dc.contributor.author | Luliro, Nadhomi Daniel | |
dc.contributor.author | Tenywa, John Stephen | |
dc.contributor.author | Majaliwa, Jackson Gilbert Mwanjalolo | |
dc.date.accessioned | 2021-12-02T14:24:52Z | |
dc.date.available | 2021-12-02T14:24:52Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Luliro, N. D., Tenywa, J. S., & Majaliwa, J. G. M. (2016). Adaptation of RUSLE to model erosion risk in a watershed with terrain heterogeneity. International Journal of Advanced Earth Science and Engineering, 2(1), 93-107. | en_US |
dc.identifier.issn | 2320 –3609 | |
dc.identifier.uri | https://nru.uncst.go.ug/xmlui/handle/123456789/159 | |
dc.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-1
yr-1
), built up area (35 t ha-1
yr-1
), grassland (25 t ha-1
yr-1
), woodland (11 t ha1
yr-1
), shrub land and seasonal wetland (2.5 t ha-1
yr-1
), permanent wetland (0 t ha-1
yr-1
). While across
soil units erosion risk was highest on Lixic Ferralsols (50 t ha-1
yr-1
), followed by Acric Ferralsols (20 t
ha-1
yr-1
), Arenosols (15 t ha-1
yr-1
), Gleyic Arenosols (2.5 t ha-1
yr-1
), and Planosols (0 t ha-1
yr-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-1
yr-1
and on lowest slopes (0-5) %, the loss was (0–2.5) t
ha-1
yr-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 nonuniform slopes much easier. | en_US |
dc.language.iso | en | en_US |
dc.publisher | International Journal of Advanced Earth Science and Engineering | en_US |
dc.subject | Erosion Risk, Slope Length and Steepness, Arc-Macro Language, GIS, Watershed | en_US |
dc.title | Adaptation of RUSLE to Model Erosion Risk in a Watershed with Terrain Heterogeneity | en_US |
dc.type | Article | en_US |