Journal des sciences de la Terre et du changement climatique

Abstrait

Integration of Geo: Spatial and RUSLE Techniques for Soil Loss Estimation and to Identify Potential Soil and Water Conservation Measures in the Northern Ethiopia

Amare Gebre Medhin Nigusse, Belete Alemu

Soil erosion is one of the most severe land degradation challenges in the Ethiopia Highlands which causes siltation of large reservoirs and decline of agricultural production and productivity. This is also happening in the lake Hayq, the northern Ethiopia resulting in series agro-ecological imbalance. Improper cultivation, deforestation and rapid population growth are the main driving forces for this natural hazard. However, scientific studies are hardly found to see the impacts happening on the study area. Hence, present study was conducted with the aim of estimating the rate of soil loss and identifies potential soil and water conservation measures to be introduced in the area. Revised Universal Soil Loss Equation (RUSLE) with an integration of geo-spatial technologies applied to address the stated objectives. The RUSLE model used six important spatial factors namely rainfall data taken from Ethiopian national metrology agency, soil data, slope length and steepness derived from Digital Elevation Model (DEM), vegetation coverage from NDVI and conservation practice implemented were used. These raster baseline maps were prepared using different soft wares derived from various sources. Finally, the raster data added to the RUSLE environment model to evaluate and estimate the soil erosion loss. Similarly, potential conservation measures identified based on social acceptance, conservation performance, labor cost for implement and maintenance. Multi-criteria decisionmaking methods used to rank the conservation measures using the principle of analytic hierarchy process. The finding of this study indicated that the minimum annual soil loss estimated was zero in the outlet area which is less than the minimum tolerable soil loss 2 metric ton/ha/yr. Whereas the maximum annual soil loss was estimated to be 76.8 ton/ha/yr in steep area which is far from the maximum tolerable soil loss (18 ton/ha/yr). Generally, the mean annual soil loss from the catchment was estimated 22.8 ton/ha/yr which accounted a total of 131,966.4 ton/ha/yr soil loss. Of the total catchment, 39.4% (1860.1 ha) of the catchment area lie from non to slightly soil loss; 34.4% (1987 ha) of the catchment under moderately soil loss; 26.2% (1514.9 ha) of the catchment estimated high to very high soil loss. This result is comparable with household’s perception. Finally, the intervention map of the study area was prepared by integration of GIS, RS and RUSLE model and multi-criteria analysis applicable for conservation planning program and sustainable land management and sound soil and water conservation measures in erosion prone areas. To conclude, the study shows the effectiveness of GIS and RS techniques together with RUSLE model in estimating soil loss which can be used as a panacea for decision making such as for water resource infrastructure planning and establishment. But, such scientific studies demanded more comprehensive, reliable and accurate input data for better outcome and decision making.