Mohammad Reza Emdad; arash tafteh; saeed ghalebi
Abstract
Introduction: Simulation models have been used for decades to analyse crop responses to environmental stresses. AquaCrop is a crop water productivity model developed by the Land and Water Division of FAO. It simulates yield response to water of herbaceous crops, and is particularly suited to address ...
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Introduction: Simulation models have been used for decades to analyse crop responses to environmental stresses. AquaCrop is a crop water productivity model developed by the Land and Water Division of FAO. It simulates yield response to water of herbaceous crops, and is particularly suited to address conditions where water is a key limiting factor in crop production. It is designed to balance simplicity, accuracy and robustness, and is particularly suited to address conditions where water is a key limiting factor in crop production. AquaCrop is a companion tool for a wide range of users and applications including yield prediction. Aquacrop has high accuracy and performance for yield prediction than other models regarding to irrigation and fertilizer management base foundation. Using Aquacrop model for crop yield simulation in different soil and water managements has high accuracy and its use requires calibration and validation. The use of models saves time and cost and, if calibrated and validated, acceptable results are expected.
Material and Methods: This research was carried out in order to calibrate and validate the Aquacrop model for simulating wheat grain yield in the three selected pilots in Hamidiyeh province of Khuzestan province in two years of cultivation.In this regard, three different plots with a total area of about 10 hectares were selected in Hamidyeh region. Sampling, measuring and determining the parameters of soil, water, plant, irrigation management (information required for the Aquacrop model) and the existing conditions of the area were carried out.The climatic data required in Aquacrop model was collected from synoptic meteorological weather station of Ahvaz. Irrigation water quality with mean water salinity of 1.9 dS/m has a good quality for irrigation. In the first year, 5 irrigation events (with a total volume of 9500 cubic meters per hectare) are available to the wheat plant at different stages. In this regard, based on meteorological data and field and vegetation data that was taken from the field level in the first year, the Aquacrop model calibration and performance variations were carried out at different times of irrigation using a simulation model. In order to validate the results simulated by the model, the best scenario provided by the model in the second year was implemented at selected farm level and its results were compared with the simulation results by the model.
Results and Discussion: Aquacrop model calibrated for the first year and then compared for different scenarios of irrigation timing (3-6 irrigation event).The amount of grain yield and total in 4 irrigation intervals are not different with the corresponding values in 5 irrigation intervals. Irrigation rotations were considered in accordance with routine irrigation rotations of the region during planting, tillering, stemming, flowering and seed filling (5 turns) for 4 steps of irrigation step and for 3 irrigation stages, the tiller and stem elongation was deleted. The model showed that, using four irrigation timing is the most appropriate irrigation scenario. Using the results of the model with considering 4 irrigation times, wheat was planted in the second year for model validation. In the second year, the average of measured and simulated wheat grain yield was 3.8 and 4.4 t/h (with 14% error).Average values of total yield and simulated wheat seeds in 4 and 5 irrigation intervals were not different, while the amount of water consumed in 4 irrigation intervals decreased by 20% compared to 5 irrigation intervals. On the other hand, water use efficiency increased by up to 21% in 4 irrigation intervals compared to 5 irrigation intervals. Also, according to the simulation, it was observed that increasing the irrigation interval at the arrival stage, while not significantly increasing the grain yield and the total, did not increase the water use efficiency in order to increase the water consumption (one irrigation interval) Reduced. Considering 3 irrigation timing, the grain yield decreased by 15%. Due to the reduced yield in three irrigation intervals than the more irrigation intervals, this scenario is not recommended for performance reasons. So, according to the simulation, at least 4 irrigation intervals (during planting, stemming, flowering and seed filling) are recommended to maintain proper production level in existing conditions. Comparison of statistical indices between measured and simulation values of wheat grain yield in both years showed that the coefficient of correlation, normalized root mean square error (RMSE) and agreement index were 0.9, 0.14, and 0.89 respectively, which indicates the proper performance of the model for simulating yield of wheat for two consecutive years. The average grain yield of simulated wheat has been estimated at 3.8 ton / ha, which estimates 14% of grain yield less than actual experimental conditions compared to its measured value, indicating the accuracy and efficiency of this model in simulating wheat yield in the present situation. With considering 4 irrigation events, the water use efficiency of wheat grain yield increased by 0.7 kg/m3, which confirms the ability and accuracy of the Aquacrop model for simulating grain yield of wheat and also improving water use efficiency.
Conclusions: The results of this study showed that the simulation of wheat yield in the first year (2.6 t/ha) has a close proximity to the measured values of yield (3 t/ha). Also, validation of the model with changing conditions in the second year showed that the simulated yield of wheat (4.4 t/ha) also had a good agreement with its measured value (3.8 t/ha), which indicates the high accuracy of this model in simulating wheat grain yields every two years. Therefore, this model has the efficiency and accuracy in simulating wheat yield in research conditions.
