Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 2: future climate
Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 2: future climate
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DOI：
10.1007/s10584-008-9461-6
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发表时间：
2009-03
期刊：
影响因子：
4.8
通讯作者：
C. Prudhomme;H. Davies
中科院分区：
文献类型：
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作者：
C. Prudhomme;H. Davies
本文的第一部分论证了由GCM得到的降水序列存在偏差，该序列使用统计技术(这里是统计降尺度模型)或动力方法(这里是高分辨率区域气候模式HadRM3)缩减到由集总水文模型估计的河流流量。本文使用了相同的模型和方法来预测未来的时间范围(本世纪80年代)，并分析了这些预测的变化与英国四个流域的基线自然变化相比有多大。UKCIP02情景也被考虑在内，这些情景在英国被广泛用于应对气候变化的影响。结果表明，GCM是未来流量的最大不确定性来源。缩小尺度技术和排放情景的不确定度具有相似的量级，通常比GCM的不确定度小。对于水文模型不确定性小于基线流量的GCM变率的集水区，这种不确定性可以在未来的预测中忽略，但在其他情况下可能会显著。与基线变异性相比，预测的变化并不总是显著的，只有不到50%的预测表明每月流量发生了重大变化。微不足道的变化可能仅仅由于气候变化而发生，因此不能归因于气候变化，但在气候变化研究中往往被忽视，并可能导致误导性的结论。目前在再现当前气候方面存在的系统性偏差确实会影响未来的预测，因此在解释结果时必须加以考虑。河流流量变异性对于水资源管理规划很重要，通过应用于基线和未来时间范围的简单重采样技术，可以很容易地评估这些变化。评估未来气候及其对河流流量的潜在影响是水资源规划者面临的一项关键挑战。这份由两部分组成的文件表明，水文和气候模型造成的不确定性必须而且可以被考虑，以便向决策者提供合理的、有科学依据的建议。
The first part of this paper demonstrated the existence of bias in GCM-derived precipitation series, downscaled using either a statistical technique (here the Statistical Downscaling Model) or dynamical method (here high resolution Regional Climate Model HadRM3) propagating to river flow estimated by a lumped hydrological model. This paper uses the same models and methods for a future time horizon (2080s) and analyses how significant these projected changes are compared to baseline natural variability in four British catchments. The UKCIP02 scenarios, which are widely used in the UK for climate change impact, are also considered. Results show that GCMs are the largest source of uncertainty in future flows. Uncertainties from downscaling techniques and emission scenarios are of similar magnitude, and generally smaller than GCM uncertainty. For catchments where hydrological modelling uncertainty is smaller than GCM variability for baseline flow, this uncertainty can be ignored for future projections, but might be significant otherwise. Predicted changes are not always significant compared to baseline variability, less than 50% of projections suggesting a significant change in monthly flow. Insignificant changes could occur due to climate variability alone and thus cannot be attributed to climate change, but are often ignored in climate change studies and could lead to misleading conclusions. Existing systematic bias in reproducing current climate does impact future projections and must, therefore, be considered when interpreting results. Changes in river flow variability, important for water management planning, can be easily assessed from simple resampling techniques applied to both baseline and future time horizons. Assessing future climate and its potential implication for river flows is a key challenge facing water resource planners. This two-part paper demonstrates that uncertainty due to hydrological and climate modelling must and can be accounted for to provide sound, scientifically-based advice to decision makers.