Simulating Maize Yield Response to Depletion of Available Soil Water and Nitrogen Management under Drip Irrigation with the FAO AquaCrop Model

• Published in: Russian agricultural sciences Vol. 46; no. 6; pp. 602 - 608
• Main Authors: Amiri, E., Abedinpour, M.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 2020; Springer Nature B.V
• Subjects: Agricultural management; Agricultural research; Agriculture; Biomass; Biomedical and Life Sciences; Calibration; Corn; Crop yield; Depletion; Drip irrigation; Field tests; Grain; Irrigation; Life Sciences; Mean square errors; Melioration; Model testing; Moisture content; Nitrogen; Nutrients; Plant Biochemistry; Root-mean-square errors; Simulation; Soil moisture; Soil water; Water stress; maize crop; management allow depletion; calibration; nitrogen; AquaCrop model; validation
• ISSN: 1068-3674; 1934-8037
• DOI: 10.3103/S1068367420060038

Crop simulation models of different complexity have been developed for predicting the effects of soil, water and nutrients on growth and water productivity of different crops. These models are calibrated and validated for a given region using the data generated from field experiments. Therefore, AquaCrop model was calibrated and validated for grain maize (Single Cross 260) under varying irrigation and nitrogen levels. The experiment was conducted at the research farm of the agricultural college, Islamic Azad University, Shiraz during summer season 2011 and 2012. Irrigation treatments consisted of different levels of depletion of available soil water. The four levels of moisture depletions considered in the study were 20, 40, 60 and 80 percent. Nitrogen application levels were 150 (N 1 ), 200 (N 2 ), 250 (N 3 ) and 300 kg ha –1 . Root Mean Square error (RMSE), Prediction error ( P e ), coefficient of determination ( R 2 ) and normalized root mean square error (RMSE n ) were used to test the model performance. The model was calibrated for simulating maize grain and biomass yield for all treatment levels with the prediction error 4 < P e < 5 per cent, 0.64 < R 2 < 0.81 and 469 < RMSE < 786 t ha –1 . Upon validation, P e between 10 and 6; R 2 between 0.65 and 0.76 and RMSE between 1062 and 1293 for grain and biomass yield, respectively. The highest and the lowest accuracy to predict yield and biomass under all nitrogen levels was obtained at I 1 (MAD: 20%) and I 4 (MAD: 80%) treatments, respectively. The results of the present study show that the AquaCrop model simulates aboveground biomass more accurately than grain yield. Also, model cannot provide satisfactory results under severe water stress conditions.