[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v305y2024ics0378377424004451.html
   My bibliography  Save this article

A distributed simulation-optimization framework for many-objective water resources allocation in canal-well combined irrigation district under diverse supply and demand scenarios

Author

Listed:
  • Zhao, Qianzuo
  • Jiang, Yanan
  • Wang, Qianyu
  • Xu, Fenfang
Abstract
To address the issues of both water resources allocation and sustainable management in agriculture areas with rising food demand, a simulation-optimization framework based on Flopy and Pymoo was proposed and developed for canal-well combined irrigation districts. The proposed framework first solved the many-objective water resources allocation problem which integrates groundwater simulation, crop production, and farmer income modules to quantitatively reveal the various trade-offs and synergies by using NSGA-III algorithm. The Entropy-TOPSIS method was then applied to recommend proper water allocation schemes. The proposed framework was further tested in Baojixia irrigation district considering various water supply and crop demand scenarios based on Copula-based uncertainty analysis. The Key findings are as follows: (1) the proposed framework could effectively optimize conjunctive water resources allocation problems of both surface water and groundwater; (2) low supply combined with high demand (p=0.17) is more likely to occur than high supply with high demand (p=0.02); (3) increased crop demand and restricted surface water negatively impact both water productivity and groundwater sustainability; and (4) the cumulative groundwater drawdown of recommend schemes is 36.9 % and 6.5 % higher under low to medium supply scenarios, while water productivity of recommend schemes decreases 28.2 % and 9.7 % with high and medium demand. This framework could provide useful insights for sustainable agricultural water management in canal-well combined irrigation district with various uncertainties in supply and demand scenarios.

Suggested Citation

  • Zhao, Qianzuo & Jiang, Yanan & Wang, Qianyu & Xu, Fenfang, 2024. "A distributed simulation-optimization framework for many-objective water resources allocation in canal-well combined irrigation district under diverse supply and demand scenarios," Agricultural Water Management, Elsevier, vol. 305(C).
  • Handle: RePEc:eee:agiwat:v:305:y:2024:i:c:s0378377424004451
    DOI: 10.1016/j.agwat.2024.109109
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377424004451
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2024.109109?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.

    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:eee:agiwat:v:305:y:2024:i:c:s0378377424004451. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    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.