Mapping Groundwater Irrigation Potential and Energy Requirements for Food Security Across Sub-Saharan Africa

Enhancing groundwater access in service of agricultural productivity and food security is a critical aspect of integrating sustainable energy solutions into agricultural practices. This is particularly important in Sub-Saharan Africa (SSA), where agricultural productivity has stagnated among smallholder farmers. Current literature is dominated by techno-economic analyses based on large-scale modeling which incorporate accurate biophysical data but lack socioeconomic realities that shape economics of groundwater access. Relatively fewer studies estimate impacts of irrigation expansion based on household surveys and agricultural interventions. The latter while providing a clearer picture of on-ground realities, often lack the scale required to incorporate biophysical data. We build upon both areas by merging biophysical and socioeconomic data to examine the drivers of irrigation technology adoption and simulate energy requirements through an agent-based model. Merging household level survey data from the Living Standards Measurement Study (LSMS) with spatial groundwater characteristics across five SSA countries reveals farm size constraints as a potential economic challenge for future farmer-led irrigation adoption. We find that while plentiful groundwater is available, the distribution of hydrogeologies imply high-energy demand across large parts of Ethiopia, Nigeria, Tanzania and Uganda. With adequate energy infrastructure, currently cultivated area can largely be irrigated even during the dry season for several crops across key food groups including fruits and vegetables, pulses, roots, and grains. To our knowledge, this is the first cross-country integration of LSMS adoption patterns with spatial groundwater constraints to map feasibility for and consequences of irrigation expansion in the region. By linking adoption patterns to groundwater constraints, we identify regions where irrigation expansion is likely, where energy requirements are a likely constraint, and which crop categories are favourable for dry season cultivation. Our findings enable policy planning that prioritises crops which maximize nutritional returns from groundwater based irrigation expansion and identify least-cost pathways for providing the energy access required. Finally, they also provide a basis for managing uncertainty and risk in current and future groundwater stocks across SSA.