We collected water quality data from several government agencies, and downloaded spatial stream data from the US Geological Survey (USGS) National Hydrography Dataset [1]. Washington water quality data was collected from Washington Department of Ecology [2], as well as Clark County Environmental Services [3]. The Portland Bureau of Environmental Services has been collecting monthly stream data at select sites consistently since 1998–2010. Twenty-one sites from Portland and 30 sites from Clark County were selected based on the available sample dates, parameters, and watershed characteristics. Each government agency collected data based on their sampling methods and quality control on USEPA standards. Seven water quality parameters were chosen based on its importance to human and aquatic life in both Portland and Vancouver study sites. Nitrogen nitrate NO3+–N (NN) and total phosphorus (TP) are generally considered to be direct measures of human activity in an area, as fertilizers, vehicle emissions, and impervious surfaces increase the amount of NN and TP in their respective natural cycles [4]. Total solids (TS) can be used as a quantitative measure of aesthetics as suspended sediments in streams make the water appear cloudy. This study also used conductivity (EC), dissolved oxygen (DO), pH, and water temperature (Temp). These measurements are associated with predicting algae bloom likelihood and habitat quality for fish and other aquatic animals. In order to account for the seasonal variation in stream flows, the data were split into wet (November–April) and dry (May–October) seasons. The seasonal data were aggregated to a geometric mean for the entire period. The geometric mean was used because it is a slightly more conservative estimate of aggregated water quality parameters than an arithmetic mean. It is also more appropriate to use a geometric mean when data are not normally distributed, which was the case for two parameters. The standard deviation of slope, derived here from a 10 m digital elevation model, has been used in past studies as a measure of topography complexity where the study area is relatively flat, which is the case in many of the urban watersheds [5]. The 2006 US National Land Cover Dataset was used to categorize percent urban, forest, agriculture, and wetlands in each area, with areas of less than 0.1% not included for analysis. Structural variables include single family residential (SFR) taxlots and street density. These spatial data allowed researchers a finer scale with which to examine land development within the study area. The percent area of SFR provided a measure of residential housing impact. Average building age of SFR homes built before 2010 was used as a measure of historical development. Street density provides a measure of habitat fragmentation as well as impervious surfaces. We used the 2010 taxlot and streets datasets produced by Clark County and the Portland Metropolitan Authority. In order to determine the association between landscape variables and water quality at each monitoring site, this study uses sectioned watersheds and riparian buffers. These sectioned zones limit the area associated with the sample site to the next site immediately upstream. The riparian buffer was used to determine if the immediate environment surrounding the stream has a stronger relationship than the entire area. Watersheds were delineated from the 51 sample sites using the 10 m DEM in ArcGIS v10.0, while the riparian areas were created by buffering the streams 100 m. The downstream watersheds and riparian areas were clipped to the upstream watershed, where applicable, to create sectioned watersheds and buffers. The area of SFR was normalized to a percent coverage of the area, and the streets layer was normalized to length (m)/(1000) area (m2). SFR house age was averaged from SFR taxlots present in the sectioned area. Land cover and topographic variables were calculated using the Spatial Analyst tools in ArcGIS.
