University of Arizona 3 credits Hydrology & Atmospheric Sci
This course introduces numerical methods and modern deep learning approaches for modeling environmental systems governed by partial differential equations (PDEs). Emphasis is placed on developing physical intuition, mathematical understanding, and computational skills for simulating flow and transport processes in porous media and related environmental applications. Traditional numerical techniques (finite difference and finite volume methods) are presented alongside emerging machine-learning-based approaches, including physics-informed neural networks and neural operators. Students will learn how these methods relate to, complement, and extend classical numerical modeling frameworks used in hydrology and environmental engineering.
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