Solar-powered drip irrigation enhances food security in the Sudano-Sahel

Abstract

Meeting the food needs of Africa's growing population over the next half-century will require technologies that significantly improve rural livelihoods at minimal environmental cost. These technologies will likely be distinct from those of the Green Revolution, which had relatively little impact in sub-Saharan Africa; consequently, few such interventions have been rigorously evaluated. This paper analyzes solar-powered drip irrigation as a strategy for enhancing food security in the rural Sudano-Sahel region of West Africa. Using a matched-pair comparison of villages in northern Benin (two treatment villages, two comparison villages), and household survey and field-level data through the first year of harvest in those villages, we find that solar-powered drip irrigation significantly augments both household income and nutritional intake, particularly during the dry season, and is cost effective compared to alternative technologies.

Fig. 1.

(A) Cartoon schematic of a PVDI system. A PV array powers a water pump, which fills a large concrete reservoir; water is then gravity-distributed at a pressure of 1–3.5 m head through drip irrigation lines. (B) Passive regulation of PVDI systems shown for January 2008–January 2009. Maximum evapotranspiration (ET) need calculated from local weather data (assuming clear sky and no rainfall) is plotted in black. Any shortfalls for expected pump output for average annual weather patterns (Red) and actual pump output (Blue) are met by actual precipitation (Green).

Fig. 2.

Robust fixed effects regression coefficients for project impact on food security indicators. Column 1 shows the difference in outcome variables across all villages and households between November 2008 and 2007 (the overall time trend). Column 2 shows the effect difference for households in treatment villages versus households in control villages over time (the simple effect of living in a project village); column 3 shows effect difference for households with a member in a women’s agricultural group versus non-group-member households across both treatment and control villages over time (the simple effect of being in a women’s agricultural group). Finally, column 4 gives the difference-in-difference coefficient for project impact—the difference in each outcome variable between women’s group member households in treatment villages and the rest of the sample—over the first year of the project. All consumption and purchase data account are given in per capita daily USD at purchasing power parity (PPP), accounting for inflation and allowing for comparison between metrics. Red and blue values are average values for the entire year; green and yellow markers show breakdown for rainy and dry seasons, respectively. [Error bars indicate 95% confidence range; significance: ^p < 0.1 *p < 0.05 **p < 0.01 ***p < .001]

Fig. 3.

NPV of comparable solar- and liquid-fuel-powered drip irrigation systems across discount rates for a range of photovoltaic system and fuel costs (n = 15 yr).