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    Use of gene-expression programming to estimate Manning's roughness coefficient for a low flow stream

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    Pu_et_al_Larhyss_Journal (408.2Kb)
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    Publication date
    2021-12
    Author
    Chaplot, B.
    Peters, M.
    Birbal, P.
    Pu, Jaan H.
    Shafie, A.
    Keyword
    Gene-expression programming
    Manning's roughness coefficient
    Open-channel flow
    Rights
    © 2021 Chaplot B. and al.; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
    Peer-Reviewed
    Yes
    Open Access status
    openAccess
    
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    Abstract
    Manning’s roughness coefficient (n) has been widely used to estimate flood discharges and flow depths in natural channels. Therefore, although extensive guidelines are available, the selection of the appropriate n value is of great importance to hydraulic engineers and hydrologists. Generally, the largest source of error in post-flood estimates is caused by the estimation of n values, particularly when there has been minimal field verification of flow resistance. This emphasizes the need to improve methods for evaluating the roughness coefficients. Trinidad and Tobago currently does not have any set method or standardised procedure that they use to determine the n value. Therefore, the objective of this study was to develop a soft computing model in the calculation of the roughness coefficient values using low flow discharge measurements for a stream. This study presents Gene-Expression Programming (GEP), as an improved approach to compute Manning’s Roughness Coefficient. The GEP model was found to be accurate, producing a coefficient of determination (R2) of 0.94 and Root Mean Square Error (RSME) of 0.0024.
    URI
    http://hdl.handle.net/10454/19342
    Version
    Published version
    Citation
    Chaplot B, Peters M, Birbal P et al (2021) Use of gene-expression programming to estimate Manning's roughness coefficient for a low flow stream. Larhyss Journal. 48: 135-150.
    Link to publisher’s version
    http://larhyss.net/ojs/index.php/larhyss/article/view/806
    Type
    Article
    Collections
    Engineering and Informatics Publications

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