大气环流因子对黄河流域长预见期农业干旱预测性能的影响  

Influences of atmospheric circulation factors on agricultural drought prediction with long lead time in the Yellow River basin

作　　者：肖悦 粟晓玲[1,2] 吴海江 XIAO Yue;SU Xiaoling;WU Haijiang(College of Water Resources and Architectural Engineering,Northwest A&F University,Yangling 712100,China;Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas,Ministry of Education,Northwest A&F University,Yangling 712100,China)

机构地区：[1]西北农林科技大学水利与建筑工程学院,杨凌712100 [2]西北农林科技大学旱区农业水土工程教育部重点实验室,杨凌712100

出　　处：《农业工程学报》2024年第11期100-108,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：中央高校基本科研业务费专项(2023HHZX004);水利部重大科技项目(SKS-2022018);国家自然科学基金项目(52079111)。

摘　　要：准确的干旱预测对于减轻或规避干旱对区域粮食生产和水资源配置的不利影响至关重要。大气环流因子可能会通过遥相关影响农业干旱的发生、发展和传递过程,在干旱预测模型中引入大气环流因子是否会改善农业干旱的预测性能尚不明晰。该研究以农业干旱、高温和大气环流因子为预测因子,在不同预见期(1、12、24、36、48个月)下采用Meta-Gaussian(MG)模型预测黄河流域典型年份的农业干旱事件,通过纳什效率系数(Nash-Sutcliffe efficiency coefficient,NSE)和均方根误差(root mean square error,RMSE)探究在MG模型中引入大气环流因子对农业干旱预测性能的影响。结果表明:大气环流因子中12个月时间尺度的标准化西太平洋副高强度指数(standardized western Pacific subtropical high intensity index,SWPSHI)与农业干旱相关性最为显著;以典型年2014年8月份为例发现MG模型预测值受预见期长度、预测因子影响较大;相比于单因子预测,引入大气环流因子的MG模型的评价指标NSE和RMSE改善网格占比最高达46%,空间上在内蒙古、宁夏、甘肃、陕西等省区1 a以上预见期明显改善,而考虑大气环流因子和高温的MG模型进一步提升了模型的预测性能,扩大了网格占比。因此在上述省区干旱预测时需考虑大气环流因子的影响。Frequent droughts have posed a serious threat to food security in the agricultural production bases of the Ningmeng Hetao Plain,FenWei Basin,and Yellow River irrigation area within the Yellow River basin.Accurately predicting drought is crucial for ensuring regional food production and water allocation.Among them,atmospheric circulation factors can significantly influence the occurrence,development,and transmission of agricultural drought via remote correlation.It is unclear whether introducing atmospheric circulation factors to the prediction model will improve the prediction performance of agricultural drought.Furthermore,the Meta-Gaussian(MG)model has been applied to drought prediction and achieved great prediction results.This study aims to determine the predictors of agricultural drought using correlation analysis,which includes agricultural drought,high temperature,and atmospheric circulation factors.Three groups of predictors were set:1)agricultural drought(MG2 model),2)agricultural drought and atmospheric circulation factors(MG3 model),and 3)agricultural drought,high temperature,and atmospheric circulation factors(MG4 model).The MG2,MG3 and MG4 models were used to predict agricultural drought in the Yellow River basin in typical years under the different forecast periods(1,12,24,36,and 48 months).Then,a systematic investigation was made to explore the influence of atmospheric circulation factors on the prediction performance of agricultural drought in the MG model using the Nash-Sutcliffe efficiency coefficient(NSE)and root mean square error(RMSE).The results showed that the agricultural drought and high temperature were suitable for the predictors to predict the later agricultural drought.The standardized western Pacific subtropical high intensity index(SWPSHI)on 12-month time scale shared the most significant correlation with agricultural drought compared to other standardized atmospheric circulation indexes.Furthermore,2014 was selected as a typical year because of the severe drought event in the Yello

关 键 词：农业 干旱 模型 预测 大气环流因子 Meta-Gaussian 黄河流域 

分 类 号：S423[农业科学—植物保护] P434[天文地球—大气科学及气象学]