3种水稻趋势产量拟合方法的比较分析

<正>确评估气象条件对粮食产量的影响必须以准确的气象产量为前提,因此,探求长时间序列粮食趋势产量提取分离方法对于更好地指导未来作物生产有重要意义。本文应用辽宁省9个地区17个站点62年的水稻历史产量数据,以相近地区农业生产力技术发展水平应具有一致性、产量序列的趋势应反映国家惠农政策对粮食增产的促进作用、相近地区热量条件变化的一致性可引起气象产量具有同升同降的特点等为评判标准,分析评价了应用HP滤波法、指数平滑法以及Logistic方法分离水稻的趋势产量、气象产量序列的合理性。研究结果表明:1)Logistic方法、HP滤波法以及指数平滑法所拟合出的趋势产量序列与辽宁省平均趋势产量序列一致,3种方法均能较好地反映辽宁省生产力发展水平的区域一致性特点;其中,沈阳、铁岭、鞍山、辽阳、丹东和锦州6个地区的趋势产量序列与辽宁省平均趋势产量序列间的一致性相关系数达0.908以上,表现为一致性极好;2)HP滤波法拟合出的趋势产量序列能较真实地反映由于生产力和国家政策变化所带来的实际产量的变化趋势,指数平滑法次之,而Logistic方法提取的趋势产量变化趋势反映社会发展实际的能力最差;3)不同趋势产量分离方法得到的气象产量区域平均值序列具有相似的年际及年代际变化特征,三者之间无显著区别(P0.05);HP滤波法分离得到的气象产量吻合气候特征的能力最强,指数平滑法次之,Logistic方法最差。综合分析,辽宁省水稻趋势产量的提取以应用HP滤波法最优,指数平滑法次之,而Logistic方法不适合辽宁省水稻趋势产量的提取。研究结果可为作物趋势产量拟合提供方法借鉴。

Comparative analysis of three fitting methods of rice trend yield

It is a prerequisite to have accurate meteorological data for correct assessment of the effects of meteorological factors on grain yield. As such,it is important to explore rational methods to fit trend yields of crops to guide future crop production efforts. In this study,62 years of historical data on rice yield from 17 sites in 9 regions in Liaoning Province were used to rationalize the separation of the trend yield of rice in relation to meteorological factors. The separated trend yields with three fitting methods-HP filter method,exponential smoothing method and logistic method,were compared and discussed. The rationality of the above three methods were evaluated based on the following preconditions:1) the agricultural productivity and technological development in similar regions was consistent,2) the yield series change reflected promoting effects of state favorable policies on crop yield,and 3) uniformity of the regions with similar heat condition caused same changes in crop yield. The results showed that:1) the trend yield series fitted by the three methods were consistent with the average trend yield series of Liaoning Province,suggesting that the three methods properly reflected the regional consistency of development. Results analysis indicated good consistencies of trend yields of Shenyang,Tieling,Anshan,Liaoyang,Dandong,Jinzhou with that of Liaoning Province,and coefficients of correlation for the regions was as high as 0.91.2) The trend yield series fitted by HP filter method truly reflected the actual trend yield affected by the changes in the levels of national productivity and national policy. This suggested that the goodness of fit for the HP filter method with actual trend yield was the best,followed by the exponential smoothing method. The extraction of the trend yield also basically reflected actual social development,whereas the goodness of fit for the logistic method had the worst performance. 3) Average regional meteorological yield series obtained with different methods had similar inter-annual and inter-decadal variation characteristics,with no significant difference among the methods (P > 0.05). Compared with the two other methods,the meteorological yield series obtained by the HP filter method matched well with climatic variations,followed by the exponential smoothing method. In conclusion,among the three methods of fitting,the HP filter method was the best for fitting the trend yield of rice in Liaoning Province,followed by the exponential smoothing method and then the Logistic method (which was actually not suitable for fitting the trend yield of rice in Liaoning Province). The research results provided the needed reference for trend yield trend fit analysis.