Virginia Institute of Marine Science
Compressed zip file under the download tab.
Read me file in the supplemental files section below.
During 1980 through 1981, the Virginia Institute of Marine Science conducted studies in the Hampton Roads Virginia vicinity to assess pollutant loading in runoff from various land use types. The 13 urban study areas also included established BMPs such as grassy swales and retention ponds to measure their effectiveness in reducing pollutant loads to the Chesapeake Bay. The focus was on nutrients, BOD and suspended solids. The studies were conducted with support of the U.S. EPA under section 208 of the Federal Clean Water Act.
Methods and results are documented in the associated publication. Data files were processed using SPSS software (Statistical Package for the Social Sciences) and are provided in Text (.csv) format. Example SPSS scripts used for processing data files are also provided. See the readme.txt file for the data dictionary and further data processing information.
Files | Description
- Readme.txt: Data dictionary and overview
Compressed zip file:
- HR_NPS_Stations.csv: Table of Non-Point (NPS) Stations
- HR_NPS_Runoff_WQ.csv: NPS Runoff monitoring Water Quality Data
- HR_NPS_Pond_WQ.csv: NPS Pond inflow/outflow Water Quality Data
- HR_NPS_Runoff_WQ.spss: SPSS script to read NPS WQ data
- HR_NPS_Runoff_Flow.spss: SPSS script to read NPS flow data
- HR_NPS_Runoff_Loads.spss: SPSS script to calculate runoff loads per hectare
Non-Point sources, pollution, Water Quality, sediments, Hampton Roads, Chesapeake Bay, Virginia, Monitoring, Runoff, Best Management Practices
Anderson, G. F., Neilson, B. J., & Campbell, D. H. (1982) Management practice evaluation for urban areas in the Hampton Roads vicinity: a report to Hampton Roads Water Quality Agency. Virginia Institute of Marine Science, William & Mary. https://scholarworks.wm.edu/reports/2726
US EPA Grant No. P003085-03
Anderson, Gary F., "Management Practices for Urban Areas in the Hampton Roads Vicinity: Data Files" (2022). Data. William & Mary.