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Optimal Design and Operation of River Basin Storage under Hydroclimatic Uncertainty.

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Title: Optimal Design and Operation of River Basin Storage under Hydroclimatic Uncertainty.
Authors: Burrow, Andy1 (AUTHOR) adburrow@yahoo.com, Hering, Amanda S.2 (AUTHOR) Mandy_Hering@baylor.edu, Morton, David P.3 (AUTHOR) david.morton@northwestern.edu, Newman, Alexandra M.4 (AUTHOR) anewman@mines.edu
Source: Journal of Water Resources Planning & Management. Sep2021, Vol. 147 Issue 9, p1-21. 21p.
Subjects: Stochastic programming, Uncertainty, Time perspective, Supply & demand, Storage
Geographic Terms: Colorado
Abstract: As populations and economies expand in regions with changing climates, demand for water can quickly grow beyond what natural supply can sustain. This paper proposes to mitigate shortages, such as those that occur along the Lower South Platte River in northeastern Colorado, via a three-step approach: (1) create flow data scenarios, which represent a wide array of hydroclimatic outcomes; (2) use an existing simulation model to process these scenarios in order to locate excess supply and unmet demand both spatially and temporally; and (3) minimize the cost of alleviating identified shortages using a new, multiperiod, two-stage stochastic programming model, which determines reservoir location, size, type, and operation over a 50-year time horizon. Results indicate that demand associated with historical and seasonally shifted scenarios can be satisfied, and unmet demand associated with more challenging reduced-mean runoff scenarios can be mitigated substantially. Furthermore, multiple smaller reservoirs are preferred over a single large reservoir to hedge against these uncertainties. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Water Resources Planning & Management is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 151717581
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Optimal Design and Operation of River Basin Storage under Hydroclimatic Uncertainty.
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  Data: <searchLink fieldCode="AR" term="%22Burrow%2C+Andy%22">Burrow, Andy</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> adburrow@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Hering%2C+Amanda+S%2E%22">Hering, Amanda S.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> Mandy_Hering@baylor.edu</i><br /><searchLink fieldCode="AR" term="%22Morton%2C+David+P%2E%22">Morton, David P.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> david.morton@northwestern.edu</i><br /><searchLink fieldCode="AR" term="%22Newman%2C+Alexandra+M%2E%22">Newman, Alexandra M.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> anewman@mines.edu</i>
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  Data: <searchLink fieldCode="DE" term="%22Stochastic+programming%22">Stochastic programming</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertainty%22">Uncertainty</searchLink><br /><searchLink fieldCode="DE" term="%22Time+perspective%22">Time perspective</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+%26+demand%22">Supply & demand</searchLink><br /><searchLink fieldCode="DE" term="%22Storage%22">Storage</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Colorado%22">Colorado</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: As populations and economies expand in regions with changing climates, demand for water can quickly grow beyond what natural supply can sustain. This paper proposes to mitigate shortages, such as those that occur along the Lower South Platte River in northeastern Colorado, via a three-step approach: (1) create flow data scenarios, which represent a wide array of hydroclimatic outcomes; (2) use an existing simulation model to process these scenarios in order to locate excess supply and unmet demand both spatially and temporally; and (3) minimize the cost of alleviating identified shortages using a new, multiperiod, two-stage stochastic programming model, which determines reservoir location, size, type, and operation over a 50-year time horizon. Results indicate that demand associated with historical and seasonally shifted scenarios can be satisfied, and unmet demand associated with more challenging reduced-mean runoff scenarios can be mitigated substantially. Furthermore, multiple smaller reservoirs are preferred over a single large reservoir to hedge against these uncertainties. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Water Resources Planning & Management is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=151717581
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1061/(ASCE)WR.1943-5452.0001337
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 21
        StartPage: 1
    Subjects:
      – SubjectFull: Stochastic programming
        Type: general
      – SubjectFull: Uncertainty
        Type: general
      – SubjectFull: Time perspective
        Type: general
      – SubjectFull: Supply & demand
        Type: general
      – SubjectFull: Storage
        Type: general
      – SubjectFull: Colorado
        Type: general
    Titles:
      – TitleFull: Optimal Design and Operation of River Basin Storage under Hydroclimatic Uncertainty.
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            NameFull: Burrow, Andy
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            NameFull: Hering, Amanda S.
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            NameFull: Morton, David P.
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            NameFull: Newman, Alexandra M.
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            – D: 01
              M: 09
              Text: Sep2021
              Type: published
              Y: 2021
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              Value: 147
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