporal Monitoring of Land Degradation Risk Due to Soil Loss in a Fire-Prone Mediterranean Landscape Using Multi-decadal Landsat Imagery," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1255-1269, February.
    15. Morteza Akbari & Ehsan Neamatollahi & Hadi Memarian & Mohammad Alizadeh Noughani, 2023. "Assessing impacts of floods disaster on soil erosion risk based on the RUSLE-GloSEM approach in western 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. 117(2), pages 1689-1710, June.
    16. Vaibhav Garg & V. Jothiprakash, 2012. "Sediment Yield Assessment of a Large Basin using PSIAC Approach in GIS Environment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(3), pages 799-840, February.
    17. 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.
    18. Bashar Bashir & Abdullah Alsalman, 2024. "Morphometric and Soil Erosion Characterization Based on Geospatial Analysis and Drainage Basin Prioritization of the Rabigh Area Along the Eastern Red Sea Coastal Plain, Saudi Arabia," Sustainability, MDPI, vol. 16(20), pages 1-26, October.
    19. Liwei Zhang & Yihe Lü & Bojie Fu & Yuan Zeng, 2017. "Uncertainties of Two Methods in Selecting Priority Areas for Protecting Soil Conservation Service at Regional Scale," Sustainability, MDPI, vol. 9(9), pages 1-12, September.
    20. Alelgn Ewunetu & Belay Simane & Ermias Teferi & Benjamin F. Zaitchik, 2021. "Mapping and Quantifying Comprehensive Land Degradation Status Using Spatial Multicriteria Evaluation Technique in the Headwaters Area of Upper Blue Nile River," Sustainability, MDPI, vol. 13(4), pages 1-27, February.

    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:endesu:v:26:y:2024:i:1:d:10.1007_s10668-022-02705-9. 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.