Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain
Assessing the Impact of Climate Change and Extreme Value Uncertainty to Extreme Flows across Great Britain
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DOI：
10.3390/w9020103
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发表时间：
2017-02-01
期刊：
影响因子：
3.4
通讯作者：
Prudhomme, Christel
中科院分区：
文献类型：
--
作者：
Collet, Lila;Beevers, Lindsay;Prudhomme, Christel
洪水是最常见和分布最广的自然风险，由于最近的事件，每年在英国造成超过10亿磅的损失。气候预测预测洪水风险的增加;迫切需要评估气候变化对极端流量的影响，并评估与这些预测有关的不确定性。本文的目的是评估极端径流的变化为1：100年重现期横跨英国的气候变化的结果，使用未来流量水文数据库。广义极值（GEV）和广义帕累托（GP）模型自动拟合基线和21世纪80年代的11个成员集合流系列。该分析评估了与极值（EV）和气候模型参数相关的不确定性。结果表明，GP和GEV给出类似的径流估计和不确定性。从基线到21世纪80年代，英格兰东部的估计和不确定性明显增加。对于GEV，归因于气候模型参数的不确定性大于GP（分别约占总不确定性的60%和40%）。这表明，在拟合两个EV模型时，必须考虑与其参数相关的不确定性，以评估极端径流。
Floods are the most common and widely distributed natural risk, causing over 1 pound billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11-member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs.