Publication:

How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications

Date

Date

Date
2017
Journal Article
Published version

Citations

Citation copied

McMillan, H., Seibert, J., Petersen-Overleir, A., Lang, M., White, P., Snelder, T., Rutherford, K., Krueger, T., Mason, R., & Kiang, J. (2017). How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications. Water Resources Research, 53, 5220–5228. https://doi.org/10.1002/2016WR020328

Abstract

Abstract

Abstract

Streamflow data are used for important environmental and economic decisions, such asspecifying 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 oftencommunicated and used without uncertainty information. In this commentary, we argue that properanalysis of uncertainty in river flow data can reduce costs and promote robust conclusions in watermanagement applications. We substantiate our argument by providing case s

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60 since deposited on 2018-01-17
Acq. date: 2025-11-12

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135 since deposited on 2018-01-17
Acq. date: 2025-11-12

Additional indexing

Creators (Authors)

  • McMillan, Hilary
    affiliation.icon.alt
  • Petersen-Overleir, Asgeir
    affiliation.icon.alt
  • Lang, Michel
    affiliation.icon.alt
  • White, Paul
    affiliation.icon.alt
  • Snelder, Ton
    affiliation.icon.alt
  • Rutherford, Kit
    affiliation.icon.alt
  • Krueger, Tobias
    affiliation.icon.alt
  • Mason, Robert
    affiliation.icon.alt
  • Kiang, Julie
    affiliation.icon.alt

Journal/Series Title

Journal/Series Title

Journal/Series Title

Volume

Volume

Volume
53

Number

Number

Number
7

Page range/Item number

Page range/Item number

Page range/Item number
5220

Page end

Page end

Page end
5228

Item Type

Item Type

Item Type
Journal Article

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Language

Language

Language
English

Publication date

Publication date

Publication date
2017

Date available

Date available

Date available
2018-01-17

Publisher

Publisher

Publisher

ISSN or e-ISSN

ISSN or e-ISSN

ISSN or e-ISSN
0043-1397

OA Status

OA Status

OA Status
Green

Free Access at

Free Access at

Free Access at
DOI

Metrics

Downloads

60 since deposited on 2018-01-17
Acq. date: 2025-11-12

Views

135 since deposited on 2018-01-17
Acq. date: 2025-11-12

Citations

Citation copied

McMillan, H., Seibert, J., Petersen-Overleir, A., Lang, M., White, P., Snelder, T., Rutherford, K., Krueger, T., Mason, R., & Kiang, J. (2017). How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications. Water Resources Research, 53, 5220–5228. https://doi.org/10.1002/2016WR020328

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