长江流域资源与环境 >> 2017, Vol. 26 >> Issue (10): 1505-.doi: 10.11870/cjlyzyyhj201710005

• 自然资源 • 上一篇    下一篇

气候变化对涟水流域蓝水绿水资源的影响

冯  畅1,毛德华1*,周  慧2,曹艳敏1,3   

  1. (1. 湖南师范大学资源与环境科学学院,湖南 长沙 410081;2. 湖南省水文水资源勘测局,湖南 长沙410007;3. 长沙市水务局,湖南 长沙 410013)
  • 出版日期:2017-10-20

IMPACTS OF CLIMATE CHANGE ON BLUE AND GREEN WATER RESOURCES IN THE LIANSHUI RIVER BASIN

FENG Chang1, MAO De-hua1, ZHOU Hui2, CAO Yan-min1,3   

  1. (1. College of Resources and Environment Science, Hunan Normal University, Changsha 410081, China; 2. Hydrology and Water Resources Survey Bureau of Hunan Province, Changsha 410007, China; 3. Changsha Water Authority, Changsha 410013, China)
  • Online:2017-10-20

摘要: 利用SWAT分布式水文模型模拟分析1996~2015年过去20 a及2020~2079年未来60 a长期气候变化背景下涟水流域蓝水绿水资源的时空分布变化特征。将气候变化划分为1996~2015年、2020~2049年、2050~2079年三段气象背景时期,选用HadGEM2-AO大气模式的RCP2.6、RCP4.5、RCP6、RCP8.5四种典型浓度路径作为未来时期的气象输入条件,并细分为9种气候变化情景。运用PSO粒子群优化算法,以KGE克林效率系数为目标函数,采用湘乡站实测径流量及MOD16蒸散发数据并行校准模型参数,通过p-factor、r-factor、R2、NSE和PBIAS评价模型模拟效果和不确定性,评价结果表明校准期及验证期蓝水绿水模拟均达到可信程度。情景分析结果表明,对比1996~2015年、2020~2049年、2050~2079年三段气候背景时期,在各RCP浓度路径下蓝水均呈现了不同程度的下降趋势,大约降低了1.4%~17.3%,绿水流均表现出一定的上升趋势,约增长3.5%~12.4%,绿水蓄量则在持续降低,大致下降了7.8%~19.7%,即使将95PPU模拟不确定性范围考虑进来,绿水流的增长趋势也较为明显。因此,将绿水资源纳入涟水流域未来水资源评价体系,实现蓝水绿水综合规划管理具有实际意义。

Abstract: SWAT, a distributed hydrological model, is used to simulate and analyze spatiotemporal characteristics of blue and green water resources in the Lianshui basin under the long-term climate change effects of 1996-2015 and 2020-2079. Climate change have been divided into three climatic background periods of 1996-2015, 2020-2049, 2070-2100, and into 9 climate change scenarios according to inputs of the future climate conditions, which were generated from HadGEM2-AO atmospheric model in typical concentration path of the rcp2.6, rcp4.5, rcp6 and rcp8.5. PSO particle swarm optimization algorithm in combination with Kling-Gupta efficiency coefficient KGE objective function is introduced to calibrate the model parameters based on Xiangxiang station measured discharges and MOD16 evapotranspiration data. Moreover, p-factor, r-factor, R2, NSE and PBIAS are also performed to evaluate the model simulation results and uncertainty, and the results indicated good performance of simulation for blue and green water both in the calibration and validation period. Consequently, scenario analysis result shows that Lianshui river basin has different-varied levels of decrease in blue water(1.4%-17.3%) and green water storage(7.8%-19.7%) while the green water flow(3.5%-12.4%) increases in different RCP concentration path scenarios during the climatic background period of 1996-2015, 2020-2049 and 2050-2079.Even taking parameter prediction uncertainty 95ppu range into consideration, the future growth trend of green water flow is also obvious. Hence, taking green water resources into the future water resources evaluation strategies to achieve blue water and green water comprehensive planning and management is indispensable for the Lianshui river basin.

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