Current courses Prof. Fletcher is teaching
CEE 366A:
Water, models, and decision-making
Computational models are frequently used as decision support tools to inform water resources planning for an uncertain future. Recent advances allow models to consider a broad range of hydrological and social processes and evaluate infrastructure development, operations, and policy. However, models are inherently limited tools, and analysts must be judicious in how models are selected, used, interpreted, and communicated. This class will examine a series of case studies in water resources planning under uncertainty and the models used to support these decisions. How can models help us enhance the robustness, resilience, and equity of our water systems? What are the strengths and limitations of models across diversity in scale, complexity, and social context? Class will draw on studies of: reservoir operations, river basin development, environmental justice, urban water supply, and virtual water. Modeling frameworks may include: simulation and optimization methods, agent-based modeling, network analysis, serious games, and participatory modeling. Assignments will center on reading and writing critiques of recent scientific literature.
CEE 266F:
Stochastic hydrology
Hydrological processes like precipitation, streamflow, and groundwater flow are highly variable over time and across locations. Quantifying the uncertainty in hydrological models and simulating future conditions is critical for informing the development and management of civil infrastructure systems. This course introduces students to statistical methods used in hydrology for data analysis, risk and uncertainty analysis, and simulation. Topics may include: flood and drought frequency, time series analysis, rainfall-runoff modeling, and lake water quality. Methods may include: applied probability theory, extreme value theory, parameter estimation, regression, time series analysis, transfer functions, Bayesian methods.
CEE 266G:
Water resource systems analysis
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.