气候及其变率变化对东北地区粮食生产的影响

Impacts of Changes in Both Climate and Its Variability on Food Production in Northeast China

利用GISS、GFDL和UKMO 3种国际上通用的平衡大气环流模型(GCM)的有关输出值,结合东北3大农业生态区19个样点近40年(1961—2000)的逐日气候资料(Baseline)以及未来气候变率变化(△CV)的3种假设,并利用天气发生器(WGEN),生成每个样点9种兼顾气候及其变率变化的(CC+△CV)情景;选用DSSAT中的SOYGRO、CERES-Maize、CERES-Wheat和CERES-Rice作为效应模型,并利用各样点的Baseline,同期大豆、玉米、小麦和水稻的产量统计资料以及典型土壤资料,对上述模型进行参数调试、可靠性检验和灵敏度分析;将各效应模型分别在CC+△CV情景及Baseline下运行,通过比较模拟结果,就CO2有效倍增时气候及其变率变化对不同生态区粮食作物的影响做出定量评价。结果表明,4种效应模型在研究区域均有较好的适应性,其作为气候变化影响评价工具具有合理性;气候变暖对东北大豆和水稻生产总体上有利,尤其是在北部高寒区与东部湿润区,模拟产量均明显提高,但CC对玉米和小麦生产的影响以负面为主,特别是玉米在各生态区不同情景下均表现为剧烈减产;随着△CV增大,雨育大豆、玉米和春小麦不仅模拟产量下降,而且稳产性变差,但对灌溉水稻影响不大。

Northeast China abounds in soybean （Glycine max L.）, maize （Zea mays L.）, wheat （Triticum aestivum L.）, and rice （Oryza sativa L.）, and is one of the most susceptive regions to climate change in the country. It has been found an increase in mean annually temperature about 0.34℃ per 10 years in recent 50 years. The probabilities of meteorological disasters, such as drought, flood and cold damages also increase with increasing of climatic variability （CV）, which has caused northeast China to be one of regions with the greatest fluctuation in grain yields in China. According to IPCC, the possible increase in mean earth temperature would be 1.8-4.0℃ from now up to the end of this century. Meanwhile, the mean temperature in northeast China would be obviously higher than that of the earth. The air temperature with adoubling of CO2concentration （555 μmol·mol^-1） in future might be 6-7℃ higher than that at present time according to the predictions of 3 GCMs. Therefore, the possible effects of changes in both climate and it variability on food production in the studied region has drawn more attentions of Chinese government and scientists. In this study, 9 scenarios of （CC＋ACV） involving both climate change （CC） and its variability （ACV） were generated at 19 sites in 3 agroecological zones in northeast China using the WGEN as a tool and based on the output of the 3 General Circulation Models （GISS, GFDL, and UKMO GCMs）, the local current daily weather data from 1961 to 2000 （Baseline） at each site as well as the 3 hypotheses about the increase in CV in future. Then 4 crop models, i.e., SOYGRO, CERES-Maize, CERES-Wheat, and CERES-Rice in DSSAT were selected as the effect models and their parameter modification, validation and sensitivity analyses were done using the baseline weather, statistical yield data of the 4 crops and the local typical soil data. Finally, the potential impacts of changes in both climate and its variability on the food production in the studied regions with a doubling of CO2 concentration doubled were assessed by running the effect models under both baseline and various （CC＋ACV） scenarios, and by making comparison between the output simulated. The results showed that the 4 effect models were available in the studied regions and can be used as a tool in climate impact study. Climate change （CC） would be favorable for soybean and rice production in the studied region, especially in the northern cold zone and eastern wet zone, but unfavorable for both maize and spring wheat, the yields simulated, particularly the maize yield, reduced significantly under all the scenarios. With increasing of CV, not only the yields reduced compared with the control （ACV=0）, but also the yield stabilities decreased for the rainfed crops, such as soybean, maize and spring wheat. However, there was no influence for the irrigated rice.