SOIL LOSS ESTIMATION USING RUSLE INTEGRATED WITH GIS AND REMOTE SENSING IN GUNUNO WATERSHED, WOLAITA ZONE OF SOUTHERN ETHIOPIA

Abstract:

Soil erosion has become a globally challenging issue that poses a serious threat to agriculture and natural resources, particularly in developing countries like Ethiopia. Estimating the magnitude of soil loss and understanding the spatial distribution of erosion-prone areas is critical to plan and effectively implement soil conservation measures with limited resources. This study was conducted in Gununo watershed, where soil erosion is threatening the sustainability of agricultural production and environmental systems, to estimate mean annual soil loss, to identify high erosion risk areas and to prioritize erosion hotspot subwatersheds in Gununo watershed in order to plan and implement evidence-based and site-specific conservation measures. The RUSLE (Revised Universal Soil Loss Equation) model integrated with GIS and remote sensing was used. Primary and secondary input data sets were collected from various sources to analyze RUSLE parameters in the ArcGIS 10.8 environment. The overall analysis was carried out by multiplying input factors together in a raster calculator to quantify soil loss of the entire watershed. The findings revealed that the annual soil loss ranged from 0 to 359.99 t ha-1 yr-1 with a mean annual value of 22.31 t ha-1 yr-1 . The result indicated that 36.06% of the study area is categorized under moderate to very severe erosion classes, which contributed 72.21% of the total soil loss. Zonal statistics result showed that, both bare land and cultivated land were found to be more vulnerable land use classes of the watershed jointly contributing about 72.77% of the total soil loss. Furthermore, the study indicated that the central west and northeast parts of the watershed are highly prone to erosion. The result signified that about 52.9% of the eroded materials including soil and nutrients are transferred to the outlet of Gununo watershed. Besides, the estimated sediment yield ranged from 0 to 42.5 t ha-1 yr-1 with a mean value of 12.02 t ha-1 yr-1 . The RUSLE model was highly sensitive to the C factor followed by LS factor. Based on mean annual soil loss, the subwatersheds SW-4, SW 5, SW-7, SW-8, SW-3, SW-9, SW-6, SW-2, SW-10, and SW-1, are given 1 to 10 sequential priority levels. The mean annual soil loss of six subwatersheds (SW-4, SW-5, SW-7, SW-8, SW 3, and SW-9) covering an area of 57.45% of the total landmass, exceeded the maximum tolerable soil loss rate and were considered as hotspot area of the watershed that need priority in intervention.
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APA

Kassa, D (2024). SOIL LOSS ESTIMATION USING RUSLE INTEGRATED WITH GIS AND REMOTE SENSING IN GUNUNO WATERSHED, WOLAITA ZONE OF SOUTHERN ETHIOPIA. Afribary. Retrieved from https://afribary.com/works/soil-loss-estimation-using-rusle-integrated-with-gis-and-remote-sensing-in-gununo-watershed-wolaita-zone-of-southern-ethiopia

MLA 8th

Kassa, Dawit "SOIL LOSS ESTIMATION USING RUSLE INTEGRATED WITH GIS AND REMOTE SENSING IN GUNUNO WATERSHED, WOLAITA ZONE OF SOUTHERN ETHIOPIA" Afribary. Afribary, 12 Apr. 2024, https://afribary.com/works/soil-loss-estimation-using-rusle-integrated-with-gis-and-remote-sensing-in-gununo-watershed-wolaita-zone-of-southern-ethiopia. Accessed 30 May. 2024.

MLA7

Kassa, Dawit . "SOIL LOSS ESTIMATION USING RUSLE INTEGRATED WITH GIS AND REMOTE SENSING IN GUNUNO WATERSHED, WOLAITA ZONE OF SOUTHERN ETHIOPIA". Afribary, Afribary, 12 Apr. 2024. Web. 30 May. 2024. < https://afribary.com/works/soil-loss-estimation-using-rusle-integrated-with-gis-and-remote-sensing-in-gununo-watershed-wolaita-zone-of-southern-ethiopia >.

Chicago

Kassa, Dawit . "SOIL LOSS ESTIMATION USING RUSLE INTEGRATED WITH GIS AND REMOTE SENSING IN GUNUNO WATERSHED, WOLAITA ZONE OF SOUTHERN ETHIOPIA" Afribary (2024). Accessed May 30, 2024. https://afribary.com/works/soil-loss-estimation-using-rusle-integrated-with-gis-and-remote-sensing-in-gununo-watershed-wolaita-zone-of-southern-ethiopia