Evaluation of MEDIWY model for simulation of wheat yield under different irrigation regimes (Case study: Karaj region)

Introduction Many countries have used crop growth models to simulate crop response to environmental stress and various management methods in different decades (Mehraban, 2013). One of the goals of crop simulation models is to be used for crop yield prediction. Researchers have proposed and used various models so far, including: Crop Environment REsource Synthesis (CERES) (Jones and Kiniry, 1986), WOrldFOodSTudies (WOFOST) (Van Keulen and Wolf, 1986), Cropping Systems Simulation Model (CropSyst) (Stockle et al., 1984), etc. However, it should be noted that proposing such models requires the user to be highly skilled at calibration since there are lots of input variables measuring of which is a difficult task. Using some underlying functions, Cordery and Graham (1989) developed a model to simulate crop growth and water value in this process. The model, which in known as MEDIWY, was then calibrated for winter wheat under Bajgah field condition (Ziaei and Sepaskhah, 2003). Generally, using common data, the model which is measured in nearly all weather stations has the potential to properly estimate both growth indices and wheat grain yield under dry and irrigated farming. Its broader application requires doing more experiments in different weather conditions. Therefore, with regard to applicability of MEDIWY model, with at least input data, the present study is to evaluate this model by simulating wheat yield (Marvdasht cultivar) under different irrigation treatments in Karaj region.       Materials and Methods The current research is conducted to study MEDIWY model in simulating wheat yield (Marvdasht Cultivar) under Karaj weather condition. In doing so, we used nine irrigation treatment data carried out in research farm of Islamic Azad University of Karaj during 2003-2004 crop year (Paknejad, 2005). Also, additional required information, such as meteorological data (amount of daily pan evaporation and rainfall) are obtained from Mahdasht weather station in Karaj region. Values concerning meteorological data (rainfall and pan evaporation) and irrigation are entered to this model as input variables. Considering that each of the irrigation treatments used in this study have a special irrigation regime and applied in different stages of growth, for more accurate calibration of MEDIWY model, irrigation treatments are divided to three groups based on level of drought stress so as to be able to calibrate each group separately. For the purpose of evaluating the model, several statistics evaluation methods are employed including: linear regression analysis of observed and simulated data and its comparison with 1:1 line method, Coefficient of Determination (R2), Root Mean Square Error (RMSE), Normalized Root Mean Square Error (NRMSE), and Model Efficiency (ME).     Results and Discussion Results showed that after calibrating MEDIWY model for simulating wheat yield (Marvdasht cultivar) in Karaj region, the obtained values for RMSE, NRMSE, and ME were 265 Kg.ha-1, 5.7%, and 0.99, respectively, which represent appropriateness of statistical indices of calibrated part of the model. According to validation results, statistical indices of RMSE, NRMSE, and ME were 412 Kg.ha-1, 8.5%, and 0.99, respectively, which indicate that the calibrated MEDIWY model can simulate wheat yield values in Karaj region very well. According to findings of the current research, although MEDIWY requires less input data compared to other crop growth models, it has great potential and accuracy for simulating crop yield. Conclusions According to findings of the current research, although MEDIWY requires less input data compared to other crop growth models, it has great potential and accuracy for simulating crop yield.