Geology topics

Kenneth Hyer

Publications and source records attributed to Kenneth Hyer.

At least 19 recordsLinked to original sources

USGS2025

Using monitoring and partnerships to provide management-relevant information about Chesapeake Bay rivers

The lands and waters of the Chesapeake Bay watershed provide more than $100 billion in economic benefits—an amount that is expected to increase by achieving the region’s clean-water goals. Achieving those goals requires accurate and timely information about the health of the watershed’s rivers and streams. The Chesapeake Bay nontidal monitoring network (NTN), a partnership of local, state, and federal agencies, as well as other partners, was established in 2004 to provide this information. The U.S. Geological Survey analyzes data collected from NTN stations to provide monitoring-based information about the amount of nitrogen, phosphorus, and sediment entering the Chesapeake Bay through its nontidal rivers. Thus, data collected from the NTN inform watershed management by providing decision makers with information on which to base their restoration and conservation actions.

Chesapeake Bay watershed↗

USGS2024

Invasive blue catfish in the Chesapeake Bay: A risk to realizing Bay restoration investments

Introduction The partners of the Chesapeake Bay are investing billions of dollars in the restoration of critical habitats to improve conditions for people and living resources throughout the Bay and its watershed. However, the recent proliferation of invasive Ictalurus furcatus (blue catfish) in the Chesapeake Bay’s major rivers has the potential to disrupt these restoration efforts and limit the full potential improvement of the ecosystem. The U.S. Geological Survey can help respond to this management challenge in the Nation’s largest estuary by leveraging its leadership and technical capabilities to work with resource managers, academics, and other stakeholders.

Chesapeake Bay↗

USGS2024

Connecting conservation practices to local stream health in the Chesapeake Bay watershed

The Chesapeake Bay Partnership is implementing conservation practices (CPs) throughout the Chesapeake Bay watershed to reduce nutrient and sediment delivery to the Bay. This study intends to provide an integrated and detailed understanding of how local streams respond to these CP-driven management efforts. Key issue: To what extent do CPs positively affect the health of local streams in the nontidal watershed (cobenefits)? Critical unknown: How do CPs change water quality and the stressors that affect stream aquatic life? Which CPs improve stream health more effectively? Critical knowledge to be delivered to stakeholders includes— the effects of CPs on local water-quality conditions, the degree to which these same CPs also provide local stream-ecosystem benefits, and a deeper understanding of local stream-ecosystems, including stressors and CPs, to guide the selection of management efforts that enhance both water quality and overall stream-ecosystem health.

Chesapeake Bay watershed↗

USGS2023

Your land, your water—Using research to guide conservation practices on local farms in the Chesapeake Bay watershed

Agricultural lands are an important part of the economy and heritage of the Chesapeake Bay watershed and are a focus of conservation activities. Streams and rivers around farms provide communities with drinking water and recreational opportunities, but these local benefits can be impaired by elevated nutrient and sediment concentrations. Compared to inputs from the atmosphere, wastewater, and urban and suburban areas, agricultural lands are the largest source of nutrients and sediment in many Chesapeake Bay streams. Farmers are voluntary conservation partners and have an important role in improving water-quality conditions. This fact sheet summarizes recent scientific insights from the U.S. Geological Survey (USGS) that can help farmers use conservation practices and their knowledge of local site conditions to achieve cleaner water.

Chesapeake Bay watershed↗

USGS2021

USGS Chesapeake Science Strategy 2021-2025

The Chesapeake Bay ecosystem is a national treasure that provides almost $100 billion annually of goods and services. The Chesapeake Bay Program (CBP), is one of the largest federal-state restoration partnerships in the United States and is underpinned by rigorous science. The U.S. Geological Survey (USGS) has a pivotal role as a science provider for assessing ecosystem condition and response in the Chesapeake watershed. Despite significant CBP accomplishments, the pressures of climate change and competing demands on land use and change require an acceleration of progress towards the 10 goals in the Chesapeake Bay Watershed Agreement. USGS Chesapeake studies are increasing efforts to provide integrated science and are engaging stakeholders to inform the multi-faceted restoration and conservation decisions to improve habitat for fish and waterfowl, and socio-economic benefits to the 18 million people living in the watershed.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2021

Nutrient trends and drivers in the Chesapeake Bay Watershed

The Chesapeake Bay Program maintains an extensive nontidal monitoring network, measuring nitrogen and phosphorus (nutrients) at more than 100 locations on rivers and streams in the watershed. Data from these locations are used by United States Geological Survey to assess the ecosystem’s response to nutrient-reduction efforts. This fact sheet summarizes recent trends in nitrogen and phosphorus in nontidal tributaries and identifies some of the complex factors that affect local water quality, and ultimately, the Chesapeake Bay.

Delaware, Maryland, New Jersey, New York, Pennsylv↗

USGS2017

U.S. Geological Survey Science—Improving the value of the Chesapeake Bay watershed

Introduction Congress directed the Federal Government to work with States to restore the Nation’s largest estuary. Chesapeake Bay restoration provides important economic and ecological benefits: 18 million people live and work in the Bay watershed and enjoy its benefits. 3,600 types of fish, wildlife, and plants underpin the economic value of the Bay ecosystem. Poor water quality and habitat loss threaten restoration and negatively impact the economy. 10 Goals to meet by 2025 through the Chesapeake Bay Program, a voluntary partnership.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2015

U.S. Geological Survey Chesapeake science strategy, 2015-2025—Informing ecosystem management of America’s largest estuary

Executive Summary The U.S. Geological Survey (USGS) has the critical role of providing scientific information to improve the understanding and management of the Chesapeake Bay ecosystem. The USGS works with Federal, State, and academic science partners to provide research and monitoring, and communicate results of these activities to enhance ecosystem management for both the Chesapeake and other National ecosystems. The USGS Chesapeake Science Strategy was prepared to guide science activities to address the Chesapeake Bay Watershed Agreement (2014–2025), to support the Department of the Interior (DOI) involvement in the Bay restoration efforts, and align with the USGS Mission Area (MA) Science strategies. The Chesapeake Bay is our Nation’s largest estuary, and provides critical goods and services to the people, fish, and wildlife that use the 64,000-square-mile watershed. The Chesapeake Bay watershed contains over 3,600 species of fish, wildlife, and plants and provides spawning grounds for many ecologically and economically important species including striped bass and blue crabs. The Bay watershed lies in the heart of the Atlantic Flyway and has 29 species of waterfowl, about 1 million of which winter in the region. The size of the Chesapeake seafood harvest is third in the Nation, only behind the Atlantic and Pacific Oceans. Along with agricultural production, tourism, and recreation, the estimated economic value of the services from the Chesapeake Bay watershed is about $100 billion annually. However, the health of the Bay ecosystem began to decline at the beginning of the 20th century due to overfishing and increasing human population and associated land change. The Chesapeake Bay Program (CBP) is the Federal-State cooperative effort that started in 1983 to restore the Bay and watershed. Given the ecological and economic importance of the Chesapeake ecosystem, President Obama issued an Executive Order (EO) in 2009 for increased Federal leadership in the CBP to enhance the pace of restoration, and the supporting strategy was released in 2010. The EO directed the Federal Government, including the U.S. Department of the Interior (DOI), represented by the National Park Service (NPS), the U.S. Fish & Wildlife Service (FWS), and the USGS, to expand its efforts and increase leadership to restore the Bay and its watershed. The USGS and other Federal agencies expanded their activities in 2011 to meet the President’s Chesapeake EO. Since the EO was released, there have been several important changes in the USGS, DOI, and the CBP including: (1) the Chesapeake Bay Watershed Agreement, (2) increased DOI leadership in the CBP, and (3) the release of the USGS MA science strategies. The EO strategy served as a foundation for the Chesapeake Bay Watershed Agreement that was signed in 2014 by the CBP Partners, and has goals and outcomes to be met by 2025. The USGS developed the Chesapeake Science Strategy to guide our activities to address the Chesapeake Bay Watershed Agreement, DOI leadership in the CBP, and USGS MA strategies. Improving the understanding of fish and wildlife population and health, and the factors affecting their condition is the emphasis of the Strategy. The science focuses on documenting the critical ecosystem connections in the Chesapeake, and providing implications to enhance decision making for restoration and conservation activities. The revised Strategy has four themes that address 7 of the 10 goals in the Chesapeake Bay Watershed Agreement: Enhance science to support restoration, and conservation of fish, wildlife, and critical habitats. Characterize and explain changes in water quality, and its effect on freshwater and estuarine ecosystems. Assess and forecast effects of climate and land change on ecosystem conditions. Synthesize and provide information to support ecosystem management. The structure and function of biological communities of the Bay and its watershed are extremely complex and are affected by a variety of stressors and conditions. To better define the issues being addressed, the USGS has developed cross-cutting questions that define some of the most important scientific challenges where multiple disciplines and collaborators are needed to address an issue. The initial questions include: How do land and climate changes affect freshwater fish communities, health, and habitats? What are the relations among land use, water quality, contaminants, and the health of fish and wildlife? How are coastal wetlands and their carrying capacity for waterbirds affected by changing climate and land use? How is the water quality of rivers and estuaries responding to restoration actions, and changing land use? What are some of the best opportunities for management actions to benefit multiple restoration outcomes?

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2015

Fluvial geomorphology and suspended-sediment transport during construction of the Roanoke River Flood Reduction Project in Roanoke, Virginia, 2005–2012

Beginning in 2005, after decades of planning, the U.S. Army Corps of Engineers (USACE) undertook a major construction effort to reduce the effects of flooding on the city of Roanoke, Virginia—the Roanoke River Flood Reduction Project (RRFRP). Prompted by concerns about the potential for RRFRP construction-induced geomorphological instability and sediment liberation and the detrimental effects these responses could have on the endangered Roanoke logperch ( Percina rex ), the U.S. Geological Survey (USGS) partnered with the USACE to provide a real-time warning network and a long-term monitoring program to evaluate geomorphological change and sediment transport in the affected river reach. Geomorphological change and suspended-sediment transport are highly interdependent and cumulatively provide a detailed understanding of the sedimentary response, or lack thereof, of the Roanoke River to construction of the RRFRP. Bed-sediment composition was usually finer in post-construction than pre-construction measurements, yet the annual changes in composition were not significantly different; thus, there was minimal evidence that RRFRP construction practices alone induced fining of bed materials. Cross-sectional surveys revealed variability in bankfull and base-flow channel geometry metrics, but no significant differences in this variability were detected between pre- and post-construction measurements, excluding designed alterations in channel geometry. A lack of channel-forming streamflow events, however, limited the ability to fully characterize the stability of the constructed channel and floodplain features, as bankfull flow events occurred only 2 of the 8 years of study. Therefore, additional channel surveys may be needed in the future, once sufficient channel-forming events have occurred, to fully assess stability. Relations between turbidity and suspended sediment were statistically indistinguishable between the upstream and downstream limits of the RRFRP construction reach. These relations did not change over time, indicating no significant changes in suspended-sediment composition or source in the construction reach during the period of study. Results of the geomorphological and suspended-sediment monitoring components were largely in agreement and consistent with those of a related effort that monitored the logperch population before and during construction. These findings suggest that construction and sediment-control practices sufficiently protected in-stream habitat and the organisms that inhabit those locations, namely the Roanoke logperch, during the period monitored.

Virginia↗

USGS2015

Evaluation and application of regional turbidity-sediment regression models in Virginia

Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications could greatly expand the usage of these methods. Suspended sediment load estimation could occur as soon as flow and turbidity monitoring commence at a site, suspended sediment sampling frequencies for various projects potentially could be reduced, and special-project applications (sediment monitoring following dam removal, for example) could be significantly enhanced. The objective of this effort was to investigate the turbidity-suspended sediment concentration (SSC) relations at all available USGS monitoring sites within Virginia to determine whether meaningful turbidity-sediment regression models can be developed by combining the data from multiple monitoring stations into a single model, known as a “regional” model. Following the development of the regional model, additional objectives included a comparison of predicted SSCs between the regional model and commonly used site-specific models, as well as an evaluation of why specific monitoring stations did not fit the regional model.

Virginia↗

USGS2013

Total nutrient and sediment loads, trends, yields, and nontidal water-quality indicators for selected nontidal stations, Chesapeake Bay Watershed, 1985–2011

The U.S. Geological Survey, in cooperation with Chesapeake Bay Program (CBP) partners, routinely reports long-term concentration trends and monthly and annual constituent loads for stream water-quality monitoring stations across the Chesapeake Bay watershed. This report documents flow-adjusted trends in sediment and total nitrogen and phosphorus concentrations for 31 stations in the years 1985–2011 and for 32 stations in the years 2002–2011. Sediment and total nitrogen and phosphorus yields for 65 stations are presented for the years 2006–2011. A combined nontidal water-quality indicator (based on both trends and yields) indicates there are more stations classified as “improving water-quality trend and a low yield” than “degrading water-quality trend and a high yield” for total nitrogen. The same type of 2-way classification for total phosphorus and sediment results in equal numbers of stations in each indicator class.

Delaware, Maryland, New York, Pennsylvania, West V↗

USGS2012

Nutrient and suspended-sediment trends, loads, and yields and development of an indicator of streamwater quality at nontidal sites in the Chesapeake Bay watershed, 1985-2010

The U.S. Geological Survey (USGS) updates information on loads of, and trends in, nutrients and sediment annually to help the Chesapeake Bay Program (CBP) investigators assess progress toward improving water-quality conditions in the Chesapeake Bay and its watershed. CBP scientists and managers have worked since 1983 to improve water quality in the bay. In 2010, the U.S. Environmental Protection Agency (USEPA) established a Total Maximum Daily Load (TMDL) for the Chesapeake Bay. The TMDL specifies nutrient and sediment load allocations that need to be achieved in the watershed to improve dissolved oxygen, water-clarity, and chlorophyll conditions in the bay. The USEPA, USGS, and state and local jurisdictions in the watershed operate a CBP nontidal water-quality monitoring network and associated database that are used to update load and trend information to help assess progress toward reducing nutrient and sediment inputs to the bay. Data collected from the CBP nontidal network were used to estimate loads and trends for two time periods: a long-term period (1985-2010) at 31 "primary" sites (with storm sampling) and a 10-year period (2001-10) at 33 primary sites and 16 "secondary" sites (without storm sampling). In addition, loads at 64 primary sites were estimated for the period 2006 to 2010. Results indicate improving flow-adjusted trends for nitrogen and phosphorus for 1985 to 2010 at most of the sites in the network. For nitrogen, 21 of the 31 sites showed downward (improving) trends, whereas 2 sites showed upward (degrading) trends, and 8 sites showed no trends. The results for phosphorus were similar: 22 sites showed improving trends, 4 sites showed degrading trends, and 5 sites indicated no trends. For sediment, no trend was found at 40 percent of the sites, with 10 sites showing improving trends and 8 sites showing degrading trends. The USGS, working with CBP partners, developed a new water-quality indicator that combines the results of the 10-year trend analysis with results from a greater number of sites (64 primary sites) where loads and yields of total nitrogen and phosphorus and sediment could be calculated. The new indicator shows fewer significant trends for the 10-year time period than for the long-term time period (1985-2010). For 2001-10, total nitrogen trends were downward (improving) at 14 sites and upward (degrading) at 2 sites; no trend was found at 17 sites. For total phosphorus, 12 sites showed improving trends, 4 sites showed degrading trends, and 17 sites showed no trend. For total sediment, most sites (21) did not exhibit a significant trend; 3 sites showed improving trends, and 10 sites showed degrading trends. Few significant trends were seen at the 16 secondary sites: improving trends for total nitrogen at 4 sites, improving trends for total phosphorus at 2 sites, and a degrading trend for sediment at 1 site. Total streamflow to the Chesapeake Bay was 20 percent higher in 2010 than in 2009 and is considered to be within the normal range of flow, whereas annual streamflow at 28 sites was greater in 2010 than in 2009. No trends in daily streamflow were detected at the 31 long-term sites. Combined loads for the farthest downstream nontidal monitoring sites (called "River Input Monitoring sites") increased 33 percent for total nitrogen, 120 percent for total phosphorus, and 330 percent for total sediment from 2009 to 2010. The large increase in phosphorus and sediment loads in 2010 was caused in large part by two large storm events that occurred during the spring in the Potomac River Basin. Yields (load per watershed area) of total nitrogen in the Chesapeake Bay watershed decreased from north to south (New York to Virginia). No spatial patterns were discernible for total phosphorus or sediment.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2012

Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed

Nutrient and sediment fluxes and changes in fluxes over time are key indicators that water resource managers can use to assess the progress being made in improving the structure and function of the Chesapeake Bay ecosystem. The U.S. Geological Survey collects annual nutrient (nitrogen and phosphorus) and sediment flux data and computes trends that describe the extent to which water-quality conditions are changing within the major Chesapeake Bay tributaries. Two regression-based approaches were compared for estimating annual nutrient and sediment fluxes and for characterizing how these annual fluxes are changing over time. The two regression models compared are the traditionally used ESTIMATOR and the newly developed Weighted Regression on Time, Discharge, and Season (WRTDS). The model comparison focused on answering three questions: (1) What are the differences between the functional form and construction of each model? (2) Which model produces estimates of flux with the greatest accuracy and least amount of bias? (3) How different would the historical estimates of annual flux be if WRTDS had been used instead of ESTIMATOR? One additional point of comparison between the two models is how each model determines trends in annual flux once the year-to-year variations in discharge have been determined. All comparisons were made using total nitrogen, nitrate, total phosphorus, orthophosphorus, and suspended-sediment concentration data collected at the nine U.S. Geological Survey River Input Monitoring stations located on the Susquehanna, Potomac, James, Rappahannock, Appomattox, Pamunkey, Mattaponi, Patuxent, and Choptank Rivers in the Chesapeake Bay watershed. Two model characteristics that uniquely distinguish ESTIMATOR and WRTDS are the fundamental model form and the determination of model coefficients. ESTIMATOR and WRTDS both predict water-quality constituent concentration by developing a linear relation between the natural logarithm of observed constituent concentration and three explanatory variables—the natural log of discharge, time, and season. ESTIMATOR uses two additional explanatory variables—the square of the log of discharge and time-squared. Both models determine coefficients for variables for a series of estimation windows. ESTIMATOR establishes variable coefficients for a series of 9-year moving windows; all observed constituent concentration data within the 9-year window are used to establish each coefficient. Conversely, WRTDS establishes variable coefficients for each combination of discharge and time using only observed concentration data that are similar in time, season, and discharge to the day being estimated. As a result of these distinguishing characteristics, ESTIMATOR reproduces concentration-discharge relations that are closely approximated by a quadratic or linear function with respect to both the log of discharge and time. Conversely, the linear model form of WRTDS coupled with extensive model windowing for each combination of discharge and time allows WRTDS to reproduce observed concentration-discharge relations that are more sinuous in form. Another distinction between ESTIMATOR and WRTDS is the reporting of uncertainty associated with the model estimates of flux and trend. ESTIMATOR quantifies the standard error of prediction associated with the determination of flux and trends. The standard error of prediction enables the determination of the 95-percent confidence intervals for flux and trend as well as the ability to test whether the reported trend is significantly different from zero (where zero equals no trend). Conversely, WRTDS is unable to propagate error through the many (over 5,000) models for unique combinations of flow and time to determine a total standard error. As a result, WRTDS flux estimates are not reported with confidence intervals and a level of significance is not determined for flow-normalized fluxes. The differences between ESTIMATOR and WRTDS, with regard to model form and determination of model coefficients, have an influence on the determination of nutrient and sediment fluxes and associated changes in flux over time as a result of management activities. The comparison between the model estimates of flux and trend was made for combinations of five water-quality constituents at nine River Input Monitoring stations. The major findings with regard to nutrient and sediment fluxes are as follows: (1)WRTDS produced estimates of flux for all combinations that were more accurate, based on reduction in root mean squared error, than flux estimates from ESTIMATOR; (2) for 67 percent of the combinations, WRTDS and ESTIMATOR both produced estimates of flux that were minimally biased compared to observed fluxes(flux bias = tendency to over or underpredict flux observations); however, for 33 percent of the combinations, WRTDS produced estimates of flux that were considerably less biased (by at least 10 percent) than flux estimates from ESTIMATOR; (3) the average percent difference in annual fluxes generated by ESTIMATOR and WRTDS was less than 10 percent at 80 percent of the combinations; and (4) the greatest differences related to flux bias and annual fluxes all occurred for combinations where the pattern in observed concentration-discharge relation was sinuous (two points of inflection) rather than linear or quadratic (zero or one point of inflection). The major findings with regard to trends are as follows: (1) both models produce water-quality trends that have factored in the year-to-year variations in flow; (2) trends in water-quality condition are represented by ESTIMATOR as a trend in flow-adjusted concentration and by WRTDS as a flow normalized flux; (3) for 67 percent of the combinations with trend estimates, the WRTDS trends in flow-normalized flux are in the same direction and magnitude to the ESTIMATOR trends in flow-adjusted concentration, and at the remaining 33 percent the differences in trend magnitude and direction are related to fundamental differences between concentration and flux; and (4) the majority (85 percent) of the total nitrogen, nitrate, and orthophosphorus combinations exhibited long-term (1985 to 2010) trends in WRTDS flow-normalized flux that indicate improvement or reduction in associated flux and the majority (83 percent) of the total phosphorus (from 1985 to 2010) and suspended sediment (from 2001 to 2010) combinations exhibited trends in WRTDS flow-normalized flux that indicate degradation or increases in the flux delivered.

Delaware, Maryland, New York, Pennsylvania, Virgin↗

USGS2010

Increasing precision of turbidity-based suspended sediment concentration and load estimates

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.

Virginia↗

USGS2009

Continuous Turbidity Monitoring in the Indian Creek Watershed, Tazewell County, Virginia, 2006-08

Thousands of miles of natural gas pipelines are installed annually in the United States. These pipelines commonly cross streams, rivers, and other water bodies during pipeline construction. A major concern associated with pipelines crossing water bodies is increased sediment loading and the subsequent impact to the ecology of the aquatic system. Several studies have investigated the techniques used to install pipelines across surface-water bodies and their effect on downstream suspended-sediment concentrations. These studies frequently employ the evaluation of suspended-sediment or turbidity data that were collected using discrete sample-collection methods. No studies, however, have evaluated the utility of continuous turbidity monitoring for identifying real-time sediment input and providing a robust dataset for the evaluation of long-term changes in suspended-sediment concentration as it relates to a pipeline crossing. In 2006, the U.S. Geological Survey, in cooperation with East Tennessee Natural Gas and the U.S. Fish and Wildlife Service, began a study to monitor the effects of construction of the Jewell Ridge Lateral natural gas pipeline on turbidity conditions below pipeline crossings of Indian Creek and an unnamed tributary to Indian Creek, in Tazewell County, Virginia. The potential for increased sediment loading to Indian Creek is of major concern for watershed managers because Indian Creek is listed as one of Virginia's Threatened and Endangered Species Waters and contains critical habitat for two freshwater mussel species, purple bean (Villosa perpurpurea) and rough rabbitsfoot (Quadrula cylindrical strigillata). Additionally, Indian Creek contains the last known reproducing population of the tan riffleshell (Epioblasma florentina walkeri). Therefore, the objectives of the U.S. Geological Survey monitoring effort were to (1) develop a continuous turbidity monitoring network that attempted to measure real-time changes in suspended sediment (using turbidity as a surrogate) downstream from the pipeline crossings, and (2) provide continuous turbidity data that enable the development of a real-time turbidity-input warning system and assessment of long-term changes in turbidity conditions. Water-quality conditions were assessed using continuous water-quality monitors deployed upstream and downstream from the pipeline crossings in Indian Creek and the unnamed tributary. These paired upstream and downstream monitors were outfitted with turbidity, pH (for Indian Creek only), specific-conductance, and water-temperature sensors. Water-quality data were collected continuously (every 15 minutes) during three phases of the pipeline construction: pre-construction, during construction, and post-construction. Continuous turbidity data were evaluated at various time steps to determine whether the construction of the pipeline crossings had an effect on downstream suspended-sediment conditions in Indian Creek and the unnamed tributary. These continuous turbidity data were analyzed in real time with the aid of a turbidity-input warning system. A warning occurred when turbidity values downstream from the pipeline were 6 Formazin Nephelometric Units or 15 percent (depending on the observed range) greater than turbidity upstream from the pipeline crossing. Statistical analyses also were performed on monthly and phase-of-construction turbidity data to determine if the pipeline crossing served as a long-term source of sediment. Results of this intensive water-quality monitoring effort indicate that values of turbidity in Indian Creek increased significantly between the upstream and downstream water-quality monitors during the construction of the Jewell Ridge pipeline. The magnitude of the significant turbidity increase, however, was small (less than 2 Formazin Nephelometric Units). Patterns in the continuous turbidity data indicate that the actual pipeline crossing of Indian Creek had little influence of downstream water quality; co

Scientific Investigations Report↗

USGS2009

A Comparison of Turbidity-Based and Streamflow-Based Estimates of Suspended-Sediment Concentrations in Three Chesapeake Bay Tributaries

Fluvial transport of sediment into the Chesapeake Bay estuary is a persistent water-quality issue with major implications for the overall health of the bay ecosystem. Accurately and precisely estimating the suspended-sediment concentrations (SSC) and loads that are delivered to the bay, however, remains challenging. Although manual sampling of SSC produces an accurate series of point-in-time measurements, robust extrapolation to unmeasured periods (especially highflow periods) has proven to be difficult. Sediment concentrations typically have been estimated using regression relations between individual SSC values and associated streamflow values; however, suspended-sediment transport during storm events is extremely variable, and it is often difficult to relate a unique SSC to a given streamflow. With this limitation for estimating SSC, innovative approaches for generating detailed records of suspended-sediment transport are needed. One effective method for improved suspended-sediment determination involves the continuous monitoring of turbidity as a surrogate for SSC. Turbidity measurements are theoretically well correlated to SSC because turbidity represents a measure of water clarity that is directly influenced by suspended sediments; thus, turbidity-based estimation models typically are effective tools for generating SSC data. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program and Virginia Department of Environmental Quality, initiated continuous turbidity monitoring on three major tributaries of the bay - the James, Rappahannock, and North Fork Shenandoah Rivers - to evaluate the use of turbidity as a sediment surrogate in rivers that deliver sediment to the bay. Results of this surrogate approach were compared to the traditionally applied streamflow-based approach for estimating SSC. Additionally, evaluation and comparison of these two approaches were conducted for nutrient estimations. Results demonstrate that the application of turbidity-based estimation models provides an improved method for generating a continuous record of SSC, relative to the classical approach that uses streamflow as a surrogate for SSC. Turbidity-based estimates of SSC were found to be more accurate and precise than SSC estimates from streamflow-based approaches. The turbidity-based SSC estimation models explained 92 to 98 percent of the variability in SSC, while streamflow-based models explained 74 to 88 percent of the variability in SSC. Furthermore, the mean absolute error of turbidity-based SSC estimates was 50 to 87 percent less than the corresponding values from the streamflow-based models. Statistically significant differences were detected between the distributions of residual errors and estimates from the two approaches, indicating that the turbidity-based approach yields estimates of SSC with greater precision than the streamflow-based approach. Similar improvements were identified for turbidity-based estimates of total phosphorus, which is strongly related to turbidity because total phosphorus occurs predominantly in particulate form. Total nitrogen estimation models based on turbidity and streamflow generated estimates of similar quality, with the turbidity-based models providing slight improvements in the quality of estimations. This result is attributed to the understanding that nitrogen transport is dominated by dissolved forms that relate less directly to streamflow and turbidity. Improvements in concentration estimation resulted in improved estimates of load. Turbidity-based suspended-sediment loads estimated for the James River at Cartersville, VA, monitoring station exhibited tighter confidence interval bounds and a coefficient of variation of 12 percent, compared with a coefficient of variation of 38 percent for the streamflow-based load.

Scientific Investigations Report↗

USGS2007

Escherichia coli Concentrations in Recreational Streams and Backcountry Drinking-Water Supplies in Shenandoah National Park, Virginia, 2005-2006

Although fecal contamination of streams is a problem of national scope, few investigations have been directed at relatively pristine streams in forested basins in national parks. With approximately 1.8 million visitors annually, Shenandoah National Park in Virginia is subject to extensive recreational use. The effects of these visitors and their recreational activities on fecal indicator bacteria levels in the streams are poorly understood and of concern for Shenandoah National Park managers. During 2005 and 2006, streams and springs in Shenandoah National Park were sampled for Escherichia coli (E. coli) concentrations. The first study objective was to evaluate the effects of recreational activities on E. coli concentrations in selected streams. Of the 20 streams that were selected, 14 were in basins with extensive recreational activity, and 6 were in control basins where minimal recreational activities occurred. Water-quality sampling was conducted during low-flow conditions during the relatively warm months, as this is when outdoor recreation and bacterial survivorship are greatest. Although most sampling was conducted during low-flow conditions, approximately three stormflow samples were collected from each stream. The second study objective was to evaluate E. coli levels in backcountry drinking-water supplies throughout Shenandoah National Park. Nineteen drinking-water supplies (springs and streams) were sampled two to six times each by Shenandoah National Park staff and analyzed by the U.S. Geological Survey for this purpose. The water-quality sampling results indicated relatively low E. coli concentrations during low-flow conditions, and no statistically significant increase in E. coli concentrations was observed in the recreational streams relative to the control streams. These results indicate that during low-flow conditions, recreational activities had no significant effect on E. coli concentrations. During stormflow conditions, E. coli concentrations increased by nearly a factor of 10 in both basin types, and the Virginia instantaneous water-quality standard for E. coli (235 colonies per 100 milliliters) frequently was exceeded. The sampling results from drinking-water supplies throughout Shenandoah National Park indicated relatively low E. coli concentrations in all springs that were sampled. Several of the streams that were sampled had slightly higher E. coli concentrations relative to the springs, but no E. coli concentrations exceeded the instantaneous water-quality standard. Although E. coli concentrations in all the drinking-water supplies were relatively low, Shenandoah National Park management continues to stress that all hikers must treat drinking water from all streams and springs prior to consumption. After determining that recreational activities in Shenandoah National Park did not have a statistically significant effect on low-flow E. coli concentrations, an additional concern was addressed regarding the quality of the water releases from the wastewater-treatment plants in the park. Sampling of three wastewater-treatment plant outfalls was conducted in 2006 to evaluate their effects on water quality. Samples were analyzed for E. coli and a collection of wastewater organic compounds that may be endocrine disruptors. Relatively elevated E. coli concentrations were observed in 2 of the 3 samples, and between 9 and 13 wastewater organic compounds were detected in the samples, including 3 known and 5 suspected endocrine-disrupting compounds.

Scientific Investigations Report↗

USGS2003

Patterns and sources of fecal coliform bacteria in three streams in Virginia, 1999-2000

Surface-water impairment by fecal coliform bacteria is a water-quality issue of national scope and importance. In Virginia, more than 175 stream segments are on the Commonwealth's 1998 303(d) list of impaired waters because of elevated concentrations of fecal coliform bacteria. These fecal coliform-impaired stream segments require the development of total maximum daily load (TMDL) and associated implementation plans, but accurate information on the sources contributing these bacteria usually is lacking. The development of defendable fecal coliform TMDLs and management plans can benefit from reliable information on the bacteria sources that are responsible for the impairment. Bacterial source tracking (BST) recently has emerged as a powerful tool for identifying the sources of fecal coliform bacteria that impair surface waters. In a demonstration of BST technology, three watersheds on Virginia's 1998 303(d) list with diverse land-use practices (and potentially diverse bacteria sources) were studied. Accotink Creek is dominated by urban land uses, Christians Creek by agricultural land uses, and Blacks Run is affected by both urban and agricultural land uses. During the 20-month field study (March 1999?October 2000), water samples were collected from each stream during a range of flow conditions and seasons. For each sample, specific conductance, dissolved oxygen concentration, pH, turbidity, flow, and water temperature were measured. Fecal coliform concentrations of each water sample were determined using the membrane filtration technique. Next, Escherichia coli (E. coli) were isolated from the fecal coliform bacteria and their sources were identified using ribotyping (a method of 'genetic fingerprinting'). Study results provide enhanced understanding of the concentrations and sources of fecal coliform bacteria in these three watersheds. Continuum sampling (sampling along the length of the streams) indicated that elevated concentrations of fecal coliform bacteria (maximum observed concentration of 290,000 colonies/100 milliliters (col/100mL) could occur along the entire length of each stream, and that the samples collected at the downstream monitoring station of each stream were generally representative of the entire upstream reach. Seasonal patterns were observed in the base-flow fecal coliform concentrations of all streams; concentrations were typically highest in the summer and lowest in the winter. Fecal coliform concentrations were lowest during periods of base flow (typically 200?2,000 col/100mL) and increased by 3?4 orders of magnitude during storm events (as high as 700,000 col/100mL). Multiple linear regression models were developed to predict fecal coliform concentrations as a function of streamflow and other water-quality parameters. The source tracking technique provided identification of bacteria contributions from diverse sources that included (but were not limited to) humans, cattle, poultry, horses, dogs, cats, geese, ducks, raccoons, and deer. Seasonal patterns were observed in the contributions of cattle and poultry sources. There were relations between the identified sources of fecal coliform bacteria and the land-use practices within each watershed. There were only minor differences in the distribution of bacteria sources between low-flow periods and high-flow periods. A coupled approach that utilized both a large available source library and a smaller, location-specific source library provided the most success in identifying the unknown E. coli isolates. BST data should provide valuable support and guidance for producing more defendable and scientifically rigorous watershed models. Incorporation of these bacteria-source data into watershed management strategies also should result in the selection of more efficient source-reduction scenarios for improving water quality.

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