Vol. 9, Issue 3, Part H (2025)

This study evaluated the FAO-AquaCrop model's performance in simulating onion crop growth and yield under varying irrigation levels and mulching conditions at the Precision Farming Development Centre, Dr. RPCAU, Pusa, Bihar, India. The experiment employed a randomized block design with six treatments combining three irrigation levels (100%, 80%, and 60% water requirement) with and without plastic mulch. The soil at the experimental site was characterized as calcareous sandy loam with 52% sand, 18% silt, and 30% clay, and a mean bulk density of 1.56 g/cc. The AquaCrop model was calibrated using crop-specific parameters including canopy growth coefficient (15.3%/day), canopy decline coefficient (8.0%/day), and growth stages for onion cultivation. Model performance was assessed using statistical indicators including prediction error (Pe), coefficient of determination (R²), mean absolute error (MAE), root mean square error (RMSE), and model efficiency (E). Results demonstrated strong correlations between simulated and observed values for both onion bulb yield (R² = 0.992, E = 0.96, RMSE = 0.33) and biomass (R² = 0.994, E = 0.99, RMSE = 0.28), with low prediction errors ranging from 1.46% to 9.71% for yield and 0.71% to 5.26% for biomass. The model performed consistently across all irrigation levels and mulching conditions, confirming Aqua Crop’s reliability as a decision support tool for optimizing onion production under various water management strategies in the sub-humid climate of Bihar, India.