This lecture conveys the mathematical basis necessary for the development and application of numerical models in the field of Environmental Science. The lecture material includes an introduction into numerical techniques for solving ordinary and partial differential equations, as well as exercises aimed at the realization of simple models using the computer language Python.
Learning objective
Ability to develop simple numerical schemes and to implement these schemes using the programming language Python. Ability to critically assess and use more complex numerical models.
Content
Classification of numerical problems, introduction to finite-difference methods, linear and nonlinear tranport equation, time integration schemes, non-linearity, conservative numerical techniques, overview of other methods. Examples and exercises from a diverse cross-section of Environmental Science.
Three exercises, each two hours in length, are integrated into the lecture. The implementation language is Python (previous experience not necessary, a Phython introduction is provided). Example programs and graphics tools are supplied.
Performance assessment as a semester course