Calibrating and validating AquaCrop model for maize crop in Northern zone of Nigeria

Abstract

Farmers in the northern Guinea Savannah ecological zone of Nigeria have been experiencing declining crop yield due to erratic water supply. In recent times, research on better water management and interaction between effects of climate, soil and field management on crop production is fast gaining grounds with the use of models. Models can be used to predict the impact of long-term climate variability, thus providing an opportunity of better techniques compared with the traditional multi-location trials. This study presents the calibration and validation of AquaCrop model for drip irrigated maize (Zea mays). Calibration was done using data of 2013, while validation across seasons was done with data of 2014. The modelling efficiency of grain yield, biomass yield and crop water use were 81%, 90%, and 85% when calibration was done, while during the validation the modelling efficiency were 86%, 74% and 50%, respectively. This indicates a good fit between the simulated output and measured data. The model has a tendency to over-predict grain and biomass yield at harvest by 3%-4%, under-predict seasonal evapotranspiration by 2%, and over-predict grain water productivity by 3% and biomass water productivity by 24% according to the coefficient of residual mass. The AquaCrop model high reliability for the simulations indicates it can be useful for on-the-desk assessing of the impact of irrigation scheduling protocols when properly calibrated.