Projects Created
Oregon 303(d) Pollutants & Summary Table
This environmental studies course is a part of the Portland State University integrated Science Cornerstone Curriculum. The official course description reads "Water in the Environment focuses on the unique properties of water in all its roles, including a study of the water cycle, water resources, treatment of municipal water, and wastewater treatment. Special attention will be placed on water as a resource, including natural and introduced constituents and the movement of natural waters.
The primary objectives of the course were for students to become aware of water quality issues in the Portland Metropolitan Region. We learned scientific terminology and concepts related to hydrology, aquatic
macroinvertebrates, water pollution, bioassessment and scientific research.
- Education on watershed, point and non-point pollution, biodiversity health metrics of rivers, water chemistry, affects of pollutants on organisms, the river/forest interdependent food web, lifecycles of stream macroinvertebrates,
- Google mapping of local watersheds using watershed delineation. Outlining rivers and stream tributaries of the overall area.
- Standard "Stream Order" numbering system to illustrate the complexity of the stream by identifying how many unique tributaries junctions contribute to a given stream.
- Common stream macroinvertebrate identification, conducting non-lethal bioassessment, and analysis of citizen scientist data.
- USGS StreamStats database to collect information on land-use of the areas that flow into watersheds.
- Introduction to the Oregon 303(d) list, a government maintained databases to analyze water quality (pollutants, oxygen level, sedimentation)
- OWEB IBI (Oregon Watershed Enhancement Board Index of Biotic integrity) used to calculate the level of impairment a stream has based on the macroinvertebrate biodiversity.
- Evaluating local stream restoration projects, efficacy, and strategies to improve stream health based on the specific impairments.
- Using boxplots and t-tests to analyze data in a categorical method and determining the likelihood of false positive results. Used programing system "R" to generate the graphs and p-value.
- Peer-review of scientific posters created by other groups
Web Design Program