Assessment of Meteorologic Condition Effects and Dynamic Yield Forecasting Based on Rice Growth Model

Using daily meteorological data and observation on rice phenology and biomass for the thirty-one agrometeorological stations of the double cropping rice region in the middle Yangtze River Valley from 1981 to 2004, based on adjusting, adaptation and validating for rice growth Model ORYZA2000, the double cropping rice region in the middle Yangtze River Valley is divided into seven areas for the phenological parameters in the model according to the phenological development rate, combined with climate, landform and genetic characteristics of rice. The application of ORYZA2000 in the middle Yangtze River Valley is implemented. Using the regionalized parameter of the crop, the simulation effect of rice phenology and biomass in early rice and late rice is simulated and tested in the growth model. The average errors of samples of fitting verification of anthesis and autumn of early rice and late rice are 3—6 days. And the ones of extrapolated samples are 3—5 days. The average relative errors of samples of fitting verification of the total aboveground biomass and weights of storage organs of autumn of early rice are 12.8% and 20.1% respectively. And ones of extrapolated samples are 10.1% and 19.9%. The average relative errors of samples of fitting verification of the total aboveground biomass and weights of storage organs of autumn of late rice are 8.5% and 6.0%. And ones of extrapolated samples are 2.9% and 3.5%. Test of assessment of meteorological condition effects in different years is carried out using the regionalization of the crop growth model. Using the relative value of annual change of the advance of development and biomass comparing with average ones in the recent three years and the previous year, evaluation of the agrometeorological condition is made (e.g., the phenology is retardation or quickens, and the biomass increases or decreases). The changes of the development stage and influence on biomass and yield of early rice in low temperature in 2002 and late rice in high temperature in 2003 are simulated by the model. The simulation results and assessments are consistent with actual conditions. Several correlation models between simulated dry matter weight of rice at various development stages (panicle initiation, flowering, kernel milky maturity, maturity) and relatively climatic yield for each station are developed, and then rice yield could be forecasted combining the prediction of yield trend. To calculate correlation coefficient significance test of the area models by t test, 23% early rice and 27% late rice yield forecasting by the models at various development stages pass significance level of 0.10, others pass significance level of 0.05, 0.01 or 0.001. With the advance development, significance level of some models raises 0.10 to 0.05. The average relative errors of rice yield forecasting at various development stages for all stations based on rice growth model are 4.8%—6.1%, the results are satisfied.