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

•Parameterizing the canopy cover curve supports accurate ET and yield estimations.•Accuracy of predictions improves when parameterization includes soil water or ET observations.•Good biomass and yield predictions were obtained after careful model parameterization.•When using model default parameters predictions are less accurate but acceptable.•The model is good for biomass and yield predictions but less good for soil water simulations. Several 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 model was assessed after its parameterization using field observations relative to leaf area index (LAI), crop evapotranspiration, soil water content, biomass and final yield data and also using default parameters. LAI data were used to calibrate the canopy cover (CC) curve. Results showed that when the CC curve is properly calibrated, with root mean square errors (RMSE) smaller than 7.4%, model simulations, namely relative to crop evapotranspiration and its partition, show an improved accuracy. The model performance relative to soil water balance simulation revealed a bias in estimation but low estimation errors, with RMSE