摘要
为探究变化背景下安徽省干湿指数时空分布格局,利用安徽省1957-2016年的逐日气象观测数据,在采用区域修正模式的FAO 56 Penman-Monteith模型计算潜在蒸散量(ET0)的基础上,通过云模型定量描述近60年安徽省干湿指数(AI)的时空分布特征、均匀性和稳定性。结果表明:安徽省AI、ET0呈现波动下降趋势,倾向率分别为-0.006 a-1和-0.583 mm/a,降水量P呈现1.155 mm/a的上升趋势,ET0和P的相向趋势造成了AI的逐渐降低,近60年安徽省总体呈现变湿趋势。相较于ET0与AI,P最为离散,稳定性最差。在四季尺度上,以夏季为主导(-0.012 a-1)的夏秋冬AI降低为安徽省干湿变化主要特征,AI超熵值由高到低依次为夏季、秋季、春冬季,不确定性逐渐降低;四季ET0变化熵值均低于年均熵值,四季ET0模糊性与随机性较差,冬季ET0具有最大不稳定性;夏冬季节的雨雪增加与春秋季降水量减少是安徽省四季降水格局的主要表现形式,且夏季降水增加趋势显著(2.467 mm/a),同时表现出最大的不均匀性和不稳定性。在空间尺度上,AI、ET0和P均呈现皖南至皖北的梯度变化特征,出现非平滑纬度地带性现象,空间上各区域熵与超熵均高于时间序列,空间上AI的分布更为离散、不稳定。
Spatio-temporal characteristics of dry-wet change are the key characterization of regional hydrological response under global change. To explore the temporal and spatial distribution characteristics of dry-wet index in Anhui Province under the background of global change,spatio-temporal distribution characteristics of aridity index was comprehensively investigated for 15 meteorological stations during1957-2016 in Anhui Province. Based on the calculation of potential evapotranspiration( ET0) by the FAO 56 Penman-Monteith model with regional correction mode,the temporal and spatial distribution characteristics,uniformity and stability of the dry-wet index( AI) in Anhui Province in the past 60 years were quantitatively described by the cloud model. The AI and ET0 in Anhui Province showed a downward trend,with propensity rates of-0. 006 a-1 and-0. 583 mm/a,respectively,and P showed an upward trend of 1. 155 mm/a. The opposite trend of ET0 and P caused the AI to gradually decrease.Anhui Province generally showed a trend of becoming wet. P was the most discrete and had the worst stability compared with ET0 and AI. On the four-season scale,summer-autumn and winter AI,which was dominated by summer(-0. 012 a-1),was the main feature of dry-wet change in Anhui Province. The AI super-entropy value with descending order was summer, autumn, spring and winter, and the uncertainty was gradually reduced. The change entropy of ET0 in the four seasons was lower than the annual average entropy. The ambiguity and randomness of the four seasons’ ET0 were poor. The winter ET0 had the greatest instability. The increase of rain and snow in summer and winter and the decrease of precipitation in spring and autumn were the four seasons’ characteristics in Anhui Province. The main form of the pattern and the summer precipitation were increased significantly( 2. 467 mm/a),while showing the greatest unevenness and instability. Spatial scale,AI,and P showed the reference crop evapotranspiration variation gradient of Wannan to Wanbei appeared non-smooth latitudes phenomenon,the spatial region of each entropy size was higher than the super time series entropy,and the spatial distribution characteristics of AI were more discrete and unstable.
作者
孙朋
郭忠臣
刘娜
戴洪宝
苏海民
SUN Peng;GUO Zhongchen;LIU Na;DAI Hongbao;SU Haimin(School of Environmental and Surveying Engineering,Suzhou University,Suzhou 234000,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2020年第4期147-155,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
安徽省教育厅高校自然科学重点项目(KJ2019A0670)
安徽省自然科学基金项目(1808085QE176)
宿州学院博士科研启动基金项目(2017jb04)
安徽省高校优秀青年人才支持计划重点项目(gxyqZD2016347)
宿州学院产学研项目(2018hx023)
宿州学院重点科研项目(2019yzd01)。
关键词
干湿指数
安徽省
潜在蒸散量
云模型
时空分布
dry-wet index
Anhui Province
potential evapotranspiration
cloud model
spatio-temporal distribution
