首页> 外文期刊>Hydrology >Understanding the Effects of Parameter Uncertainty on Temporal Dynamics of Groundwater-Surface Water Interaction
【24h】

Understanding the Effects of Parameter Uncertainty on Temporal Dynamics of Groundwater-Surface Water Interaction

机译:了解参数不确定性对地下水与地表水相互作用的时间动态的影响

获取原文
           

摘要

This study presents the understanding of temporal dynamics of groundwater-surface water (GW-SW) interaction due to parameter uncertainty by using a physically-based and distributed gridded surface subsurface hydrologic analysis (GSSHA) model combined with a Monte Carlo simulation. A study area along the main stem of the Kiskatinaw River of the Kiskatinaw River watershed, Northeast British Columbia, Canada, was used as a case study. Two different greenhouse gas (GHG) emission scenarios (i.e., A2: heterogeneous world with self-reliance and preservation of local identities, and B1: a more integrated and environmental-friendly world) of the Special Report on Emissions Scenarios (SRES) from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) for 2013 were used as case scenarios. Before conducting uncertainty analysis, a sensitivity analysis was performed to find the most sensitive parameters to the model output (i.e., mean monthly groundwater contribution to stream flow). Then, a Monte Carlo simulation was used to conduct the uncertainty analysis. The uncertainty analysis results under both case scenarios revealed that the pattern of the cumulative relative frequency distribution of the mean monthly and annual groundwater contributions to stream flow varied monthly and annually, respectively, due to the uncertainties of the sensitive model parameters. In addition, the pattern of the cumulative relative frequency distribution of a particular month’s groundwater contribution to the stream flow differed significantly between both scenarios. These results indicated the complexities and uncertainties in the GW-SW interaction system. Therefore, it is of necessity to use such uncertainty analysis results rather than the point estimates for better water resources management decision-making.
机译:这项研究通过结合基于物理的分布式网格化地表地下水文分析(GSSHA)模型和蒙特卡洛模拟,提出了对由于参数不确定性引起的地下水-地表水(GW-SW)相互作用的时间动态的理解。以加拿大不列颠哥伦比亚省东北部的Kiskatinaw河流域的Kiskatinaw河主干沿研究区域为例。 《全球排放情景特别报告》(SRES)的两种不同的温室气体排放情景(即,A2:具有自力更生和维护本地身份的异质世界,B1:更加综合和环境友好的世界)政府间气候变化专门委员会(IPCC)2013年的第四次评估报告被用作案例。在进行不确定性分析之前,先进行了敏感性分析,以找到对模型输出最敏感的参数(即平均每月地下水对水流的贡献)。然后,使用蒙特卡洛模拟进行不确定性分析。在这两种情况下的不确定性分析结果表明,由于敏感模型参数的不确定性,月平均和年度地下水对水流贡献的累积相对频率分布模式分别每月和每年变化。此外,在两种情况下,特定月份地下水对水流贡献的累积相对频率分布模式也有很大差异。这些结果表明了GW-SW相互作用系统的复杂性和不确定性。因此,有必要使用这种不确定性分析结果而不是点估计来更好地进行水资源管理决策。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号