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    Hybrid Approach to Rainfall Disaggregation Using Artificial Intelligence and Multivariate Disaggregation Considering Spatial Correlation

    Source: Journal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004::page 04026011-1
    Author:
    Akhila, R.
    ,
    Pramada, S. K.
    ,
    Berndtsson, R.
    DOI: 10.1061/JHYEFF.HEENG-6766
    Publisher: American Society of Civil Engineers
    Abstract: AbstractHigh-resolution rainfall data are essential for various hydrological applications such as flood modeling, soil erosivity studies, and urban water management. However, the scarcity of subdaily data, particularly in remote regions, necessitates ...
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      Hybrid Approach to Rainfall Disaggregation Using Artificial Intelligence and Multivariate Disaggregation Considering Spatial Correlation

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311734
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    contributor authorAkhila, R.
    contributor authorPramada, S. K.
    contributor authorBerndtsson, R.
    date accessioned2026-08-20T11:07:58Z
    date available2026-08-20T11:07:58Z
    date copyright2026/04/23
    date issued2026
    identifier otherJHYEFF.HEENG-6766.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311734
    description abstractAbstractHigh-resolution rainfall data are essential for various hydrological applications such as flood modeling, soil erosivity studies, and urban water management. However, the scarcity of subdaily data, particularly in remote regions, necessitates ...
    publisherAmerican Society of Civil Engineers
    titleHybrid Approach to Rainfall Disaggregation Using Artificial Intelligence and Multivariate Disaggregation Considering Spatial Correlation
    typeJournal Article
    journal volume31
    journal issue4
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/JHYEFF.HEENG-6766
    journal fristpage04026011-1
    journal lastpage04026011-13
    page13
    treeJournal of Hydrologic Engineering:;2026:;Volume ( 031 ):;issue: 004
    contenttypeFulltext
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