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    CMIP5 Decadal Precipitation at Catchment Level and Its Implication to Future Prediction

    Hossain MM 2022 Public 2years.pdf (9.010Mb)
    Access Status
    Open access
    Authors
    Hossain, Md Monowar
    Date
    2022
    Supervisor
    Faisal Anwar
    Type
    Thesis
    Award
    PhD
    
    Metadata
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    Faculty
    Science and Engineering
    School
    School of Civil and Mechanical Engineering
    URI
    http://hdl.handle.net/20.500.11937/89149
    Collection
    • Curtin Theses
    Abstract

    This study assesses the monthly precipitation of CMIP5 decadal experiment over Brisbane River catchment for a spatial resolution of 0.050 and then predicts the monthly precipitation for decadal timescale through a Bidirectional LSTM and Machine Learning Algorithms using GCMs and observed data. To use GCM data in this future prediction, investigations were carried out for a suitable spatial interpolation method, a better simulation period, model drifts, and drift correction alternatives based on different skill tests.

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