Assessing the risk of soil loss using geographical information system (GIS) and the revised universal soil loss equation (RUSLE)
Article Sidebar
Main Article Content
Abstract
Soil erosion poses a significant environmental challenge in many developing nations, and critically evaluating the threat of soil erosion is paramount for sustainable land management practices. This study aims to identify the contributing factors to erosion and estimate the amount of soil loss in the Bosso Local Government Area of Niger State, Nigeria, using the Revised Universal Soil Loss Equation (RUSLE) model. Factors like rainfall erosivity soil erodibility topography cover and management and support practices were integrated into a Geographic Information System (GIS) environment to generate variable layers. The estimated values of ranged between 438.866 and 444.319 MJmmha-1 h-1 yr-1, 0.06 to 0.015 megajoules per hectare hour megajoules-1 hectare-1 millimeter-1, 0 and 572, 0 to 0.2, and 0 to 1, respectively. GIS raster calculations derived from these factors revealed a mean estimated soil loss rate of 0-6672.83t/h/yr-1 (tons per hectare per year). Notably, rainfall emerged as the most influential factor driving soil erosion within the study area. The study highlights the necessity for immediate intervention to mitigate soil erosion in the study area. Furthermore, to formulate effective conservation and management strategies, this study advocates for further research prioritizing severity analysis areas and estimating sediment loss across the regionSoil erosion poses a significant environmental challenge in many developing nations, and critically evaluating the threat of soil erosion is paramount for sustainable land management practices. This study aims to identify the contributing factors to erosion and estimate the amount of soil loss in the Bosso Local Government Area of Niger State, Nigeria, using the Revised Universal Soil Loss Equation (RUSLE) model. Factors like rainfall erosivity soil erodibility topography cover and management and support practices were integrated into a Geographic Information System (GIS) environment to generate variable layers. The estimated values of ranged between 438.866 and 444.319 MJmmha-1 h-1 yr-1, 0.06 to 0.015 megajoules per hectare hour megajoules-1 hectare-1 millimetre-1, 0 and 572, 0 to 0.2, and 0 to 1, respectively. GIS raster calculations derived from these factors revealed a mean estimated soil loss rate of 0-6672.83t/h/yr-1 (tons per hectare per year). Notably, rainfall emerged as the most influential factor driving soil erosion within the study area. The study highlights the necessity for immediate intervention to mitigate soil erosion in the study area. Furthermore, to formulate effective conservation and management strategies, this study advocates for further research prioritizing severity analysis areas and estimating sediment loss across the region.
Article Details
References
Abdulfatai, I. A, Okunlola, I. A, Akande, W.G, Momoh, L.O., & Ibrahim, K. O. (2014). Review of gully erosion in Nigeria: Causes, impacts and possible solutions. Journal of Geosciences and Geomatics, 2(3), 125-129. https://doi.org/10.12691/jgg-2-3-8
Adediji, A., Tukur, A. M., & Adepoju, K. A. (2010). Assessment of revised universal soil loss equation (RUSLE) in Katsina area, Katsina state of Nigeria using remote sensing (RS) and geographic information system (GIS). Iranian (Iranica) Journal of Energy and Environment, 1(3), 1–18.
Adesina, E., Ajayi O., Odumosu, J., & Illah, A. (2023). GIS-based soil loss estimation using revised universal soil loss equation (RUSLE). Proceedings Book of 7th Intercontinental Geoinformation Days (IGD), Peshawar, Pakistan, 44-48.
Alewoye Getie, M., Legesse, S. A., Mekonnen, M., & Aschalew, A. (2020). Soil properties and crop productivity strategies as a potential climate variability adaptation option in Adefwuha Watershed, Ethiopia. Earth Systems and Environment, 4(2), 359–368. https://doi.org/10.1007/s41748-020-00156-8
Andualem, T. G., Hagos, Y. G., Kefale, A., & Zelalem, B. (2020). Soil erosion-prone area identification using multi-criteria decision analysis in Ethiopian highlands. Modelling Earth Systems and Environment, 6(3), 1407–1418. https://doi.org/10.1007/s40808-020-00757-2
Aneseyee, A. B., Elias, E., Soromessa, T., & Feyisa, G. L. (2020). Land use/land cover change effect on soil erosion and sediment delivery in the Winike watershed, Omo Gibe Basin, Ethiopia. The Science of the Total Environment, 728, 138776. https://doi.org/10.1016/j.scitotenv.2020.138776
Ashiagbor, G., Forkuo, E. K., Laari, P., & Aabeyir, R. (2013). Modeling soil erosion using RUSLE and GIS tools. International Journal Remote Sensing Geoscience, 2(4), 1–17.
Ayalew, D. A., Deumlich, D., Šarapatka, B., & Doktor, D. (2020). Quantifying the sensitivity of NDVI-based C factor estimation and potential soil erosion prediction using Spaceborne earth observation data. Remote Sensing, 12(7), 1136. https://doi.org/10.3390/rs12071136
Ayalew, G., & Selassie, Y. G. (2015). Soil loss estimation for soil conservation planning using geographic information system in Guang watershed, Blue Nile basin. Journal Environment Earth Science, 5(1), 126–134.
Balabathina, V. N., Raju, R. P., Mulualem, W., & Tadele, G. (2020). Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia. Environmental Systems Research, 9(1), 1–32. https://doi.org/10.1186/s40068-020-00203-3
Bastola, S., Seong, Y. J., Lee, S. H., Shin, Y., & Jung, Y. (2019). Assessment of soil erosion loss by using RUSLE and GIS in the Bagmati basin of Nepal. Journal of the Korean GEO-Environmental Society, 20(3), 5–14.
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. Environmental Systems Research, 8(1), 20. https://doi.org/10.1186/s40068-019-0149-x
Berendse, F., van Ruijven, J., Jongejans, E., & Keesstra, S. (2015). Loss of plant species diversity reduces soil erosion resistance. Ecosystems, 18(5), 881–888. https://doi.org/10.1007/s10021-015-9869-6
Bombino, G., Porto, P., Tamburino, V., & Zimbone, S. M. (2004, August, 14-17). Crop and management factor estimate for applying RUSLE in rangeland areas [Paper presentation]. ASAE Annual Meeting, San Francisco, CA, USA.
Chakrabortty, R., & Pal, S. C. (2023). Modeling soil erosion susceptibility using GIS-based different machine learning algorithms in monsoon dominated diversified landscape in India. Modelling Earth Systems and Environment, 9(2), 2927–2942. https://doi.org/10.1007/s40808-022-01681-3.
Chalise, D., Kumar, L., Spalevic, V., & Skataric, G. (2019). Estimation of sediment yield and maximum outflow using the Int ErO model in the Sarada River Basin of Nepal. Water. 11(5), 952. https://doi.org/10.3390/w11050952
Colman, C. B., Garcia, K. M. P., Pereira, R. B., Shinma, E. A., Lima, F. E., Gomes, A. O., & Oliveira, P. T. S. (2018). Different approaches to estimate the sediment yield in a tropical watershed. RBRH, 23(0), 1–9. https://doi.org/10.1590/2318-0331.231820170178
David Raj, A., &Kumar. S. (2022). Soil quality assessment in hilly and mountainous landscape. Springer International Publishing. https://doi.org/10.1007/978-3-031-09270-1_13
Deressa, A., Yli-Halla, M., & Mohamed, M. (2020). Soil organic carbon stock and retention rate among land uses along Didessa Topo Sequence in Humid Western Ethiopia. Environmental Systems Research, 9(1), 1–12. https://doi.org/10.21203/rs.3.rs-75409/v1
Dutta, D., Das, S., Kundu, A., & Taj, A. (2015). Soil erosion risk assessment in Sanjal watershed, Jharkhand (India) using geo-informatics, RUSLE model and TRMM data. Modelling Earth Systems and Environment, 1(4), 1–9. https://doi.org/10.1007/s40808-015-0034-1
Egbueri, J. C., Igwe, O., & Ifediegwu, S. I. (2022). Erosion risk mapping of Anambra State in southeastern Nigeria: Soil loss estimation by RUSLE model and geoinformatics. Bulletin of Engineering Geology and the Environment, 81(3), 91. https://doi.org/10.1007/s10064-022-02589-z
Erencin, Z. (2000). C-factor mapping using remote sensing and GIS: A case study of Lom Sak/Lom Kao [Master's thesis, Universitat Giessen]. Geographisches Institut der Justus-Liebig-Universität Giessen. http://dx.doi.org/10.22029/jlupub-15990
Erol, A., Koşkan, Ö., & Başaran, M. A. (2015). Socioeconomic modifications of the universal soil loss equation. Solid Earth. 6(3), 1025–1035. https://doi.org/10.5194/se-6-1025-2015
FAO. (2015). Agriculture Organization: Status of the World’s Soil Resources (SWSR)–Main Report. Food and Agriculture Organization of the United Nations and Intergovernmental Technical Panel on Soils. Retrieved October 29, 2023, from https://openknowledge.fao.org/server/api/core/bitstreams/6ec24d75-19bd-4f1f-b1c5-5becf50d0871/content
Ferro, V., & Porto, P. (2000). Sediment delivery distributed (SEDD) model. Journal of Hydrologic Engineering, 5(4), 411–422. https://doi.org/10.1061/(ASCE)1084-0699
Ganasri, B. P. & Ramesh, H. (2016). Assessment of soil erosion by RUSLE model using remote sensing and GIS-A case study of Nethravathi Basin. Geoscience Frontiers 7(6), 953–961. https://doi.org/10.1016/j.gsf.2015.10.007
Gessesse, B., Bewket, W., & Bräuning, A. (2015). Model-based characterization and monitoring of runoff and soil erosion in response to land use/land cover changes in the Modjo watershed, Ethiopia. Land Degradation and Development, 26(7), 711–724. https://doi.org/10.1002/ldr.2276
Getu, L. A., Nagy, A., & Addis, H. K. (2022). Soil loss estimation and severity mapping using the RUSLE model and GIS in Megech watershed, Ethiopia. Environmental Challenges, 8. https://doi.org/10.1016/j.envc.2022.100560
Ghafari, H., Gorji, M., Arabkhedri, M., Roshani, G. A., Heidari, A., & Akhavan, S. (2017). Identification and prioritization of critical erosion areas based on onsite and offsite effects. CATENA, 156, 1–9. https://doi.org/10.1016/j.catena.2017.03.014.
Haile, G. W., & Fetene, M. (2012). Assessment of soil erosion hazard in Kilie catchment, East Shoa, Ethiopia. Land Degradation and Development, 23(3), 293–306. https://doi.org/10.1002/ldr.1082
Heald, C. L, Jacob, D. J., Park, R. J., Russell, L. M., Huebert, B. J., Seinfeld, J.H., (2015). A large organic aerosol source in the free troposphere missing from current models. Geophysical Research Letters. 32(18). https://doi.org/10.1029/2005GL023831
Hurni, K., Zeleke, G., Kassie, M., Tegegne, B., Kassawmar, T., Teferi, E., Moges, A., Tadesse, D., Ahmed, M., Degu, Y., Kebebew, Z., Hodel, E., Amdihun, A., Mekuriaw, A., Debele, B., Deichert, G., & Hurni, H. (2015). The economics of land degradation. Ethiopia case study: Soil degradation and sustainable land management in the rain fed agricultural areas of Ethiopia: An assessment of the economic implications. Rep. Econ. Land Degrading.
Kebede, S., & Fufa, F. (2023). Estimation of average annual soil loss rates and its prioritization at sub-watershed level using RUSLE: A case of Finca’aa, Oromiya, Western Ethiopia. Environmental Health Engineering and Management, 10(1), 41–50. https://doi.org/10.34172/EHEM.2023.05
Kiptoo, O., & Mirzabaev, A. (2014). Economics of land degradation in Eastern Africa. ZEF working paper series.
Kouli, M., Soupios, P., & Vallianatos, F. (2009). Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environmental Geology. 57(3), 483-497. https://doi.org/10.1007/s00254-008-1318-9
Kumar, R., Kumar, M., Shah, A. I., Bhat, S. A., Wani, M. A., Ram, D. (2016a). Modelling of soil loss using USLE through Remote Sensing and Geographical Information System in micro-watershed of Kashmir valley, India. Journal of Soil and Water Conservation 15(1), 40-45.
Kumar, R., Ashraf, I., Khan, T., Hamid, N., Khan, J. N., Bhat, O. A. & Ram, D. (2016b). Watershed based drainage morphometric analysis using geographical information system and remote sensing of Kashmir valley, India. Journal of Soil and Water Conservation, 15(3), 265-272.
Kushwaha, N., Elbeltagi, A., Mehan, S., Malik, A., & Yousuf, A. (2022). Comparative study on morphometric analysis and RUSLE-based approaches for microwatershed prioritization using remote sensing and GIS. Arabian Journal of Geosciences 15(7), 564. https://doi.org/10.1007/s12517-022-09837-2
Legesse, D., Vallet-Coulomb, C., & Gasse, F. (2004). Analysis of the hydrological response of a tropical terminal lake, Lake Abiyata (Main Ethiopian Rift Valley) to changes in climate and human activities. Hydrological Processes, 18(3), 487–504. https://doi.org/10.1002/hyp.1334
Moisa, M. B., Dejene, I. N., Merga, B. B., & Gemeda, D. O. (2022). Soil loss estimation and prioritization using geographic information systems and the RUSLE model: A case study of the Anger River sub-basin, Western Ethiopia. Journal of Water and Climate Change, 13(3), 1170–1184. https://doi.org/10.2166/wcc.2022.433
Morgan, R. P. C., Morgan, D. D. V., & Finney, H. J. (1984). A predictive model for the assessment of soil erosion risk. Journal of Agricultural Engineering Research, 30, 245-253. https://doi.org/10.1016/S0021-8634(84)80025-6
Moore, I. D., & Burch, G. J. (1986). Physical basis of the length-slope factor in the universal soil loss equation. Soil Science Society of America Journal 50(5), 1294–1298. https://doi.org/10.2136/sssaj1986.03615995005000050042x
Nearing, M. A., Pruski, F. F., & O'neal, M. R. (2004). Expected climate change impacts on soil erosion rates: A review. Journal of Soil and Water Conservation. 59(1), 43- 50.
Odumosu, J. O., Ajayi, O. G., & Adesina E. A. (2014). Modeling surface runoff and mapping flood vulnerability in Lagos State from digital elevation model. Proceedings Book of XXV FIG Conference Malaysia, Kaula Lumpur, Malaysia.
Pal, S. C., & Chakrabortty, R. (2019a). Modeling of water induced surface soil erosion and the potential risk zone prediction in a sub-tropical watershed of Eastern India. Modelling Earth Systems and Environment, 5(2), 369–393. https://doi.org/10.1007/s40808-018-0540-z
Pal, S. C., & Chakrabortty, R. (2019b). Simulating the impact of climate change on soil erosion in sub-tropical monsoon dominated watershed based on RUSLE, SCS runoff and MIROC5 climatic model. Advances in Space Research, 64(2), 352–377. https://doi.org/10.1016/j.asr.2019.04.033
Pal, S. C., Chakrabortty, R., Arabameri, A., Santosh, M., Saha, A., Chowdhuri, I., Roy, P., & Shit, M. (2022a). Chemical weathering and gully erosion causing land degradation in a complex river basin of Eastern India: An integrated field, analytical and artificial intelligence approach. Natural Hazards, 110(2), 847–879. https://doi.org/10.1007/s11069-021-04971-8
Pal, S. C., & Chakrabortty, R. (2022b). Soil loss estimation using different empirical and semi-empirical models. Springer Nature.
Pal, S. C., Chakrabortty, R., Roy, P., Chowdhuri, I., Das, B., Saha, A., & Shit, M. (2021). Changing climate and land use of 21st century influences soil erosion in India. Gondwana Research, 94, 164–185. https://doi.org/10.1016/j.gr.2021.02.021
Pal, S. C., Ruidas, D., Saha, A., Islam, A. R. M. T., & Chowdhuri, I. (2022b). Application of novel data-mining technique based nitrate concentration susceptibility prediction approach for coastal aquifers in India. Journal of Cleaner Production, 346, 131205. https://doi.org/10.1016/j.jclepro.2022.131205
Panagos, P., Borrelli, P., Meusburger, K., Alewell, C., Lugato, E., & Montanarella, L. (2015a). Estimating the soil erosion cover management factor at the European scale. Land Use Policy, 48, 38–50. https://doi.org/10.1016/j.landusepol.2015.05.021
Panagos, P., Borrelli, P., Meusburger, K., Van der Zanden, E.H., Poesen, J., & Alewell, C. (2015b). Modelling the effect of support practices (P-factor) on the reduction of soil erosion by water at European scale. Environmental Science and Policy. 51, 23-34. https://doi.org/10.1016/j.envsci.2 015.03.012
Piniewski, M., Bieger, K., & Mehdi, B. (2019). Advancements in soil and water assessment tool (SWAT) for ecohydrological modelling and application. Ecohydrology and Hydrobiology, 19(2), 179–181. https://doi.org/10.1016/j.ecohyd.2019.05.001
Prasannakumar, V., Vijith, H., Abinod, S., & Geetha, N. (2012). Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology. Geoscience Frontiers. 3(2), 209-215. https://doi.org/10.1016/j.gsf.2011 .11.003
Reddy, G. P., Kurothe, R. S., Sena, D. R., Harindranath, C. S., Niranjana, K. V., Naidu, L. G. K., Singh, S. K., Sarkar, D., Mishra, P. K., & Sharda, V. N. (2016). Assessment of soil erosion in tropical ecosystem of Goa, India using universal soil loss equation, geostatistics and GIS. Indian Journal of Soil Conservation, 44(1),1–7.
Renard, K. G., Foster, G. R., Weesies, G. A. and Porter, J. P. (1991). RUSLE: Revised universal soil loss equation. Journal of Soil and Water Conservation, 46(1), 30– 33.
Renard, K. G. (1997). Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). US Department of Agriculture, Agricultural Research Service.
Roy, P., Pal, S. C., Chakrabortty, R., Islam, A. R. M. T., Chowdhuri, I., & Saha, A. (2023). The role of indigenous plant species in controlling the erosion of top soil in sub-tropical environment: In-situ field observation and validation. Journal of Hydrology, 625, 129993. https://doi.org/10.1016/j.jhydrol.2023.129993
Sharma, N., Kaushal, A., Yousuf, A., Sood, A., Kaur, S. and Sharda. R. (2023). Geospatial technology for assessment of soil erosion and prioritization of watersheds using RUSLE model for lower Sutlej sub-basin of Punjab, India. Environmental Science and Pollution Research, 30(1), 515–531. https://doi.org/10.1007/s11356-022-22152-3
Singh, G., Babu, R., Narain, P., Bhushan, L. S. & Abrol, I. P. (1992). Soil erosion rates in India. Journal of Soil and Water Conservation, 47(1), 97–99.
Smaling, E. M. A., & Oenema, O. (2020). Estimating nutrient balances in agro-ecosystems at different spatial scales. Methods for Assessment of Soil Degradation, 229–252. https://doi.org/10.1201/9781003068716-12
Strahler, A. H., & Strahler, A. (2013). Introducing physical geography. Wiley.
Tarboton, D. G. (1997). A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resources Research, 33(2), 309– 319. https://doi.org/10.1029/96WR03137
Tesfaye, A. (2015). GIS-based time series assessment of soil erosion risk using RUSLE model: A case study of Cheraqe Watershed, Bilate River Sub-Basin, AAU, Ethiopia.
Teshome, A., Halefom, A., Teshome, M., Ahmad, I., Taddele, Y., Dananto, M., Demisse, S., & Szucs, P. (2021). Soil erosion modelling using GIS and revised universal soil loss equation approach: A case study of Guna-Tana landscape, Northern Ethiopia. Modelling Earth Systems and Environment, 7(1), 125–134. https://doi.org/10.1007/s40808-020-00864-0
Thapa, P. (2020). Spatial estimation of soil erosion using RUSLE modeling: A case study of Dolakha district, Nepal. Environmental Systems Research, 9(1), 1–10. https://doi.org/10.1186/s40068-020-00177-2
Tsegaye, L., & Bharti, R. (2021). Soil erosion and sediment yield assessment using RUSLE and GIS-based approach in Anjeb watershed, Northwest Ethiopia. SN Applied Sciences, 3(5), 1–19. https://doi.org/10.1007/s42452-021-04564-x
Ugese, A. A., Ajiboye, J. O., Ibrahim, E. S., Gajere, E. N., Itse, A., & Shaba, H. A. (2022). Soil loss estimation using remote sensing and RUSLE model in Koromi-Federe catchment area of Jos-East LGA, Plateau State, Nigeria. Geomatics, 2(4), 499-517. https://doi.org/10.3390/geomatics2040027
Williams, J. R., Arnold, J. G., Kiniry, J. R., Gassman, P. W., & Green, C. H. (2008). History of model development at Temple, Texas. Hydrological Sciences Journal, 53(5), 948–960. https://doi.org/10.1623/hysj.53.5.948
Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses: A guide to conservation planning (No. 537). Department of Agriculture, Science and Education Administration.
Yesuph, A. Y., & Dagnew, A. B. (2019). Soil erosion mapping and severity analysis based on RUSLE model and local perception in the Beshillo Catchment of the Blue Nile Basin, Ethiopia. Environmental Systems Research, 8(1), 1–21. https://doi.org/10.1186/s40068-019-0145-1
Yousuf, A., Singh, M.J., Benipal, A.K., & Sharma, N. (2022). Soil erosion and sediment yield assessment using RUSLE and GIS based approach in a forest watershed in Kandi region of Punjab. Journal of Soil and Water Conservation, 21(4), 354–360. https://doi.org/10.1007/s42452-021-04564-x
Zanchin, M., Moura, M. M. D., Nunes, M. C. M., Beskow, S., Miguel, P., Lima, C. L. R. D., & Bressiani, D. D. A. (2021). Soil loss estimated by means of the RUSLE model in a subtropical climate watershed. Revista Brasileira de Ciência Do Solo, 45. https://doi.org/10.36783/18069657rbcs20210050