The Lake St. Clair Regional Monitoring Project partners planned a 3-year assessment study of the surface water in the Lake St. Clair drainage basins in Michigan. This study included water-quality monitoring and analysis, collection of discrete (grab) and automatic water-quality samples, monitoring of bacteria, and the creation of a database to store all relevant data collected from past and future field-data-collection programs.

In cooperation with the Lake St. Clair Monitoring Project, the U.S. Geological Survey assessed nonpoint-source loads of nutrients and total suspended solids in the Black, Belle, and Pine River basins. The principal tool for the assessment study was the USEPA’s PLOAD model, a simplified GIS-based numerical program that generates gross estimates of pollutant loads. In this study, annual loads were computed for each watershed using the USEPA’s Simple Method, which is based on scientific studies showing a correlation between different land-use types and loading rates.

The two land-use data sets used in the study (representing 1992 and 2001) show a maximum of 0.02-percent change in any of the 15 land use categories between the two timeframes. This small change in land use is reflected in the PLOAD results of the study area between the two time periods. PLOAD model results for the 2001 land-use data include total-nitrogen loads from the Black, Belle, and Pine River basins of approximately 495,599 lb/yr, 156,561 lb/yr, and 121,212 lb/yr, respectively; total-phosphorus loads of 80,777 lb/yr, 25,493 lb/yr, and 19,655 lb/yr, respectively; and total-suspended-solids loads of 5,613,282 lb/yr, 1,831,045 lb/yr, and 1,480,352 lb/yr, respectively. The subbasins in the Black, Belle, and Pine River basin with comparatively high loads are characterized by comparatively high percentages of industrial, commercial, transportation, or residential land use.

The results from the PLOAD model provide useful information about the approximate average annual loading rates from the three study basins. In particular, the results identify subbasins with comparatively high loading rates per square mile. This could aid water-resources managers and planners in evaluation of the effectiveness of public expenditures for water-quality improvements, assessment of progress towards achieving established water-quality goals, and planning of preventive actions.