Performance evaluation of AquaCrop model for maize crop in a semi-arid environment

Abstract

Crop growth simulation models of varying complexity have been developed for predicting the effects of soil, water and nutrients on grain and biomass yields and water productivity of different crops. These models are calibrated and validated for a given region using the data generated from field experiments. In this study, a water-driven crop model AquaCrop, developed by FAO was calibrated and validated for maize crop under varying irrigation and nitrogen regimes. The experiment was conducted at the research farm of the Water Technology Centre, IARI, New Delhi during/chaff 2009 and 2010. Calibration was done using the data of 2009 and validation with the data of 2010. Irrigation applications comprised rainfed, i.e. no irrigation (W-1) irrigation at 50% of field capacity (FC) (W-2) at 75% FC (W-3) and full irrigation (W-4). Nitrogen application levels were no nitrogen (N-1), 75 kg ha(-1) (N-2) and 150 kg ha(-1) (N-3). Model efficiency (E), coefficient of determination (R-2), Root Mean Square error (RMSE) and Mean Absolute Error (MAE) were used to test the model performance. The model was calibrated for simulating maize grain and biomass yield for all treatment levels with the prediction error statistics 0.95 < E < 0.99, 0.29 < RMSE < 0.42, 0.9 < R-2 < 0.91 and 0.17 < MAE < 0.51 t ha(-1). Upon validation, the E was 0.95 and 0.98; MAE was 0.11 and 1.08 and RMSE was 0.1 and 0.75 for grain and biomass yield, respectively. The prediciton error in simulation of grain yield and biomass under all irrigation and nitrogen levels ranged from a minimum of 0.47% to 5.91% and maximum of 4.36% to 11.05%, respectively. The highest and the lowest accuracy to predict yield and biomass was obtained at W4N3 and W-1 N-1 treatments, respectively. The model prediciton error in simulating the water productivity (WP) varied from 2.35% to 27.5% for different irrigation and nitrogen levels. Over all, the FAO AquaCrop model predicted maize yield with acceptable accuracy under variable irrigation and nitrogen levels. (C) 2012 Elsevier B.V. All rights reserved.