Developing a Spatial Decision Support System for Climate-Smart Agriculture in Nigeria’s Semi-Arid Zone

Climate-smart agriculture requires spatially differentiated recommendations accounting for local agroclimatic conditions, market access, and farmer capacity. This study develops a spatial decision support system for climate-smart agriculture across Nigeria's semi-arid zone covering Kano, Katsina, Sokoto, Zamfara, and Jigawa states. The system architecture integrates remote sensing-derived climate and soil datasets, crop simulation model outputs from DSSAT, GIS-based market accessibility analysis, and socioeconomic vulnerability indicators into a web-based spatial platform. Agroclimatic recommendation zones are delineated using cluster analysis of 40 years of CHIRPS rainfall data combined with soil and terrain attributes. For each recommendation zone, climate-smart practice options including drought-tolerant variety adoption, conservation tillage, and supplemental irrigation are evaluated against simulated yield stability and profitability metrics. A participatory design process involving 200 extension agents and smallholder farmers in iterative prototype testing ensures the decision support system meets operational usability requirements. System uptake evaluation conducted over a 12-month period with the Kano State Agricultural Development Programme demonstrates a 43 percent improvement in spatial targeting of extension interventions. Keywords: spatial decision support, climate-smart agriculture, semi-arid, Nigeria, crop simulation