Computer Modelling Techniques in Environmental Hydraulics and Water Resource Engineering

Mathematical models have played increasingly important roles in investigating complex water resources and water environmental problems over the past one hundred years. With the rapid development of big data technology, scientific computing is now evolving from the traditional physical-based calculations to the increasingly popular data-driven models grounded on artificial neural networks. The active research topics include the model selection, algorithm output judgement, visualization of results, useful information extraction, and the integration of physical-based and machine learning approaches. This Reprint focuses on mathematical modelling and numerical simulations in the fields of environmental hydraulics and water resource engineering, aiming to share the latest research endeavours, technological progress, and case studies from around the world. It includes the integration and application of artificial intelligence technologies into the conventional computational modelling exercises, addressing the difficulties of small datasets, interconnected systems, and extreme environmental changes.