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 783
Special Issue Editors
Interests: ecohydrology; river restoration; hydrodynamics; stormwater management; machine learning
Special Issues, Collections and Topics in MDPI journals
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
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
Special Issues, Collections and Topics in MDPI journals
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
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Keywords
- computational fluid dynamics
- environmental fluid dynamics
- hydrodynamic and water quality modelling
- hydraulic engineering management
- optimization strategies
- artificial intelligence
- machine learning
