Assessing the performance of the FAO Aquacrop model to estimate maize yields and water use under full and deficit irrigation with focus on model parametrization

Abstract

tSeveral maize field experiments, including deficit and full irrigation, were performed in Ribatejo region,Portugal and were used to assess water stress impacts on yields using the AquaCrop model. The modelwas assessed after its parameterization using field observations relative to leaf area index (LAI), cropevapotranspiration, soil water content, biomass and final yield data and also using default parameters. LAIdata were used to calibrate the canopy cover (CC) curve. Results showed that when the CC curve is properlycalibrated, with root mean square errors (RMSE) smaller than 7.4%, model simulations, namely relative tocrop evapotranspiration and its partition, show an improved accuracy. The model performance relative tosoil water balance simulation revealed a bias in estimation but low estimation errors, with RMSE < 13% ofthe total available soil water. However the model tends to overestimate transpiration and underestimatesoil evaporation. A good model performance was obtained relative to biomass and yield predictions, withRMSE lower than 11% and 9% of the average observed biomass and yield, respectively. Overall results showadequacy of AquaCrop for estimating maize biomass and yield under deficit irrigation conditions, mainlywhen an appropriate parameterization is adopted. The model showed less good performance when usingthe default parameters but errors are likely acceptable when field data are not available