以长江中下游平原7个省(市)的19个地区作为样点,统计分析了各样点近36年(1970—2005年)水稻始穗前15d至始穗后20d内日最高气温≥35℃的时空分布特点;并根据全球气候渐变模型GISS GCM Transient B Runs生成的研究区域2030、2050年的气候渐变情景,分析了该地区未来水稻孕穗开花期≥35℃高温逆境的时空演变趋势。结果表明:近36年来长江中下游的早稻孕穗开花期出现高温日数的上升趋势显著,未来气候情景下水稻逆境指标出现日数最多的是单季稻,其次依次为早稻、后季稻;双季稻种植区,在未来气候变化中,长江中游地区温度逆境出现日数将大于下游地区。研究区域水稻气候产量的增减与该地区水稻逆境指标的关系说明,高温导致的颖花败育是水稻减产的重要原因;未来气候变化的两种(2030、2050)情景下,长江中游地区的减产幅度大于长江下游地区,减产幅度最大的是长江中游地区的后季稻。
To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data （Method 1）. The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety （Method 2）, using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology （Method 3）, and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels （Method 4）. The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error （RMSE） values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.
