潜在蒸散发(ET0)是反映流域水文-气象过程演变的一项关键指标,了解ET0变化特征及其驱动要素的定量影响,对应对未来气候变化下的水循环变异具有重要意义。基于5种气候模拟预测集合数据,通过Peman-Monteith公式预测中国2030—2060年ET0的时空变化趋势,并利用偏微分方法定量分析了驱动ET0变化的各要素贡献。结果表明:在RCP4.5和RCP8.5情景下,未来中国5大气候分区ET0都呈现增加趋势,增加速率分别为1.32 mm/a和1.96 mm/a,亚热带气候区ET0增速最快,而高原山地气候区增速最小,5个气候区在RCP8.5情景下ET0增速都比RCP4.5情景下大。年内4个季节ET0都呈现增加趋势,在RCP4.5情景下秋季ET0增速最快(0.56 mm/a),在RCP8.5情景下夏季ET0增速最快(0.63 mm/a)。未来ET0变化主要受日最高气温、日最低气温以及实际水汽压的影响,其中日最高气温是未来ET0变化的主导气象要素,实际水汽压次之,在年内4个季节ET0变化的驱动要素分析中也发现了类似规律。研究成果可为中国未来水资源优化配置和农业灌溉管理提供参考依据。
Abstract
Potential evapotranspiration (ET0 ) is a critical element that impacts the water cycle of a river basin. Understanding the characteristics of future changes in ET0 and the quantitative impact of its driving factors is of great significance for coping with the variation of water cycle under future climate changes. Using the Peman-Monteith formula and ensemble data from five climate models, we estimated the temporal and spatial trends of China’s potential evapotranspiration from 2030 to 2060, and applied partial differential methods to quantify the contributions of various factors driving ET0 changes. The findings reveal that under the RCP4.5 and RCP8.5 scenarios, the ET0 of five major climate zones in China will exhibit an increasing trend in the future, with rates of increase reaching 1.32 mm/a and 1.96 mm/a, respectively. The fastest growth rate of ET0 is observed in the subtropical climate zone, while in the plateau mountain climate zone, the growth rate is the smallest. The growth rate of ET0 in the five climate zones under the RCP8.5 scenario is greater than that under the RCP4.5 scenario. Overall, ET0 exhibits an increasing trend in all four seasons of the year. Under the RCP4.5 scenario, the ET0 growth rate is the greatest in autumn (0.56 mm/a), while under the RCP8.5 scenario, the largest growth rate is observed in summer (0.63 mm/a). Future changes in ET0 are primarily affected by daily maximum and minimum temperatures, as well as actual water vapor pressure. Daily maximum temperature is the dominant meteorological element governing the magnitude of ET0 changes, followed by actual water vapor pressure. Similar patterns were found in the analysis of the driving factors of ET0 changes in all four seasons. The research findiugs provide reference for optimal allocation of water resources and agricultural irragation management in future.
关键词
潜在蒸散发 /
气候分区 /
Peman-Monteith公式 /
变化特征 /
驱动因子
Key words
potential evapotranspiration /
climatic regions /
Peman-Monteith formula /
change characteristics /
driving factors
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参考文献
[1] 雷慧闽, 蔡建峰, 杨大文, 等. 黄河下游大型引黄灌区蒸散发长期变化特性[J]. 水利水电科技进展, 2012, 32(1): 13-17.
[2] TRENBERTH K E,DAI A,VAN DER SCHRIER G,et al. Global Warming and Changes in Drought[J]. Nature Climate Change, 2014, 4(1): 17-22.
[3] 刘昌明,张 丹.中国地表潜在蒸散发敏感性的时空变化特征分析[J].地理学报,2011,66(5):579-588.
[4] 张永生, 陈 喜, 高 满, 等. 不同气候区潜在蒸散发全局敏感性分析[J]. 河海大学学报(自然科学版), 2017, 45(2): 137-144.
[5] 赵亚迪, 刘永和, 李建林, 等. 1960—2013年中国地表潜在蒸散发时空变化及其对气象因子的敏感性[J]. 沙漠与绿洲气象, 2018, 12(3): 1-9.
[6] WANG Y, JIANG T, BOTHE O, et al. Changes of Pan Evaporation and Reference Evapotranspiration in the Yangtze River Basin[J]. Theoretical and Applied Climatology, 2007, 90(1/2): 13-23.
[7] DONG Y, ZHAO Y, ZHAI J, et al. Changes in Reference Evapotranspiration over the Non-Monsoon Region of China during 1961-2017: Relationships with Atmospheric Circulation and Attributions[J]. International Journal of Climatology, 2021, 41(S1): E734-E751.
[8] 童 瑞, 杨肖丽, 任立良, 等. 黄河流域1961—2012年蒸散发时空变化特征及影响因素分析[J]. 水资源保护, 2015, 31(3): 16-21.
[9] 毕彦杰, 赵 晶, 赵 勇, 等. 京津冀地区潜在蒸散量时空演变特征及归因分析[J]. 农业工程学报, 2020, 36(5): 130-140.
[10] 刘玉婷, 许继军, 姚立强, 等. 基于水量平衡的长江上游地区气象水文要素时空变化特征分析[J]. raybet体育在线
院报, 2022, 39(3): 13-20.
[11] 杜加强, 舒俭民, 刘成程, 等. 黄河上游参考作物蒸散量变化特征及其对气候变化的响应[J]. 农业工程学报, 2012, 28(12): 92-100.
[12] WANG L, CHEN W. A CMIP5 Multimodel Projection of Future Temperature, Precipitation, and Climatological Drought in China[J]. International Journal of Climatology, 2014, 34(6): 2059-2078.
[13] LI C,WU P,LI X,et al. Spatial and Temporal Evolution of Climatic Factors and Its Impacts on Potential Evapotranspiration in Loess Plateau of Northern Shaanxi, China[J]. Science of the Total Environment, 2017, 589: 165-172.
[14] SHARIFI A, DINPASHOH Y. Sensitivity Analysis of the Peman-Monteith Reference Crop Evapotranspiration to Climatic Variables in Iran[J]. Water Resources Management, 2014, 28(15): 5465-5476.
[15] 刘小莽,郑红星,刘昌明,等.海河流域潜在蒸散发的气候敏感性分析[J]. 资源科学,2009,31(9):1470-1476.
[16] HAN J,WANG J,ZHAO Y,et al. Spatio-Temporal Variation of Potential Evapotranspiration and Climatic Drivers in the Jing-Jin-Ji Region, North China[J]. Agricultural and Forest Meteorology, 2018,256/257:75-83.
[17] SHAN N,SHI Z,YANG X,et al.Spatiotemporal Trends of Reference Evapotranspiration and Its Driving Factors in the Beijing-Tianjin Sand Source Control Project Region, China[J].Agricultural and Forest Meteorology,2015,200:322-333.
[18] 张明军,李瑞雪,贾文雄,等.中国天山山区潜在蒸发量的时空变化[J]. 地理学报,2009,64(7):798-806.
[19] WANG J, WANG Q, ZHAO Y, et al. Temporal and Spatial Characteristics of Pan Evaporation Trends and Their Attribution to Meteorological Drivers in the Three-River Source Region, China[J]. Journal of Geophysical Research: Atmospheres, 2015, 120(13): 6391-6408.
[20] YANG P, XIA J, ZHANG Y, et al. Comprehensive Assessment of Drought Risk in the Arid Region of Northwest China Based on the Global Palmer Drought Severity Index Gridded Data[J]. Science of the Total Environment, 2018, 627: 951-962.
[21] HUO Z, DAI X, FENG S, et al. Effect of Climate Change on Reference Evapotranspiration and Aridity Index in Arid Region of China[J]. Journal of Hydrology, 2013, 492: 24-34.
[22] PRYOR S C, LEDOLTER J. Addendum to “Wind Speed Trends over the Contiguous United States”[J]. Journal of Geophysical Research, 2010, 115(D10): D10103.
[23] NING T, LI Z, LIU W, et al. Evolution of Potential Evapotranspiration in the Northern Loess Plateau of China: Recent Trends and Climatic Drivers[J]. International Journal of Climatology, 2016, 36(12): 4019-4028.
[24] 金 巍, 赵春雨, 曲 岩, 等. 中国气温和降水时空分布特征及其各气候区的周期变化分析[C]//第31届中国气象学会年会S4:极端气候事件和灾害风险管理. 北京:中国气象学会,2014: 334.
[25] HEMPEL S,FRIELER K,WARSZAWSKI L,et al.A Trend-Preserving Bias Correction-the ISI-MIP Approach[J]. Earth System Dynamics, 2013, 4(2): 219-236.
[26] 袁 星, 王钰淼, 张 苗, 等. 关于骤旱研究的一些思考[J]. 大气科学学报, 2020, 43(6): 1086-1095.
[27] 王琳瑛. 中国区域骤发干旱的归因和影响研究[D]. 北京: 中国科学院大学, 2017.
[28] 韩子轩. 不同气候背景下全球大气水分循环的变化特征和机理研究[D]. 兰州: 兰州大学, 2020.
[29] 李绅东, 马 燕, 孙光宝, 等. 1960—2013年昭通市极端降雨时空演变规律研究[J]. raybet体育在线
院报, 2018, 35(7): 19-24, 29.
[30] 李鹏飞, 孙小明, 赵昕奕. 近50年中国干旱半干旱地区降水量与潜在蒸散量分析[J]. 干旱区资源与环境, 2012, 26(7): 57-63.
[31] 毕彦杰, 赵 晶, 吴 迪, 等. GFDL-ESM2M气候模式下京津冀地区未来潜在蒸散量时空变化[J]. 农业工程学报, 2020, 36(5): 141-149, 335.
基金
国家重点研发计划项目(2019YFC0408804);浙江省基础公益研究计划项目(LGF19E090003)