Spatial Targeting of Soil Loss Using RUSLE in GIS: the case of Asokore Mampong Municipality, Ghana

Gift Dumedah; Evans Kyeremanteng; Ema Dari

doi:10.30871/jagi.v3i1.1029

Gift Dumedah Kwame Nkrumah University of Science & Technology
Evans Kyeremanteng
Ema Dari

DOI: https://doi.org/10.30871/jagi.v3i1.1029

Keywords: Soil erosion, Revised Universal Soil Loss Equation (RUSLE), GIS, QGIS, Graphical Modeler, Spatial targeting

Abstract

Soil erosion is a serious environmental problem that is associated with societal impacts including flooding, poor water quality, and loss of plant nutrient leading to low agricultural productivity. Soil erosion wears away the top soil and is controlled by the interaction between several factors including rainfall, steepness of slope, length of slope, vegetation cover, and land management practices. This study developed Geographic Information System (GIS) graphical model based on the Revised Universal Soil Loss Equation (RUSLE), to calculate soil loss in the Asokore Mampong Municipality of the Ashanti region, Ghana. The estimated soil loss was examined the spatial patterns of soil loss and intensity per areas, as an important method for proper planning of management measures. The graphical model was developed using the popular open source GIS software, QGIS, ensuring the availability of the model, automation for any specific area, and its execution to the general public. Data sources used include Digital Elevation Model (DEM) derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), soil properties data obtained from the Global Soil Grids, land cover data from the Global Land Cover by National Mapping Organization (GLCNMO), NDVI (normalized difference vegetation index) data from MODIS (MOD13Q1, 16 Day), and rainfall data from GPCC version 7 (Global Precipitation Climatology Centre). Our results show high levels of soil loss (in tons per hectare per year) in the Municipality, with the capability to spatially target mitigation measures leading to cost effective environmental management.

Downloads

Download data is not yet available.

References

AMMA (2017). Asokore Mampong Municipal Assembly Medium Term Development Plan (2014-2017). Annual Report.

Anurogo, W., & Lubis, M. Z. (2018). Modified Soil-Adjusted Vegetation Index In Multispectral Remote Sensing Data for Estimating Tree Canopy Cover Density at Rubber Plantation. Journal of Geoscience, Engineering, Environment, and Technology, 3(1), 15-24.

Belasri A., Lakhouili A., and Halima Iben O. 2017. Soil erodibility mapping and its correlation with soil properties of Oued El Makhazine watershed, Morocco. Journal of Materials and Environmental Sciences. ISSN : 2028-2508. 8(9): 3208-3215.

De Jong, S. M. (1994) Application of Reflective Remote Sensing for Land Degradation Studies in a Mediterranean Environment (Utrecht: Netherlands Geographical Studies, University of Utrecht).

Foster GR, Yoder DC, Weesies GA, McCool DK, McGregor KC, Bringer RL (2002). User’s Guide—revised universal soil loss equation version 2 (RUSLE 2). USDA-Agricultural Research Services, Washington, DC.

Fujaco Maria Augusta Gonçalves, Leite Mariangela Garcia Praça, and Neves, Antônio Henrique Caldeira Jorge. 2016. A gis-based tool for estimating soil loss in agricultural river basins. REM: Int. Eng. J., Ouro Preto, 69(4), 417-424, http://dx.doi.org/10.1590/0370-44672015690197.

Ghana Statistical Service (2014). Population and Housing Census, Ashanti Regional Analytical Report.

Ghana Statistical Service. (2012). Asante Akim North District; Ghana Statistical Service.

Joshi Veena U. 2018. Soil Loss Estimation based on RUSLE along the Central Hunter Valley Region, NSW, Australia. Journal Geological Society of India, Vol.91, May 2018, pp.554-562, doi: 10.1007/s12594-018-0904-z.

Karaburun Ahmet. 2010. Estimation of C factor for soil erosion modeling using NDVI in Buyukcekmece watershed. Ozean Journal of Applied Sciences 3(1): 77-85.

Kostadinov, S., (2002). Erosion and Torrent Control in Mountainous Regions of Serbia. Preceeding Keynote Paper, International Year of Mountainous Conference. Natural and Socio-economic Effects of Erosion Control in Mountainous Regions.

Le Van Bien, Phuoc Minh Truong, Thi An Tran, and Raghavan Venkatesh. 2014. An Open Source GIS Approach for Soil Erosion Modeling in Danang City, Vietnam. International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences 2014.

Meyer, L. D (1984). Evaluation of the universal soil loss equation, J. Soil Water Conserv., 39, 99–104.
Millward A, Mersey JE (1999). Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena 38:109–129.

Ozsoy G, Aksoy E, Dirim M,Tumsavas Z (2012). Determination of Soil erosion risk in the Mustafa kemalpasa River Basin, Turkey using the revised universal soil loss equation, geographic information system, and remote sensing. Environ Manag 50:679–694.

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. Geosci Front 3:209–215.

Raissouni, A., L.K. Issa, A. El. Arrim, M. Maatouk and R Passalacqua (2012). GIS Based Model to Assess Erosion Sensitivity in Northern Morocco, Laou Watershed Case Study. International Journal of Geosciences, 2012, 3, 610-626.

Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., and Yoder, D. C (1997). A guide to conservation planning with the revised universal soil loss equation (RUSLE), S.US Department of Agriculture, Agricultural Handbook, No. 703.

Roose, E. J. (1975) Erosion et ruisellement en Afrique de l’ouest: vingt annees de mesures en petites parcelles experimentales Cyclo. ORSTOM, Adiopodoume, Ivory Coast.

Sinha, Abhishek P. and Regulwar D.G. 2015. Soil Erosion Estimation of Watershed Using Quantum Geographic Information System (QGIS) and Universal Soil Loss Equation (USLE). International Journal of Science and Research (IJSR). ISSN (Online): 2319-7064, pp: 173-176.

Wischmeier WH, Smith DD (1978). Predicting rainfall erosion losses: a guide to conservation planning. USDA Handbook 537, Washington DC.

Wischmeier, W. H. and Smith, D. D (1965). Predicting rainfall erosion losses from cropland east of the Rocky Mountains: guide for selection for practices for soil and water conservation, in: Agriculture handbook. Department of Agriculture, Science and Education Administration, Washington.

Wischmeier, W.H. (1959) A rainfall erosion index for a universal soil loss equation. Soil Sci. Sec. Amer., Proc., v.23, pp.246-249.

Wischmeier, W.H. And Smith, D.D. (1962) Soil loss estimation as a tool in soil and water management planning, Int. Assoc. Scient. Hydrol. Pub. 59, pp.148-159.