Calibration and Validation of AquaCrop Model for Rice under Prayagraj Agro-Climatic Conditions

Abstract

Rice (Oryza sativa L.) is the principal food crop of the Indo-Gangetic plains, and its sustainable production is increasingly constrained by water scarcity and climatic variability. Crop simulation models offer a robust means of evaluating crop response to management practices without the cost and time demands of exhaustive field trials. This study calibrated and validated the FAO AquaCrop model for rice cultivar SARJU-52 grown under three transplanting dates (1, 11 and 21 July) and five irrigation regimes (rainfed, continuous flooding, alternate wetting and drying, irrigation at 3-day intervals, and irrigation at 7-day intervals) at the Field Nursery, College of Forestry, SHUATS, Prayagraj, during the 2019 and 2020 kharif seasons. Field-observed grain yield, above-ground biomass, harvest index and canopy cover (derived from Leaf Area Index using the Beer–Lambert relationship) from 2019 were used to calibrate the model, while the independent 2020 dataset was used for validation. Model performance was assessed using the root mean square error (RMSE), normalised RMSE (NRMSE), coefficient of determination (R²) and mean absolute error (MAE). The calibrated model reproduced observed grain yield with R² values of 0.97 (sowing windows) and 0.94 (irrigation schedules) during calibration, and R² values of 0.92 and 0.93, respectively, during validation, with correspondingly low RMSE and NRMSE. Biomass simulations showed R² values of 0.88 or above in both phases, while canopy cover at 60 and 90 days after sowing was reproduced with NRMSE values generally below 5%. Among treatments, early transplanting (1 July) and moderate, well-timed irrigation (alternate wetting and drying and 7-day interval irrigation) produced the highest observed and simulated yields, whereas rainfed conditions and delayed transplanting reduced productivity. These results confirm that AquaCrop, after site-specific calibration, is a dependable decision-support tool for simulating rice growth, yield and water-use responses under the agro-climatic conditions of Prayagraj and provides a validated basis for subsequent irrigation-scheduling and climate-impact studies.