Soil loss estimation using GIS and Remote sensing techniques: A case of Koga watershed, Northwestern Ethiopia
Habtamu Sewnet Gelagay, Amare Sewnet Minale
Abstract
Open-access reader
Habtamu Sewnet Gelagay, Amare Sewnet Minale
Abstract
Open-access reader
Soil loss by runoff is a severe and continuous ecological problem in Koga watershed. Deforestation, improper cultivation and uncontrolled grazing have resulted in accelerated soil erosion. Information on soil loss is essential to support agricultural productivity and natural resource management. Thus, this study was aimed to estimate and map the mean annual soil loss by using GIS and Remote sensing techniques. The soil loss was estimated by using Revised Universal Soil Equation (RUSLE) model. Topographic map of 1:50,000 scale, Aster Digital Elevation Model (DEM) of 20 m spatial resolution, digital soil map of 1:250,000 scale, thirteen years rainfall records of four stations, and land sat imagery (TM) with spatial resolution of 30 m was used to derive RUSLE's soil loss variables. The RUSLE parameters were analyzed and integrated using raster calculator in the geo-processing tools in ArcGIS 10.1 environment to estimate and map the annual soil loss of the study area. The result revealed that the annual soil loss of the watershed extends from none in the lower and middle part of the watershed to 265 t ha−1 year−1 in the steeper slope part of the watershed with a mean annual soil loss of 47 t ha−1 year−1. The total annual soil loss in the watershed was 255283 t, of these, 181801 (71%) tones cover about 6691 (24%) hectare of land. Most of these soil erosion affected areas are spatially situated in the upper steepest slope part (inlet) of the watershed. These are areas where Nitosols and Alisols with higher soil erodibility character (0.25) values are dominant. Hence, Slope gradient and length followed by soil erodibility factors were found to be the main factors of soil erosion. Thus, sustainable soil and water conservation practices should be adopted in steepest upper part of the study area by respecting and recognizing watershed logic, people and watershed potentials.
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Soil loss by runoff is a severe and continuous ecological problem in Koga watershed. Deforestation, improper cultivation and uncontrolled grazing have resulted in accelerated soil erosion. Information on soil loss is essential to support agricultural productivity and natural resource management. Thus, this study was aimed to estimate and map the mean annual soil loss by using GIS and Remote sensing techniques. The soil loss was estimated by using Revised Universal Soil Equation (RUSLE) model. Topographic map of 1:50,000 scale, Aster Digital Elevation Model (DEM) of 20 m spatial resolution, digital soil map of 1:250,000 scale, thirteen years rainfall records of four stations, and land sat imagery (TM) with spatial resolution of 30 m was used to derive RUSLE's soil loss variables. The RUSLE parameters were analyzed and integrated using raster calculator in the geo-processing tools in ArcGIS 10.1 environment to estimate and map the annual soil loss of the study area. The result revealed that the annual soil loss of the watershed extends from none in the lower and middle part of the watershed to 265 t ha−1 year−1 in the steeper slope part of the watershed with a mean annual soil loss of 47 t ha−1 year−1. The total annual soil loss in the watershed was 255283 t, of these, 181801 (71%) tones cover about 6691 (24%) hectare of land. Most of these soil erosion affected areas are spatially situated in the upper steepest slope part (inlet) of the watershed. These are areas where Nitosols and Alisols with higher soil erodibility character (0.25) values are dominant. Hence, Slope gradient and length followed by soil erodibility factors were found to be the main factors of soil erosion. Thus, sustainable soil and water conservation practices should be adopted in steepest upper part of the study area by respecting and recognizing watershed logic, people and watershed potentials.
Key concepts: Universal Soil Loss Equation, Watershed, Environmental science, Soil map, Hydrology (agriculture), Surface runoff, Advanced Spaceborne Thermal Emission and Reflection Radiometer, Digital elevation model