Application of Hydrodynamic Simulation and Artificial Intelligence in Hydraulic Engineering

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

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