摘要
依据安徽省春季连阴雨灾害指标,采用统计学方法,分析了安徽省近50年连阴雨空间变化规律;进一步利用近40年(1961—1999年)历史气象数据及油菜产量数据,分区域建立了油菜灾损率与连阴雨致灾因子的定量关系,并用近10年(2000—2009年)油菜产量资料验证了该模型的准确性。结果表明:(1)安徽省连阴雨过程、持续降水量和连阴雨频率空间分布,自北向南呈台阶状增加,淮河以北连阴雨出现频率和强度最低,沿江江南连阴雨出现频率和强度最高,尤其是皖南山区南部地区;(2)江淮地区,模型能够较好地反映该区域连阴雨对油菜产量的影响,相对误差为13.4%;沿江地区,实际灾损率在20%~25%之间模拟效果较好,相对误差为13.0%;皖南山区,在实际灾损率较大的情况下,模型可较准确地反映油菜的减产情况,相对误差为15.8%。此方法建立的连阴雨灾害指标与油菜产量的定量关系,可用于定量评估连阴雨灾害发生时,油菜产量损失状况。
In order to evaluate the risks of spring continuous precipitation in Anhui Province objectively and accurately,the spatial variation of spring continuous precipitations was calculated and analyzed according to the standard definition of the spring continuous-rain disaster and a quantitative assessment was made of the loss of rape yield,sub-regionally using the related meteorological data and rape yield data from 1960 to 1999,the model ’ s veracity was verified by means of the yield data from 2000-2009.The results showed that:(1) the quantity and intensity of the steady raining distribution increased dramatically from north to south in Anhui Province,the lowest appears in the north of the Huai River and the highest appeared in the south of the Yangtze,especially in the Anhui south region;(2) The model used in Jianghuai region had good performances on predicting the rape yield in response to the spring continuous-rain disaster,the relative errors(RE) for yield reduction was 13.4%;The model used in the areas along the Yangtze River could have a good forecast when the actual yield reduction was between 20% and 25%,the relative errors(RE) for yield reduction was 13.0%;The model for Anhui south region performed well when the actual yield reduction was high,the relative errors(RE) for yield reduction was 15.8%.Based on the results,the quantitative model could be used to evaluate the rape yield loss.
出处
《中国农学通报》
CSCD
2012年第34期252-256,共5页
Chinese Agricultural Science Bulletin
基金
公益性行业(气象)科研专项"遥感技术在作物生长模式及农业气象预报中的应用研究"(GYHY201106027)
关键词
春季连阴雨
分布特征
油菜
产量
评估
spring continuous precipitations
spatial variation
rape
yield
assessment