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    Deep Learning–Based Streamflow Forecasting in a Snowmelt-Dominated Basin: A Regime-Aware Evaluation

    Source: Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004::page 04026012-1
    Author:
    Vazirian, Roya
    DOI: 10.1061/JHYEFF.HEENG-6651
    Publisher: American Society of Civil Engineers
    Abstract: AbstractArtificial intelligence, particularly deep learning, is transforming discharge forecasting to address climate challenges and enhance water management by capturing complex, nonlinear, long-term dependencies. This study provides a process-based ...
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      Deep Learning–Based Streamflow Forecasting in a Snowmelt-Dominated Basin: A Regime-Aware Evaluation

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311720
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    contributor authorVazirian, Roya
    date accessioned2026-08-20T11:07:15Z
    date available2026-08-20T11:07:15Z
    date copyright2026/05/07
    date issued2026
    identifier otherJHYEFF.HEENG-6651.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311720
    description abstractAbstractArtificial intelligence, particularly deep learning, is transforming discharge forecasting to address climate challenges and enhance water management by capturing complex, nonlinear, long-term dependencies. This study provides a process-based ...
    publisherAmerican Society of Civil Engineers
    titleDeep Learning–Based Streamflow Forecasting in a Snowmelt-Dominated Basin: A Regime-Aware Evaluation
    typeJournal Article
    journal volume31
    journal issue4
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/JHYEFF.HEENG-6651
    journal fristpage04026012-1
    journal lastpage04026012-8
    page8
    treeJournal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004
    contenttypeFulltext
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