Quantifying Uncertainty in the Modelling Process; Future Extreme Flood Event Projections Across the UK
Quantifying Uncertainty in the Modelling Process; Future Extreme Flood Event Projections Across the UK
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DOI：
10.3390/geosciences11010033
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发表时间：
2021-01
期刊：
影响因子：
2.7
通讯作者：
C. Ellis;A. Visser-Quinn;G. Aitken;L. Beevers
中科院分区：
文献类型：
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作者：
C. Ellis;A. Visser-Quinn;G. Aitken;L. Beevers
有证据表明，气候变化正在导致水文循环内的变化，因此，强有力地模拟水文气候响应的能力至关重要。这篇论文评估了极端径流-1：2和1：30年重现期(RP)事件-到本世纪80年代(2069-2098)可能在整个英国的区域水平上发生怎样的变化。为了捕捉水文气候模型链中的不确定性，从EDGE(欧洲水资源部门改进决策的端到端演示器)多模式集合中提取了流量预测：五个耦合模式相互比较项目(CMIP5)一般环流模型和四个在排放情景下强制的水文模型，例如典型浓度路径2.6和RCP 8.5(5×4×2链)。通过考虑广义极值(GeV)和广义Logistic(GL)两种方法来捕捉极值参数的不确定性。该方法被应用于192个流域，并聚集到8个地区。结果表明，到20世纪80年代，许多地区的极端径流可能会大幅增加，最大平均变化信号在苏格兰东部(1：2年RP)出现+34%。再加上日益加剧的城市化，这些估计为英国未来的洪水景观描绘了一幅令人担忧的图景。虽然极值(EV)参数不确定性在1：30年RP(在一些地区超过60%)成为主导，但到本世纪80年代，模型链的不确定性被发现增加，这突显了捕捉相关EV参数和集合不确定性的重要性。
With evidence suggesting that climate change is resulting in changes within the hydrologic cycle, the ability to robustly model hydroclimatic response is critical. This paper assesses how extreme runoff—1:2- and 1:30-year return period (RP) events—may change at a regional level across the UK by the 2080s (2069–2098). Capturing uncertainty in the hydroclimatic modelling chain, flow projections were extracted from the EDgE (End-to-end Demonstrator for improved decision-making in the water sector in Europe) multi-model ensemble: five Coupled Model Intercomparison Project (CMIP5) General Circulation Models and four hydrological models forced under emissions scenarios Representative Concentration Pathway (RCP) 2.6 and RCP 8.5 (5 × 4 × 2 chains). Uncertainty in extreme value parameterisation was captured through consideration of two methods: generalised extreme value (GEV) and generalised logistic (GL). The method was applied across 192 catchments and aggregated to eight regions. The results suggest that, by the 2080s, many regions could experience large increases in extreme runoff, with a maximum mean change signal of +34% exhibited in East Scotland (1:2-year RP). Combined with increasing urbanisation, these estimates paint a concerning picture for the future UK flood landscape. Model chain uncertainty was found to increase by the 2080s, though extreme value (EV) parameter uncertainty becomes dominant at the 1:30-year RP (exceeding 60% in some regions), highlighting the importance of capturing both the associated EV parameter and ensemble uncertainty.