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    Comparing Robust Optimization Approaches for Addressing Hydrologic Model Uncertainty in Infrastructure Planning: A Green Infrastructure Example

    Source: Journal of Water Resources Planning and Management:;2025:;Volume ( 151 ):;issue: 009::page 04025042-1
    Author:
    Smith, Jared D.
    ,
    Quinn, Julianne D.
    ,
    Band, Lawrence E.
    DOI: 10.1061/JWRMD5.WRENG-6729
    Publisher: American Society of Civil Engineers
    Abstract: AbstractWater resources planning is dependent on hydrologic models to estimate flows and storage in candidate engineering designs. However, such models are calibrated with limited flow data relative to the many model parameters. This may result in ...
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      Comparing Robust Optimization Approaches for Addressing Hydrologic Model Uncertainty in Infrastructure Planning: A Green Infrastructure Example

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4313923
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    contributor authorSmith, Jared D.
    contributor authorQuinn, Julianne D.
    contributor authorBand, Lawrence E.
    date accessioned2026-08-20T21:05:01Z
    date available2026-08-20T21:05:01Z
    date copyright2025/07/09
    date issued2025
    identifier otherJWRMD5.WRENG-6729.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313923
    description abstractAbstractWater resources planning is dependent on hydrologic models to estimate flows and storage in candidate engineering designs. However, such models are calibrated with limited flow data relative to the many model parameters. This may result in ...
    publisherAmerican Society of Civil Engineers
    titleComparing Robust Optimization Approaches for Addressing Hydrologic Model Uncertainty in Infrastructure Planning: A Green Infrastructure Example
    typeJournal Article
    journal volume151
    journal issue9
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/JWRMD5.WRENG-6729
    journal fristpage04025042-1
    journal lastpage04025042-13
    page13
    treeJournal of Water Resources Planning and Management:;2025:;Volume ( 151 ):;issue: 009
    contenttypeFulltext
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