IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v27y2013i1p153-167.html
   My bibliography  Save this article

Uncertainties in the Methods of Flood Discharge Measurement

Author

Listed:
  • Yen-Chang Chen
  • Yung-Chia Hsu
  • Kuang-Ting Kuo

Abstract

This study demonstrates an application of uncertainty analysis in evaluating methods of discharge measurement including: the velocity-area, rating curve and efficient methods based on the probabilistic velocity distribution equation. The measurement of river discharge plays a large part in the distribution of water resources. The conventional methods of discharge measurement are costly, time-consuming, and dangerous. Therefore the efficient method of discharge measurement which bases on the relationship between maximum and mean velocities being constant was employed to justify its alternative for the conventional methods: velocity-area and rating curve methods. Distribution test was applied to investigate the statistical properties of the uncertainties involved in the three methods of discharge measurement. Latin hypercube sampling (LHS) method was employed accordingly to assess the discharge features of the three methods of discharge measurement. The main purpose of this study is to quantify the uncertainty involved in several discharge measurement methods and justify the availability and reliability of using the efficient method as an alternative of the conventional methods. Results show that the correlation analysis also validates that the efficient method is a more reliable method than the rating curve method to yield accurate discharge measurements. Moreover, it also yielded comparably accurate measurements as those by the velocity-area method. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Yen-Chang Chen & Yung-Chia Hsu & Kuang-Ting Kuo, 2013. "Uncertainties in the Methods of Flood Discharge Measurement," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 153-167, January.
  • Handle: RePEc:spr:waterr:v:27:y:2013:i:1:p:153-167
    DOI: 10.1007/s11269-012-0174-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-012-0174-2
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11269-012-0174-2?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. Yung‐Chia Hsu & Serge Rohmer, 2010. "Probabilistic Assessment of Industrial Synergistic Systems," Journal of Industrial Ecology, Yale University, vol. 14(4), pages 558-575, August.
    2. Chandrasekaran Sivapragasam & Nitin Muttil, 2005. "Discharge Rating Curve Extension – A New Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(5), pages 505-520, October.
    3. Woo Lee & Kil Lee & Sang Kim & Eun-Sung Chung, 2010. "The Development of Rating Curve Considering Variance Function Using Pseudo-likelihood Estimation Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(2), pages 321-348, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guangming Yu & Sa Wang & Qiwu Yu & Lei Wu & Yong Fan & Xiaoli He & Xia Zhou & Huanhuan Jia & Shu Zhang & Xiaojuan Tian, 2014. "The Regional Limit of Flood-Bearing Capability: A Theoretical Model and Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(7), pages 1921-1936, May.
    2. 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.

    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. Prashant Srivastava & Dawei Han & Miguel Ramirez & Tanvir Islam, 2013. "Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 3127-3144, June.
    2. Jordan Clayton & Jason Kean, 2010. "Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3641-3664, October.
    3. Andres Ticlavilca & Mac McKee, 2011. "Multivariate Bayesian Regression Approach to Forecast Releases from a System of Multiple Reservoirs," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(2), pages 523-543, January.
    4. 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.
    5. Mohamad Basel Al Sawaf & Kiyosi Kawanisi & Cong Xiao, 2020. "Measuring Low Flowrates of a Shallow Mountainous River Within Restricted Site Conditions and the Characteristics of Acoustic Arrival Times Within Low Flows," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3059-3078, August.
    6. Abdüsselam Altunkaynak, 2007. "Forecasting Surface Water Level Fluctuations of Lake Van by Artificial Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(2), pages 399-408, February.
    7. Koji Kimita & Sergio A. Brambila‐Macias & Anne‐Marie Tillman & Tomohiko Sakao, 2021. "Failure analysis method for enhancing circularity through systems perspective," Journal of Industrial Ecology, Yale University, vol. 25(3), pages 544-562, June.
    8. Ozgur Kisi, 2015. "Streamflow Forecasting and Estimation Using Least Square Support Vector Regression and Adaptive Neuro-Fuzzy Embedded Fuzzy c-means Clustering," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5109-5127, November.
    9. By Huang & Hund-Der Yeh, 2012. "Parameter Identification for a Slug Test in a Well with Finite-Thickness Skin Using Extended Kalman Filter," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(14), pages 4039-4057, November.

    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:27:y:2013:i:1:p:153-167. 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.