Mapping of erosive risks is a prerequisite in an erosion control approach. It makes it possible to locate the sectors most vulnerable to erosive processes. The establishment of the erosive risk map results from the spatialization of the Revised Universal Soil Loss Equation (Rusle). This equation is combined with Geographic Information Systems (GIS) and Remote Sensing (RS) techniques to estimate and map average rates of soil loss. If it is possible to significantly reduce soil water erosion through adapted farming techniques such as crop rotation, milling, banding and mulching, it is first necessary to target strong erosion requiring priority intervention. This study was conducted in the Diarha watershed and its sub-basins to assess potential soil losses and map the main factors involved in soil erosion processes. The results show that the erosive risks vary according to climatic and topographic gradients but also soil characteristics of the watershed. Potential soil losses vary between 0 and 1873 t/ha/year depending on the sector. The assessment yielded an average of 36.4t/ha/year and a standard deviation of 105.3t/ha/year. Annual soil losses in the entire Diarha catchment area are estimated at 31882t/year; with a specific degradation of 42t/km2/year. The results will be compared to those of the Gambia watershed in Kedougou station which is contiguous to it.
| Published in | American Journal of Remote Sensing (Volume 5, Issue 4) |
| DOI | 10.11648/j.ajrs.20170504.11 |
| Page(s) | 30-42 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Diarha, GIS and RS, Rusle, Watershed
| [1] | WISCHMEIER W. H. AND SMITH D. D. (1978). Predicting rainfall erosion losses – a guide for conservation planning. U.S. Department of Agriculture, Agriculture Handbook, Washington. |
| [2] | FOTSING, 1993. Erosion of cultivated land and proposals for conservatory soil management in Bamileke country (West Cameroon), House of Remote Sensing, ORSTOM Laboratory 500, rue J. F. Breton, 34093, Montpellier France, http://horizon.documentation.ird.fr/exl-doc/pleins_textes/cahiers/PTP/10009100. PDF. |
| [3] | IBRAHIMA THIAW. Rainfall Variability and Water Supplies in the Diarha Watershed (Tributary of Gambia River). Hydrology. Vol. 5. No. 4, 2017, pp. 41-57. doi:10.11648/j.hyd.20170504.11. |
| [4] | JAH, M. K. AND R. C. PAUDEL, 2010, « Erosion Predictions by Empirical Models in a Mountainous Watershed », Journal of Spatial Hydrology, vol. 10, n°. 1, 14 p. |
| [5] | ARNOLD, J. G., J. R. WILLIAMS, R. SRINIVASAN, K. W. KING ET R. H. GIGGS, 1995, SWAT Soil and Water assessment Tool: draft user manual, US department of Agriculture, Agriculture Service, Temple, TX. |
| [6] | ROOSE, E., 1967. 10 years of measuring erosion and runoff in Senegal, Tropical Agronomy, Extract No 2 February 1967-ORSTOM. |
| [7] | RENARD K. G., G. R. FOSTER, G. A. WEESIES, D. K. MCCOOL AND D. C. YODER (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE), Agricultural Handbook No. 703, US Department of Agriculture, Washington DC. |
| [8] | ROOSE, E., 1994. Introduction to the conservative management of water, biomass and soil fertility, FAO, Soil, Bulletin, 70p.http://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers11-03/41504.pdf. |
| [9] | MCCOOL D, BROWN L, FOSTER G, MUTCHLER C AND MEYER L (1987). « Revised Slope steepness factor for the Universal Soil Loss Equation ». Trans. Am. Soc. Ag. Eng. 30 p. 1387-1396. |
| [10] | HUDSON, N. W., 1973, Soil conservation, Batsford, London, 320 p. |
| [11] | MATI, B. M., R. P. C. MORGAN, F. N. GICHUKI, J. N. QUINTON, T. R. BREWER ET H. P. LINIGER, 2000, « Assessment of erosion hazard with the USLE and GIS: A case study of the Upper EwasoNg’iro North basin of Kenya » International Journal of Applied Earth Observation and Geoinformation, vol. 2, n°. 2, pp. 78-86. |
| [12] | RENARD K. G AND G. R FOSTER 1983. Soil Conservation: Principles of erosion by water. In H. E Dregne and W. O Willis, eds. Dryland Agriculture pp. 155-176. Agronomy Monogr. 23, Am. Soc. Agron., Crop Sci. Soc. Am., and Soil sci. Soc. Am. Madison, Wisconsin. |
| [13] | FAO/IIASA/ISRIC/ISS-CAS/JRC, 2009. Harmonized World Soil Database (version 1.1). FAO, Rome, Italy and IIASA, Laxenburg, Austria. |
| [14] | BROWN, R. B., 2003, Soil Texture, Soil and Water Science Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida, Fact Sheet SL29, 8 p. |
| [15] | STONE, R. P. ET D. HILLBORN, 2000, Universal Soil Loss Equation, Ontario, Canada, Ontario Ministry of Agriculture and Food (OMAFRA), http://www.giser.be/wp-content/uploads/2012/05/USLE-infosCanada.pdf. |
| [16] | EL GAROUANI, A., H. CHEN, L. LEWIS, A. TRIBACK ET M. ABAHROUR, 2008, "Mapping of land use and net erosion from satellite images and IDRISI GIS in North-East Morocco", Remote sensing, vol. 8, n° 3, p. 193201, http://www.teledetection.net/upload/TELEDETECTION/pdf/Vol8No3_193_201.pdf. |
| [17] | ARNOLDUS H. M. 1980. An approximation of the rainfall factor in the Universal Soil Loss Equation. In Assessments of Erosion, de Boodts M, Gabriels D (Eds). John Wiley and Sons Ltd, Chichester 127–132. |
| [18] | OLIVEIRA JR, R. C., MEDINA, B. F. 1990. The erosivity of rainfall in Manaus (AM). Rev. Bras. Solo 14, 235–239. |
| [19] | RENARD, K. G. AND FREIMUND, J. R. 1994. Using Monthly Precipitation Data to Estimate the R factor in the Revised USLE. J. Hydrol. 157: 287–306. |
| [20] | ROOSE, E., 1977, « Application of the Universal Soil Loss Equation of Wischmeier and Smith in West Africa », Soil Conservation Society of America, Ankeny, Iowa, pp. 50-71, http://horizon.documentation.ird.fr/exl-doc/pleins_textes/pleins_textes_5/b_fdi_08-09/09135.pdf. |
| [21] | FICK, S. E AND R. J. HIJMANS, 2017. Wordclim 2: New 1 km spatial resolution climate surfaces for global land areas. International Journal of Climatology. |
| [22] | SCHONBRODT, S.; SAUMER, P.; BEHRENS, T.; SEEBER, C.; SCHOLTEN, T., 2010. Assessing the USLE crop and management factor C for soil erosion modeling in a large, mountainous watershed in Central China. Journal of Earth Science, v.21, p.835-845, 2010. DOI: 10.1007/s12583-010-0135-8. |
| [23] | DURIGON, V. L.; CARVALHO, D. F.; ANTUNES, M. A. H.; OLIVEIRA, P. T. S.; FERNANDES, M. M, 2014. NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of Remote Sensing, v.35, p.441-453. DOI: 10.1080/01431161.2013.871081. |
| [24] | CARVALHO D. F, DURIGON V. L, ANTUNES M. A. H, ALMEIDA W. S, AND OLIVEIRA P. T. S. Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5; Pesq. agropec. bras., Brasília, v.49, n.3, p.215-224, mar.2014; DOI:10.1590/S0100-204X2014000300008. |
| [25] | GANASRI, B. P., RAMESH, H., Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin, Geoscience Frontiers (2015), http://dx.doi.org/10.1016/j.gsf.2015.10.007. |
| [26] | MORSCHEL J. AND FOX D. A method of mapping erosive risk: Application to the hills of Terrefort, Lauragais. M @ ppemonde 76 (2004, 4) http://mappemonde.mgm.fr/num4/articles/art04404.html. |
| [27] | LERIQUE J., 1975. Solid suspended transports in the Gambia at Kedougou and Gouloumbou stations. Results of the 1974 campaign. ORSTOM report, Dakar, multigr., 11p. |
| [28] | BAMBA S. B., 1987. Assessment of water and matter in the Upper Guinean Basin of the Gambia River. UCAD, doctoral, thesis. http://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers16-09/24301.pdf. |
APA Style
Ibrahima Thiaw, Honoré Dacosta. (2018). Mapping of Soil Erosion Risk in the Diarha Watershed Using Rusle, RS and GIS. American Journal of Remote Sensing, 5(4), 30-42. https://doi.org/10.11648/j.ajrs.20170504.11
ACS Style
Ibrahima Thiaw; Honoré Dacosta. Mapping of Soil Erosion Risk in the Diarha Watershed Using Rusle, RS and GIS. Am. J. Remote Sens. 2018, 5(4), 30-42. doi: 10.11648/j.ajrs.20170504.11
AMA Style
Ibrahima Thiaw, Honoré Dacosta. Mapping of Soil Erosion Risk in the Diarha Watershed Using Rusle, RS and GIS. Am J Remote Sens. 2018;5(4):30-42. doi: 10.11648/j.ajrs.20170504.11
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ajrs.20170504.11,
author = {Ibrahima Thiaw and Honoré Dacosta},
title = {Mapping of Soil Erosion Risk in the Diarha Watershed Using Rusle, RS and GIS},
journal = {American Journal of Remote Sensing},
volume = {5},
number = {4},
pages = {30-42},
doi = {10.11648/j.ajrs.20170504.11},
url = {https://doi.org/10.11648/j.ajrs.20170504.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20170504.11},
abstract = {Mapping of erosive risks is a prerequisite in an erosion control approach. It makes it possible to locate the sectors most vulnerable to erosive processes. The establishment of the erosive risk map results from the spatialization of the Revised Universal Soil Loss Equation (Rusle). This equation is combined with Geographic Information Systems (GIS) and Remote Sensing (RS) techniques to estimate and map average rates of soil loss. If it is possible to significantly reduce soil water erosion through adapted farming techniques such as crop rotation, milling, banding and mulching, it is first necessary to target strong erosion requiring priority intervention. This study was conducted in the Diarha watershed and its sub-basins to assess potential soil losses and map the main factors involved in soil erosion processes. The results show that the erosive risks vary according to climatic and topographic gradients but also soil characteristics of the watershed. Potential soil losses vary between 0 and 1873 t/ha/year depending on the sector. The assessment yielded an average of 36.4t/ha/year and a standard deviation of 105.3t/ha/year. Annual soil losses in the entire Diarha catchment area are estimated at 31882t/year; with a specific degradation of 42t/km2/year. The results will be compared to those of the Gambia watershed in Kedougou station which is contiguous to it.},
year = {2018}
}
TY - JOUR T1 - Mapping of Soil Erosion Risk in the Diarha Watershed Using Rusle, RS and GIS AU - Ibrahima Thiaw AU - Honoré Dacosta Y1 - 2018/01/20 PY - 2018 N1 - https://doi.org/10.11648/j.ajrs.20170504.11 DO - 10.11648/j.ajrs.20170504.11 T2 - American Journal of Remote Sensing JF - American Journal of Remote Sensing JO - American Journal of Remote Sensing SP - 30 EP - 42 PB - Science Publishing Group SN - 2328-580X UR - https://doi.org/10.11648/j.ajrs.20170504.11 AB - Mapping of erosive risks is a prerequisite in an erosion control approach. It makes it possible to locate the sectors most vulnerable to erosive processes. The establishment of the erosive risk map results from the spatialization of the Revised Universal Soil Loss Equation (Rusle). This equation is combined with Geographic Information Systems (GIS) and Remote Sensing (RS) techniques to estimate and map average rates of soil loss. If it is possible to significantly reduce soil water erosion through adapted farming techniques such as crop rotation, milling, banding and mulching, it is first necessary to target strong erosion requiring priority intervention. This study was conducted in the Diarha watershed and its sub-basins to assess potential soil losses and map the main factors involved in soil erosion processes. The results show that the erosive risks vary according to climatic and topographic gradients but also soil characteristics of the watershed. Potential soil losses vary between 0 and 1873 t/ha/year depending on the sector. The assessment yielded an average of 36.4t/ha/year and a standard deviation of 105.3t/ha/year. Annual soil losses in the entire Diarha catchment area are estimated at 31882t/year; with a specific degradation of 42t/km2/year. The results will be compared to those of the Gambia watershed in Kedougou station which is contiguous to it. VL - 5 IS - 4 ER -
Information
Email: