Calibration and validation of the AquaCrop model for production arrangements of forage cactus and grass in a semi-arid environment

Abstract

Understanding the best strategies for growing forage plants is important in balancing livestock production, as is the improvement of management techniques aimed at increasing food production. Models that simulate plant growth are therefore important tools for agricultural planning. The aim of this study was to calibrate and validate the AquaCrop model for agricultural systems of the forage cactus, millet and sorghum under different production arrangements. Twelve production units were cultivated from 2019 to 2020, using different cactus clones, and millet and sorghum cultivars, with variations in crop configuration, ground cover, water regime and crop density. Data on the crops (phenology, biometry and biomass throughout the cycle, and productivity at harvest), climate, irrigation, soil and management were observed. In all, data from six production units were used for calibration and six for validation. The performance of the model was evaluated using statistical indices. AquaCrop resulted in admissible errors in predicting the productivity of the crops under evaluation, showing good accuracy with a coefficient of determination greater than 0.80 and performance classified as ‘very good’ (confidence coefficient > 0.80). The Orelha de Elefante Mexicana clone showed the highest mean water productivity (39 g m−2). It was concluded that the model can be used to simulate crop productivity under different cropping arrangements in agricultural environments in the semi-arid region of Brazil with the aim of meeting the forage deficit of livestock in the region.