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

• Published in: Ecological modelling 2024-02, Vol.488, p.110606, Article 110606
• Main Authors: Pinheiro, Antonio Gebson, Alves, Cleber Pereira, Souza, Carlos André Alves de, Araújo Júnior, George do Nascimento, Jardim, Alexandre Maniçoba da Rosa Ferraz, Morais, José Edson Florentino de, Souza, Luciana Sandra Bastos de, Lopes, Daniela de Carvalho, Steidle Neto, Antonio José, Montenegro, Abelardo Antonio de Assunção, Gomes, João Emanoel Ambrósio, Silva, Thieres George Freire da
• Format: Article
• Language: English
• Subjects: Agricultural resilience; biomass; biometry; Brazil; cacti and succulents; cultivars; Cultivation strategies; food production; Forage; grasses; irrigation; Livestock; livestock production; millets; model validation; Modelling; phenology; plant density; plant growth; semiarid zones; soil
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2023.110606

•The AquaCrop proved to be efficient and applicable for semi-arid regions.•Improved performance of AquaCrop for simulating crops without using mulch.•AquaCrop excels in calibrating/validating forage plant systems efficiently. 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.