Application of Hydrodynamic Simulation and Artificial Intelligence in Hydraulic Engineering

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

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 842

Special Issue Editors

School of Civil Engineering, Tianjin University, Tianjin, China
Interests: ecohydrology; river restoration; hydrodynamics; stormwater management; machine learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Environment Fluid Dynamic Laboratory, Department of Civil Engineering, Queen's University, Kingston, ON, Canada
Interests: environmental fluid dynamics; sediment resuspension; coastal oceanography; hydrodynamic and water quality modelling; physical limnology and physical-biogeochemical coupling; internal waves; turbulence and mixing in stratified flows; impacts of climate change on water quality and fish habitat

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Guest Editor
Department of Civil and Environmental Engineering, Western University, Ontario, ON N6A 3K7, Canada
Interests: watershed hydrology; hydroclimatic extremes; climate change impact assessment; detection and attribution; infrastructure risk and resilience; regional frequency analysis; multi-modeling and uncertainty assessment; downscaling and bias correction
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Special Issue Information

Dear Colleagues,

Surface waters (lakes, rivers, reservoirs, estuaries, water conveyance projects, and the coastal zone) play an important role in supporting human and ecosystem health and promote social and economic development. Anthropogenic changes in the internal or external conditions of the water body will lead to changes in the ecosystem and the implementation of water resources management plans will have a positive or negative impact on surface water resources. In order to improve management and utilization of surface water resources, decision-making must be based on reliable scientific models. However, the complexity of natural water bodies and the application of commonly applied process-based models faces many challenges, such as the selection of empirical parameters, high computational cost, and assessing the impacts of uncertainty in boundary conditions and process parameterizations. In contrast to process-based models, Artificial Intelligence (AI) and Machine Learning (ML) methods develop relationships purely from data and are particularly suitable for application in complex and non-linear systems. The application of AI and ML to surface waters has prompted remarkable achievements in recent years, allowing for efficient simulation models to provide decision support. This Special Issue of Water focuses on the application of AI and ML for the simulation of surface water hydrodynamics,  water quality, and management.

Dr. Xin Zhao
Prof. Dr. Leon Boegman
Dr. Mohammad Reza Najafi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • computational fluid dynamics
  • environmental fluid dynamics
  • hydrodynamic and water quality modelling
  • hydraulic engineering management
  • optimization strategies
  • artificial intelligence
  • machine learning

Published Papers

There is no accepted submissions to this special issue at this moment.
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