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首页> 外文期刊>Advances in Water Resources >The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments
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The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments

机译:水文模拟不确定性在爱尔兰河流域气候变化影响评估中的作用

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This study attempts to assess the uncertainty in the hydrological impacts of climate change using a multi-model approach combining multiple emission scenarios, GCMs and conceptual rainfall-runoff models to quantify uncertainty in future impacts at the catchment scale. The uncertainties associated with hydro-logical models have traditionally been given less attention in impact assessments until relatively recently. In order to examine the role of hydrological model uncertainty (parameter and structural uncertainty) in climate change impact studies a multi-model approach based on the Generalised Likelihood Uncertainty Estimation (GLUE) and Bayesiart Model Averaging (BMA) methods is presented. Six sets of regionalised climate scenarios derived from three GCMs, two emission scenarios, and four conceptual hydrological models were used within the GLUE framework to define the uncertainty envelop for future estimates of stream flow, while the GLUE output is also post processed using BMA, where the probability density function from each model at any given time is modelled by a gamma distribution with heteros-cedastic variance. The investigation on four Irish catchments shows that the role of hydrological model uncertainty is remarkably high and should therefore be routinely considered in impact studies. Although, the GLUE and BMA approaches used here differ fundamentally in their underlying philosophy and representation of error, both methods show comparable performance in terms of ensemble spread and predictive coverage. Moreover, the median prediction for future stream flow shows progressive increases of winter discharge and progressive decreases in summer discharge over the coming century.
机译:这项研究尝试使用多模型方法结合多种排放情景,GCM和概念性降雨径流模型来评估气候变化对水文影响的不确定性,以量化集水区未来影响的不确定性。传统上,与水文模型相关的不确定性在影响评估中一直很少受到关注,直到最近。为了检验水文模型不确定性(参数和结构不确定性)在气候变化影响研究中的作用,提出了一种基于广义似然不确定性估计(GLUE)和贝叶斯平均模型(BMA)方法的多模型方法。在GLUE框架内,使用了从三个GCM,两个排放情景和四个概念性水文模型得出的六组区域化气候情景,以定义不确定性包络,用于将来的河流量估算,同时还使用BMA对GLUE的输出进行后处理,其中每个模型在任何给定时间的概率密度函数均由具有异质-方差的伽马分布建模。对爱尔兰四个流域的调查表明,水文模型不确定性的作用非常高,因此应在影响研究中常规考虑。尽管此处使用的GLUE和BMA方法在基本原理和错误表示上有根本不同,但在整体传播和预测覆盖率方面,这两种方法均显示出可比的性能。此外,对未来河流流量的中值预测表明,在未来的一个世纪中,冬季流量将逐渐增加,夏季流量将逐渐减少。

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