Geology topics

John W. Fulton

Publications and source records attributed to John W. Fulton.

15 recordsLinked to original sources

USGS2020

QCam: sUAS-based doppler radar for measuring river discharge

The U.S. Geological Survey is actively investigating remote sensing of surface velocity and river discharge (discharge) from satellite-, high altitude-, small, unmanned aircraft systems- (sUAS or drone), and permanent (fixed) deployments. This initiative is important in ungaged basins and river reaches that lack the infrastructure to deploy conventional streamgaging equipment. By coupling alternative discharge algorithms with sensors capable of measuring surface velocity, streamgage networks can be established in regions where data collection was previously impractical or impossible. To differentiate from satellite or high-altitude platforms, near-field remote sensing is conducted from sUAS or fixed platforms. QCam is a Doppler (velocity) radar mounted and integrated on a 3DR © Solo sUAS. It measures the along-track surface velocity by spot dwelling in a river cross section at a vertical where the maximum surface velocity is recorded. The surface velocity is translated to a mean-channel (mean) velocity using the probability concept (PC), and discharge is computed using the PC-derived mean velocity and cross-sectional area. Factors including surface-scatterer quality, flight altitude, propwash, wind drift, and sample duration may affect the radar-returns and the subsequent computation of mean velocity and river discharge. To evaluate the extensibility of the method, five science flights were conducted on four rivers of varying size and dynamics and included the Arkansas River, Colorado (CO), USA (two events); Salcha River near Salchaket, Alaska (AK), USA; South Platte River, CO, USA; and the Tanana River, AK, USA. QCam surface velocities and river discharges were compared to conventional streamgaging methods, which represented truth. QCam surface velocities for the Arkansas River, Salcha River, South Platte River, and Tanana River were 1.02 meters per second (m/s) and 1.43 m/s; 1.58 m/s; 0.90 m/s; and 2.17 m/s, respectively. QCam discharges (and percent differences) were 9.48 (0.3%) and 20.3 cubic meters per second (m 3 /s) (2.5%); 62.1 m 3 /s (−10.4%); 3.42 m 3 /s (7.3%), and 1579 m 3 /s (−18.8%). QCam results compare favorably with conventional streamgaging and are a viable near-field remote sensing technology that can be operationalized to deliver real-time surface velocity, mean velocity, and river discharge, if cross-sectional area is available.

Remote Sensing↗

USGS2019

Remote sensing of river flow in Alaska—New technology to improve safety and expand coverage of USGS streamgaging

The U.S. Geological Survey monitors water level (water surface elevation relative to an arbitrary datum) and measures streamflow in Alaska rivers to compute and compile river flow records for use by water resource planners, engineers, and land managers to design infrastructure, manage floodplains, and protect life, property, and aquatic resources. Alaska has over 800,000 miles of rivers including the Yukon River, the third longest river in the United States. These rivers are home to rare and important ecosystems and are used for recreation, hydropower generation, commercial fishing, and transportation. River flow measurements are essential for wise and safe development and use of Alaska rivers.

Alaska↗

USGS2018

Computing under-ice discharge: A proof-of-concept using hydroacoustics and the Probability Concept

Under-ice discharge is estimated using open-water reference hydrographs; however, the ratings for ice-affected sites are generally qualified as poor. The U.S. Geological Survey (USGS), in collaboration with the Colorado Water Conservation Board, conducted a proof-of-concept to develop an alternative method for computing under-ice discharge using hydroacoustics and the Probability Concept. The study site was located south of Minturn, Colorado (CO), USA, and was selected because of (1) its proximity to the existing USGS streamgage 09064600 Eagle River near Minturn, CO, and (2) its ease-of-access to verify discharge using a variety of conventional methods. From late September 2014 to early March 2015, hydraulic conditions varied from open water to under ice. These temporal changes led to variations in water depth and velocity. Hydroacoustics (tethered and uplooking acoustic Doppler current profilers and acoustic Doppler velocimeters) were deployed to measure the vertical-velocity profile at a singularly important vertical of the channel-cross section. Because the velocity profile was non-standard and cannot be characterized using a Power Law or Log Law, velocity data were analyzed using the Probability Concept, which is a probabilistic formulation of the velocity distribution. The Probability Concept-derived discharge was compared to conventional methods including stage-discharge and index-velocity ratings and concurrent field measurements; each is complicated by the dynamics of ice formation, pressure influences on stage measurements, and variations in cross-sectional area due to ice formation. No particular discharge method was assigned as truth. Rather one statistical metric (Kolmogorov-Smirnov; KS), agreement plots, and concurrent measurements provided a measure of comparability between various methods. Regardless of the method employed, comparisons between each method revealed encouraging results depending on the flow conditions and the absence or presence of ice cover. For example, during lower discharges dominated by under-ice and transition (intermittent open-water and under-ice) conditions, the KS metric suggests there is not sufficient information to reject the null hypothesis and implies that the Probability Concept and index-velocity rating represent similar distributions. During high-flow, open-water conditions, the comparisons are less definitive; therefore, it is important that the appropriate analytical method and instrumentation be selected. Six conventional discharge measurements were collected concurrently with Probability Concept-derived discharges with percent differences (%) of −9.0%, −21%, −8.6%, 17.8%, 3.6%, and −2.3%. This proof-of-concept demonstrates that riverine discharges can be computed using the Probability Concept for a range of hydraulic extremes (variations in discharge, open-water and under-ice conditions) immediately after the siting phase is complete, which typically requires one day. Computing real-time discharges is particularly important at sites, where (1) new streamgages are planned, (2) river hydraulics are complex, and (3) shifts in the stage-discharge rating are needed to correct the streamflow record. Use of the Probability Concept does not preclude the need to maintain a stage-area relation. Both the Probability Concept and index-velocity rating offer water-resource managers and decision makers alternatives for computing real-time discharge for open-water and under-ice conditions.

Colorado↗

USGS2017

Engaging the user community for advancing societal applications of the Surface Water Ocean Topography mission

Scheduled for launch in 2021, the Surface Water and Ocean Topography (SWOT) mission will be a truly unique mission that will provide high-temporal-frequency maps of surface water extents and elevation variations of global water bodies (lakes/reservoirs, rivers, estuaries, oceans, and sea ice) at higher spatial resolution than is available with current technologies (Biancamaria et al. 2016; Alsdorf et al. 2007). The primary instrument on SWOT is based on a Ka-band radar interferometer (KaRIN), which uses radar interferometery technology. The satellite will fly two radar antennas at either end of a 10-m (33 ft) mast, allowing it to measure the elevation of the surface along a 120-km (75 mi)-wide swath below. The availability of high-frequency and high-resolution maps of elevations and extents for surface water bodies and oceans will present unique opportunities to address numerous societally relevant challenges around the globe (Srinivasan et al. 2015). These opportunities may include such diverse and far-ranging applications as fisheries management, flood inundation mapping/risk mitigation/forecasting, wildlife conservation, global data assimilation for improving forecast of ocean tides and weather, reservoir management, climate change impacts and adaptation, and river discharge estimation, among others. Although SWOT is a research mission and not scheduled for launch for another 4 years, there is a need to build engagement within the application community now and to explore how best to advance the societal relevance and benefits of the SWOT mission from concept to reality. The SWOT Applications Working Group organized a workshop on 5–6 April 2017 at the U.S. Geological Survey (USGS) headquarters in Reston, Virginia. The goal of the workshop was to understand and communicate how the applications community can use SWOT data to address problems of profound societal relevance.

Bulletin of the American Meteorological Society↗

USGS2016

Occurrence and trends in the concentrations of fecal-indicator bacteria and the relation to field water-quality parameters in the Allegheny, Monongahela, and Ohio Rivers and selected tributaries, Allegheny County, Pennsylvania, 2001–09

The U.S. Geological Survey (USGS), in cooperation with the Allegheny County Health Department and Allegheny County Sanitary Authority, collected surface-water samples from the Allegheny, Monongahela, and Ohio Rivers and selected tributaries during the period 2001–09 to assess the occurrence and trends in the concentrations of fecal-indicator bacteria during both wet- and dry-weather conditions. A total of 1,742 water samples were collected at 52 main-stem and tributary sites. Quantifiable concentrations of Escherichia coli ( E. coli ) were reported in 1,667 samples, or 97.0 percent of 1,719 samples; concentrations in 853 samples (49.6 percent) exceeded the U.S. Environmental Protection Agency (EPA) recreational water-quality criterion of 235 colonies per 100 milliliters (col/100 mL). Quantifiable concentrations of fecal coliform (FC) bacteria were reported in 1,693 samples, or 98.8 percent of 1,713 samples; concentrations in 780 samples (45.5 percent) exceeded the Commonwealth of Pennsylvania water contact criterion of 400 col/100 mL. Quantifiable concentrations of enterococci bacteria were reported in 912 samples, or 87.5 percent of 1,042 samples; concentrations in 483 samples (46.4 percent) exceeded the EPA recreational water-quality criterion of 61 col/100 mL. The median percentage of samples in which bacteria concentrations exceeded recreational water-quality standards across all sites with five or more samples was 48 for E. coli , 43 for FC, and 75 for enterococci. E. coli , FC, and enterococci concentrations at main-stem sites had significant positive correlations with streamflow under all weather conditions, with rho values ranging from 0.203 to 0.598. Seasonal Kendall and logistic regression were evaluated to determine whether statistically significant trends were present during the period 2001–09. In general, Seasonal Kendall tests for trends in E. coli and FC bacteria were inconclusive. Results of logistic regression showed no significant trends in dry-weather exceedance of the standards; however, significant decreases in the likelihood that wet-weather E. coli and FC bacteria concentrations will exceed EPA recreational standards were found at the USGS streamgaging station Allegheny River at 9th Street Bridge. Nonparametric correlation analysis, including Spearman’s rho and the paired Prentice-Wilcoxon test, was used to screen for associations among fecal indicator bacteria concentrations and the field characteristics streamflow, water temperature, pH, specific conductance, dissolved-oxygen concentration, and turbidity.

Pennsylvania↗

USGS2015

Water-budgets and recharge-area simulations for the Spring Creek and Nittany Creek Basins and parts of the Spruce Creek Basin, Centre and Huntingdon Counties, Pennsylvania, Water Years 2000–06

This report describes the results of a study by the U.S. Geological Survey in cooperation with ClearWater Conservancy and the Pennsylvania Department of Environmental Protection to develop a hydrologic model to simulate a water budget and identify areas of greater than average recharge for the Spring Creek Basin in central Pennsylvania. The model was developed to help policy makers, natural resource managers, and the public better understand and manage the water resources in the region. The Groundwater and Surface-water FLOW model (GSFLOW), which is an integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Groundwater Flow Model (MODFLOW-NWT), was used to simulate surface water and groundwater in the Spring Creek Basin for water years 2000–06. Because the groundwater and surface-water divides for the Spring Creek Basin do not coincide, the study area includes the Nittany Creek Basin and headwaters of the Spruce Creek Basin. The hydrologic model was developed by the use of a stepwise process: (1) develop and calibrate a PRMS model and steady-state MODFLOW-NWT model; (2) re-calibrate the steady-state MODFLOW-NWT model using potential recharge estimates simulated from the PRMS model, and (3) integrate the PRMS and MODFLOW-NWT models into GSFLOW. The individually calibrated PRMS and MODFLOW-NWT models were used as a starting point for the calibration of the fully coupled GSFLOW model. The GSFLOW model calibration was done by comparing observations and corresponding simulated values of streamflow from 11 streamgages and groundwater levels from 16 wells. The cumulative water budget and individual water budgets for water years 2000–06 were simulated by using GSFLOW. The largest source and sink terms are represented by precipitation and evapotranspiration, respectively. For the period simulated, a net surplus in the water budget was computed where inflows exceeded outflows by about 1.7 billion cubic feet (0.47 inches per year over the basin area); storage increased by about the same amount to balance the budget. The rate and distribution of recharge throughout the Spring Creek, Nittany Creek, and Spruce Creek Basins is variable as a result of the high degree of hydrogeologic heterogeneity and karst features. The greatest amount of recharge was simulated in the carbonate-bedrock valley, near the toe slopes of Nittany and Tussey Mountains, in the Scotia Barrens, and along the area coinciding with the Gatesburg Formation. Runoff extremes were observed for water years 2001 (dry year) and 2004 (wet year). Simulated average recharge rates (water reaching the saturated zone as defined in GSFLOW) for 2001 and 2004 were 5.4 in/yr and 22.0 in/yr, respectively. Areas where simulations show large variations in annual recharge between wet and dry years are the same areas where simulated recharge was large. Those areas where rates of groundwater recharge are much higher than average, and are capable of accepting substantially greater quantities of recharge during wet years, might be considered critical for maintaining the flow of springs, stream base flow, or the source of water to supply wells. The slopes of the Bald Eagle, Tussey, and Nittany Mountains are relatively insensitive to variations in recharge, primarily because of reduced infiltration rates and steep slopes.

Pennsylvania↗

USGS2015

Effects of high salinity wastewater discharges on unionid mussels in the Allegheny River, Pennsylvania

We examined the effect of high salinity wastewater (brine) from oil and natural gas drilling on freshwater mussels in the Allegheny River, Pennsylvania, during 2012. Mussel cages (N = 5 per site) were deployed at two sites upstream and four sites downstream of a brine treatment facility on the Allegheny River. Each cage contained 20 juvenile northern riffleshell mussels Epioblasma torulosa rangiana). Continuous specific conductance and temperature data were recorded by water quality probes deployed at each site. To measure the amount of mixing throughout the entire study area, specific conductance surveys were completed two times during low-flow conditions along transects from bank to bank that targeted upstream (reference) reaches, a municipal wastewater treatment plant discharge upstream of the brine-facility discharge, the brine facility, and downstream reaches. Specific conductance data indicated that high specific conductance water from the brine facility (4,000–12,000 µS/cm; mean 7,846) compared to the reference reach (103–188 µS/cm; mean 151) is carried along the left descending bank of the river and that dilution of the discharge via mixing does not occur until 0.5 mi (805 m) downstream. Juvenile northern riffleshell mussel survival was severely impaired within the high specific conductance zone (2 and 34% at and downstream of the brine facility, respectively) and at the municipal wastewater treatment plant (21%) compared to background (84%). We surveyed native mussels (family Unionidae) at 10 transects: 3 upstream, 3 within, and 4 downstream of the high specific conductance zone. Unionid mussel abundance and diversity were lower for all transects within and downstream of the high conductivity zone compared to upstream. The results of this study clearly demonstrate in situ toxicity to juvenile northern riffleshell mussels, a federally endangered species, and to the native unionid mussel assemblage located downstream of a brine discharge to the Allegheny River.

Pennsylvania↗

USGS2014

Using science to strengthen our Nation's resilience to tomorrow's challenges: understanding and preparing for coastal impacts

Hurricane Sandy caused unprecedented damage across some of the most densely populated coastal areas of the northeastern United States. The costly, landscape-altering destruction left in the wake of this storm is a stark reminder of our Nation’s need to become more resilient as we inevitably face future coastal hazards. As our Nation recovers from this devastating natural disaster, it is clear that accurate scientific information is essential as we seek to identify and develop strategies to address trends in coastal landscape change and reduce our future vulnerability to major storm events. To address this need, the U.S. Geological Survey (USGS) received $43.2 million in supplemental appropriations from the Department of the Interior (DOI) to conduct the scientific research needed to guide response, recovery, and rebuilding activities and to develop effective strategies for protecting coastal communities and resources in the future. This fact sheet describes how the USGS is combining interdisciplinary science with state-of-the-art technologies to achieve a comprehensive understanding of coastal change caused by Hurricane Sandy. By assessing coastal change impacts through research and by developing tools that enhance our science capabilities, support coastal stakeholders, and facilitate effective decision making, we continue to build a greater understanding of the processes at work across our Nation’s complex coastal environment—from wetlands, estuaries, barrier islands, and nearshore marine areas to infrastructure and human communities. This improved understanding will increase our resilience as we prepare for future short-term, extreme events as well as long-term coastal change.

Fact Sheet↗

USGS2014

Calibration of a two-dimensional hydrodynamic model for parts of the Allegheny, Monongahela, and Ohio Rivers, Allegheny County, Pennsylvania

The U.S. Geological Survey (USGS), in cooperation with the Allegheny County Sanitary Authority, developed a validated two-dimensional Resource Management Associates2 (RMA2) hydrodynamic model of parts of the Allegheny, Monongahela, and Ohio Rivers (Three Rivers) to help assess the effects of combined sewer overflows (CSOs) and sanitary sewer overflows (SSOs) on the rivers. The hydrodynamic model was used to drive a water-quality model of the study area that was capable of simulating the transport and fate of fecal-indicator bacteria and chemical constituents under open-water conditions. The study area includes 14 tributary streams and parts of the Three Rivers where they enter and exit Allegheny County, an area of approximately 730 square miles (mi 2 ). The city of Pittsburgh is near the center of the county, where the Allegheny and Monongahela Rivers join to form the headwaters of the Ohio River. The Three Rivers are regulated by a series of fixed-crest dams, gated dams, and radial (tainter) gates and serve as the receiving waters for tributary streams, CSOs, and SSOs. The RMA2 model was separated into four individual segments on the basis of the U.S. Army Corps of Engineers navigational pools in the study area (Dashields; Emsworth; Allegheny River, Pool 2; and Braddock), which were calibrated individually using measured water-surface slope, velocity, and discharge during high- and low-flow conditions. The model calibration process included the comparison of water-surface elevations at five locations and velocity profiles at more than 80 cross sections in the study area. On the basis of the calibration and validation results that included water-surface elevations and velocities, the model is a representative simulation of the Three Rivers flow patterns for discharges ranging from 4,050 to 47,400 cubic feet per second (ft 3 /s) on the Allegheny River, 2,550 to 40,000 ft 3 /s on the Monongahela River, and 10,900 to 99,000 ft 3 /s on the Ohio River. The Monongahela River was characterized by unsteady conditions during low and high flows, which affected the calibration range. The simulated low-flow water-surface elevations typically were within 0.2 feet (ft) of measured values, whereas the simulated high-flow water-surface elevations were typically within 0.3 ft of the measured values. The mean error between simulated and measured velocities was less than 0.07 ft/s for low-flow conditions and less than 0.17 ft/s for high-flow conditions.

Pennsylvania↗

USGS2014

Remediation scenarios for attenuating peak flows and reducing sediment transport in Fountain Creek, Colorado, 2013

The U.S. Geological Survey (USGS) in cooperation with the Fountain Creek Watershed, Flood Control and Greenway District assessed remediation scenarios to attenuate peak flows and reduce sediment loads in the Fountain Creek watershed. To evaluate these strategies, the U.S. Army Corps of Engineers Hydrologic Engineering Center (HEC) hydrologic and hydraulic models were employed. The U.S. Army Corps of Engineers modeling system HEC-HMS (Hydrologic Modeling System) version 3.5 was used to simulate runoff in the Fountain Creek watershed, Colorado, associated with storms of varying magnitude and duration. Rain-gage precipitation data and radar-based precipitation data from the April 28–30, 1999, and September 14–15, 2011, storm events were used in the calibration process for the HEC-HMS model. The curve number and lag time for each subwatershed and Manning's roughness coefficients for each channel reach were adjusted within an acceptable range so that the simulated and measured streamflow hydrographs for each of the 12 USGS streamgages approximated each other. The U.S. Army Corps of Engineers modeling system HEC-RAS (River Analysis System) versions 4.1 and 4.2 were used to simulate streamflow and sediment transport, respectively, for the Fountain Creek watershed generated by a particular storm event. Data from 15 USGS streamgages were used for model calibration and 7 of those USGS streamgages were used for model validation. The calibration process consisted of comparing the simulated water-surface elevations and the cross-section-averaged velocities from the model with those surveyed in the field at the cross section at the corresponding 15 and 7 streamgages, respectively. The final Manning’s roughness coefficients were adjusted between –30 and 30 percent at the 15 calibration streamgages from the original left, right, and channel-averaged Manning's roughness coefficients upon completion of calibration. The U.S. Army Corps of Engineers modeling system HEC-RAS version 4.2 was used to simulate streamflow and sediment transport for the Fountain Creek watershed generated by a design-storm event. The Laursen-Copeland sediment-transport function was used in conjunction with the Exner 5 sorting method and the Ruby fall-velocity method to predict sediment transport. Six USGS streamgages equipped with suspended-sediment samplers were used to develop sediment-flow rating curves for the sediment-transport-model calibration. The critical Shields number in the Laursen-Copeland sediment-transport function and the volume of sediment available at a given cross section were adjusted during the HEC-RAS sediment-model calibration process. HEC-RAS model simulations used to evaluate the 14 remediation scenarios were based on unsteady-state streamflows associated with a 24-hour, 1-percent annual exceedance probability (100-year) National Oceanic and Atmospheric Administration Type II precipitation event. Scenario 0 represents the baseline or current conditions in the watershed and was used to compare the remaining 13 scenarios. Scenarios 1–8 and 12 rely on side-detention facilities to reduce peak flows and sediment transport. Scenario 9 has a diversion channel, and scenario 10 has a reservoir. Scenarios 11 and 13 incorporate channel armoring and channel widening, respectively. Scenarios 8 and 10, the scenario with the most side-detention facilities, and the scenario with the reservoir, respectively, were the most effective at reducing sediment transport and peak flow at the Pueblo, Colorado, streamgage. Scenarios 8 and 10 altered the peak flow by –58.9 and –56.4 percent, respectively. In turn, scenarios 8 and 10 altered the sediment transport by –17.7 and –62.1 percent, respectively.

Colorado↗

USGS2013

Velocity, water-quality, and bathymetric surveys of the Grays Landing and Maxwell Navigation Pools, and Selected Tributaries to the Monongahela River, Pennsylvania, 2010–11

The U.S. Geological Survey (USGS) conducted velocity, water-quality, and bathymetric surveys from spring 2010 to summer 2011 in the Grays Landing and Maxwell navigation pools of the Monongahela River, Pennsylvania, and selected tributaries in response to elevated levels of total dissolved solids (TDS) recorded in early September 2009. Velocity data were collected using an Acoustic Doppler Current Profiler. Water-quality surveys included the in-situ collection of specific-conductance, water-temperature, and turbidity data using a water-quality sonde. Additionally, discrete water samples were collected and analyzed for TDS, chloride, and sulfate. Bathymetric data were collected using an echo sounder, and the shoreline was delineated using a laser range finder and electronic compass. The data were geo-referenced using a differential global positioning system and navigational software. Horizontal (x, y) coordinates were referenced to the North American Datum of 1983. Depth (z) elevations were referenced to the North American Vertical Datum of 1988. The data are provided in electronic format (appendix 1) and may be downloaded and can be used in a geographic information system for cartographic display and data analysis.

Pennsylvania↗

USGS2010

Hydraulic modeling of mussel habitat at a bridge-replacement site, Allegheny River, Pennsylvania, USA

The Allegheny River in Pennsylvania supports a large and diverse freshwater-mussel community, including two federally listed endangered species, Pleurobema clava (Clubshell) and Epioblasma torulosa rangiana (Northern Riffleshell). It is recognized that river hydraulics and morphology play important roles in mussel distribution. To assess the hydraulic influences of bridge replacement on mussel habitat, metrics such as depth, velocity, and their derivatives (shear stress, Froude number) were collected or computed. The objectives of the project were to evaluate mussel and hydraulic data at a reference site and to compare those findings to a bridge-replacement site. The findings were used to support a statistical analysis, which establishes correlations between mussel count and hydraulics, and a numerical model to forecast habitat based on the statistics. ArcGIS was selected to manage the data and generate a grid to compute area statistics for 3319, 4.9-m × 4.9-m cells (cell) for total mussel count, depth, velocity, shear stress, and Froude number. The Wilcoxon Rank Sum test indicated no statistical significance between the total mussel count and the hydraulic variables; however, trellis graphs were used to account for the spatial variability in the data set. For the flow conditions measured, the total mussel count per cell is greatest at sections where (1) velocities range from 0.061 to 0.21 m/s, (2) shear stresses range from 0.48 to 3.8 dyne/cm 2 , and (3) Froude numbers range from 0.006 to 0.04. Based on the statistical targets established, the hydraulic model results suggest that an additional 2428 m 2 or a 30-percent increase in suitable mussel habitat could be generated at the replacement-bridge site when compared to the baseline condition associated with the existing bridge at that same location. The study did not address the influences of substrate, acid mine drainage, sediment loads from tributaries, and surface-water/ground-water exchange on mussel habitat. Future studies could include methods for quantifying (1) channel–substrate composition and distribution using tools such as hydroacoustic echosounders specifically designed and calibrated to identify bed composition and mussel populations, (2) surface-water and ground-water interactions, and (3) a high-streamflow event.

Pennsylvania↗

USGS2006

Fecal-indicator bacteria in the Allegheny, Monongahela, and Ohio Rivers and selected tributaries, Allegheny County, Pennsylvania, 2001-2005

Concentrations of fecal-indicator bacteria were determined in 1,027 water-quality samples collected from July 2001 through August 2005 during dry- (72-hour dry antecedent period) and wet-weather (48-hour dry antecedent period and at least 0.3 inch of rain in a 24-hour period) conditions in the Allegheny, Monongahela, and Ohio Rivers (locally referred to as the Three Rivers) and selected tributaries in Allegheny County. Samples were collected at five sampling sites on the Three Rivers and at eight sites on four tributaries to the Three Rivers having combined sewer overflows. Water samples were analyzed for three fecal-indicator organisms fecal coliform, Escherichia coli (E. coli), and enterococci bacteria. Left-bank and right-bank surface-water samples were collected in addition to a cross-section composite sample at each site. Concentrations of fecal coliform, E. coli, and enterococci were detected in 98.6, 98.5, and 87.7 percent of all samples, respectively. The maximum fecal-indicator bacteria concentrations were collected from Sawmill Run, a tributary to the Ohio River; Sawmill Run at Duquesne Heights had concentrations of fecal coliform, E. coli, and enterococci of 410,000, 510,000, and 180,000 col/100 mL, respectively, following a large storm. The samples collected in the Three Rivers and selected tributaries frequently exceeded established recreational standards and criteria for bacteria. Concentrations of fecal coliform exceeded the Pennsylvania water-quality standard (200 col/100 mL) in approximately 63 percent of the samples. Sample concentrations of E. coli and enterococci exceeded the U.S. Environmental Protection Agency (USEPA) water-quality criteria (235 and 61 col/100 mL, respectively) in about 53 and 47 percent, respectively, of the samples. Fecal-indicator bacteria were most strongly correlated with streamflow, specific conductance, and turbidity. These correlations most frequently were observed in samples collected from tributary sites. Fecal-indicator bacteria concentrations and turbidity were correlated to the location of sample collection in the cross section. Most differences were between bank and composite samples; differences between right-bank and left-bank samples were rarely observed. The Allegheny River sites had more significant correlations than the Monongahela or Ohio River sites. Comparisons were made between fecal-indicator bacteria in composite samples collected during dry-weather, wet-weather day-one, wet-weather day-two (tributary sites only), and wet-weather day-three (Three Rivers sites only) events in the Three Rivers and selected tributary sites. The lowest median bacteria concentrations generally were observed in the dry-weather composite samples. All median bacteria concentrations in dry-weather composite samples in the five Three Rivers sites were below water-quality standards and criteria; bacteria concentrations in the upstream tributary sites rarely met all standards or criteria. Only Turtle Creek, Thompson Run, and Chartiers Creek had at least one median bacteria concentration below water-quality standards or criteria. Median bacteria concentrations in the composite samples generally were higher the day after a wet-weather event compared to dry-weather composite samples and other wet-weather composite samples collected. In the five Three Rivers sites, median bacteria concentrations 3 days after a wet-weather event in composite samples tended to fall below the water-quality standards and criteria; in the eight tributary sites, median bacteria concentrations in the dry-weather and wet-weather composite samples generally were above the water-quality standards or criteria. Composite samples collected at the upstream sites on the Three Rivers and selected tributaries generally had lower median bacteria concentrations than composite samples collected at the downstream sites during dry- and wet-weather events. Higher concentrations downstream may be because o

Pennsylvania↗

USGS2005

Hydrogeologic setting and conceptual hydrologic model of the Spring Creek Basin, Centre County, Pennsylvania, June 2005

The Spring Creek Basin, Centre County, Pa., is experiencing some of the most rapid growth and development within the Commonwealth. This trend has resulted in land-use changes and increased water use, which will affect the quantity and quality of stormwater runoff, surface water, ground water, and aquatic resources within the basin. The U.S. Geological Survey (USGS), in cooperation with the ClearWater Conservancy (CWC), Spring Creek Watershed Community (SCWC), and Spring Creek Watershed Commission (SCWCm), has developed a Watershed Plan (Plan) to assist decision makers in water-resources planning. One element of the Plan is to provide a summary of the basin characteristics and a conceptual model that incorporates the hydrogeologic characteristics of the basin. The report presents hydrogeologic data for the basin and presents a conceptual model that can be used as the basis for simulating surface-water and ground-water flow within the basin. Basin characteristics; sources of data referenced in this text; physical characteristics such as climate, physiography, topography, and land use; hydrogeologic characteristics; and water-quality characteristics are discussed. A conceptual model is a simplified description of the physical components and interaction of the surface- and ground-water systems. The purpose for constructing a conceptual model is to simplify the problem and to organize the available data so that the system can be analyzed accurately. Simplification is necessary, because a complete accounting of a system, such as Spring Creek, is not possible. The data and the conceptual model could be used in development of a fully coupled numerical model that dynamically links surface water, ground water, and land-use changes. The model could be used by decision makers to manage water resources within the basin and as a prototype that is transferable to other watersheds.

Pennsylvania↗

USGS2004

Fecal-indicator bacteria in the Allegheny, Monongahela, and Ohio Rivers, near Pittsburgh, Pennsylvania, July-September 2001

This report presents the results of a study by the Allegheny County Health Department (ACHD) and the U.S. Geological Survey (USGS) to determine the concentrations of fecal-indicator bacteria in the Allegheny, Monongahela, and Ohio Rivers (Three Rivers) in Allegheny County, Pittsburgh, Pa. Water-quality samples and river-discharge measurements were collected from July to September 2001 during dry- (72-hour dry antecedent period), mixed-, and wet-weather (48-hour dry antecedent period and at least 0.3 inch of rain in a 6-hour period) conditions at five sampling sites on the Three Rivers in Allegheny County. Water samples were collected weekly to establish baseline conditions and during successive days after three wet-weather events. Water samples were analyzed for fecal-indicator organisms including fecal-coliform (FC) bacteria, Escherichia coli (E. coli), and enterococci bacteria. Water samples were collected by the USGS and analyzed by the ACHD Laboratory. At each site, left-bank and right-bank surface-water samples were collected in addition to a composite sample (discharge-weighted sample representative of the channel cross section as a whole) at each site. Fecal-indicator bacteria reported in bank and composite samples were used to evaluate the distribution and mixing of bacteria-source streams in receiving waters such as the Three Rivers. Single-event concentrations of enterococci, E. coli, and FC during dry-weather events were greater than State and Federal water-quality standards (WQS) in 11, 28, and 28 percent of the samples, respectively; during mixed-weather events, concentrations of fecal-indicator bacteria were greater than WQS in 28, 37, and 43 percent of the samples, respectively; and during wet-weather events, concentrations of fecal-indicator bacteria were greater than WQS in 56, 71, and 81 percent of samples, respectively. Single-event, wet-weather concentrations exceeded those during dry-weather events for all sites except the Allegheny River at Oakmont. For this site, dilution during wet-weather events or the lack of source streams upgradient of the site may have caused this anomaly. Additionally, single-event concentrations of E. coli and FC frequently exceeded the WQS reported during wet-weather events. It is difficult to establish a short-term trend in fecal-indicator bacteria concentrations as a function of time after a wet-weather event due to factors including the spatial variability of sources contributing fecal material, dry-weather discharges, resuspension of bottom sediments, and flow augmentation from reservoirs. Relative to E. coli and enterococci, FC concentrations appeared to decrease with time, which may be attributed to the greater die-off rate for FC bacteria. Fecal-indicator bacteria concentrations at a site are dependent on the spatial distribution of point sources upstream of the station, the time-of-travel, rate of decay, and the degree of mixing and resuspension. Therefore, it is difficult to evaluate whether the left, right, and composite concentrations reported at a particular site are significantly different. To evaluate the significance of the fecal-indicator bacteria concentrations and turbidity reported in grab and composite samples during dry-, mixed-, and wet-weather events, data sets were evaluated using Wilcoxon rank sum tests. Tests were conducted using the fecal-indicator bacteria colonies and turbidity reported for each station for a given weather event. For example, fecal coliform counts reported in the left-bank sample were compared against the right-bank and composite samples, respectively, for the Ohio River at Sewickley site during dry-, mixed-, and wet-weather events. The statistical analyses suggest that, depending on the sampling site, the fecal-bacteria concentrations measured at selected locations vary spatially within a channel (left bank compared to right, right bank compared to composite). The most significant differences occurred between feca

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