Parameterization and Evaluation of the AquaCrop Model for Full and Deficit Irrigated Cotton

Abstract

Predicting yield is increasingly important to optimize irrigation under limited available water for enhanced sustainability and profitable production. Food and Agriculture Organization (FAO) of the United Nations addresses this need by providing a yield response to water simulation model (AquaCrop) with limited sophistication. In this study, AquaCrop was parameterized and tested for cotton (Gossypium hirsutum L.) under full (100%) and deficit (40, 60, and 80% of full) irrigation regimes in the hot, dry, and windy Mediterranean environment of northern Syria. Model parameterization used the 2006 data and was straightforward within the designed user-interface, owing to the limited number of key parameters. Accurate simulation of canopy cover was central to sound prediction of evapotranspiration and biomass accumulation. Key user-input parameters for this purpose were identified as the coefficients defining canopy development and the threshold soil water depletion levels for the water stress indices. The parameterized model was tested using data from the 2004 and 2005 seasons, resulting in accurate prediction of evapotranspiration (<13% error). The predicted yield values were within 10% of measurements, except in the 60 and 80% irrigation regimes in 2004, with errors up to 32%. The model closely predicted the trend in total soil water, but deviation existed for individual soil layers. This study provides first estimate values for cotton parameters useful for future model testing and use. Model parameterization is site-specific, and thus the applicability of key calibrated parameters must to be tested under different climate, soil, variety, irrigation methods, and field management.