IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i18p8184-d1481466.html
   My bibliography  Save this article

Spatial-Temporal Evaluation and Prediction of Water Resources Carrying Capacity in the Xiangjiang River Basin Using County Units and Entropy Weight TOPSIS-BP Neural Network

Author

Listed:
  • Jiacheng Wang

    (Center for Ecological Environment Management and Assessment, Central South Forestry University of Science and Technology, Changsha 410004, China
    These authors contributed equally to this work.)

  • Zhixiang Wang

    (Center for Ecological Environment Management and Assessment, Central South Forestry University of Science and Technology, Changsha 410004, China
    These authors contributed equally to this work.)

  • Zeding Fu

    (Yueyang City Water Resources Bureau, Yueyang 414000, China
    These authors contributed equally to this work.)

  • Yingchun Fang

    (Hunan Kaidi Engineering Technology Co., Ltd., Yueyang 414000, China)

  • Xuhong Zhao

    (Center for Ecological Environment Management and Assessment, Central South Forestry University of Science and Technology, Changsha 410004, China)

  • Xiang Ding

    (Center for Ecological Environment Management and Assessment, Central South Forestry University of Science and Technology, Changsha 410004, China)

  • Jing Huang

    (Center for Ecological Environment Management and Assessment, Central South Forestry University of Science and Technology, Changsha 410004, China)

  • Zhiming Liu

    (Henan Academy of Sciences, Zhengzhou 450046, China)

  • Xiaohua Fu

    (Center for Ecological Environment Management and Assessment, Central South Forestry University of Science and Technology, Changsha 410004, China)

  • Junwu Liu

    (Hunan Kaidi Engineering Technology Co., Ltd., Yueyang 414000, China)

Abstract

To improve the water resources carrying capacity of the Xiangjiang River Basin and achieve sustainable development, this article evaluates and predicts the Xiangjiang River Basin’s water resources carrying capacity level based on county-level units. This article takes 44 county-level units in the Xiangjiang River Basin as the evaluation target, selects TOPSIS and the entropy weight method to determine weights, calculates the water resources carrying capacity level of the evaluation sample, uses a BP neural network model to calculate the predicted water resources carrying capacity level for the next 5 years, and adds the GIS method for spatiotemporal analysis.(1) The water resources carrying capacity of the Xiangjiang River Basin has remained relatively stable for a long period, with overloaded areas being the majority. (2) There are relatively significant spatial differences in the carrying capacity of water resources: Zixing City, located upstream of the tributary, is far ahead due to its possession of the Dongjiang Reservoir; the water resources carrying capacity in the middle and lower reaches (northern region) is generally higher than that in the upper reaches (southern region). (3) According to the BP neural network model prediction, the water resources carrying capacity of the Xiangjiang River Basin will maintain a stable development trend in 2022, while areas such as Changsha and Zixing City will be in a critical state, and other counties and cities will be in an overloaded state.This study has important references value for the evaluation and early warning work of the Xiangjiang River Basin and related research, providing a scientific and systematic evaluation method and providing strong support for water resource management and planning in Hunan Province and other regions.

Suggested Citation

  • Jiacheng Wang & Zhixiang Wang & Zeding Fu & Yingchun Fang & Xuhong Zhao & Xiang Ding & Jing Huang & Zhiming Liu & Xiaohua Fu & Junwu Liu, 2024. "Spatial-Temporal Evaluation and Prediction of Water Resources Carrying Capacity in the Xiangjiang River Basin Using County Units and Entropy Weight TOPSIS-BP Neural Network," Sustainability, MDPI, vol. 16(18), pages 1-27, September.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8184-:d:1481466
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/18/8184/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/18/8184/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Xiaoge Yu & Rongmei Deng & Fuqiang Li & Daiting Zhai & Can Meng, 2025. "Evaluation and Obstacle Factors of Water Resources Carrying Capacity in Tai’an, China," Sustainability, MDPI, vol. 17(5), pages 1-22, 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:gam:jsusta:v:16:y:2024:i:18:p:8184-:d:1481466. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.