基于春季阴雨过程的冬小麦涝渍指数模型构建与应用

发布时间：2019-07-04 11:14

【摘要】：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。
文内图片：

图片说明：图１阴雨过程中逐日影响权重拟合Ｆｉｇ．逦１逦Ｔｈｅ邋ｆｉｔｔｉｎｇ逦ｖａｌｕｅｓ逦ｏｆ逦ｗｅｉｇｈｔ逦ｄｕｒｉｎｇｒａｉｎｙ邋Ｗｅａｔｈｅｒ邋ｐｒｏｃｅｓｓｅｓ
[Abstract]:The waterlogging disaster in spring has a serious influence on the growth, development and yield of wheat in the south of China. Based on the revision of the coefficient of yin and humidity, the waterlogging index model of winter wheat is constructed by using the Logistic curve equation. According to the critical value of waterlogging index, the duration of the disaster and the possible yield reduction of winter wheat, the waterlogging disaster in spring is divided into three grades. The historical inversion of the model is carried out by using the daily meteorological data of 59 meteorological stations in Jiangsu Province from 1961 to 2010. The results showed that the waterlogging index in spring was negatively correlated with the relative meteorological yield of winter wheat, and the meteorological yield of wheat decreased linearly with the increase of waterlogging index, and the waterlogging process occurred in the disaster year was the most, more than 80%, and the least was more than 5 times, accounting for 1.9%. Finally, the waterlogging index model is applied to the discrimination and evaluation of winter wheat spring waterlogging disaster in 2014, and the effect is very good. Fig. 1 Daily influence weight fitting Fig. / The / fitting / of / weight / duringrainy / processes / of / weight / duringrainy / Weather / processes / of / weight / duringrainy / processes
【作者单位】：江苏省气象台;江苏省气象服务中心;
【基金】：中国气象局气象关键技术集成与应用项目(CMAGJ2015M24) 公益性行业(气象)科研专项(GYHY201406028) 国家自然科学基金项目(11371412)共同资助
【分类号】：S512.11;S422

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