MODELLING CURRENT AND FUTURE IMPACTS OF CLIMATE CHANGE ON MAIZE YIELD IN KANO STATE, NIGERIA
DOI:
https://doi.org/10.33003/fjs-2026-1002-4519Keywords:
SDSM, Rcps, Climate Parameters, Maize Yield, Non-Parametric Statistics, KanoAbstract
IPCC predicts that climate change will have an impact on agriculture in the future and increase the risk of hunger and water scarcity, with the need to expand agricultural output to feed an estimated nine billion people by 2050. Agricultural system in Kano State depends largely on natural rainfall as the main source of crop production, and thus, exposed to spatial and temporal variability of the climatic parameters of rainfall and temperature. This study used the SDSM tool to downscale current and future temperature and precipitation scenarios in Kano State, Nigeria using data obtained from NASA power for current scenarios and GCM’s CMIP5 for the future scenarios. The results showed an increase in temperature and wet day’s percentages in the future through the RCP8.5, which might impact the maize yield positively or negatively. A non-parametric statistic using Mann-Kendall and Sen.’s slope estimator alongside simple linear regression was conducted on the observed data to check the trend of temperature and precipitation over the years, at the same time the regression analysis was done to check whether the dependent variable (maize) can be affected by the independent variables (temperature and precipitation). The findings showed that precipitation has no significance on maize yield, but temperature has slight significance on the level of maize yield in the study area. Therefore, for future climate projections, it is recommended that other variables such as soil moisture, crop varieties, irrigation and climate-smart agricultural practices be considered for effective increase in maize yield in the study area.
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Copyright (c) 2026 Maryam Shu'aibu Hassan, Isah Usman Hassan; Prof. Amos T. Kabobah
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