收稿日期: 2007-04-09
修回日期: 2007-06-18
网络出版日期: 2007-08-10
The Advances in Studying Detection of Streamflow Trend Influenced by Climate Change
Received date: 2007-04-09
Revised date: 2007-06-18
Online published: 2007-08-10
气候变化对基于自然稳定气候假定的流量变化趋势的检测和水资源评价方法提出了挑战。在流量变化趋势的检测中分离出气候变化的影响,不仅对水资源管理和水利工程设计有重要的应用价值,而且有助于了解气候变化以何种方式、在何时、何地、已经或尚未对水文循环产生影响,对改进气候模型的模拟与预测有重要的科学价值。统计方法是检验流量变化趋势显著性的有效工具。直接用气候模型模拟和预测未来径流变化的可靠性取决于模型对当代降水模拟的可信度。多个气候模型集合分析有可能在一定程度上减少模型对降水、径流模拟的不确定性。近年发展起来的多个气候模型集合分析与统计显著性检验技术结合的方法,有可能模拟并预测出气候强迫导致大尺度径流空间分布的变化。随着气候模型尤其是陆—气耦合的区域气候模型对降水模拟的改进,可以预见径流变化的检测、归因和预测的趋同化模拟已为期不远。将温室气体外强迫导致的水文气候变化作为一个因子引入到水资源评价中,对于水资源管理经济与生态评估,以及未来的发展规划将是一件十分重要的变革。
刘春蓁 . 气候变化对江河流量变化趋势影响研究进展[J]. 地球科学进展, 2007 , 22(8) : 777 -783 . DOI: 10.11867/j.issn.1001-8166.2007.08.0777
Detection of streanflow trend and water resources assessment based on the natural and stationary climatic condition have been challenged by global warming. Identifying and separating contribution of climate change in streamflow trend, facilitate not only in water management practice and water project construction, but also enable understanding where, when and by which way the impact of climate change on hydrological cycle becomes detectable or not yet.The statistical test is a powerful tool for the detection of hydrological trend. It is necessary to consider both the serial correlation of the data series and the cross-correlation between the hydrological variables at different locations for correctly determining the significance level. A complete study of the detection of streamflow trend includes description of trend characteristics and its attribution as well. For natural river basin fed by snow and glaciers melt, the streamflow trend is determined mainly by temperature variation, associated with natural climate variability and external forcing produced climate warming. For managed water systems, supplied by precipitation, streamflow trend is affected not only by climatic variables, but also by anthropogenic disturbances-direct and indirect factors. The methodology of statistical interrelation of multifactors is helpful to determining contribution of each element in streamflow trend.However, by only relying on statistical method alone, it is hard to weigh the interaction among factors as well as to identify the impact of climatic variability and forced climate change on streamflow. The reliability of simulation and projection on future streamflow with climate model directly is directly determined by the ability of the climate model to simulate precipitation of current time-horizon. The ensemble mean from a subset of climate models could reduce uncertainties in precipitation and runoff simulations. Recently developed methodology of ensemble mean of multiclimate models combined with statistical analysis has been used to show the potential in simulation and projection of spatial pattern of macro-scale streamflow trend caused by forced climate change. In the course of improving climate model and regional climate models' simulation of precipitation in particular, it is anticipated that the detection, attribution and projection of streamflow alteration tend to be simulated in an identical way in the near future.
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