IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i13d10.1007_s11269-022-03286-y.html
   My bibliography  Save this article

Distribution and Prediction of Boundary Shear in Diverging Compound Channels

Author

Listed:
  • B. Sree Sai Prasad

    (National Institute of Technology Rourkela)

  • Anurag Sharma

    (National Institute of Technology Rourkela)

  • Kishanjit Kumar Khatua

    (National Institute of Technology Rourkela)

Abstract

Measurement of bed shear stress is always a challenging task for engineers. In river engineering, bed shear is a fundamental variable and is important in estimating flow resistance and sediment transport. In this study, experiments are carried out in diverging compound channel with smooth bed (perspex sheet) and rough bed (Gravel) conditions to determine the effect of roughness. The shear velocity is estimated from universal logarithmic law. The effect of geometry and roughness on Von-Karman constant, eddy viscosity coefficient, friction factor is studied. The mass conservation and momentum conservation equations are used to derive apparent shear forces at interface of main channel and floodplain. A genetic algorithm model is developed to predict percentage of shear force (%Sfp) carried by sub-sections. To perform better with less and unseen data K-Fold cross-validation technique is used. The model is compared with available models in literature and it is observed that developed model gave better predictions with low MAPE.

Suggested Citation

  • B. Sree Sai Prasad & Anurag Sharma & Kishanjit Kumar Khatua, 2022. "Distribution and Prediction of Boundary Shear in Diverging Compound Channels," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 4965-4979, October.
  • Handle: RePEc:spr:waterr:v:36:y:2022:i:13:d:10.1007_s11269-022-03286-y
    DOI: 10.1007/s11269-022-03286-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03286-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11269-022-03286-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Abinash Mohanta & K. C. Patra & Arpan Pradhan, 2020. "Enhanced Channel Division Method for Estimation of Discharge in Meandering Compound Channel," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 1047-1073, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abinash Mohanta & Arpan Pradhan & Monalisa Mallick & K. C. Patra, 2021. "Assessment of Shear Stress Distribution in Meandering Compound Channels with Differential Roughness Through Various Artificial Intelligence Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4535-4559, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:36:y:2022:i:13:d:10.1007_s11269-022-03286-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.