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Africa is grappling with severe food security challenges driven by population growth, climate change, land degradation, water scarcity, and socio-economic factors such as poverty and inequality. Climate variability and extreme weather events, including droughts, floods, and heatwaves, are intensifying food insecurity by reducing agricultural productivity, water availability, and livelihoods. This study examines the projected threats to food security in Africa, focusing on changes in temperature, precipitation patterns, and the frequency of extreme weather events. Using an Exponential Growth Model, we estimated the population from 2020 to 2050 across Africa’s five sub-regions. The analysis assumes a 5% reduction in crop yields for every degree of warming above historical levels, with a minimum requirement of 225 kg of cereals per person per year. Climate change is a critical factor in Africa’s food systems, with an average temperature increase of approximately +0.3 °C per decade. By 2050, the total food required to meet the 2100-kilocalorie per adult equivalent per day will rise to 558.7 million tons annually, up from 438.3 million tons in 2020. We conclude that Africa’s current food systems are unsustainable, lacking resilience to climate shocks and relying heavily on rain-fed agriculture with inadequate infrastructure and technology. We call for a transformation in food systems through policy reform, technological and structural changes, solutions to land degradation, and proven methods of increasing crop yields that take the needs of communities into account.

Land degradation, food and tenure insecurity are significant problems in the northern highlands of Ethiopia, particularly in the region known as the country’s famine corridor. Addressing these twine issues in the region has become a focal point for both local and international organizations, underscoring the significance of preventive measures. Since 2000, the Government of Ethiopia (GoE) has been implementing sustainable land management and certification programs. This study aims on households involved in these programs, specifically in Dessie Zuria and Kutaber Woredas, South Wello Zone (SWZ). The primary objectives of the research were to assess households’ current food security status, identify factors influencing their food security, and classify coping and survival strategies employed by households during food shortages. Primary and secondary sources have been used to collect both qualitative and quantitative data. Quantitative data were collected from surveyed households and analyzed USING SPSS software version 26, whereas qualitative data were transcribed, grouped, and interpreted in line with the aim of the research. Three food security models, namely the Household Food Balance Model, Months of Adequate Household Food Provisioning, and Household Dietary Diversity Score, were employed to evaluate food security. Consequently, a significant percentage of the surveyed households, amounting to 88.3%, 35.6%, and 93.8%, were found to experience food insecurity according to the respective models. Rainfall shortages and variability, crop pests and diseases, shrinking farm plots, and land degradation are among the identified food security determinants. During dearth periods, households deploy a variety of coping and survival strategies. To mitigate food insecurity stemming from both natural and socio-economic factors, the research suggests several recommendations. These include advocating for tenure policy reforms by the GoE, and the local governments should promote the adoption of efficient land management practices, instituting a land certification system based on cadasters, encouraging family planning, boosting investments in education and literacy, raising awareness and providing training in climate-smart agriculture techniques, educating communities on optimal grain utilization, saving, trade, and storage methods, facilitating opportunities for income generation through off-farm and non-farm activities, and offering support for crop and livestock diversification.

Land is a precious resource in the Ethiopian highlands, where the entire agricultural system depends on rain-fed system. The resource faces multiple interconnected environmental and socioeconomic challenges. Among these, the absence of tenure security has significantly affected farmers’ willingness to adopt soil and water conservation practices (SWCPs), leading to a decline in land productivity, hindering household food security, and contributing to an increase in land-related disputes. Bearing this in mind, the government of Ethiopia (GoE) has undertaken two rounds of land certification programs in selected regions, one of which was Amhara National Regional State (ANRS). This study examined how land certification strengthens tenure security, lowers land-related disputes, motivates farmers to employ SWCPs, and raises the productivity of farm plots in Dessie Zuria and Kutaber Woredas. The research followed an exploratory survey method which utilized both qualitative and quantitative data. The survey involved purposefully selected 401 household heads. Additionally, cross sectional data were collected from various sources, including Woreda and zonal agriculture, court, land, and Natural Resource Management (NRM) offices. Quantitative data were analyzed using frequency tables, percentages, graphs, figures, cross-tabulation, and descriptive statistical methods. Meanwhile, qualitative data were transcribed, grouped, and interpreted in line with the research’s objectives. SPSS software version 26 was used for data analysis. The findings denoted a positive relationship between land certification and tenure security. Furthermore, enhanced tenure security has played a positive role in reducing land-related disputes, initiating farmers to invest in SWC practices and improving the productivity of farm plots. The research suggests the adoption of a cadastral land registration system, the encouragement of community involvement, and the enforcement of laws and bylaws. The research recommend implementation of cadastral land registration system, promote community participation, and enforcement of laws and bylaws. The work has implications for development practitioners, academia and policymakers working on land tenure, SWC practices, and food security.

Addis Ababa is one of the eleven cities in Africa that have been taking bold action in meeting the objectives of the Paris Agreement. At the present time, the city is working toward reducing greenhouse gas emissions and enabling the city to be resilient to the impacts of climate change. To make the city carbon neutral and resilient to climate change, the coordination of different sectors and actors is crucial. To this end, the planning and implementation of mitigation and adaptation measures needs effective climate change governance. Thus, this study was intended to explore the effectiveness of climate change governance in Addis Ababa City, Ethiopia. The study followed both quantitative and qualitative research approaches and relied on both primary and secondary data sources. A survey of 232 respondents, who were environment experts at different levels, was conducted using questionnaires. In addition, interviews and observations were conducted to gather relevant data. Secondary data were collected from different sources. The quantitative data were analysed using relative importance index (RII) analysis. The study found that existing environmental policies, strategies, regulations, proclamations, laws, and implementations in the city were facing major challenges in terms of weak accountability, the poor enforcement of regulation, and the failure to involve key actors, especially NGOs, communities, and private sectors; these failures were characterized by weak institutional setup and a lack of formal systems allowing actors (private sectors, communities, and NGOs) to interact to respond to climate change. Hence, climate change governance was ineffective in terms of accountability, participation, law enforcement, equity, institutions, the role of actors, and partnership. Thus, the Addis Ababa City Environmental Protection and Green Development Commission should give more emphasis to the coordination of other actors (NGOs, communities, private sectors, and research institutions) to respond to climate change in the city. In addition, the commission should provide training to the lower layers of experts and mobilise the community for climate change response, particularly in the undertaking of adaptation measures. Furthermore, Addis Ababa City administrators should give due attention to climate change response through an established strong accountability system to enforce regulation, rules, proclamations, laws, policies, and strategies in different sectors.

Agricultural land is an indispensable resource for agrarian communities worldwide. There is a growing awareness that the world’s arable land supplies are limited and finite. For the last five decades, the Government of Ethiopia (GoE) and other development organisations have carried out land preservation uptakes intended to curb the effects of land degradation and improve agricultural productivity through various soil and water conservation practices (SWCPs). The study assessed the sustainability, drivers, and constraints of SWCPs in Dessie Zuria and Kutaber Woredas of South Wollo. We used the exploratory case study approach, involving qualitative and quantitative methods. Catastrophic weather conditions, the presence of the soil and water conservation program, and declining soil fertility were the top drivers influencing the program’s implementation. Based on the identified farm-level indicators and views of the respondents, physical measures were more sustainable than biological and mixed methods. The prominent factors hurdling the intervention were lack of tenure security, risk of rodent infestation, and losing a sense of ownership. Training community members on the importance of land preservation, amending the existing rigid land tenure policy, incorporating indigenous SWCPs, broadening the scale and extent of community participation, and enforcing laws and bylaws are recommended for the upcoming interventions. The finding has implications for land preservation and food security actors working to scale up evidence-based sustainable land management practices to the broader area.

Northern Ethiopia is characterised by fragile mountain eco-systems that are highly susceptible to land degradation, impacting food security and livelihoods. This study appraises Land Use Land Cover Changes (LULCC) and their determinants from 2000 to 2020 in Dessie Zuria and Kutaber Woredas. It explores the LULCC and the key anthropogenic drivers of the change over the past 20 years through a mix of satellite imagery and a survey of local understandings. Six land use types (agriculture, forest, area closure, grazing, settlement and bare land) were mapped from satellite imagery that was acquired from Landsat 7 for the years 2000, 2005, and 2010, and Landsat 8 and OLI multispectral imageries for the years 2015 and 2020 with a spectral resolution of 30-m obtained from USGS. The results showed that agricultural land increased from 29.68% in 2000 to 35.77% in 2020.Furthermore, settlement and grazing lands enlarged from 5.95% and 6.04%, respectively, to 8.31% and 6.35% during the same period, while bare land increased from 9.89% to 10.92% in 2020. On the contrary, forest and area closure decreased from 18.45% and 29.99% to 17.8% and 17.38%, respectively. Meanwhile, population growth, unrestricted grazing, losing a sense of ownership of protected area closures and forests, lack of cooperation, using the free labour mobilisation schemes for government-induced agendas, weak enforcement of laws and bylaws, and engaging farmers for extended days on the campaign were prominent determinants of the changes. This research has implications for development actors across land management and food security towards implementing sustainable land management in the area and beyond.

The headwaters of the Blue Nile River in Ethiopia contain fragile mountain ecosystems and are highly susceptible to land degradation that impacts water quality and flow dynamics in a major transboundary river system. This study evaluates the status of land use/cover (LULC) change and key drivers of change over the past 31 years through a combination of satellite remote sensing and surveying of the local understanding of LULC patterns and drivers. Seven major LULC types (forest land, plantation forest, grazing land, agriculture land, bush and shrub land, bare land, and water bodies) from Landsat images of 1986, 1994, 2007, and 2017 were mapped. Agriculture and plantation forest land use/cover types increased by 21.4% and 368.8%, respectively, while other land use/cover types showed a decreasing trend: water body by 50.0%, bare land by 7.9%, grassland by 41.7%, forest by 28.9%, and bush and shrubland by 38.4%. Overall, 34.6% of the landscape experienced at least one LULC transition over the past 31 years, with 15.3% representing the net change and 19.3% representing the swap change. The percentage change in plantation forest land increased with an increasing altitude and slope gradient during the study period. The mapped LULC changes are consistent with the pressures reported by local residents. They are also consistent with root causes that include population growth, land tenure and common property rights, persistent poverty, weak enforcement of rules and low levels of extension services, a lack of public awareness, and poor infrastructure. Hence, the drivers for LULC should be controlled, and sustainable resources use is required; otherwise, these resources will soon be lost and will no longer be able to play their role in socioeconomic development and environmental sustainability.

Generating land capability class guidelines at a watershed scale has become a priority in sustainable agricultural land use. This study analyzed the area of cultivated land use situated on the non-arable land-capability class in the Jema watershed in the Upper Blue Nile River Basin. Soil surveys, meteorological ground observations, a digital elevation model (DEM) at 30 m, Meteosat at 10 km × 10 km and Landsat at 30 m were used to generate the sample soil texture class, average annual total rainfall (ATRF in mm), terrain, slope (%), elevation (m a.s.l) and land-use land cover (%). The land capability class was analyzed by considering raster layers of terrain, the average ATRF and soil texture. Geo-statistics was employed to fit a surface of soil texture and average ATRF estimates. An overlay technique was used to compute the proportion of cultivated land placed on non-arable land. As per the results of the terrain analysis, the elevation (m a.s.l) of the watershed is in the range of 1895 to 3518 m. The slope was found to be in the range of 0 to 45%. The amount of estimated rainfall ranged from 1640 to 131 mm with value declined from the lower to the higher elevation. Clay loam, clay and heavy clay were found to be the major soil texture classes. Four land capability classes, i.e., II, III, IV (arable) and V (non-arable), were identified with proportions of 28.56%, 45.74%, 22.16% and 3.54%, respectively. Seven land-use land covers were identified, i.e., annual crop land, grazing land, bush land, bare land, settlement land, forestland and water bodies, with proportions of 42.1, 35.9, 8.90, 8.3, 2.6, 2.1, and 0.2, respectively. Around 1707.7 ha of land in the watershed is categorized under non-arable land that cannot be used for annual crop cultivation at any level of intensity. Around 437 ha (3.5%) of land was cultivated on non-arable land. To conclude, the observed unsustainable crop land use could maximize soil loss in upstream regions and siltation and flooding downstream. The annual crop land use that was observed on non-arable land needs to be replaced with perennial crops, pasture and/or forest land uses.

The association between elevation (agro-climatic zones, ACZs) and the mean annual total rainfall (MATRF) is not straightforward in different parts of the world. This study sought to estimate the amount of MATRF across four elevation zones of Jema watershed, which is situated in the northwestern highlands of Ethiopia, by employing an appropriate interpolation method. The elevation of the watershed ranges from 1895 to 3518 m a.s.l. For the sake of this study, 34 sample MATRF data were extracted from satellite and nearby gauge stations that were recorded from 1983 to 2010. These data sources were reconstructed by International Research Institute for Climate and Society at Columbia University, USA, at a scale of 10 km by 10 km. An elevation data set generated from a digital elevation model with 30-m resolution (DEM 30 m) was considered as a covariable to estimate the MATRF. To identify the optimal interpolation model, mean errors were computed using cross-validation statistics. The root-mean-square error (RMSE) analysis showed that ordinary cokriging (OCK) was the most accurate model with a predictive power of 87.3%. The root-mean-square standardized (RMSSE) analysis showed that the best precision value (0.72) occurred in OCK. Stable and Gaussian trend lines together with local polynomial types of trend removal, and an elliptical neighborhood search function could perform best to maximize the accuracy and the precision of estimating MATRF. Elevation, as a covariable, enhanced the degree of accuracy and precision of estimation. The value of the trend line function (least square) between the MATRF and elevation was very weak (R2 = 0.07), whereas the value of trend line function (least square) between the MATRF and the longitude coordinates (east–west direction) was medium (R2 = 0.34). The estimated MATRF for the entire watershed under study ranged from 1228 to 1640 mm. To conclude, elevation could contribute to the estimation of the MATRF. The value of the MATRF showed a declining pattern from the lower to higher elevation areas of the watershed.

Ethiopia is a largely agrarian country with nearly 85% of its employment coming from agriculture. Nevertheless, it is not known how much land is under cultivation. Mapping land cover at finer resolution and global scales has been particularly difficult in Ethiopia. The study area falls in a region of high mapping complexity with environmental challenges which require higher quality maps. Here, remote sensing is used to classify a large area of the central and northwestern highlands into eight broad land cover classes that comprise agriculture, grassland, woodland/shrub, forest, bare ground, urban/impervious surfaces, water, and seasonal water/marsh areas. We use data from Landsat spectral bands from 2000 to 2011, the Normalized Difference Vegetation Index (NDVI) and its temporal mean and variance, together with a digital elevation model, all at 30-m spatial resolution, as inputs to a supervised classifier. A Support Vector Machines algorithm (SVM) was chosen to deal with the size, variability and non-parametric nature of these data stacks. In post-processing, an image segmentation algorithm with a minimum mapping unit of about 0.5 hectares was used to convert per pixel classification results into an object based final map. Although the reliability of the map is modest, its overall accuracy is 55%—encouraging results for the accuracy of agricultural uses at 85% suggest that these methods do offer great utility. Confusion among grassland, woodland and barren categories reflects the difficulty of classifying savannah landscapes, especially in east central Africa with monsoonal-driven rainfall patterns where the ground is obstructed by clouds for significant periods of time. Our analysis also points out the need for high quality reference data. Further, topographic analysis of the agriculture class suggests there is a significant amount of sloping land under cultivation. These results are important for future research and environmental monitoring in agricultural land use, soil erosion, and crop modeling of the Abay basin.