IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-656-7_5.html

Overview of Research Progress on Water Conservancy Big Data in China

In: Proceedings of 2024 4th International Conference on Public Management and Big Data Analysis (PMBDA 2024)

Author

Listed:
  • Xi He

    (Zhejiang University of Water Resources and Electric Power)

  • Mingchao Zhang

    (Zhejiang University of Water Resources and Electric Power)

Abstract

Water conservancy big data refers to a technical means in the water conservancy industry that collects, stores, processes, and analyses massive amounts of data to reveal the laws of water resource utilization, water conservancy engineering operation, water disaster prevention and control, and provide scientific basis for water conservancy management and decision-making. This article reviews the research progress of water conservancy big data in China, analyzes the current application status, challenges, and future development trends of big data technology in the field of water conservancy. By reviewing existing literature, this paper explores how big data technology can assist in water conservancy informatization and intelligent management, as well as the future development prospects in areas such as further intelligence and digitization of water conservancy, data privacy and security, technology integration and innovation, talent cultivation and cooperation mechanisms, and regulatory and policy support.

Suggested Citation

  • Xi He & Mingchao Zhang, 2025. "Overview of Research Progress on Water Conservancy Big Data in China," Advances in Economics, Business and Management Research, in: Soon M. Chung & Fairouz Kamareddine & Azah Kamilah Draman & Sim Kwan Yong (ed.), Proceedings of 2024 4th International Conference on Public Management and Big Data Analysis (PMBDA 2024), pages 38-46, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-656-7_5
    DOI: 10.2991/978-94-6463-656-7_5
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:advbcp:978-94-6463-656-7_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.

    We have no bibliographic references for this item. You can help adding them by using 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.