ENSO影响下安徽省旱涝灾害及农业生产损失时空变化特征

基于1961—2014年25个气象站资料,采用线性趋势法、标准化降水蒸散指数(SPEI)、M-K趋势检验以及皮尔逊相关分析法,分析了ENSO影响下安徽省1961—2014年近54年旱涝时空特征及对农业生产影响。研究表明:(1)与ENSO事件有关的中度以上干旱(洪涝)发生次数占中度以上干旱(洪涝)总次数的68%(83%),且干旱事件受厄尔尼诺次年及拉尼娜年影响大,洪涝受厄尔尼诺当年影响更大;(2)春、秋季SPEI波动幅度大于夏季和冬季,洪旱灾害风险增大。春季呈干旱化趋势,冬季在20世纪90年代湿润化达到最大,随后趋向于干旱化。与皖北地区相比较,皖南地区各月份趋势变化大;(3)安徽各地区的旱涝指数与SSTA的相关性在ENSO冷暖事件中不同,ENSO暖事件对皖南地区相关系数最大达0.32,超过99%置信度检验,影响更为显著,而ENSO冷事件对皖北地区相关系数最大达0.28,超过99%置信度检验,影响更为显著。随着滞后性月份的增加,安徽各区域的旱涝指数与SSTA的相关系数逐渐增大,皖南地区与SSTA相关性大于皖北地区,SSTA对未来3个月皖南旱涝有明显的影响;(4)近20年皖北、皖南地区稻、麦减产主要发生在ENSO事件年或者前一年,且减产率高。皖北地区和江淮地区的小麦减产发生次数较少,小麦减产率较大,而皖南地区小麦减产发生年份较多,小麦减产率较小。ENSO对农业生产的影响与旱涝分布状况有关,江淮地区良好的灌溉条件会降低ENSO年农业旱涝受灾风险。

Temporal and spatial variations of ENSO-induced flood and drought disasters and loss in agricultural production in Anhui Province

Based on daily precipitation data from 25 meteorological stations during the period from 1961 to 2014, the temporal and spatial variations of floods and droughts affected by the El Niñ o-Southern Oscillation(ENSO)and related impacts on agricultural production in Anhui Province in the recent 54 years were analyzed using the linear trend method, the standardized precipitation evapotranspiration index(SPEI), the Mann-Kendall trend test method, and the Pearson correlation analysis method. The results are as follows: (1)ENSO-induced floods and droughts of middle or above levels accounted for 83% and 68% of the total floods and droughts of such levels, respectively, and the droughts were closely related to La Nina events in a same year and El Niñ o events in the subsequent years, while the floods were closely related to El Niñ o events. (2)Higher variability was found in the SPEI in the spring and autumn than in the summer and winter, indicating higher flood and drought risks during the spring and autumn. Generally, a drought tendency was identified in the spring, and flood risk in the winter was relatively higher and a drought tendency was then identified. The tendency changes were more significant in the southern Anhui Province than in the northern Anhui Province. (3)Relations between SPEI and SSTA shifted during the warm and cold phases of ENSO. The warm phase of ENSO had larger impacts on SPEI in the southern Anhui Province, with the largest correlation coefficient being 0. 32, which was above the 99% confidence level. The cold phase of ENSO had more significant impacts on SPEI variations in the northern Anhui Province, with the largest correlation coefficient being 0. 28, which was above the 99% confidence level. The coefficient of correlation between SPEI and SSTA increased with the increasing lag time. The coefficient of correlation between SPEI and SSTA for the southern Anhui Province was larger than that for the northern Anhui Province. SSTA had a great influence on the floods and droughts in the southern Anhui Province in the following three months. (4)Serious reduction of rice and wheat over the recent 20 years in the southern and northern Anhui Province mainly occurred in the ENSO year or in the year prior to the ENSO events. The reduction amount of wheat was larger in the northern Anhui Province and the Jianghuai region with less occurrence frequencies compared to that in the southern Anhui Province. The impact of ENSO on agricultural production was related to the distributions of floods and droughts. The suitable irrigation conditions in the Jianghuai region might reduce the risk of flood and drought disasters in ENSO years.