Monthly mean air temperature (AT) at 85 sites and instantaneous stream-water temperature (WT) at 129 sites for 1960-2010 are examined for the mid-Atlantic region, USA. Temperature anomalies for two periods, 1961-1985 and 1985-2010, relative to the climate normal period of 1971-2000, indicate that the latter period was statistically significantly warmer than the former for both mean AT and WT. Statistically significant temporal trends across the region of 0.023°C per year for AT and 0.028°C per year for WT are detected using simple linear regression. Sensitivity analyses show that the irregularly sampled WT data are appropriate for trend analyses, resulting in conservative estimates of trend magnitude. Relations between 190 landscape factors and significant trends in AT-WT relations are examined using principal components analysis. Measures of major dams and deciduous forest are correlated with WT increasing slower than AT, whereas agriculture in the absence of major dams is correlated with WT increasing faster than AT. Increasing WT trends are detected despite increasing trends in streamflow in the northern part of the study area. Continued warming of contributing streams to Chesapeake Bay likely will result in shifts in distributions of aquatic biota and contribute to worsened eutrophic conditions in the bay and its estuaries.
For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.Suggested citation: Jastram, J.D., 2014, Streamflow, water quality, and aquatic macroinvertebrates of selected streams in Fairfax County, Virginia, 2007-12 AbstractEfforts to mitigate the effects of urbanization on streams rely on best management practices (BMPs) that are implemented with the intent of reducing and retaining stormwater runoff. A cooperative monitoring effort between the U.S. Geological Survey and Fairfax County, Virginia was initiated in 2007 to assess the condition of county streams and document watershed-scale responses to the implementation of BMPs. Assessment of the data collected during the first 5 years of this monitoring program focused on characterizing the hydrologic and ecological condition of 14 monitored streams.Hydrologic, chemical, and macroinvertebrate community conditions in the streams monitored were found to be consistent, overall, with conditions commonly observed in urban streams. Hydrologically, the monitored streams were found to be flashy, with flashiness positively related to road cover in the watershed. Typical pH values of streams throughout the network centered around neutrality (pH = 7) with strong daily fluctuations apparent in the continuous data. Patterns in specific conductance were largely representative of anthropogenic disturbances-watersheds having the greatest percentage of open space and estate residential land-use had the lowest typical specific conductance values, and specific conductance variability was less than what is observed in watersheds that are more intensively developed. In watersheds having greater road coverage, and more development in general, increases in specific conductance over several orders of magnitude were observed during winter months as a result of the application of de-icing salts on impervious surfaces. Dissolved oxygen conditions were typically within the range required to support healthy biological communities, although occasional departures during summer months at some sites fell below the impairment threshold for streams in Virginia.Nitrogen (N) and phosphorus (P), concentration patterns were largely consistent across the network, with few exceptions. Nitrogen concentrations in monthly samples were generally low and dominated by nitrate. Exceptions to the generally low N concentra...
Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.
whose comments greatly improved the clarity and continuity of the report.
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