Soil erosion assessment using Revised Universal Soil Loss Equation (RUSLE) and Geographical information system in May Gabat sub catchment, Northern Ethiopia.
Soil erosion is a major threat to ecosystem health. It is a natural process that occurs when the force of raindrops, wind or running water on the soil surface exceeds the cohesive forces binding the soil particles together. It is a prevalent problem in sub-Saharan countries where it is thought to lead to loss of over 30% of productive land. This study aimed to assess the annual soil erosion rate and develop a soil erosion intensity map for different land units within May Gabat sub-watershed in Ethiopia. A comprehensive methodology that integrated Geographic Information System (GIS) techniques and Revised Universal Soil Loss Equation (RUSLE) model was adopted. Data on soil, slope gradient/length, cover factor and management factors were collected in the field while rainfall raster data was obtained from the wolrdclim database. All the parameters were calculated in excel using relevant models; the results were later exported to ArcMap. Using Raster calculator, the five parameters raster maps were combined together using RUSLE model to produce erosion map. Five erosion classes were obtained, the first class (Very low), are areas that are losing between 0 to 5 tonnes/ha/year of soil; mainly located within the flat areas, well covered by grass and make up 49.02% of the study area. The second class lose between 5 and 12 tonnes/ha/year of soil which is the second largest class covering about 26.48% of the total area and mainly gently sloping areas. The third class make up 3.64% of the study are, losing between 12 and 25 tonnes/ha/year of soil, categorized as medium. The fourth class, High, are losing between 25 and 60 tonnes/ha/year. This category makes up 9.15% of the total study area, commonly in the steep, agriculture and open scrubs and finally, very high class, which is losing over 60 tonnes of soil/ha/year, covers 3.88% of the study area. The results of this suggest that May Gabat is losing a lot of soil through erosion and it may be used to inform management decisions.
Remote sensing; GIS; RUSLE