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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
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
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
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
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
Beck MB (1987) Water quality modeling: a review of the analysis of uncertainty. Water Resour Res 23:1393–1442
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
Fadhil AM (2009) Land degradation detection using geo-information technology for some sites in Iraq. J Al-Nahrain Univ Sci 12:94–108
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
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
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
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
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)
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
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)
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
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
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
Louis J, Debaecker V, Pflugetal B (2016) Sentinel-2Sen2Cor:L2A processor for users. In: Living planet symposium, p 91. Prague, Czech Republic
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
Merritt WS, Letcher RA, Jakeman AJ (2003) A review of erosion and sediment transport model. Environ Model Softw 18:761–799
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
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
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
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
Oldeman LR (1994) The global extent of land degradation. In: Greenland DJ Szabolcs I (eds) Land resilience and sustainable land use. CABI, Wallingford, UK
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
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
Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R-factor in the revised USLE. J Hydrol 157:287–306
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
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
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
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
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
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
Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses. Agriculture Handbook No. 537, USDA-Science and Education Administration, p 58
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
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
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
DOI: https://doi.org/10.1007/978-3-031-58315-5_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-58314-8
Online ISBN: 978-3-031-58315-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)