Lake Superior Binational Program
Stormwater Demonstration Project
Project Summary

Managing nonpoint source pollution in urban areas is a key to preserving the water quality of Lake Superior and its tributaries. Measuring the factors that contribute to nonpoint source pollution and predicting total pollutant loads are important first step in understanding and controlling the effects of nonpoint source pollution on this unique resource.

The purpose of this study is to demonstrate the use of geographic information system (GIS) based methods to provide geographic data necessary for nonpoint source pollution modeling for 14 communities in the Lake Superior Basin, and to use this information to provide specific recommendations about stormwater management. The report focuses on the initial component of the study: acquisition and automation of geographic data used in an empirical urban nonpoint source pollution model known as SLAMM (Source Loading And Management Model). This study is part of a broader project, the Lake Superior Binational Program, designed to achieve the societal goal of protecting the waters of Lake Superior and its tributaries.

This work builds on past research by the University of Wisconsin-Madison in the Beaver Dam and Kinnickinnic River (Wisconsin) Priority Watersheds to use GIS to make improvements in data acquisition, analysis, and display for urban nonpoint pollution assessment. Two primary research issues arise from the objective to create GIS databases for 14 diverse communities. The first concerns integration and standardization of data from many sources. The second is the development of information processing routines to ensure consistent and reliable model results within and between communities.

The spatial database for each community consists of several components: a reference framework of streets, hydrography, topography, and political boundaries; the storm sewer network and the drainage basins (termed sewersheds) they serve; and current land use. The automation of these data results in the ability to calculate the acreage of individual land uses within each sewershed. This information is used as input to SLAMM and will be further manipulated to predict pollutant loadings.

Three data sources were used extensively: digital base maps, aerial photography, and local storm sewer maps. All local data providers were extremely cooperative in sharing data at little or no cost to the project. Digital data varied widely in scale, format, and currency, and generally were poorly documented. Aerial photography (NAPP and NHAP2) was obtained from the United States Geological Survey. Whereas it was affordable and consistent in scale and quality, the scale was too small for effective urban land use delineation. Local storm sewer maps also varied in scale, format, and currency. Most sewer maps were in hard copy map form -- paper or diazo prints.

Techniques used to standardize information processing included the use of a standard file naming convention; the use of double-line streets and a "road-folding" algorithm to produce more aesthetic maps and ensure consistent model results; the use of map templates to produce maps in a variety of sizes with a minimal amount of effort; and the use of an automated procedure to document the databases produced. The use of larger-scale photography and digital orthophotos were recommended to simplify the land use coding and editing processes.

Products from the automation of geographic data for the 14 communities will be distributed to those communities and are contained in a community map atlas included as a supplement to this report. The community map atlas includes a summary of land use statistics, as well as maps of land use, storm sewer networks, and sewersheds.