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Uncertainty in Rating-Curves Due to Manning Roughness Coefficient

Author

Listed:
  • Sajjad M. Vatanchi

    (Ferdowsi University of Mashhad)

  • Mahmoud F. Maghrebi

    (Ferdowsi University of Mashhad)

Abstract

River stage-discharge rating curve are very crucial for flood control and sustainable development of the river basin. The stage and discharge data can be extracted by rating curves. Recently, a new approach based on the concept of isovel contours for estimating the rating curves is introduced by Maghrebi et al. (2016). It uses the geometric properties of the flow section and roughness variations of the boundary. One of the essential parameters in setting up the rating curves is the Manning roughness coefficient. However, the determination of this parameter is accompanied by some uncertainties. In natural rivers, due to heterogeneous of boundary roughness, changing equivalent roughness with the stage will be important. A proper estimation of equivalent roughness in the proposed rating curve can significantly help to reduce the errors of stage-discharge prediction. The total number of investigated equations of equivalent roughness is 30, which are divided into four groups. Each one of these equations is examined in the La Suela and Trent rivers. This study has shown that choosing the right method to determine the equivalent roughness can significantly affect the performance of the model and play a substantial role in the more accurate estimation of the rating curve. The results show that in the La Suela and Trent rivers, roughness variations in banks create significant uncertainty in the estimation of the rating curves.

Suggested Citation

  • Sajjad M. Vatanchi & Mahmoud F. Maghrebi, 2019. "Uncertainty in Rating-Curves Due to Manning Roughness Coefficient," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(15), pages 5153-5167, December.
  • Handle: RePEc:spr:waterr:v:33:y:2019:i:15:d:10.1007_s11269-019-02421-6
    DOI: 10.1007/s11269-019-02421-6
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    References listed on IDEAS

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    1. Helton, J.C. & Johnson, J.D. & Sallaberry, C.J. & Storlie, C.B., 2006. "Survey of sampling-based methods for uncertainty and sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1175-1209.
    2. Asgeir Petersen-Øverleir & André Soot & Trond Reitan, 2009. "Bayesian Rating Curve Inference as a Streamflow Data Quality Assessment Tool," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(9), pages 1835-1842, July.
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    Cited by:

    1. Mohammad Bahrami Yarahmadi & Abbas Parsaie & Mahmood Shafai-Bejestan & Mostafa Heydari & Marzieh Badzanchin, 2023. "Estimation of Manning Roughness Coefficient in Alluvial Rivers with Bed Forms Using Soft Computing Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3563-3584, July.
    2. Kazem Shahverdi & Hossein Talebmorad, 2023. "Automating HEC-RAS and Linking with Particle Swarm Optimizer to Calibrate Manning’s Roughness Coefficient," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 975-993, January.
    3. Saritha Padiyedath Gopalan & Akira Kawamura & Hideo Amaguchi & Gubash Azhikodan, 2020. "A Generalized Storage Function Model for the Water Level Estimation Using Rating Curve Relationship," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2603-2619, June.

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