Application of the CSM–CERES–Wheat Model for Yield Prediction and Planting Date Evaluation at Guanzhong Plain in Northwest China. (1st January 2017)

• Record Type: Journal Article
• Authors: Zheng, Zhen; Cai, Huanjie; Yu, Lianyu; Hoogenboom, Gerrit
• Is Part Of: Agronomy Journal. Volume 109:Number 1(2017)
• Page Start: 204
• Page End: 217
• Publication Date: 2017-01-01
• Subjects: Agronomy -- Periodicals; 630
• DOI: 10.2134/agronj2016.05.0289
• Languages: English
• ISSNs: 0002-1962

Abstract

Abstract : Core Ideas: CSM‐CERES‐Wheat model simulated different irrigation regimes under shield and field conditions. Simulated and measured phenology, LAI, total biomass, and grain yield agreed well. The model was not suitable as a tool to determine the optimum sowing date. High density and medium irrigation was the best management practice for wheat. Water is the most important limiting factor for winter wheat ( Triticum aestivum L.) production on the Guanzhong Plain in Northwest China. It is important to develop water management practices by knowing when to irrigate and how much water should be applied. The impact of different irrigation conditions on crop production can be analyzed with crop simulation models. The objectives of this study were (i) to evaluate the performance of the Cropping System Model (CSM)–CERES–Wheat model for simulating the impact of different irrigation regimes on winter wheat growth, development, and grain yield, and (ii) to determine the optimum sowing dates for irrigated and rainfed winter wheat grown under semiarid conditions using the CSM–CERES–Wheat model. Data were obtained from two experiments with three irrigation levels that were conducted under both field conditions and controlled conditions in a rain‐out shelter in Yangling, Shaanxi Province of China, during the 2011–2012 and 2012–2013 growing seasons. The simulation results showed that the model performed well, as indicated by a close correspondence of simulated crop phenology, final aboveground biomass, leaf area index, and grain yield with observed data. The model was inaccurate in simulating winter wheat biomass under stressed conditions. The normalized root mean square error was <2% for phenology, 15.4% for final aboveground biomass, and 14.8% for grain yield. The sowing date analysis showed that a delayed sowing date from 7 September to 27 October caused a decrease in the average yield of 36.7% for all the rainfed and irrigated scenarios. The optimum sowing date was determined to be 7 October for the local farming system.