Water resources planners use computational systems engineering models to inform decisions about operations, infrastructure development, and policy. Systems models evaluate alternative decisions against performance metrics like water reliability, access, cost, electricity production, and ecosystem services under a range of hydrological and social conditions. This course will introduce computational methods used in decision-support and common applications in water resources. Focus is on applied optimization methods such as linear programming, dynamic programming, and evolutionary algorithms as well as stochastic simulation. Application areas may include: reservoir operation, environmental flow alteration, hydropower, and flood control. Attention will be given to multi-objective analysis and climate change adaptation. Assignments will involve programming in Python; some Python tutorials will be provided, but prior programming experience is recommended. Prerequisites: CEE 166A or equivalent.
3 units · Letter or Credit/No Credit
Water resources planners use computational systems engineering models to inform decisions about operations, infrastructure development, and policy. Systems models evaluate alternative decisions against performance metrics like water reliability, access, cost, electricity production, and ecosystem services under a range of hydrological and social conditions. This course will introduce computational methods used in decision-support and common applications in water resources. Focus is on applied optimization methods such as linear programming, dynamic programming, and evolutionary algorithms as well as stochastic simulation. Application areas may include: reservoir operation, environmental flow alteration, hydropower, and flood control. Attention will be given to multi-objective analysis and climate change adaptation. Assignments will involve programming in Python; some Python tutorials will be provided, but prior programming experience is recommended. Prerequisites: CEE 166A or equivalent.