Ethiopia is facing an acute land degradation problem attributable to complex natural andrnmanmade drivers, and this challenged the ability of rural farmers to meet the growing of foodrndemand. The main objective of this study was to assess land degradation and sustainable landrnmanagement to improve household food security in the north Gojjam sub-basin of the Upper BluernNile. The study was depended on the holistic data gathered through multistage sampling viarndifferent instruments including from Landsat images, 414 randomly selected householdsâ€™ survey,rnkey informant interviews, series of focus group discussions, and field observation. Landsat imagesrnwere analyzed using ArcGIS10.5, QGIS3.1, and ERDAS IMAGINE14 software. Whereasrnsocioeconomic data were analyzed using advanced econometric models and simple descriptivernstatistics using STATA14 and Microsoft excel. The analysis of the LULC results informs thatrnagricultural land use was the most dominant cover, followed by grazing land and bush andrnshrublands. From the period 1986 to 2017 there were significant LULC changes in the sub-basin.rnAgriculture and plantation forest covers have been increased, but other land covers (waterbodies,rnbar land, forest, grazing land, and bush and shrublands) have been decreased due to human andrnnatural driving and pressure. The RUSLE showed that on average 46t ha-1rnyr-1 or a total of 65.21rnmillion tons of topsoil have been lost annually from the sub-basin. The finding of combined spatialrnmulticriteria analysis (MCA) of biological, chemical, and physical land degradation indicatorsrnshow, one-third of the sub-basin was highly degraded. Similarly, land users also confirmed as landrndegradation is a severe problem and has been increasing in the last 10 years. There was arnconsensus with land owners as the productivity of crops, livestock, and the quantity and quality ofrnwater and firewood have been declined and in turn, adversely affect the income and food securityrnof the community. The most widely used SLM measures in the sub-basin were inorganic fertilizer,rnsoil bund, and animal manure. The result from MVP model analysis shows that most adopted SLMrntechnologies are complementary. The model result also depicts farm size, family size, male-headedrnhousehold, participating in local institution, perception on soil erosion severity, livestock size,rntotal income, and extension service increased the adoption probability of most SLM technologies.rnThe result of the endogenous switching regression (ESR) model shown that the adoption ofrnintegrated SLM technologies significantly increased rural farm household food security. Hence,rnthe study suggested that drivers of land degradation should be ceased and sustainable resourcernuse is required, otherwise the limited land resources will be soon lost and no longer be able tornplay their role in socio-economic development. The adoption of integrated SLM technologiesrncontributes to improving householdsâ€™ welfare and the pathway for reducing rural poverty. Thus,rnISLM practice should be promoted in the study area and elsewhere through the motivating of landrnusers via education and training as well as increasing the supply of external agriculture inputs.