Scientia Agricultura Sinica ›› 2013, Vol. 46 ›› Issue (6): 1136-1148.doi: 10.3864/j.issn.0578-1752.2013.06.006

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Regional Prediction and Evaluation of Wheat Phenology Based on the Wheat Grow and CERES Models

 吕Zun-Fu , LIU  Xiao-Jun, TANG  Liang, LIU  Lei-Lei, CAO  Wei-Xing, ZHU  Yan   

  1. College of Agriculture, Nanjing Agricultural University/National Engineering and Technology Center for Information Agriculture/Jiangsu Key Laboratory for Information Agriculture, Nanjing 210095
  • Received:2012-10-01 Online:2013-03-15 Published:2012-12-05

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Abstract: 【Objective】The objectives of this study are to investigate the key techniques of wheat phenological model for regional application, and to evaluate the validity of regional application techniques through analyzing the simulated phenology results of WheatGrow and CERES-Wheat at regional scale. 【Method】First, the daily meteorological data at different weather stations were interpolated using the method of Thin Plate Spline (TPS) , and the gridded daily meteorological surface data was generated. Then, the historical sowing dates of wheat at different stations were interpolated using TPS method, and the multi-year average values of interpolated results were generated as regional sowing date surface data. In addition, by integrating the Markov Chain Monte Carlo (MCMC) method with the above two wheat models, the region-specific cultivar parameters were estimated with the measured phenology data from 1998 to 2003, and were taken as the typical cultivar parameters of each province. Finally, the regional daily meteorological data, sowing surface data and region-specific cultivar parameters were input into the above two models, which took grid as basic unit to simulate regional wheat phenology. Meanwhile, the simulated results were evaluated with observed data and the uncertainty coming from cultivar parameters was quantified at site and regional scales. 【Result】The estimated values from the above two models agreed well with the observed values at regional scale. R2 between estimated and observed values of jointing date, heading date and maturity date were 0.85, 0.87 and 0.86 (WheatGrow), 0.87, 0.85 and 0.82 (CERES), respectively. RMSE between the estimated and observed values of jointing date, heading date and maturity date were 9.6, 7.2 and 6.3 d (WheatGrow), 9.4, 7.8 and 6.6 d (CERES), respectively. By analyzing the simulated results of the two models at regional scale, the WheatGrow model had higher prediction accuracy than CERES-Wheat, while the uncertainty came from crop parameters were also higher than CERES-Wheat model.【Conclusion】Through combining the TPS interpolation method with MCMC-based parameter estimation techniques, the mechanism-based model could be effectively extended to regional scales to accurately predict the regional wheat phenology, and quantify the uncertainty coming from the parameter estimation. These results will provide a technology support for estimating crop productivity at regional scale in the future.

Key words: wheat , phenology , TPS interpolating method , MCMC , regional application , uncertainty

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