Estimation of Nitrogen Nutrition Index Using AquaCrop and HYDRUS Simulation Models during Maize Growing Period

Monitoring nitrogen nutrition index (NNI) during the growing season requires costly experiments and is a time-consuming process. Recently, some remarkable studies have been carried out in order to determine NNI by employing different plant parameters which can improve fertilizer and water use efficiency and reduce environmental hazards. The main objective of this study was to estimate the NNI during the growing season of maize by using a non-destructive method. Dry matter (W) and actual nitrogen uptake (Nu), the required parameters for predicting NNI, were estimated by AquaCrop and HYDRUS-2D models, respectively. The critical nitrogen curve, proposed by Ranjbar et al. for summer maize in Iran, was used in this study. Plant and soil samples were taken for calibration and validation of the two models during the two growing seasons. The results showed that AquaCrop can accurately predict maize dry matter production during the growth period (R2 =0. 995, NRMSE= 14. 21 %). Moreover, the accuracy of the estimation of nitrogen uptake by the HYDRUS-2D was relatively acceptable (R2 >0. 907, NRMSE< 28. 20 %). Finally, NNI was calculated using measured (NNIo) and simulated (NNIp) data over the two seasons. Comparing the NNIp versus the NNIo revealed that accuracy of the estimated values was acceptable based on the R2and NRMSE criteria (>0. 638 and <20. 86, respectively) in both years.