Soil erosion is a fundamental problem in Ethiopia with tremendous impact on soil quality, land productivity, water pollution and sedimentation (e.g.,Tamene, Park, Dikau, & Vlek, 2006a; Hurni, 1983). In many areas of the mountainous regions of northern Ethiopia, erosion has caused critical loss of topsoil and rapid siltation of water harvesting reservoirs (Adimassu, Mekonnen, Yirga, & Kessler, 2014; Tamene et al., 2006a; Tilahun, Esser, Vägen, & Haile, 2002). To tackle the on- and off-sites damages due to erosion,adequate information on the rates and determinants of soil loss as well as spatial distribution of major sediment sources are needed. Since there are wide differences in the rates of sediment yield from different landscape units and application of conservation measures to all areas experiencing erosion is uneconomical and undesirable, conservation measures should be targeted to critical areas experiencing high soil loss. Identification of “hotspot” areas of erosion is therefore imperative from economic, management and sustainability point of view. Soil erosion models are commonly used to investigate the physical processes and mechanisms governing erosion rates and identifying high risk areas of soil loss to aid conservation planning (Jetten, Govers, & Hessel, 2003; Mitasova, Batron, Ullah, Hofierka, & Harmon, 2013). Recent advances in the development of Geographic Information System (GIS) have promoted the application of distributed soil erosion and sediment delivery models at catchment scales (Kamaludin et al., 2013; Mitasova et al., 2013; Tanyas, Kolatb, & Süzenc, 2015). Studies show that terrain shape and topographic complexity play dominant role on the spatial variation of hydrological processes at the catchment scale (Desmet & Govers, 1996a; Mitasova, Hofierka, Zloch, & Iverson, 1996; Van Oost et. al., 2000). Model formulation with topography being treated in more detail may thus allow reproduction of the basic patterns of erosion and deposition in complex landscapes (Wilson & Gallant, 2000). Soil erosion models that emphasize terrain can be the best compromise between the availability of input data and the reliability of soil loss estimates (Ferro, Di Stefano, & Minacapilli, 2003). The slope steepness-length component of the Universal Soil Loss Equation can be adjusted to appropriately simulate the impacts of complex terrain and various soil-and land-cover changes on the spatial distribution of soil erosion (Desmet & Govers, 1996; Mitasova et al., 1996; Moore & Burch, 1986; Moore, Turner, Wilson, Jensen, & Band, 1993; Wilson & Gallant, 2000). In this study the RUSLE adjusted for complex terrain (RUSLE3D)(e.g.,Desmet & Govers, 1996a; Mitasova et al., 1996) was applied to assess landscape sensitivity to erosion using a spatially distributed model in a GIS environment in northern Ethiopia. The RUSLE3D was integrated with sediment delivery ratio (SDR) to estimate sediment yield of catchments. The model was applied in three catchments of scale ca. 10–۲۰ km2 where different forms of erosion processes and a mosaic of heterogeneous environmental factors are observed. Model results were compared with sediment deposition in reservoirs and with data acquired from field surveys.