A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis.
Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States.
Robertson
Dale M
DM
United States Geological Survey, Wisconsin Water Science Center, Middleton, Wisconsin, USA. derobert@usgs.gov
Saad
David A
DA
Heisey
Dennis M
DM
D004784:Environmental Monitoring / Q000706:statistics & numerical data*; D019015:Geologic Sediments; D015146:Midwestern United States; D010758:Phosphorus / Q000032:analysis; D012044:Regression Analysis; D045483:Rivers; D014874:Water Pollutants, Chemical / Q000032:analysis*
D014874:Water Pollutants, Chemical; D010758:Phosphorus