Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR020328 |
How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications | |
McMillan, Hilary1; Seibert, Jan2; Petersen-Overleir, Asgeir3; Lang, Michel4; White, Paul5; Snelder, Ton6; Rutherford, Kit7; Krueger, Tobias8; Mason, Robert9; Kiang, Julie9 | |
2017-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:7 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Switzerland; Norway; France; New Zealand; Germany |
英文摘要 | Streamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions. Plain Language Summary In this commentary, we show how analyzing uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. River flow data can contain large uncertainties but are often communicated and used without uncertainty information. We give case studies from Norway and New Zealand where flow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial watermanagement policy, and tested the accuracy of water quality trends. We conclude that flow uncertainty analysis is critical for goodwater management decisions. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000407895000003 |
WOS关键词 | RATING CURVES ; HYDROLOGICAL SIGNATURES ; QUALITY ; PREDICTIONS ; FRAMEWORK ; STATIONS ; TRENDS ; RISK |
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/21542 |
专题 | 资源环境科学 |
作者单位 | 1.San Diego State Univ, Dept Geog, San Diego, CA 92182 USA; 2.Univ Zurich, Dept Geog, Zurich, Switzerland; 3.Statkraft Energi AS, Market Operat Hydrol, Oslo, Norway; 4.Irstea, UR HHLY, Hydrol Hydraul, Lyon, France; 5.Inst Geol & Nucl Sci, Taupo, New Zealand; 6.LWP Ltd, Christchurch, New Zealand; 7.Natl Inst Water & Atmospher Res, Napier, New Zealand; 8.Humboldt Univ, IRI THESys, Berlin, Germany; 9.US Geol Survey, Off Surface Water, 959 Natl Ctr, Reston, VA 22092 USA |
推荐引用方式 GB/T 7714 | McMillan, Hilary,Seibert, Jan,Petersen-Overleir, Asgeir,et al. How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications[J]. WATER RESOURCES RESEARCH,2017,53(7). |
APA | McMillan, Hilary.,Seibert, Jan.,Petersen-Overleir, Asgeir.,Lang, Michel.,White, Paul.,...&Kiang, Julie.(2017).How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications.WATER RESOURCES RESEARCH,53(7). |
MLA | McMillan, Hilary,et al."How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications".WATER RESOURCES RESEARCH 53.7(2017). |
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