水资源与水工程学报

文章摘要

杨少康，刘冀，张特，曹孟，程雄，刘艳丽.长江上游流域地表干燥度指数时空变化特征及其对气象因子的响应研究Journal of Water Resources and Water Engineering[J].,2021,32(4):101-108

长江上游流域地表干燥度指数时空变化特征及其对气象因子的响应研究

Characteristics of spatio temporal variations of surface aridity index and its response to meteorological factors in the upper reaches of the Yangtze River

DOI：10.11705/j.issn.1672-643X.2021.04.14

中文关键词: 地表干燥度指数时空演变气象因子贡献率敏感性长江上游

英文关键词: surface aridity index (AI) spatio temporal evolution meteorological factor contribution rate sensitivity the upper reaches of the Yangtze River

基金项目:国家重点研发计划项目（2018YFC1508104）；国家自然科学基金项目（51679145、91747103、51609124）

Author Name

Affiliation

YANG Shaokang^1,2,3，LIU Ji^1,2,3，ZHANG Te⁴，CAO Meng^5,6，CHENG Xiong¹，LIU Yanli^5,6

（1.三峡大学水利与环境学院，湖北宜昌 443002； 2.三峡库区生态环境教育部工程研究中心，湖北宜昌 443002；3.水资源安全保障湖北省协同创新中心，湖北武汉 430072； 4.西北农林科技大学水利与建筑工程学院，陕西杨陵 712100； 5.南京水利科学研究院水文水资源与水利工程科学国家重点实验室，江苏南京 210098；6.水利部应对气候变化研究中心，江苏南京 210029）

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中文摘要:

长江上游流域作为我国重要的水资源区，在全球气候变暖背景下揭示其地表干燥度演变规律，对于流域水旱灾害防治、生态环境保护及水资源合理开发利用具有重要意义。采用长江上游流域67个气象站1961-2019年逐月气象数据，利用Penman-Monteith模型计算潜在蒸散量，进一步计算地表干燥度指数(AI)，采用气候倾向率、累积距平法、滑动t检验、Mann-Kendall检验法及Morlet小波方法分析AI时空变化特征，采用气候敏感系数法评估AI对主要气象因子的敏感性，进而量化各气象因子对AI变化的贡献率。结果表明：长江上游流域年平均降水量以0.809 mm/10a的速率显著下降（P＜0.05），潜在蒸散量以0.946 mm/10a的速率显著上升（P＜0.05），流域平均AI值以0.014/10a的速率减小，且存在23 a左右的主周期，在1998年发生突变；AI季节性变化显著，冬、春季干燥，夏、秋季相对湿润；长江上游流域多年平均AI分布大致呈东南向西北增加的趋势，半干旱和半湿润区域面积占比分别为47.8%和40.7%；日照时数与平均气温是研究区西北部AI变化的主控因子，风速和相对湿度是东南部AI变化的主控因子。

英文摘要:

The upper reaches of the Yangtze River is an important water resources area in china, revealing the evolution of its surface aridity under the background of global warming is of great significance to the prevention and control of flood and drought disasters in the basin, the protection of ecological environment and rational development and utilization of water resources. Based on the monthly meteorological data from 67 weather stations in the upper reaches of the Yangtze River from 1961 to 2019, the Penman-Monteith model was adopted to calculate the potential evapotranspiration, and then the surface aridity index (AI), climate tendency rate, accumulative anomaly method, sliding t test, Mann-Kendall test and Morlet wavelet method were combined to analyze the characteristics of AI spatio temporal changes, and the climate sensitivity coefficient method was used to assess the sensitivity of AI to the major meteorological factors, by which the contribution rate of each meteorological factor to AI changes was quantified. The results show that the annual average precipitation in the upper reaches of the Yangtze River decreased significantly at a rate of 0.809 mm/10a (P＜0.05), the potential evapotranspiration increased significantly at a rate of 0.946 mm/10a (P＜0.05), and the average AI decreased at a rate of 0.014/10a, with a main cycle of about 23 a and an abrupt change in 1998. Seasonal changes of AI were significant, resulting in dry winters and springs, and relatively humid summers and autumns. The distribution of multi year average AI of the basin generally increased from southeast to northwest. The area of semi arid and semi humid regions accounted for 47.8% and 40.7% respectively. The number of sunshine hours and average temperature were the main influencing factors of AI changes in the northwestern part of the study area, whereas wind speed and relative humidity were the main influencing factors of AI changes in the southeast.

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