Document Type : Research Paper
Authors
1
PhD student Department of Irrigation and Drainage, Shoushtar Branch, Islamic Azad University Shoushtar, Iran.
2
Department of Irrigation and Drainage, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran.
3
Department of Civil Engineering-water Resources Engineering and Management, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran
4
Department of Irrigation and Drainage, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
Abstract
In this study, the effect of Aquasorb 3005 on improving the moisture conditions of the plant's root environment and increasing the yield production has been evaluated. This polymer can be used for improving the soil porous media structure to increase water availability in the root zone. The main mechanism of modeling is divided in three parts: field operations, simulation of growth model and analysis. Therefore, an experiment was conducted as split plot based on a randomized complete block design with three replications for evaluating the effect of water tension and superabsorbent treatments on yield production and water productivity. The next step was developing the simulation model by AquaCrop with estimation of canopy cover using four-time steps of each growing period including emergence, maximum canopy, senescence, and maturity. The error statistics of calibration process were evaluated by root mean square error, Nash– Sutcliffe efficiency index normalized objective function, and mean absolute error for the simulated and observed yield production values. Three scenarios of Aquasorb 3005 application (A1=0 kg/ha, A2=300 kg/ha and A3=600 kg/ha) have been considered. Four levels of irrigation water are allocated to the plant including I1=125%, I2=100%, I3=75%, and I4=50% of the total water requirement. According to the error criteria, the highest RMSE value was in scenario I3 at the second cultivation, because the observed values in different replications were very different from each other. The mean absolute error (MAE) values for the first and second growing seasons were 11 and 43 kg/ha, respectively based on 36 observation events.
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