Intelligent Analysis, Monitoring and Assessment of Debris Flow

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydraulics and Hydrodynamics".

Deadline for manuscript submissions: 25 July 2025 | Viewed by 37

Special Issue Editor


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Guest Editor
College of Civil and Transportation Engineering, Hohai University, Nanjing, China
Interests: extreme rainfall; water–soil coupling; debris flow; numerical simulation; impact force; machine learning; artificial neural network; risk assessment; mitigation measures
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Special Issue Information

Dear Colleagues,

Extreme rainfall events occur frequently around the world and trigger a number of geohazards, causing great suffering and loss. Debris flow, one such serious water-induced geohazard, has attracted more and more attention from scholars worldwide who seek to prevent disasters and reduce damage. Meanwhile, artificial intelligence techniques have developed substantially, providing new analysis approaches, monitoring means, and risk evaluation tools for debris flows. Related studies can enhance our understanding of this kind of hazard and assist in hazard mitigation.

Therefore, this Special Issue aims to present original research and review articles that discuss slope stability under rainfall, water–soil coupling mechanisms in the flow process, and site monitoring and hazard assessment of debris flows using artificial intelligence.

Potential topics include, but are not limited to, the following:

  1. Stability analysis of slopes under rainfall events;
  2. Water–soil coupling in the flow process;
  3. Artificial intelligence approaches in the analysis of debris flows;
  4. Site monitoring of potential debris flows;
  5. Influence range evaluation and risk assessment.

We look forward to receiving your contributions.

Prof. Dr. Weijie Zhang
Guest Editor

Manuscript Submission Information

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Keywords

  • debris flow
  • water–soil coupling
  • artificial intelligence
  • numerical analysis
  • monitoring
  • risk evaluation
  • mitigation measure

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Published Papers

This special issue is now open for submission.
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