Stream flow is a controlling element in the ecology of rivers and streams. Knowledge of the natural flow regime facilitates the assessment of whether specific hydrologic attributes have been altered by humans in a particular stream and the establishment of specific goals for stream‐flow restoration. Because most streams are ungaged or have been altered by human influences, characterizing the natural flow regime is often only possible by estimating flow characteristics based on nearby stream gages of reference quality, i.e., gaged locations that are least disturbed by human influences. The ability to evaluate natural stream flow, that which is not altered by human activities, would be enhanced by the existence of a nationally consistent and up‐to‐date database of gages in relatively undisturbed watersheds. As part of a national effort to characterize stream‐flow effects on ecological condition, data for 6785 U.S. Geological Survey (USGS) stream gages and their upstream watersheds were compiled. The sites comprise all USGS stream gages in the conterminous United States with at least 20 years of complete‐year flow record from 1950–2007, and for which watershed boundaries could reliably be delineated (median size = 578 km2). Several hundred watershed and site characteristics were calculated or compiled from national data sources, including environmental features (e.g., climate, geology, soils, topography) and anthropogenic influences (e.g., land use, roads, presence of dams, or canals). In addition, watersheds were assessed for their reference quality within nine broad regions for use in studies intended to characterize stream flows under conditions minimally influenced by human activities. Three primary criteria were used to assess reference quality: (1) a quantitative index of anthropogenic modification within the watershed based on GIS‐derived variables, (2) visual inspection of every stream gage and drainage basin from recent high‐resolution imagery and topographic maps, and (3) information about man‐made influences from USGS Annual Water Data Reports. From the set of 6785 sites, we identified 1512 as reference‐quality stream gages. All data derived for these watersheds as well as the reference condition evaluation are provided as an online data set termed GAGES (geospatial attributes of gages for evaluating stream flow).

The development of field sampling designs that employ multiple reference and polluted sites has been proposed as an alternative to the traditional upstream vs. downstream approach used in most biomonitoring studies. Spatially extensive monitoring programs can characterize ecological conditions within an ecoregion and provide the necessary background information to evaluate future changes in water quality. We measured physicochemical characteristics, heavy‐metal concentrations, and benthic macroinvertebrate community structure at 95 sites in the Southern Rocky Mountain ecoregion in Colorado, USA. Most sites (82%) were selected using a systematic, randomized sampling design. Each site was placed into one of four metal categories (background, low, medium, and high metals), based on the cumulative criterion unit (CCU), which we defined as the ratio of the instream metal concentration to the U.S. Environmental Protection Agency criterion concentration, summed for all metals measured. A CCU of 1.0 represents a conservative estimate of the total metal concentration that, when exceeded, is likely to cause harm to aquatic organisms. Although the CCU was less than 2.0 at most (66.3%) of the sites, values exceeded 10.0 at 13 highly polluted stations. Differences among metal categories were highly significant for most measures of macroinvertebrate abundance and all measures of species richness. We observed the greatest effects on several species of heptageniid mayflies (Ephemeroptera: Heptageniidae), which were highly sensitive to heavy metals and were reduced by >75% at moderately polluted stations. The influence of taxonomic aggregation on responses to metals was also greatest for mayflies. In general, total abundance of mayflies and abundance of heptageniids were better indicators of metal pollution than abundance of dominant mayfly taxa. We used stepwise multiple‐regression analyses to investigate the relationship between benthic community measures and physicochemical characteristics at the 78 randomly selected sites. Heavy‐metal concentration was the most important predictor of benthic community structure at these sites. Because of the ubiquitous distribution of heavy‐metal pollution in the Southern Rocky Mountain ecoregion, we conclude that potential effects of heavy metals should be considered when investigating large‐scale spatial patterns of benthic macroinvertebrate communities in Colorado's mountain streams.

Human impacts on watershed hydrology are widespread in the US, but the prevalence and severity of stream‐flow alteration and its potential ecological consequences have not been quantified on a national scale. We assessed streamflow alteration at 2888 streamflow monitoring sites throughout the conterminous US. The magnitudes of mean annual (1980–2007) minimum and maximum streamflows were found to have been altered in 86% of assessed streams. The occurrence, type, and severity of streamflow alteration differed markedly between arid and wet climates. Biological assessments conducted on a subset of these streams showed that, relative to eight chemical and physical covariates, diminished flow magnitudes were the primary predictors of biological integrity for fish and macroinvertebrate communities. In addition, the likelihood of biological impairment doubled with increasing severity of diminished streamflows. Among streams with diminished flow magnitudes, increasingly common fish and macroinvertebrate taxa possessed traits characteristic of lake or pond habitats, including a preference for fine‐grained substrates and slow‐moving currents, as well as the ability to temporarily leave the aquatic environment.

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Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national-and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites.