GSTDTAP  > 资源环境科学
DOI10.1029/2017WR022024
Decision-Making and Flood Risk Uncertainty: Statistical Data Set Analysis for Flood Risk Assessment
Collet, L.1,2; Beevers, L.2; Stewart, M. D.3
2018-10-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2018
卷号54期号:10页码:7291-7308
文章类型Article
语种英语
国家France; Scotland
英文摘要

Floods are a significant issue worldwide with over 1 billion people living in areas of potential flood risk. With climate change these risks are anticipated to increase, but there is great uncertainty associated with future projections, which poses challenges to those making decisions on flood management. Climate change projections which explicitly capture climate model parameters uncertainty are available in the United Kingdom; however, their use by practitioners, rather than researchers, has so far been limited. This paper takes an inclusive approach, working with end users, to answer practitioner relevant questions regarding future climate change influence for flood hazards. The method developed demonstrates the findings across Scotland, United Kingdom and investigates (i) the regional impacts to extreme flows and the associated uncertainty, (ii) the changes in extreme peak flows in terms of frequency, and (iii) the physical and hydroclimatic factors controlling these results. The method used industry standard statistical methods, driven by practitioner requirements, and explicitly includes the statistical uncertainty in the climate and extreme value distribution models in extreme flow estimates. Results are analyzed using hierarchical clustering and decision tree analysis, and the subsequent trends are shown to be constrained by different hydrological, climatic, and physical catchment characteristics. Results suggest that there is a high probability that low return period peak flow events would exceed the baseline extreme high return period event by the 2080s, which has significant implications for future-proofing infrastructure design. This study provides a practical example and outputs resulting from collaboration between research and industry practices.


领域资源环境
收录类别SCI-E ; SSCI
WOS记录号WOS:000450726000011
WOS关键词CLIMATE-CHANGE ; PROBABILISTIC IMPACTS ; L-MOMENT ; METHODOLOGY ; PROJECTIONS ; INTENSITY ; ENSEMBLE
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/20997
专题资源环境科学
作者单位1.Irstea, Antony, France;
2.Heriot Watt Univ, Sch Energy Geosci Infrastruct & Soc, Edinburgh, Midlothian, Scotland;
3.Kaya Consulting, Bellshill, Scotland
推荐引用方式
GB/T 7714
Collet, L.,Beevers, L.,Stewart, M. D.. Decision-Making and Flood Risk Uncertainty: Statistical Data Set Analysis for Flood Risk Assessment[J]. WATER RESOURCES RESEARCH,2018,54(10):7291-7308.
APA Collet, L.,Beevers, L.,&Stewart, M. D..(2018).Decision-Making and Flood Risk Uncertainty: Statistical Data Set Analysis for Flood Risk Assessment.WATER RESOURCES RESEARCH,54(10),7291-7308.
MLA Collet, L.,et al."Decision-Making and Flood Risk Uncertainty: Statistical Data Set Analysis for Flood Risk Assessment".WATER RESOURCES RESEARCH 54.10(2018):7291-7308.
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