Envirnmntl Sci & Policy (ESP)

Managing natural resources for multiple objectives, in a sustainable manner, is a challenge that both practitioners and researchers face in today's highly complex socio-political environment. Decision analysis skills are highly valued in the field of environmental science. This course will present current theories and applications related to decision making for natural resource management. Students will have the chance to work through local and regional decision making scenarios and compare different tools and theories on the ground.

This course will provide a qualitative and quantitative understanding of concepts and physical principles governing the occurrence, distribution, and circulation of water near the Earth's surface. Emphasis will be on the physical understanding and parameterization of hydrologic processes such as how rainfall and snowmelt become streamflow, evapotranspiration, and groundwater. This course is expected to serve as prerequisite to Watershed Management and Snow Hydrology, and co- or pre-requisite to Field Methods in Water Resources.

This course will focus on data analysis techniques in environmental science. Topics will include exploratory analysis, research design, univariate and multivariate statistical approaches, a few basic machine learning algorithms, and Monte Carlo propagation of uncertainty. The course is project based, so students will work with a large data set of their choice throughout the semester.

Students select a topic in consultation with their advisor and committee. A timeline, proposal, and defense are outlined. A final thesis is prepared in accordance with program thesis guidelines. Pass/No Pass.