IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p1939-d1041556.html
   My bibliography  Save this article

Soil Erosion Type and Risk Identification from the Perspective of Directed Weighted Complex Network

Author

Listed:
  • Ping Tu

    (Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou 350108, China
    The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China)

  • Qianqian Zhou

    (Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou 350108, China
    College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China)

  • Meng Qi

    (Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou 350108, China
    The Academy of Digital China (Fujian), Fuzhou University, Fuzhou 350108, China)

Abstract

Identifying the geographic distribution and erosion risks of various soil erosion regions are critical inputs to the implementation of extensive and effective land protection planning. To obtain more accurate and sufficient erosion information on a large scope, this paper introduced the complex network theory to quantitatively simulate the topographic spatial structure and topological relationship of the erosion area. The watershed was selected as the basic study unit and the directed weighted complex network (DWCN) of each watershed was constructed from DEM data. The directed weighted complex network factor (DWCNF) of each watershed was calculated by the DWCN. After combining DWCNFs with existing SEEF, the soil erosion types and risks of sample areas in the Chinese Loess Plateau were identified by the random forest model. The results show that in both typical and atypical sample areas, the identification performance of soil erosion by combining DWCNFs with existing SEEFs was performed better than that by employing only the DWCNFs or SEEFs dataset. It is suggested that the quantitative description of the spatial structure and topological relationship of the watershed from the perspective of a complex network contributes to obtaining more accurate soil erosion information. The DWCNF of structural entropy, betweenness centrality, and degree centrality were of high importance, which can reliably and effectively identify the types and risks of soil erosion, thus providing a broader factor reference for relevant research. The method proposed in this paper of vectoring terrain into complex network structures is also a novel sight for geological research under complex terrain conditions.

Suggested Citation

  • Ping Tu & Qianqian Zhou & Meng Qi, 2023. "Soil Erosion Type and Risk Identification from the Perspective of Directed Weighted Complex Network," Sustainability, MDPI, vol. 15(3), pages 1-22, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:1939-:d:1041556
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/1939/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/1939/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Singh, R. & Subramanian, K. & Refsgaard, J. C., 1999. "Hydrological modelling of a small watershed using MIKE SHE for irrigation planning," Agricultural Water Management, Elsevier, vol. 41(3), pages 149-166, August.
    Full references (including those not matched with items on IDEAS)

    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. Galelli, S. & Gandolfi, C. & Soncini-Sessa, R. & Agostani, D., 2010. "Building a metamodel of an irrigation district distributed-parameter model," Agricultural Water Management, Elsevier, vol. 97(2), pages 187-200, February.
    2. Phong Nguyen Thanh & Thinh Le Van & Tuan Tran Minh & Tuyen Huynh Ngoc & Worapong Lohpaisankrit & Quoc Bao Pham & Alexandre S. Gagnon & Proloy Deb & Nhat Truong Pham & Duong Tran Anh & Vuong Nguyen Din, 2023. "Adapting to Climate-Change-Induced Drought Stress to Improve Water Management in Southeast Vietnam," Sustainability, MDPI, vol. 15(11), pages 1-27, June.
    3. Rejani Raghavan & Kondru Venkateswara Rao & Maheshwar Shivashankar Shirahatti & Duvvala Kalyana Srinivas & Kotha Sammi Reddy & Gajjala Ravindra Chary & Kodigal A. Gopinath & Mohammed Osman & Mathyam P, 2022. "Assessment of Spatial and Temporal Variations in Runoff Potential under Changing Climatic Scenarios in Northern Part of Karnataka in India Using Geospatial Techniques," Sustainability, MDPI, vol. 14(7), pages 1-21, March.

    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:15:y:2023:i:3:p:1939-:d:1041556. 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: 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.