Evaluation of AquaCrop model for estimating of changes process of soil moisture, evapotranspiration and yield of maize under salinity and fertility stresses

IntroductionIn the presence of environmental stresses such as salinity and fertility stresses, water and nutrients less absorbed by the plant. Despite the stresses of salinity and nitrogen deficiency (fertility stress), the determination of the actual water requirement of plants with the AquaCrop model, will be important. Therefore, the aim of this research was to evaluate the AquaCrop model for estimating the soil moisture, evapotranspiration and yield of maize, under the salinity and fertility stresses.Materials and methodsIn this research, two treatments of water salinity and nitrogen deficity in four levels and three replications, with a control plot, were implemented as a factorial experiment in a randomized complete of block design. The studied plant was maize with cultivar of 704 Sc and was planted in plots with dimensions of 3 × 3 meters and 1.5 meters apart. In this plan, fertility stress was in the form of nitrogen fertilizer consumption and at four levels. Treatments of N_0، N_1، N_2 and N_3consisted of consumption of 100, 75, 50 and 25% of nitrogen fertilizer based on fertilizer recommendation, respectively. Salinity stress has been applied by irrigation of the plant with saline water. Water salinity treatments were selected based on yield potential of maize at four levels of 100, 90, 75 and 50% (3). According to the above four performance levels, treatments of S_0، S_1، S_2 and S_3 were included; irrigation water with electric conductivity of 0.5, 1.2, 3.5 and 7.5 (ds/m) respectively. Determining the irrigation time, was the same as the moisture content reached the RAW (Readily Available Water) level. Between the two irrigation intervals, the stomatal resistance of maize leaf, was measured by the AP4 prometer device. At the same time as increasing stomatal resistance, RAW was calculated and plots were irrigated. In the days of between two irrigation, was measured the soil moisture content of the plots at the depth of root development. The daily evapotranspiration of the plant, was calculated based on the amount of daily water depletion. For optimal calibration of parameters in the AquaCrop model, was used the method of Generalized Likelihood Uncertainty Estimation (GLUE). Among 16 treatments, 8 treatments were randomly selected for calibration and the rest were selected for validation. Results and discussionResults were obtained for evaluating the AquaCrop model at the validation stage. The root mean square error (RMSE) of soil moisture simulation, varied from 1.43 to 2.6%. The normalized error value (NRMSE) ranged from 4 to 6 percent. The AquaCrop model showed a similar trend in the evapotranspiration simulation. The root mean square error (RMSE) of evapotranspiration simulation, varied from 1.85 to 2.35 mm. The normalized error value (NRMSE) ranged from 3.5 to 4.5 percent. For yield simulation, RMSE was 0.34 ton. ha-1 and NRMSE was 0.65%. The value of the R^2, EF, and d statistics showed a good correlation between the data and the optimal efficiency of the modeling. Therefore, the results showed that the performance of the model was good in estimating the parameters. ConclusionsEvaluating the capability of the models is a great help to the agricultural sector planners, in estimation the parameters. In this research, evaluated the estimation of soil moisture content, evapotranspiration and yield of maize, under salinity and fertility stresses with AquaCrop model. The purpose of the model calibration was to nearing the simulated data to the real data (measured in the region). The obtained amounts for NRMSE and R^2 were less than 10% and greater than 0.9, respectively, which indicated the optimal performance of the model in this regard.