长江流域资源与环境 >> 2024, Vol. 33 >> Issue (5): 1004-1017.doi: 10.11870/cjlyzyyhj202405009

• 自然资源 • 上一篇    下一篇

基于CMIP6的嘉陵江流域径流及水文干旱预估

吴明炎,倪福全*,邓玉,岳紫莹,江楠,康文东,向军   

  1. (四川农业大学水利水电学院,四川  雅安 625014)
  • 出版日期:2024-05-20 发布日期:2024-05-29

Projections of Runoff and Hydrological Drought in the Jialing River Basin Based on CMIP6

WU Ming-yan, NI Fu-quan,DENG Yu, YUE Zi-ying, JIANG Nan, KANG Wen-dong, XIANG Jun   

  1. (College of Water Conservancy and Hydropower Engineering , Sichuan Agricultural University , Ya’an 625014,China)
  • Online:2024-05-20 Published:2024-05-29

摘要: 探究嘉陵江在未来气候下径流及水文干旱变化,可为嘉陵江流域水资源管理和水旱灾害防治提供参考依据。基于嘉陵江流域1980~2020年水文气象数据构建土水评估工具(Soil and Water Assessment Tool, SWAT)模型,使用第六次耦合模式比较计划(Coupled Model Intercomparison Project Phase 6, CMIP6)5个气候模式中的4个情景数据驱动SWAT模型,分析未来(2021~2100)气候变化下嘉陵江流域径流变化情况。结果表明:(1)嘉陵江流域控制站北碚水文站月径流率定期和验证期决定系数(coefficient of determination, R2)和纳什系数(Nash-Sutcliffe,NES)均大于0.8,偏差百分比(Percent Bias, PBIAS)小于±10,SWAT模型能够较好地适用于目标流域;(2)基于历史时期统计降尺度后的CMIP6数据能够提供可靠的径流及干旱预估;(3)加权多模式集合形式能较好地提高模拟精度,降低单个CMIP6气候模式的不确定性;(4)与历史时期 (1980~2014)相比,未来嘉陵江流域最高、低气温、降水量、蒸散发均呈现增加趋势。(5)SSP1-2.6情景嘉陵江未来径流显著增长,SSP2-4.5和SSP5-8.5径流非显著增加,SSP3-7.0径流非显著减少;夏季径流减少幅度最大。(6)未来流域标准径流指数(Standardized Runoff Index, SRI)呈增长趋势,流域表现出湿润化,干旱事件集中发生于秋、冬两季;由近期至远期,SSP1-2.6、SSP2-4.5和SSP3-7.0情景干旱发生在秋季频率减少,而冬季频率增加。

Abstract: In order to provide technical supports for the planning of Water and drought prevention and control, this work studied the change of runoff and hydrological drought of the Jialing River Basin under the background of climate change. Based on the hydro-meteorological data of the Basin from 1980 to 2020, a hydrological model was developed using SWAT. Driven by four scenarios of the CMIP6 data from five meteorological models, the model was used to project future changes in runoff in the Basin under future climate change from 2021 to 2100. The results showed that (1) The SWAT model performed well in the Basin. The R2 , NES of the simulated monthly runoff at the Beibei hydrological station were both greater than 0.8, with PBIAS less than ±10; (2)The CMIP6 data after statistical downscaling based on the historical period provided reliable runoff and drought estimates; (3)A weighted multi-model ensemble could improve the simulation accuracy and reduce the uncertainty of a single CMIP6 climate model; (4) Compared with the historical period (1980-2014), the temperature, precipitation, and evapotranspiration in the Basin all showed an increasing trend, for future climate scenarios, which implied that the Basin may become more humid and hotter. The runoff showed a significant increasing trend under the SSP1-2.6 scenario, while for other scenarios, the trend was not significant. The annual average runoff was lower than the historical runoff; (5) From the perspective of SRI at the scale of 12 months, the overall trend of the Basin was becoming more humid. Hydrological droughts were reduced under the SSP1-2.6 scenario, while in the other scenarios there was a fluctuation of various drought indicators; (6) From the perspective of SRI at the scale of one month, hydrological droughts in the Basin was mainly concentrated in autumn and winter. It was shown that there existed a shift from autumn drought to winter drought, in the scenarios other than SSP5-8.5.

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