Advanced Modelling Strategies for Hydraulic Engineering and River Research

Dear Colleagues,

Our society, as a whole, and the work environment in particular, are currently undergoing large-scale digital transformation. This development is particularly beneficial for the field of water-related engineering. Advances in computer power have led to the evolvement of numerical methods, providing solutions to issues in hydraulic engineering and river research that were considered intractable in the past.

While 2D or 3D Reynolds-Averaged Navier–Stokes (RANS) methods are often the first choice for numerically tackling problems in applied hydraulics, high-resolution techniques such as Large Eddy Simulations (LES) have also been employed successfully for ever larger modelling domains. Advances in particle-based methods, such as Smoothed Particle Hydrodynamics (SPH) or Lattice Boltzmann Methods (LBM) could yield robust and highly accurate results. Also, strategies involving machine learning and artificial intelligence have matured in recent years. Further highly promising modelling strategies are the extension of numerical models to the physical domain by hybrid models, and the dissemination of results to a broader public audience by real-time virtual and augmented reality.

This Special Issue invites contributions related to the development or employment of advanced modelling strategies, such as (but not limited to) the aforementioned techniques, to solve applied issues involving hydraulic structures, rivers or reservoirs. This particularly applies to processes related to hydrodynamics, sediment transport (bedload, suspended load), sedimentation, erosion, morphodynamics, pollutant transport, density-driven currents, and flow–vegetation interactions, and potentially entails further ecological processes in an interdisciplinary view.

Dr. Michael Tritthart
Guest Editor

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