基于春季阴雨过程的冬小麦涝渍指数模型构建与应用

Construction and Application of Waterlogging Index Model of Winter Wheat Based on Spring Rainy Weather

春季涝渍灾害对南方小麦生长发育和产量形成严重影响,本文在对阴湿系数做降尺度修订的基础上,利用Logistic曲线方程构建了冬小麦涝渍指数模型,根据涝渍指数临界值、持续天数以及冬小麦的可能减产率将春季涝渍灾害划分为三个等级,并使用江苏省59个气象站1961-2010年逐日气象资料对模型进行历史反演。结果发现,春季涝渍指数与冬小麦相对气象产量呈显著负相关,随着涝渍指数增加,小麦气象产量线性下降;灾年发生的涝渍过程以1~3次为最多,超过80%,5次以上最少,占1.9%。最后,将涝渍指数模型应用于2014年冬小麦春季涝渍灾害的判别及评估,效果很好。

Spring waterlogging disaster seriously affect the growth and yields of winter wheat in South Chi- na. In this paper, a waterlogging index model of winter wheat is constructed by using the Logistic curve equation based on downscaling amended cloud-moist coefficient. According to the critical index value, the sustained days of rainy weather and the potential yield reduction rate of winter wheat, spring waterlogging disasters are divided into three levels. Then, the model is retrieved by using daily meteorological data from 59 stations in Jiangsu Province from 1961 to 2010. The results show that the waterlogging index are negatively correlated to the relative meteorological yields of wheat. With the increase of waterlogging index, the yields decrease. In wet years the disaster of waterlogging would occur one to three times （87.1%）, and the least was 5 times （1.9%）. Finally, the waterlogging index model is applied to the 2014 spring waterlogging disaster, achieving good result.