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Steven G. Paulsen

Publications and source records attributed to Steven G. Paulsen.

3 recordsLinked to original sources

Quantifying form resistance is essential for estimating summer low and bankfull flow from stream survey channel morphology

Reliable estimates of low flow and flood discharge at ungaged locations are required for evaluating stream flow alteration, designing culverts and stream crossings, and interpreting regional surveys of habitat and biotic condition. Very few stream gaging stations are located on small, remote streams, which typically have complex channel morphology. Adequate gaging is also lacking on larger streams that are remote, smaller than those typically gaged, or have channel morphology not conducive to installation of gages. Complex channels typically contain large scale hydraulic roughness elements that dominate flow patterns (i.e., form roughness), making it difficult to measure channel cross-section area and water velocity, or to measure channel volume even where discharge is known. In channels with large channel form roughness, it is equally difficult to estimate discharge using commonly applied equations based on slope and channel dimensions or basin area. We employed a novel approach that explicitly accounts for hydraulic resistance from large wood and riffle-pool morphology (form roughness) in calculating low flow and bankfull discharge from stream and river physical habitat data collected from 4229 stream and river sites in the conterminous US (CONUS) sampled in 2008–9 and 2013–14 as part of the US Environmental Protection Agency's N ational R ivers and S treams A ssessment (NRSA). Hydraulic resistance derived from form roughness clearly dominated resistance derived from bed particles (particle resistance) during summer low flows in wadeable streams across the spectrum of channel slopes and substrate sizes smaller than boulders. Under bankfull conditions, the influence of form resistance relative to particle resistance was diminished, but form resistance still dominated except in large low gradient rivers lacking complex channels, and in streams or rivers with boulder-size bed particles. We validated our hydraulic resistance estimates by comparing measured discharges with calculated discharges that used those hydraulic resistance estimates along with measured NRSA channel morphology data. Morphology-based summer discharge (low flow) estimates and direct field measurements of discharge in 2333 wadeable CONUS streams showed reasonable agreement (median difference < 2.5×) for discharges ranging from 3.6 × 10 −5 to 123 m 3 /s and drainage areas of 0.12 to 171,000 km 2 . In a subset of 759 of NRSA's larger wadeable stream and non-wadeable river sites where nearby U.S. Geological Survey (USGS) gage data were available and adequate, our morphology-based summer discharge estimates agreed fairly well (median difference < 2.0×) with USGS 20-yr average August mean flows ranging from 0.003 to 16,000 m 3 /s. Similarly, morphology-based estimates of bankfull flow ranging from 0.3 to 100,000 m 3 /s agreed reasonably well with the 1.5-yr recurrence interval flood in these gaged sites (median deviation <2.2×). These findings demonstrate the importance of quantifying flow resistance from large-scale form roughness features in natural channels and provide a novel approach for estimating discharge from widely available survey data. This will allow examination of discharge and its ecological influence across the full range of stream and river sizes sampled by NRSA or other synoptic surveys where comprehensive measures of biota, physical habitat, and chemistry are also made. Although these morphology-based estimates exhibit some variability, they are adequate for examining regional patterns in discharge and flow alteration and their association with instream biota and anthropogenic disturbances, providing summer low and bankfull flow information where reliable estimates are lacking.

Geomorphology

Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment

Patterns of nitrogen (N) concentrations in streams sampled by the National Rivers and Streams Assessment (NRSA) were examined semiquantitatively to identify regional differences in stream N levels. The data were categorized and analyzed by watershed size classes to reveal patterns of the concentrations that are consistent with the spatial homogeneity in natural and anthropogenic characteristics associated with regional differences in N levels. Ecoregions and mapped information on human activities including agricultural practices were used to determine the resultant regions. Marked differences in N levels were found among the nine aggregations of ecoregions used to report the results of the NRSA. We identified distinct regional patterns of stream N concentrations within the reporting regions that are associated with the characteristics of specific Level III ecoregions, groups of Level III ecoregions, groups of Level IV ecoregions, certain geographic characteristics within ecoregions, and/or particular watershed size classes. We described each of these regions and illustrated their areal extent and median and range in N concentrations. Understanding the spatial variability of nutrient concentrations in flowing waters and the apparent contributions that human and nonhuman factors have on different sizes of streams and rivers is critical to the development of effective water quality assessment and management plans. This semi-quantitative analysis is also intended to identify areas within which more detailed quantitative work can be conducted to determine specific regional factors associated with variations in stream N concentrations.

Journal of Soil and Water Conservation

Design tradeoffs for trend assessment in aquatic biological monitoring programs

Assessments of long-term (multiyear) temporal trends in biological monitoring programs are generally undertaken without an adequate understanding of the temporal variability of biological communities. When the sources and levels of variability are unknown, managers cannot make informed choices in sampling design to achieve monitoring goals in a cost-effective manner. We evaluated different trend sampling designs by estimating components of both short- and long-term variability in biological indicators of water quality in streams. Invertebrate samples were collected from 32 sites—9 urban, 6 agricultural, and 17 relatively undisturbed (reference) streams—distributed throughout the United States. Between 5 and 12 yearly samples were collected at each site during the period 1993–2008, plus 2 samples within a 10-week index period during either 2007 or 2008. These data allowed calculation of four sources of variance for invertebrate indicators: among sites, among years within sites, interaction among sites and years (site-specific annual variation), and among samples collected within an index period at a site (residual). When estimates of these variance components are known, changes to sampling design can be made to improve trend detection. Design modifications that result in the ability to detect the smallest trend with the fewest samples are, from most to least effective: (1) increasing the number of years in the sampling period (duration of the monitoring program), (2) decreasing the interval between samples, and (3) increasing the number of repeat-visit samples per year (within an index period). This order of improvement in trend detection, which achieves the greatest gain for the fewest samples, is the same whether trends are assessed at an individual site or an average trend of multiple sites. In multiple-site surveys, increasing the number of sites has an effect similar to that of decreasing the sampling interval; the benefit of adding sites is greater when a new set of different sites is selected for each sampling effort than when the same sites are sampled each time. Understanding variance components of the ecological attributes of interest can lead to more cost-effective monitoring designs to detect trends.

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