Version 1
: Received: 22 February 2021 / Approved: 23 February 2021 / Online: 23 February 2021 (15:54:25 CET)
How to cite:
Tamiru, H.; Wagari, M. RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.. Preprints2021, 2021020526. https://doi.org/10.20944/preprints202102.0526.v1
Tamiru, H.; Wagari, M. RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.. Preprints 2021, 2021020526. https://doi.org/10.20944/preprints202102.0526.v1
Tamiru, H.; Wagari, M. RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.. Preprints2021, 2021020526. https://doi.org/10.20944/preprints202102.0526.v1
APA Style
Tamiru, H., & Wagari, M. (2021). RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.. Preprints. https://doi.org/10.20944/preprints202102.0526.v1
Chicago/Turabian Style
Tamiru, H. and Meseret Wagari. 2021 "RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia." Preprints. https://doi.org/10.20944/preprints202102.0526.v1
Abstract
The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. In this paper, a RUSLE model-based soil loss quanti-fication technique is presented to estimate the annual soil loss and identify the severity of the erosion in the catchment. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. A model builder for the RUSLE model was developed and raster map calcula-tion algebra was applied in ArcGIS version 10.4 to quantify the total annual soil loss. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. The information about the spatial variation of soil loss severity map generated in RUSLE model has a paramount role to alert land resources man-agers and all stakeholders in controlling the effects via implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.
Keywords
RUSLE; Quantification; Severity; Significant Factors; Soil Erosion; Soil Loss
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
