IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i8d10.1007_s11269-022-03174-5.html
   My bibliography  Save this article

Entropy-Based Flow and Sediment Routing in Data Deficit River Networks

Author

Listed:
  • Pooja Patel

    (IIT Bhubaneswar)

  • Arindam Sarkar

    (IIT Bhubaneswar)

Abstract

The reliable estimate of the sediment load and streamflow is essential for water resources and flood management. In this study, the entropy-based technique and HEC-RAS are used for flow routing followed by sediment routing in HEC-RAS. The paper’s novelty is its application to data-deficit river networks, where observed sediment load and flow on tributaries are absent. The proposed method accommodates the flow and sediment contribution from the tributaries to the downstream station on a reach, despite unavailable observed data on it. The adopted flow routing techniques are applied to predict downstream flow on three different reaches (on the Mahanadi and the Godavari River). The prediction accuracy is evaluated using three statistical indices ‒ Nash–Sutcliffe efficiency (NSE), relative error (RE), and Coefficient of determination (R2). Both flow routing techniques showed good performance for all three reaches (with or without tributaries), having NSE, R2 > 0.8, and RE 0.85, and RE

Suggested Citation

  • Pooja Patel & Arindam Sarkar, 2022. "Entropy-Based Flow and Sediment Routing in Data Deficit River Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2757-2777, June.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:8:d:10.1007_s11269-022-03174-5
    DOI: 10.1007/s11269-022-03174-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03174-5
    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/s11269-022-03174-5?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. Xiaoyan Bai & Wen Shen & Peng Wang & Xiaohong Chen & Yanhu He, 2020. "Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(13), pages 3987-4002, October.
    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. Hadi Norouzi & Jalal Bazargan, 2022. "Calculation of Water Depth during Flood in Rivers using Linear Muskingum Method and Particle Swarm Optimization (PSO) Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4343-4361, September.

    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. Xiao Zhang & Xiaomin Chen & Wanshun Zhang & Hong Peng & Gaohong Xu & Yanxin Zhao & Zhenling Shen, 2022. "Impact of Land Use Changes on the Surface Runoff and Nutrient Load in the Three Gorges Reservoir Area, China," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    2. Ying Chen & Binbin Lu & Chongyu Xu & Xingwei Chen & Meibing Liu & Lu Gao & Haijun Deng, 2022. "Uncertainty Evaluation of Best Management Practice Effectiveness Based on the AnnAGNPS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1307-1321, March.
    3. Zhongfa Zhou & Weiquan Zhao & Sisi Lv & Denghong Huang & Zulun Zhao & Yaopeng Sun, 2023. "Spatiotemporal Transfer of Source-Sink Landscape Ecological Risk in a Karst Lake Watershed Based on Sub-Watersheds," Land, MDPI, vol. 12(7), pages 1-19, July.
    4. Mingtao Yan & Jianji Zhao & Jiajun Qiao & Dong Han & Qiankun Zhu & Yang Yang & Qi Liu & Zhipeng Wang, 2023. "Spatial Pattern Evolution and Influencing Factors on Agricultural Non-Point Source Pollution in Small Town Areas under the Background of Rapid Industrialization," IJERPH, MDPI, vol. 20(3), pages 1-19, February.

    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:8:d:10.1007_s11269-022-03174-5. 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.