Skip to main content

Predicting Soil Erosion Using RUSLE Model in Duhok Governorate, Kurdistan Region of Iraq

  • Chapter
  • First Online:
Natural Resources Deterioration in MENA Region

Abstract

Soil erosion is a main cause of land degradation, adveresly impacting soil health, soil fertility, and soil carbon. This study used the revised universal soil loss equation (RUSLE) model and geoinformatics tools to predict soil erosion rates in the Duhok governorate, located in the Kurdistan Region of Iraq (KRI). The RUSLE model integrates several to predict annual soil loss: soil erodibility factor (K), rainfall erosivity factor (R), slope (L), slope steepness factor (S), land use/cover factor (C), and conservation methods (P). Information layers for these variables were created using ArcGIS 10.3, showing the extent of soil erosion. Additionally, we identified and prioritized erosion hotspots to implement conservation practices. The results showed that approximately 78% of the study area experienced very low and low levels of soil erosion, whereas only 4 and 7% were subject to high and very high erosion rates, respectively. The findings also emphasized the significance of slope and land-use interactions in accelerating soil erosion, particularly in agricultural areas characterized by steep slopes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alexakis DD, Hadjimitsis DG, Agapiou A (2013) Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of Yialias in Cyprus. Atmos Res 131:108–124

    Article  Google Scholar 

  • Al-Quraishi AMF (2003) Soil erosion risk prediction with RS and GIS for the Northwestern part of Hebei Province, China. J Appl Sci 3:659–666

    Article  Google Scholar 

  • Al-Quraishi AMF (2004) Assessment of soil erosion risk using RUSLE and geoinformation technology for North Shaanxi Province, China. J China Univ Geosci l5:31–39

    Google Scholar 

  • ASTER-GDEM (2013) ASTER global digital elevation model (GDEM). http://gdem.ersdac.jspacesystems.or.jp/. Accessed on 15 Aug 2018

  • Bag R, Mondal I, Dehbozorgi M, Bank SP, Das DN, Bandyopadhyay J, Pham QB, Al-Quraishi AMF, Nguyen XC (2022) Modelling and mapping of soil erosion susceptibility using machine learning in a tropical hot sub-humid environment. J Clean Prod 364:132428

    Article  Google Scholar 

  • Beck MB (1987) Water quality modeling: a review of the analysis of uncertainty. Water Resour Res 23:1393–1442

    Article  CAS  Google Scholar 

  • Belayneh M, Yirgu T, Tsegaye D (2019) Potential soil erosion estimation and area prioritization for better conservation planning in Gumara watershed using RUSLE and GIS techniques. Environ Syst Res 8:20

    Article  Google Scholar 

  • Fadhil AM (2009) Land degradation detection using geo-information technology for some sites in Iraq. J Al-Nahrain Univ Sci 12:94–108

    Article  Google Scholar 

  • Fadhil AM (2013) Sand dunes monitoring using remote sensing and GIS techniques for some sites in Iraq. In: Tan H (ed) PIAGENG 2013: intelligent information, control, and communication technology for agricultural engineering

    Google Scholar 

  • Fang G, Yuan T, Zhang Y, Wen X, Lin R (2019) Integrated study on soil erosion using RUSLE and GIS in Yangtze river basin of Jiangsu Province (China). Arab J Geosci 12. https://doi.org/10.1007/s12517-019-4331-2

  • FAO (2019) Soil erosion: the greatest challenge to sustainable soil management. Rome, p 100

    Google Scholar 

  • Fereshtehpour M, Esmaeilzadeh M, Saleh Alipour R, Burian S (2024) Impacts of DEM type and resolution on deep learning-based flood inundation mapping. Earth Sci Inf 1–21. https://doi.org/10.1007/s12145-024-01239-0

  • Ganasri BP, Ramesh H (2016) Assessment of soil erosion by RUSLE model using remote sensing and GIS–a case study of Nethravathi Basin. Geosci Front 7:953–961

    Article  Google Scholar 

  • Haregeweyn N, Tsunekawa A, Poesen J, Tsubo M, Meshesha DT, Fenta AA, Nyssen J, Adgo E (2017) Comprehensive assessment of soil erosion risk for better land use planning in river basins: case study of the Upper Blue Nile River. Sci Total Environ 1(574):95–108. https://doi.org/10.1016/j.scitotenv.2016.09.019

  • Hossini H, Karimi H, Mustafa YT, Al-Quraishi AMF (2022) Role of effective factors on soil erosion and land degradation: a review. In: Al-Quraishi AMF, Mustafa YT, Negm AM (eds) Environmental degradation in Asia. Earth and environmental sciences library. Springer, Cham

    Google Scholar 

  • Igwe PU, Onuigbo AA, Chinedu OC, Ezeaku II, Muoneke MM (2017) Soil erosion: a review of models and applications. Int J Adv Eng Res Sci 4(12)

    Google Scholar 

  • Karimi H, Jafarnezhad J, Kakhani A (2020) Landsat time-series for land use change detection using support vector machine: case study of Javanrud District, Iran. Int Conf Comp Sci Softw Eng (CSASE) 2020:128–131

    Google Scholar 

  • Karimi H, Jafarnezhad J, Khaledi J, Ahmadi P (2018) Monitoring and prediction of land use/land cover changes using CA-Markov model: a case study of Ravansar County in Iran. Arab J Geosci 11(592)

    Google Scholar 

  • Karimi H, Mustafa YT, Hossini H, Al-Quraishi AMF (2022) Assessment of land degradation vulnerability using GIS-based multicriteria decision analysis in Zakho District, Kurdistan Region of Iraq. In: Al-Quraishi AMF, Mustafa YT, Negm AM (eds) Environmental degradation in Asia. Earth and environmental sciences library. Springer, Cham

    Google Scholar 

  • Koirala P, Thakuri S, Joshi S, Chauhan R (2019) Estimation of soil erosion in Nepal using a RUSLE modeling and geospatial tool. Geosciences 9:147

    Article  CAS  Google Scholar 

  • KouroshNiya A, Huang J, Kazemzadeh-Zow A, Karimi HN (2020) Comparison of three hybrid models to simulate land use changes: a case study in Qeshm Island, Iran. Environ Monit Assess 192:302

    Article  Google Scholar 

  • Louis J, Debaecker V, Pflugetal B (2016) Sentinel-2Sen2Cor:L2A processor for users. In: Living planet symposium, p 91. Prague, Czech Republic

    Google Scholar 

  • Mehri A, Salman Mahiny A, Mikaeili Tabrizi A, Mirkarimi H, Sadoddin A (2018) Investigation of likely effects of land use planning on reduction of soil erosion rate in river basins: case study of the Gharesoo River Basin. CATENA 167:116–129

    Article  Google Scholar 

  • Merritt WS, Letcher RA, Jakeman AJ (2003) A review of erosion and sediment transport model. Environ Model Softw 18:761–799

    Article  Google Scholar 

  • Meshesha DT, Tsunekawa A, Tsubo M, Haregeweyn N (2012) Dynamics and hotspots of soil erosion and management scenarios of the Central Rift Valley of Ethiopia. Int J Sediment Res 27:84–99

    Article  Google Scholar 

  • Moghaddasi P, Kerachian R, Sharghi S (2022) A stakeholder-based framework for improving the resilience of groundwater resources in arid regions. J Hydrol 609:127737

    Article  Google Scholar 

  • Mohammed S, Alsafadi K, Talukdar S, Kiwan S, Hennawi S, Alshihabi O, Sharaf M, Harsanyie E (2020) Estimation of soil erosion risk in southern part of Syria by using RUSLE integrating geoinformatics approach. In: Remote sensing applications, p 20

    Google Scholar 

  • Neamat S, Karimi H (2020) A systematic review of GIS-based landslide hazard mapping on determinant factors from international databases. Int Conf Adv Sci Eng (ICOASE) 2020:180–183

    Google Scholar 

  • Oldeman LR (1994) The global extent of land degradation. In: Greenland DJ Szabolcs I (eds) Land resilience and sustainable land use. CABI, Wallingford, UK

    Google Scholar 

  • Pirsaheb M, Nouri M, Karimi H, Mustafa YT, Hossini H, Naderi Z (2020) Occurrence of residual organophosphorus pesticides in soil of some Asian countries, Australia and Nigeria. IOP Conf Ser Mater Sci Eng 737:012175

    Google Scholar 

  • Renard KG, Foster GR, Weesies GA, McCool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE). US Department of Agriculture-Agriculture Handbook No. 703. p 384

    Google Scholar 

  • Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R-factor in the revised USLE. J Hydrol 157:287–306

    Article  Google Scholar 

  • Sadeghi A, Galalizadeh S, Zehtabian G et al (2021) Assessing the change of groundwater quality compared with land-use change and precipitation rate (Zrebar Lake’s Basin). Appl Water Sci 11:170. https://doi.org/10.1007/s13201-021-01508-z

    Article  CAS  Google Scholar 

  • Sun W, Shao Q, Liu J, Zhai J (2014) Assessing the effects of land use and topography on soil erosion on the Loess Plateau in China. CATENA 121:151–163

    Article  Google Scholar 

  • Tadesse L, Suryabhagavan KV, Sridhar G, Legesse G (2017) Land use and land cover changes and Soil erosion in Yezat Watershed, North Western Ethiopia. Int Soil Water Conserv Res 5:85–94

    Article  Google Scholar 

  • Teng H, Liang Z, Chen S, Liu Y, Viscarra Rossel RA, Chappell A, Yu W, Shi Z (2018) Current and future assessments of soil erosion by water on the Tibetan Plateau based on RUSLE and CMIP5 climate models. Sci Total Environ 635:673–686

    Article  CAS  Google Scholar 

  • Tsunekawa A, Poesen J, Tsubo M, Meshesha DT, Fenta AA, Nyssen J, Adgo E (2017) Comprehensive assessment of soil erosion risk for better land use planning in river basins: Case study of the Upper Blue Nile River. Sci Total Environ 574:95–108

    Article  Google Scholar 

  • USGS (2005) The shuttle radar topography mission. http://gdex.cr.usgs.gov/gdex/. Accessed on 10 May 2013

  • Wang L, Li Y, Gan Y, Zhao L, Qin W, Ding L (2024) Rainfall erosivity index for monitoring global soil erosion. CATENA 234

    Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses. Agriculture Handbook No. 537, USDA-Science and Education Administration, p 58

    Google Scholar 

Download references

Acknowledgements

The authors thank the University of Zakho's assistance and the Department of Agriculture at the University of Duhok for providing us with the necessary data and information.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hazhir Karimi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Mehri, A., Karimi, H., Mustafa, Y.T., Al-Quraishi, A.M.F., Galalizadeh, S. (2024). Predicting Soil Erosion Using RUSLE Model in Duhok Governorate, Kurdistan Region of Iraq. In: Al-Quraishi, A.M.F., Mustafa, Y.T. (eds) Natural Resources Deterioration in MENA Region. Earth and Environmental Sciences Library. Springer, Cham. https://doi.org/10.1007/978-3-031-58315-5_9

Download citation

Publish with us

Policies and ethics