Chinese Journal of Agrometeorology ›› 2013, Vol. 34 ›› Issue (04): 425-433.doi: 10.3969/j.issn.1000-6362.2013.04.008

• 论文 • Previous Articles     Next Articles

Analysis on the Simulation Adaptability of ORYZA2000 Model for Rice with Different Sowing Date in Anhui Province

HAO Yu, JING Yuan shu, MA Xiao qun, GENG Li ning, YANG Shen bin   

  1. 1Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology/College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China;2Anhui Institute of Meteorology, Hefei 230002
  • Received:2012-10-23 Online:2013-08-20 Published:2014-01-03

Abstract: Simulation was conducted in Xuancheng, Anhui by using of ORYZA2000 model based on observed data of two rice varieties (Liangyou-6326, Nanjing-44) under three different sowing date (May 5,15,25), daily meteorological data as well as soil data during the period from 2010 to 2011. Observed data in 2010 was specified as calibration data set to calibrate model parameters, while observed data in 2011 were classified as validation data set to estimate rice development stages, leaf area index, biomass and yield. The results showed that most rice growth stage development rate of Liangyou-6326 was slightly higher than that of Nanjing-44, the basic nutrition and reproductive stage growth rate of Liangyou-6326 in the third sowing date was largest. However, the growth rate of spike differentiation stage of Nanjing-44 was less, the simulated value of rice growing period was smaller than measured value, the difference was 2~7d. Furthermore, the normalized root mean square error (NRMSE) of different development stages ranged from 3.4% to 7.5%. While the NRMSE of other rice parameters were 16%-22% for aboveground biomass, 20%-25% for green leaves biomass, 17%-21% for stem biomass, 19%-25% for panicle biomass, 24%-26% for leaf area index, 6%-13% for final biomass, and 5%-14% for yield. Over all,ORYZA2000 model could be applied to obtain satisfied simulations of rice growth, development stages and dynamic process of dry matter accumulation on the basis of crop parameter calibration.

Key words: Crop model, ORYZA2000, Sowing date, Rice, Growth season, Yield