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基于气候适宜度指数的作物产量预报中,各旬气候适宜度加权集成构成了气候适宜度指数,权重系数的确定对预报的准确性至关重要.本文以山东省冬小麦为例,分别采用绝对值法、归一化法和相关系数法确定各旬产量预报的权重系数,分析不同权重系数确定方法得到的气候适宜度指数之间的相关性及气候适宜度指数与农业气象产量的相关性,并利用相对较优的方法进行冬小麦产量动态预报.结果表明:与绝对值法和归一化法相比,采用相关系数法确定的权重系数计算的气候适宜度指数与气象产量的相关系数多数均通过了P<0.01水平的显著性检验,可较全面的反映冬小麦生长发育随气候条件的变化关系.建立的冬小麦产量动态预报模型历史回代检验的准确率基本均为94.5%以上,标准化均方根误差n-RMSE均小于7.0%,表明建立的模型模拟性能较好.对2010—2011年山东省冬小麦产量的外推预报表明,预报平均准确率为93.0%以上,多数预报准确率为96.0%以上,可满足冬小麦产量预报的业务需求.
In crop forecasting based on climate suitability index, climate suitability index is formed by weighted integration of climate suitability at each ten-day period, and the determination of weight coefficient is very important for forecasting accuracy.In this paper, taking winter wheat in Shandong Province as an example, Law, normalization method and correlation coefficient method to determine the weight coefficient of each ten-day forecast, analyze the correlation between climate suitability index obtained by different weight coefficient determination methods and the correlation between climate suitability index and agricultural meteorological output, and The results showed that compared with the absolute value method and the normalized method, most of the correlation coefficients between the climate suitability index and the weather yield calculated by using the weight coefficient determined by the correlation coefficient method all passed The significance test of P <0.01 can comprehensively reflect the relationship between the growth and development of winter wheat and the climatic conditions.The accuracy of the historical back-up test of the dynamic prediction model of winter wheat yield is basically above 94.5%, and the standard error of root mean square error n-RMSE are less than 7.0%, indicating that the established model simulation performance is good.For winter 2010-2011 winter wheat production The extrapolated forecast shows that the average forecast accuracy is above 93.0% and the majority forecast accuracy is above 96.0%, which can meet the business demand of winter wheat yield forecast.