Data Series 345
U.S. GEOLOGICAL SURVEY
Data Series 345
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Samples were collected within the CCYK and CNBR study units in 2003 and in the ACFB/GAFL, PODL, and WHMI in 2004. Field parameters of water quality, water chemistry, benthic and seston algae, chlorophyll a and biomass, algal communities, macroinvertebrate communities, habitat parameters, riparian data and basin features were collected or measured at all 143 sites. Fish community data were collected only in the WHMI study area.
Field parameters were collected at a cross section within a reach. Water temperature and dissolved oxygen were measured directly from the stream at several locations across the cross section for a stream average (U.S. Geological Survey, variously dated). Discharge was calculated at the same cross section where the other field parameters were collected (U.S. Geological Survey, variously dated). Specific conductance, alkalinity, pH, and turbidity measurements, were measured from a churn splitter (U.S. Geological Survey, variously dated).
Water chemistry samples also were subsampled from the churn splitter. Ammonia, nitrite, nitrate plus nitrite, and orthophosphate samples were filtered through a 0.45–µm glass fiber filter, chilled and maintained at 4°C, and immediately shipped to the USGS National Water Quality Laboratory (NWQL) in Lakewood, Colo., and analyzed according to methods in Fishman (1993). Unfiltered total nitrogen (NH3+NO2+NO3+ organic) and phosphorus samples were acidified with 1 mL of 4.5 normality sulfuric acid, chilled and maintained at 4°C, and immediately shipped to NWQL to be analyzed according to the methods described by the U.S. Environmental Protection Agency (1993). Nutrients (nitrogen and phosphorus) were collected about 30 days prior to and again at the time of biological sampling.
The dissolved organic carbon samples were filtered using a SUPOR® filter. The filtered water sample was placed in a 125-mL amber glass bottle. The sample was acidified to a pH of less than 2 with sulfuric acid, chilled and maintained at 4°C, and immediately shipped to NWQL for analysis (Brenton and Arnett, 1993).
Water was filtered through 25-mm glass fiber filters for inorganic carbon, organic carbon, inorganic plus organic carbon, and total nitrogen. These filters were folded in half, wrapped in aluminum foil, placed in Whirlpak bags, chilled and maintained at 4°C, and immediately shipped to NWQL. Laboratory analysis was completed according to guidelines as stated in the Office of Water Quality Technical Memorandum, 2000.08 (U.S. Geological Survey, 2000).
Water samples from the churn splitter were collected for suspended-sediment analysis. Concentrations of suspended sediments were analyzed at USGS sediment laboratories according to methods described by Guy (1969) and the American Society for Testing and Materials (2002).
Seston (water column) algae also were sampled from the churn splitter. The water sample was filtered through a 47-mm glass fiber filter. The filter was folded into quarters, wrapped in aluminum foil, placed in a labeled Petri dish, placed in a plastic bag, and frozen on dry ice for shipment to NWQL (Moulton and others, 2002). Both chlorophyll a and pheophytin a were analyzed by NWQL using protocols outlined in Arar and Collins (1997).
Benthic algae were sampled within the richest targeted habitat (RTH) areas consisting of coarse rocks or woody debris using methods as described in Moulton and others (2002). A subsample of the RTH sample was filtered for chlorophyll a concentration (Moulton and others, 2002), frozen on dry ice, and sent to NWQL for analysis (Britton and Greeson, 1987), and what was not filtered was retained and preserved for community composition (Moulton and others, 2002) and sent to the Academy of Natural Sciences of Philadelphia for identification and enumeration processing (Charles and others, 2002).
Benthic algae also were sampled in the depositional habitat (DTH) areas of organically rich or sandy sediment along stream margins using methods as described in Moulton and others (2002). NAWQA does not have a standardized method for the field processing of DTH chlorophyll concentrations, therefore, methods were modified from Stevenson and Stoermer (1981). In order to filter the DTH chlorophyll sample and not clog the filters with sand, an elutriation process was used to separate the algae from the fine-grained material. Drinking water, 100 mL, was added to the sample. The sample bottle was capped and the bottle was inverted 15 times. The cap was removed and the sample was allowed to settle for 5 seconds. The algal-water mixture was pored into a clean 1-L plastic container, taking care not to introduce sand into the clean container. This process was repeated two more times for a total of three elutriations. The elutriated sample was then homogenized by shaking the algal-water mixture in the 1-L container, and then a 10-mL subsample was withdrawn from the mixture and filtered as described in Moulton and others (2002). If relatively few solids were present on the filter surface, then the filtering process was repeated until a thin, pigmented film was deposited on the filter. The filter was then removed and processed as described in Moulton and others (2002), frozen on dry ice, and sent to NWQL for analysis (Britton and Greeson, 1987). The remaining DTH sample was preserved according to Moulton and others (2002) and sent to the Academy of Natural Sciences of Philadelphia for identification and enumeration processing (Charles and others, 2002).
Benthic invertebrates were collected from RTH habitats—areas of coarse-grained riffles or woody snags—for identification and enumeration (Moulton and others, 2002). RTH samples were collected using a 500-µm mesh Nitex slack-sampler with an attached 500-µm mesh Dolphin bucket (Moulton and others, 2002). Samples were collected at five discrete locations and composited, rinsed, and elutriated by pouring the sample through a 500-µm mesh sieve to retain the sample but not the water. The retained sample was placed in a jar and preserved with 10-percent buffered formalin (Moulton and others, 2002). If woody snags were used as the RTH, five snag locations were selected (if present) and two lengths of the snags from each location were collected by placing a 500-µm mesh sampler just downstream of the snag while removing the length of snag using a saw or lopping shears (Moulton and others, 2002). The snag was cleaned, the area cleaned was recorded, and the sample was composited and preserved (Moulton and others, 2002). Samples were sent to NWQL for identification and enumeration (Moulton and others, 2000).
The WHMI staff sampled fish communities as part of this assessment. Fish were collected by electrofishing (Moulton and others, 2002). These fish were identified to species, which was recorded along with the number of fish of each species. The fish were then released back into the stream.
Habitat data were collected along the sample reach. A total of 11 equidistant transects oriented perpendicular to streamflow were established throughout the reach, with channel width measured at each transect. Water depth, water velocity, and substrate type (bedrock, boulder, cobble, gravel, sand, and silt) were measured at three points across each transect. Fitzpatrick and others (1998) provides additional details on methods used to collect habitat data.
Water temperature was recorded every 30 minutes using an internal logging meter. The meters were either suspended in the middle of the water column or anchored to the stream bottom depending on the depth of the stream. The internal logging meters were installed about 3 months prior to the biological sampling.
Shade analysis was determined using a Solar Pathfinder© (2003). This device was used to estimate solar energy along the study reach at the time biological samples were collected. Data were collected midchannel at 5 of the 11 habitat transects.
The method used for determining the percentage of either submerged macrophytes or macroalgae cover or both was modified from Biggs and Kilroy (2000). Five points along each of the 11 transects were sampled. A 0.09-m2 quadrat (a measured and marked rectangle used to isolate a sample area for the purpose of counting the population of different species in that area) was placed at each sampling point. The cover of filamentous algae and/or submerged macrophytes greater than 3 cm in length was estimated to the nearest 10 percent. These 55 values were then averaged to obtain an estimate of the average percentage of cover of the site by macroalgae and macrophytes.
The basin coverages were aggregated by the NAWQA Geographic Information System (GIS) team. Basin and riparian data were calculated for each site using a nationally consistent approach from various national data sources and methods. Variables included drainage area, land cover, ecoregions, physiography, geology, hydrologic landscape regions, and various climatic, soil, and hydrology. The GIS software used for processing the ancillary data was the Environmental Systems Research Institute’s ArcInfo Workstation and all GIS data were stored in the Albers Conical Equal-Area projection.
The area of each drainage basin was determined from the area of the polygon that represented the drainage basin boundary. Geographers in the USGS determined the drainage basin delineations from digital topographic and hydrologic maps ranging from 1:24,000 to 1:250,000 scale, depending on the size of the drainage basin. The digital maps of each drainage basin were converted from vector to raster format at 30-m resolution.
Land cover, ecoregions, physiography, geology, and hydrologic landscape regions were characterized by component percentage of the drainage basin. The source for land-cover data was an enhanced version of the USGS 1992 National Landuse Cover Database (NLCD) (Vogelmann and others, 2001; Nakagaki and Wolock, 2005). The 30-m resolution satellite-imagery-based land-cover data were used to compile percentages of drainage basins by land classification as well as the drainage basin percentages of riparian areas as much as 90 m from the stream centerline. The national datasets of (1) land cover (U.S. Geological Survey, 1999), (2) level III ecoregions (Omernik, 1987) aggregated for national nutrient assessment (Omernik, 2000), (3) physiography (Fenneman and Johnson, 1946), (4) bedrock geology (King and Beikman, 1974a, 1974b; Schruben and others, 1998), and (5) surficial geology (Hunt, 1979; Clawges and Price, 1999) were all gridded at 30-m resolution, then overlaid with the 30-m resolution drainage basin boundaries to determine the area of each classification in the drainage basin. The hydrologic landscape regions (Wolock, 2003a) were gridded at 100-m resolution prior to the overlay process with the drainage basin boundary. The drainage basin areas of each classification were then divided by the drainage area to compute the percentage of drainage basin by classification.
Stream density was computed for a drainage basin by clipping the coverage of the national streams data by the polygon defining the basin boundary and summing of the length of all streams in the basin divided by the area of the drainage basin. The source for nationwide streams data was the 1:100,000-scale National Hydrography Dataset (U.S. Geological Survey and U.S. Environmental Protection Agency, 2003).
The basin estimates for the climatic variables—runoff, the R factor of the Universal Soil Loss Equation, altitude, and the baseflow index [total volume of base flow divided by total volume of runoff for a period (Wahl and Wahl, 1995)]—were determined by overlaying the 30-m resolution basin boundary with the national data layers to compute the average of the grid cell data values in the drainage basin. The source for mean annual and monthly precipitation and temperature was the 1-km resolution grid data from the Daymet conterminous United States database (Thorton and Running, 1999). Potential evapotranspiration for drainage basins was estimated using 1-km resolution national temperature data (David W. Wolock, U.S. Geological Survey, written commun., 2005) derived from the Parameter-Elevation Regressions on Independent Slopes Model (Daly, 2006) and the equation for potential evapotranspiration (Hamon, 1961). The source for estimating average annual runoff from 1990 through 2002 in drainage basins was a time series of runoff (streamflow per unit area), computed for the hydrologic cataloging units in the conterminous United States (Steeves and Nebert, 1994) following the approach of Krug and others (1987). The mean annual (1971–2000) R factor (rainfall erosivity) of the Universal Soil Loss Equation was based on a national 2.5-minute (about 4-km) resolution grid GIS coverage developed by Daly and Taylor (2002). The average altitude in the drainage basin was based on the USGS National Elevation Dataset (U.S. Geological Survey, 2003) gridded at the 100-m resolution. Baseflow, the component of streamflow that can be attributed to ground-water discharge into streams, was estimated for drainage basins from the national baseflow index 1-km resolution dataset developed by Wolock (2003b).
Soil characteristics included but were not limited to soil hydrologic groups, available water capacity, permeability, and the K factor (soil erodibility) of the Universal Soil Loss Equation, which were all based on State Soil Geographic (STATSGO) database (Natural Resources Conservation Service, 1994). The STATSGO database is organized by geographic soil map units based on the proportionate extent of the component soils and their properties [Soil Survey Geographic (SSURGO) Database, 2006]. Each map unit is associated with many tabular files of soil characteristics. Soil map units were gridded at 100-m resolution and overlaid with 30-m resolution basin boundaries to first determine the areal weights of solid characteristics by using soil map units for each drainage basin, followed by the computation of the weighted average value for each soil characteristic. Soil hydrologic groups were extracted from an enhanced version of STATSGO (Barbara C. Ruddy and William A. Battaglin, U.S. Geological Survey, written commun., 1998), in which missing soil hydrologic group values were populated based on soil characteristics described by Foth and Schafer (1980). Many of the remaining STATSGO soil parameters in this study were compiled by Wolock (1997); soil parameters not included in Wolock (1997) were assembled using the same methods (David M. Wolock, U.S. Geological Survey, written commun., 2004). The mean K factor was estimated for the uppermost soil horizon.
Riparian zone characteristics were determined at both the reach and segment scales based on the site locations in GIS. Protocols used for this work are described in Johnson and Zelt (2005). The riparian area was characterized using several different fixed-width buffer zones along the stream segment. At the segment scale, four specific buffer zones were delimited on the basis of respective buffer distances from the stream centerline—50, 100, 150, and 250 m. The relative extent of various categories of land use and land cover (LULC) in each buffer zone was estimated by delimiting and classifying polygons of contrasting LULC on aerial digital orthophotographic quadrangles (DOQ) on the basis of standard methods for photograph interpretation (U.S. Fish and Wildlife Service, 1995). LULC data, primarily woody vegetation, were used in evaluating nutrient-enrichment conditions at the segment and reach scales for a subset of the NAWQA major river basins.
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