Evaluation of the AquaCrop Model for Simulating Cotton Yield Under a Semi-Arid Environment and Different Field Management Practices
Ghorban Ghorbani Nasrabad, Meysam Abedinpour, and Abotaleb Hazarjaribi
Received: May 02, 2022 / Revised: March 27, 2023 / Accepted: March 31, 2023 https://doi.org/10.62550/EDE44022
Cotton plays an important role in increasing productivity in the agricultural sector and related industries in the province of Golestan, Iran. However, the cultivation areas decreased considerably in the last couple of decades due to the high costs of production, water scarcity, and climate change. To encourage sustainable increase in production, crop simulation models are parameterized for each region using observed field data. In this study, the AquaCrop model was calibrated and validated for cotton under different field management scenarios using data from a 3-yr field experiment, which was conducted at the research farm of the National Cotton Research Institute, Golestan, Iran. The field experiment comprised six irrigation treatments (W1: rainfed/no irrigation, W2: irrigation at 33% of water requirement [WR], W3: irrigation at 66% WR, W4: irrigation at 88% WR, W5: irrigation at 100% WR/full irrigation, and W6: irrigation at 125% WR/over-irrigation) and four rates based on the recommended dose of nitrogen (RDN) (N1: 0 or no N, N2: 33% RDN, N3: 66% RDN, and N4: 100% recommended RDN). The model was calibrated using data from the 1st experimental yr and validated with data from the 2nd and 3rd yr. Simulated and observed data of cotton yield and above ground biomass yield were compared, and the resulting prediction error statistics were 0.85 < E < 0.93, 0.27 < RMSE < 0.58 t ha-1 , and 8.08 < MAE < 14.6%. Moreover, validation results for yield and biomass amounting to 0.85 < E < 0.92 and 0.27 < RMSE < 0.58 t/ha were calculated for 2013 and 2014. Overall, the AquaCrop model estimated cotton yield and biomass with reasonable accuracy under varying field conditions.