Calibration and validation of AquaCrop Model for Maize in Sub-Humid and semi- arid Regions of Central Highlands of Kenya

Farmers in the central highlands of Kenya have been experiencing declining crop yields due to low soil water availability caused by low and unreliable rainfall and poor water harvesting techniques. To increase crop yields, and reduce production risks, research on better use of available rainfall and the interactions between effects of climate, soil and field management on crop production is required. Simulation models, driven by daily climatic data, can be used to predict the impact of long-term climate variability on the probability of success of a range of crop, water and soil management strategies thus providing an opportunity of ‘accelerated learning’ compared with the traditional multi-location, multi-seasonal and multi-factorial field trials. We calibrated the crop water productivity model AquaCrop for maize and validated its performance over three growing season with contrasting rainfall patterns at a sub-humid and a semi-arid site in Central Kenya. The results showed high goodness of fit between observed and the simulated canopy cover with a model efficiency (E) of 0.82 in a sub-humid site and 0.81 in a semi-arid site. The grain and biomass yield simulation was better for the sub-humid site (E = 0.96 for short rains season and 0.88 for long rains season) than for the semi-arid site, though the fit was still acceptable for the latter. Soil water contents showed high correlations between themeasured and the simulated values in 3 depth intervals (0-15, 15- 25, 25-35 cm). AquaCrop’s high reliability for the simulations of grain and biomass yield implies that, when properly calibrated, it can be used in developing strategies for improvement of field management decisions by small scale farmers in reducing crop production risks through ex-ante analyses of rainwater management and field operations options prior to implementation of the best bets.