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Adaptation of RUSLE to Model Erosion Risk in a Watershed with Terrain Heterogeneity


 
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1. Title Title of document Adaptation of RUSLE to Model Erosion Risk in a Watershed with Terrain Heterogeneity
 
2. Creator Author's name, affiliation, country Nadhomi Daniel Luliro; Department of Geography, Geo-Informatics and Climatic Sciences, Makerere University, Kampala; Uganda
 
2. Creator Author's name, affiliation, country John Stephen Tenywa; Department of Agricultural Production, Makerere University, Kampala; Uganda
 
2. Creator Author's name, affiliation, country Jackson Gilbert Mwanjalolo Majaliwa; Department of Geography, Geo-Informatics and Climatic Sciences, Makerere University, Kampala; Uganda
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Erosion Risk, Slope Length and Steepness, Arc-Macro Language, GIS, Watershed
 
4. Description Abstract

The modeling capability of the Revised Universal Soil Loss Equation (RUSLE) on a heterogeneous landscape is usually limited due to computational challenges of slope length and slope steepness (LS) factor. RUSLE can be adapted to Arc-Macro (C++) executable programs to obtain LS values even for highly variable landscapes based on Digital Elevation Models (DEMs); and then predict erosion risk. The objective of this study was to compute LS factor from DEM using C++; and predict soil erosion risk in a banana-coffee watershed of the Lake Victoria Basin (LVB) of Uganda. DEM data of Nabajuzi watershed were used as an input file for running the (C++) executable program to obtain LS factor. The predicted LS values were calibrated against tabulated LS values; and a strong linear relationship (R = 0.998) was observed between them. The LS factor increased with slope length and slope gradient. Erosion risk across landuse were predicted as follows: small scale farmland (38 t ha-1yr-1), built up area (35 t ha-1yr-1), grassland (25 t ha-1yr-1), woodland (11 t ha-1yr-1), shrub land and seasonal wetland (2.5 t ha-1yr-1), permanent wetland (0 t ha-1yr-1). While across soil units erosion risk was highest on Lixic Ferralsols (50 t ha-1yr-1), followed by Acric Ferralsols (20 t ha-1yr-1), Arenosols (15 t ha-1yr-1), Gleyic Arenosols (2.5 t ha-1yr-1), and Planosols (0 t ha-1yr-1). The risk of erosion increased linearly with slope gradient in the site (R = 0.96). On the steepest slopes (15-18) %, the loss ranged from (38–68) t ha-1yr-1 and on lowest slopes (0-5) %, the loss was (0–2.5) t ha-1yr-1. We conclude that embedding C++ with GIS data derives LS factor from DEMs. It provides a bench mark for understanding slope morphology; hence making erosion risk prediction on non-uniform slopes much easier.

 

 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2013-09-28
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://scientific.cloud-journals.com/index.php/IJAESE/article/view/140
11. Source Journal/conference title; vol., no. (year) International Journal of Advanced Earth Science and Engineering; Volume 2 (Year 2013)
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
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