Modelling the potential impact of climate change on the productivity of soybean in the Nigeria Savannas

A well-calibrated and evaluated GROPGRO module of the Decision Support System for Agro-technological Transfer (DSSAT) was used to simulate productivity of soybean in northern Nigeria under climate change. Both historical (1990–2019) and projected climate scenarios from 5 general circulation models (GCMs) under two representative
concentration pathways (RCP 4.5 and RCP 8.5) in the mid-century (2040–2069) and end of the century (2070–2099) periods were used. Depending on climate scenario, the minimum temperature is expected to rise by 1.7–4.4oC at Kano in the Sudan savanna (SS) agroecological zone (AEZ) and 1.4–4.0oC at Zaria in the northern Guinea savanna
(NGS) AEZ, while maximum temperatures are projected to increase by 1.7–4.1oC in the SS and 1.3–3.6oC in the NGS. Seasonal average rainfall will increase by 4.8–14.5% in the SS and decrease by 2.6–3.8% in the NGS, relative to the baseline climate. The model predicted delaying trends for days to flowering and maturity for both varieties
in all climate scenarios in the two AEZs.