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This report presents a framework for compiling available data and for establishing statistical relationships between water quality and several regional factors of climate, physiography, and land use. The framework is applied to the Susquehanna River basin in Pennsylvania and New York. The Susquehanna River drains 27,510 mi^ of diverse terrain and has a moderate climate. A statistical approach is used in this study to assess the spatial variability of water quality among 80 subbasins of the Susquehanna River basin. Water quality, for purposes of this study, is defined by 17 characteristics of calculated annual yields or mean concentrations of suspended sediment, dissolved solids, and various chemical species of nitrogen and phosphorus. The water-quality characteristics are related experimentally to 57 basin characteristics which were compiled from available sources of data. The 57 basin characteristics were selected to account for nonpoint-sources of pollution or to describe processes which control the 17 water-quality characteristics. The six general categories of basin characteristics are (1) climate, (2) topography, (3) geology, (4) soils, (5) streamflow, and (6) land use. Multiple-linear-regression equations were developed to relate waterquality characteristics (dependent variables) to basin characteristics (independent variables). Usable regression equations were developed for 14 of the 17 water-quality characteristics. These equations explain from 56 to 89 percent of the variation of the water-quality characteristics with, standard errors of estimate ranging from 17 to 75 percent. The 14 regression equations can be used to estimate water quality at any stream site in the study region. These equations are also used to simulate generalized effects of specific basin characteristics on water quality. For example, simulated ranges of background water-quality characteristics can be generalized by mathematically removing the land-use variables from the regression equations. Comparison of simulated ranges of background water quality to observed ranges gives a general indication of the effects of the land-use variables. For example, observed nitrate yields are as much as 20 times greater than simulated background yields. This increase is believed to be a result of animal wastes, the application of chemical fertilizers, and of increasing urbanization. Landuse variables affected by human activities and economic development had measurable impacts in all 14 of the usable regression functions. It is concluded that this technique is a useful screening technique to assess the gross effects of land use and other basin variables on water quality in the Susquehanna River basin. On the basis of these results, it appears that similar regression-analysis techniques might be applicable to other regions. j

water-resources investigations report

Regional analysis of the effects of land use on stream-water quality; methodology and application in the Susquehanna River Basin, Pennsylvania and New York