Climate change and soil erosion are major environmental challenge in the world, which affects societies at whole. The objective of the study was to assess the status of climate change, impact of future change in climate variables on the soil erosion, to provide valuable insight to decision makers on the local vulnerability of the Rib watershed basin area with the RUSLE and SDSM 4.2 model. Satellite remotely sensed data and other ancillary data were used. Software such as ArcGIS 10.4.1 and remote sensing techniques were used. The result of RUSLE model shows that the potential average annual soil loss of the watershed ranges from 0 to 95.05 t/ha/year with a mean annual soil loss of 35.62 ton/ha/year in the year 2008 and 40.91 t/ha/year in the year 2018. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like land use change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of in rib watershed in the Abay basin, north-western highland of Ethiopia, to obtain future impact on soil erosion within the basin. Statistical Downscaling Model (SDSM 4.2) was used to downscale large scale predictors into finer scale resolution. Climate change scenarios of precipitation, maximum and minimum temperature were divided into four time windows of 25 years each from 2001- 2099. The period from 1989-2003 were taken as a base period. To recommend a certain finding there should be a result of riptide compiled research. So it is better that other researcher to conduct further tests of such experiment at this area. But until the experiments being conducted, since this finding was synchrony with other several researches conducted in similar environmental conditions and the result of this finding is the best. However, this needs to be verified with multi-year research. Keywords: ArcGIS, LULC, Soil erosion, Climate Change, SDSM (Statistical downscaling model) , RUSLE (Revised Universal Soil Loss Equation)