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82 records · Page 5Linked to original sources
USGS2005

Occurrence of fecal-indicator bacteria and protocols for identification of fecal-contamination sources in selected reaches of the West Branch Brandywine Creek, Chester County, Pennsylvania

The presence of fecal-indicator bacteria indicates the potential presence of pathogens originating from the fecal matter of warm-blooded animals. These pathogens are responsible for numerous human diseases ranging from common diarrhea to meningitis and polio. The detection of fecal-indicator bacteria and interpretation of the resultant data are, therefore, of great importance to water-resource managers. Current (2005) techniques used to assess fecal contamination within the fluvial environment primarily assess samples collected from the water column, either as grab samples or as depth- and (or) width-integrated samples. However, current research indicates approximately 99 percent of all bacteria within nature exist as attached, or sessile, bacteria. Because of this condition, most current techniques for the detection of fecal contamination, which utilize bacteria, assess only about 1 percent of the total bacteria within the fluvial system and are, therefore, problematic. Evaluation of the environmental factors affecting the occurrence and distribution of bacteria within the fluvial system, as well as the evaluation and modification of alternative approaches that effectively quantify the larger population of sessile bacteria within fluvial sediments, will present water-resource managers with more effective tools to assess, prevent, and (or) eliminate sources of fecal contamination within pristine and impaired watersheds. Two stream reaches on the West Branch Brandywine Creek in the Coatesville, Pa., region were studied between September 2002 and August 2003. The effects of sediment particle size, climatic conditions, aquatic growth, environmental chemistry, impervious surfaces, sediment and soil filtration, and dams on observed bacteria concentrations were evaluated. Alternative approaches were assessed to better detect geographic sources of fecal contamination including the use of turbidity as a surrogate for bacteria, the modification and implementation of sandbag bacteria samplers, and the use of optical brighteners. For the purposes of this report, sources of bacteria were defined as geographic locations where elevated concentrations of bacteria are observed within, or expected to enter, the main branch of the West Branch Brandywine Creek. Biologic sources (for example, waterfowl) were noted where applicable; however, no specific study of biologic sources (such as bacterial source tracking) was conducted. Data indicated that specific bacterial populations within fluvial sediments could be related to specific particle-size ranges. This relation is likely the result of the reduced porosity and permeability associated with finer sediments and the ability of specific bacteria to tolerate particular environments. Escherichia coli (E. coli) showed a higher median concentration (2,160 colonies per gram of saturated sediment) in the 0.125 to 0.5-millimeter size range of natural sediments than in other ranges, and enterococcus bacteria showed a higher median concentration (61,830 colonies per gram of saturated sediment) in the 0.062 to 0.25-millimeter size range of natural sediments than in other ranges. There were insufficient data to assess the particle-size relation to fecal coliform bacteria and (or) fecal streptococcus bacteria. Climatic conditions were shown to affect bacteria concentrations in both the water column and fluvial sediments. Drought conditions in 2002 resulted in lower overall bacteria concentrations than the more typically wet year of 2003. E. coli concentrations in fluvial sediment along the Coatesville study reach in 2002 had a median concentration of 92 colonies per gram of saturated sediment; in 2003, the median concentration had risen to 4,752 colonies per gram of saturated sediment. Symbiotic relations between bacteria and aquatic growth were likely responsible for increased bacteria concentrations observed within an impoundment area on the Coatesville study reach. This reach showed evidence of elevated aquatic growth and sharp increases in E. coli concentrations from upstream to downstream through the impoundment area in both 2002 and 2003. In 2003, E. coli concentrations within the waters column increased from 940 colonies per 100 milliliters upstream to 6,000 colonies per 100 milliliters at the dam crest. Given that these bacteria likely resulted from natural bacterial regrowth, the use of E. coli as an indicator of fecal contamination was severely impaired. Variable environmental conditions along the West Branch Brandywine Creek made the common field-chemical parameters of specific conductance, temperature, pH, and dissolved oxygen ineffective and (or) impossible to use for the determination of inputs of fecal contamination. Extreme variations in chemical gradients commonly were related to the urban/industrial signature of the watershed. For example, during base-flow sampling in 2002, specific-conductance values exceeding 1,000 microsiemens per centimeter observed in effluent from a local steel mill. This effluent raised the specific conductance within the West Branch Brandywine from just above 200 microsiemens per centimeter upstream from the outfall to just below 500 microsiemens per centimeter downstream from the outfall. These chemical gradients also, likely, had an effect on the initial colonization of bacteria, the formation of biofilms, and the persistence of certain types of bacteria along the study reach. Data collected in 2003 indicated that nutrients increased during both base-flow and stormflow conditions along the Coatesville study reach. For example, during base-flow sampling in 2003, 20 pounds of phosphorus was shown to enter the West Branch Brandywine Creek along the Coatesville study reach. The largest contributors to this base-flow nutrient load were likely two wastewater-treatment facilities adjacent to the study reach. During stormflow sampling in 2003, 480 pounds of phosphorus was shown to enter the West Branch Brandywine Creek along the Coatesville study reach. Data, along with other research, indicated the largest contributor to this stormflow nutrient load was likely remobilized sediment originating from a large dam impoundment. These elevated nutrient concentrations were considered sufficient to promote accelerated aquatic growth along the reach. Data collected in 2003 showed that wastewater constituents entered the West Branch Brandywine Creek largely from urban storm-sewer systems. Samples from the primary storm sewer for the city of Coatesville had detections for 20 of 69 wastewater constituents. These constituents included both strong and weak indicators of fecal contamination and generally indicated the storm-sewer system along the Coatesville study reach was a likely source of fecal-indicator bacteria and fecal contamination under base-flow conditions. By comparison, 5 constituents were detected in samples from the upstream end of the reach, and 10 constituents were detected in samples from the downstream end of the reach. During stormflow, numbers of detections were similar along the entire length of the study reach-five in samples from the upstream end, eight in samples from the center of the reach, and seven in samples from the downstream end of the reach. These data indicate that point sources (such as culverts and pipes, septic systems, and wastewater-treatment facilities) are not likely the origin of bacteria contamination during stormflow. The bacteria concentrations observed during stormflow events probably result from remobilized sessile bacteria stored within fluvial sediments. In this case, these bacteria should not be considered indicators of current fecal contamination. Impervious surfaces were found to increase bacteria concentrations along the West Branch Brandywine Creek because contaminated runoff from impervious areas generally flows into, and is concentrated within, the confines of the local storm-sewer system. During 2002, storm-sewer outfalls draining impervious areas were associated with all major locations of elevated bacterial concentrations (greater than 1,200 colonies per gram of saturated sediment) in fluvial sediments. During 2003, wetter conditions and overall bacteria concentrations higher than in 2002 resulted in point sources of bacterial contamination becoming less pronounced; however, the storm-sewer system, draining adjacent impervious areas, was still observed to be the primary source of bacteria along the reach. Where stormwater and (or) other runoff from these areas was allowed to infiltrate and (or) flow through wetland and riparian buffers, bacteria concentrations were not observed to be elevated above background levels commonly observed throughout similar areas of the same reach. Two run-of-the-river dams along the Coatesville study reach were evaluated for their effects on observed bacterial concentrations. These dams were shown to have greater or lesser effects on bacterial concentrations depending on the size of the structure and the capacity of the structure to impede flows. The smaller upstream dam had an approximate height of 3 feet and showed little observed effect on measured turbidity values; these data indicated that the dam did not effectively impede the flow of water or sediment within the West Branch Brandywine Creek. Consequently, this small dam did not show any observed effect on bacterial concentrations either upstream or downstream of the structure. The larger dam, near the middle of the reach, had an approximate height of 20 feet and showed greater effects on both turbidity and bacteria concentrations. The capacity of the larger dam to impede flows, combined with nutrients entering the reach, resulted in increased biologic activity throughout the impoundment area. Within this larger impoundment, enterococcus bacteria populations were observed to decrease sharply and E. coli bacteria populations were observed to increase sharply as flow approached the dam crest. All bacteria levels were then observed to drop to background levels, in both the water column and fluvial sediment, immediately downstream from the dam crest. Additional study is required to determine the cause for this rapid die off. Turbidity was assessed as a potential surrogate for E. coli bacteria. Regression analysis indicated higher turbidity levels usually can indicate higher concentrations of bacteria (R2 = 0.67), but the relation was too sporadic on the West Branch Brandywine Creek to use turbidity as a surrogate for estimated bacteria concentrations. Evaluation of data from individual base-flow and stormflow events resulted in variable and generally poor statistical relations between E. coli bacteria and turbidity (R2 values ranged from 0.02 to 0.94). Sandbag samplers were used in 2003 to determine their suitability for the assessment of fecal contamination. Sandbag samplers rely on the ability of bacteria to attach to surfaces and use the larger sessile bacteria populations instead of the more commonly used planktonic bacteria populations. E. coli bacteria concentrations observed in the sandbag samplers, after 1 week in place, were similar to those found within natural sediments collected concurrently. Enterococcus bacteria concentrations within the same sandbag samplers were not similar, and were generally lower, than those observed within the natural sediments. This discrepancy was likely because sand within the samplers was sieved to a size that was likely too coarse for enterococcus bacteria to persist. Optical-brightener samplers were installed along with each sandbag sampler. Optical brighteners are additives used in common household detergents; therefore, detection of optical brighteners, along with elevated fecal-indicator bacteria concentrations, strongly indicates a link to humans. Positive results for optical brighteners were detected only at the outfalls of two sewage-treatment facilities; because of treatment of the effluent from these facilities, these samples did not have elevated bacteria concentrations. The lack of additional positive results was largely because this method is not sensitive to low concentrations of optical brighteners.

Pennsylvania↗
USGS2014

Digital data in support of studies and assessments of coal and petroleum resources in the Appalachian basin

The Appalachian basin is a mature basin containing abundant oil, gas, and coal resources. Its fossil-fuel-bearing strata range in age from Cambrian to Permian and extend over the States of New York, Pennsylvania, Maryland, Ohio, West Virginia, Virginia, Kentucky, Tennessee, Georgia, and Alabama. The basin has provided abundant fossil fuels to support the Nation’s economic growth for at least 150 years and U.S. Geological Survey (USGS) assessments suggest that substantial untapped resources remain. A merger of new and old geologic data and ideas is required to locate and extract those remaining resources. This chapter brings together abundant existing datasets in a common and integrated spatial format to advance our understanding of the distribution, geologic framework, burial history, and geochemical character of the basin’s oil, gas, and coal resources. These datasets support the information and findings in chapters B through G of this volume, which include (1) geologic cross sections, seismic profiles, and burial history models that document the depositional and structural framework of the basin; (2) assessments of Carboniferous coal-bed gas and Devonian shale gas; (3) studies about the distribution of oil, gas, and coal fields and the geochemistry of natural gas and oil; and (4) a history of fossil-fuel production in the basin. The data that supported these studies were refined and made more accessible using geographic information system (GIS) tools. The following types of data are included: (1) the bedrock geology of States included within the boundary of the Appalachian basin, (2) the locations of oil and gas wells and fields, (3) data produced for the National Oil and Gas Assessment, and (4) the stratigraphy, geochemistry, and production of coal. Data layers are available in shapefile and Zipped Keyhole Markup Language (KMZ) formats, which can be viewed using ArcGIS, Google Earth, or any software package that supports these data formats. Metadata for these datasets are available in HTML and XML formats. Metadata files contain information about the sources of data used to create the dataset, the creation process steps, the data quality, the geographic coordinate system and horizontal datum used for the dataset, the values of attributes used in the dataset table, information about the publication and the publishing organization, and other information that may be useful to the reader. All links in the metadata were valid at the time of compilation. Some of these links may no longer be valid. No attempt has been made to determine the new online location (if one exists) for the data.

Appalachian basin↗
USGS2004

Metadata for ReVA logistic regression dataset

The U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency's Regional Vulnerability Assessment Program, has developed a set of statistical tools to support regional-scale, ground-water quality and vulnerability assessments. The Regional Vulnerability Assessment Program goals are to develop and demonstrate approaches to comprehensive, regional-scale assessments that effectively inform water-resources managers and decision-makers as to the magnitude, extent, distribution, and uncertainty of current and anticipated environmental risks. The U.S. Geological Survey is developing and exploring the use of statistical probability models to characterize the relation between ground-water quality and geographic factors in the Mid-Atlantic Region. Available water-quality data obtained from U.S. Geological Survey National Water-Quality Assessment Program studies conducted in the Mid-Atlantic Region were used in association with geographic data (land cover, geology, soils, and others) to develop logistic-regression equations that use explanatory variables to predict the presence of a selected water-quality parameter exceeding specified management concentration thresholds. The resulting logistic-regression equations were transformed to determine the probability, P(X), of a water-quality parameter exceeding a specified management threshold. Additional statistical procedures modified by the U.S. Geological Survey were used to compare the observed values to model-predicted values at each sample point. In addition, procedures to evaluate the confidence of the model predictions and estimate the uncertainty of the probability value were developed and applied. The resulting logistic-regression models were applied to the Mid-Atlantic Region to predict the spatial probability of nitrate concentrations exceeding specified management thresholds. These thresholds are usually set or established by regulators or managers at national or local levels. At management thresholds of 1 milligram per liter, and 3 milligrams per liter, the probability of nitrate concentrations exceeding these levels is greater than 50 percent (.50) throughout much of the Mid-Atlantic Region. This includes extensive areas throughout central Maryland, southeastern Pennsylvania, northwestern Pennsylvania and the Delmarva Peninsula. In addition, extensive areas in North Carolina and Virginia also have high probabilities of nitrate concentrations in ground water exceeding management thresholds of 1 milligram per liter and 3 milligrams per liter. The mapped areas showing a high predicted probability of nitrate concentrations in ground water exceeding 1 milligram per liter and 3 milligrams per liter correspond to areas that are mapped as cultivated land cover overlying carbonate rocks. At a management threshold of 10 milligrams per liter (corresponding to the U.S. Environmental Protection Agency standard for nitrate in drinking water of 10 milligrams per liter), the predicted probability of nitrate concentrations in ground water exceeding this level are low for most of the Mid-Atlantic Region except for the Delmarva Peninsula, southeastern Pennsylvania, and areas mapped as carbonate rocks in Virginia, Maryland, and Pennsylvania.

Open-File Report↗
USGS2005

Ground-water vulnerability to nitrate contamination at multiple thresholds in the mid-Atlantic region using spatial probability models

The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency?s Regional Vulnerability Assessment Program, has developed a set of statistical tools to support regional-scale, ground-water quality and vulnerability assessments. The Regional Vulnerability Assessment Program?s goals are to develop and demonstrate approaches to comprehensive, regional-scale assessments that effectively inform managers and decision-makers as to the magnitude, extent, distribution, and uncertainty of current and anticipated environmental risks. The U.S. Geological Survey is developing and exploring the use of statistical probability models to characterize the relation between ground-water quality and geographic factors in the Mid-Atlantic Region. Available water-quality data obtained from U.S. Geological Survey National Water-Quality Assessment Program studies conducted in the Mid-Atlantic Region were used in association with geographic data (land cover, geology, soils, and others) to develop logistic-regression equations that use explanatory variables to predict the presence of a selected water-quality parameter exceeding a specified management concentration threshold. The resulting logistic-regression equations were transformed to determine the probability, P(X), of a water-quality parameter exceeding a specified management threshold. Additional statistical procedures modified by the U.S. Geological Survey were used to compare the observed values to model-predicted values at each sample point. In addition, procedures to evaluate the confidence of the model predictions and estimate the uncertainty of the probability value were developed and applied. The resulting logistic-regression models were applied to the Mid-Atlantic Region to predict the spatial probability of nitrate concentrations exceeding specified management thresholds. These thresholds are usually set or established by regulators or managers at National or local levels. At management thresholds of 1 milligram per liter and 3 milligrams per liter as nitrogen, the probability of nitrate concentrations exceeding these levels is greater than 50 percent (0.50) throughout much of the Mid-Atlantic Region. This includes extensive areas throughout central Maryland, southeastern Pennsylvania, northwestern Pennsylvania, and the Delmarva Peninsula. In addition, extensive areas in North Carolina and Virginia also have high probabilities of nitrate concentrations in ground water exceeding management thresholds of 1 milligram per liter and 3 milligrams per liter. The mapped areas showing a high predicted probability of nitrate concentrations in ground water exceeding 1 milligram per liter and 3 milligrams per liter correspond to areas that are mapped as cultivated land cover and/or overlying carbonate rocks. At a management threshold of 10 milligrams per liter (corresponding to the U.S. Environmental Protection Agency standard for nitrate in drinking water of 10 milligrams per liter), the predicted probability of nitrate concentrations in ground water exceeding this level is low for most of the Mid-Atlantic Region, except for the Delmarva Peninsula, southeastern Pennsylvania, and areas mapped as carbonate rocks in Virginia, Maryland, and Pennsylvania.

Scientific Investigations Report↗
USGS2024

Comparing risk of chronic wasting disease occurrence using Bayesian hierarchical spatial models and different surveillance types

Spatial modeling of wildlife diseases can be used to describe patterns of disease risk, understand biological mechanisms of disease occurrence, and for spatial prediction. Risk of wildlife disease occurrence in relation to environmental variables is often modeled and predicted using Markov chain Monte Carlo (MCMC) methods, which are unsuitable for large datasets and those covering large spatial extents. Integrated nested Laplace approximation (INLA) and INLA using the stochastic partial differential equation (INLA-SPDE) approach have become popular alternatives to MCMC for Bayesian inference because of their fast computational time and ability to process large datasets. Studies investigating risk of disease occurrence in wildlife, to our knowledge, have not yet compared Bayesian hierarchical spatial models over large spatial extents using real world data. Using chronic wasting disease (CWD) surveillance data from white-tailed deer ( Odocoileus virginianus ) collected in Pennsylvania, United States, as a case study, we first demonstrate how parameter estimates compare among MCMC, INLA, and INLA-SPDE modeling frameworks. We then model CWD (detected/non-detected) using INLA-SPDE over a much larger spatial extent than has been conducted previously for this disease to determine how surveillance type (e.g., hunter harvest, roadkill, or all surveillance) influences model parameters and predicted risk of CWD occurrence at locations not sampled. Fixed effects considered in the models included deer age and sex, elevation, slope, distance to streams, percent clay, and proportion of two habitat classes (forest and open) known to influence deer movements. We found INLA to produce comparable estimates to MCMC and permit modeling large datasets covering expansive spatial extents much faster and more efficiently than MCMC. We identified potential biases in surveillance types, indicating the value of including all surveillance in models rather than only a single type. Comparing modeling tools available for mapping diseases of wildlife in relation to ecological variables at large spatial extents will guide future modeling efforts for CWD and other wildlife diseases. Understanding spatial patterns of CWD using different surveillance types can help improve understanding of CWD disease outbreaks, assist with control of CWD through geographical targeting, and inform future CWD surveillance efforts.

Ecological Modeling↗
USGS1987

Seismicity map of the state of Pennsylvania

This map is one of a series of seismicity maps produced by the U. S. Geological Survey that show earthquake data of individual states or groups of states at the scale of 1:1,000,000. This map shows only those earthquakes with epicenters located within the boundaries of Pennsylvania, even though earthquakes in nearby states may have been felt or may have caused damage in Pennsylvania. The data in table 1 were used to compile the seismicity map; these data are a corrected, expanded, and updated (through 1983) version of the data used by Algermissen (1969) for a study of seismic risk in the United States. The locations and intensities of some earthquakes were revised and intensities were assigned where none had been before. Many earthquakes were added to the original list from new data sources as well as from some old data sources that had not been previously used. The data in table 1 represent best estimates of the location of the epicenter, magnitude, and intensity of each earthquake on the basis of historical and current information. Some of the aftershocks from large earthquakes are listed, but not all, especially for earthquakes that occurred before seismic instruments were universally used. The latitude and longitude coordinates of each epicenter were rounded to the nearest tenth of a degree and sorted so that all identical locations were grouped and counted. These locations are represented on the map by a triangle. The number of earthquakes at each location is shown on the map by the arabic number to the right of the triangle. A Roman numeral to the left of a triangle is the maximum Modified Mercalli intensity (Wood and Neumann, 1931) of a11 earthquakes at that geographic location. The absence of an intensity value indicates that no intensities have been assigned to earthquakes at that location. The year shown below each triangle is the latest year for which the maximum intensity was recorded.

Pennsylvania↗
USGS2014

Flood-inundation maps for the West Branch Susquehanna River near the Boroughs of Lewisburg and Milton, Pennsylvania

Digital flood-inundation maps for an approximate 8-mile reach of the West Branch Susquehanna River from approximately 2 miles downstream from the Borough of Lewisburg, extending upstream to approximately 1 mile upstream from the Borough of Milton, Pennsylvania, were created by the U.S. Geological Survey (USGS) in cooperation with the Susquehanna River Basin Commission (SRBC). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict the estimated areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 01553500, West Branch Susquehanna River at Lewisburg, Pa. In addition, the information has been provided to the Susquehanna River Basin Commission (SRBC) for incorporation into their Susquehanna Inundation Map Viewer (SIMV) flood warning system ( http://maps.srbc.net/simv/ ). The National Weather Service (NWS) forecasted peak-stage information ( http://water.weather.gov/ahps ) for USGS streamgage 01553500, West Branch Susquehanna River at Lewisburg, Pa., may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. Calibration of the model was achieved using the most current stage-discharge relations (rating number 11.1) at USGS streamgage 01553500, West Branch Susquehanna River at Lewisburg, Pa., a documented water-surface profile from the December 2, 2010, flood, and recorded peak stage data. The hydraulic model was then used to determine 26 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum ranging from 14 feet (ft) to 39 ft. Modeled flood stages, as defined by NWS, include Action Stage, 14 ft; Flood Stage, 18 ft; Moderate Flood Stage, 23 ft; and Major Flood Stage, 28 ft. Geographic information system (GIS) technology was then used to combine the simulated water-surface profiles with a digital elevation model (DEM) derived from light detection and ranging (lidar) data to delineate the area flooded at each water level. The availability of these maps, along with World Wide Web information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Pennsylvania↗
USGS2014

Flood-inundation maps for the Mississinewa River at Marion, Indiana, 2013

Digital flood-inundation maps for a 9-mile (mi) reach of the Mississinewa River from 0.75 mi upstream from the Pennsylvania Street bridge in Marion, Indiana, to 0.2 mi downstream from State Route 15 were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Mississinewa River at Marion (station number 03326500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site. Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current stage-discharge relation at the Mississinewa River streamgage, in combination with water-surface profiles from historic floods and from the current (2002) flood-insurance study for Grant County, Indiana. The hydraulic model was then used to compute seven water-surface profiles for flood stages at 1-fo (ft) intervals referenced to the streamgage datum and ranging from 10 ft, which is near bankfull, to 16 ft, which is between the water levels associated with the estimated 10- and 2-percent annual exceedance probability floods (floods with recurrence interval between 10 and 50 years) and equals the “major flood stage” as defined by the NWS. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging (lidar) data having a 0.98 ft vertical accuracy and 4.9 ft horizontal resolution) to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗
USGS2018

Preliminary geologic framework developed for a proposed environmental monitoring study of a deep, unconventional Marcellus Shale drill site, Washington County, Pennsylvania

Background In the fall of 2011, the U.S. Geological Survey (USGS) was afforded an opportunity to participate in an environmental monitoring study of the potential impacts of a deep, unconventional Marcellus Shale hydraulic fracturing site. The drill site of the prospective case study is the “Range Resources MCC Partners L.P. Units 1-5H” location (also referred to as the “RR–MCC” drill site), located in Washington County, southwestern Pennsylvania. Specifically, the USGS was approached to provide a geologic framework that would (1) provide geologic parameters for the proposed area of a localized groundwater circulation model, and (2) provide potential information for the siting of both shallow and deep groundwater monitoring wells located near the drill pad and the deviated drill legs. The lead organization of the prospective case study of the RR–MCC drill site was the Groundwater and Ecosystems Restoration Division (GWERD) of the U.S. Environmental Protection Agency. Aside from the USGS, additional partners/participants were to include the Department of Energy, the Pennsylvania Geological Survey, the Pennsylvania Department of Environmental Protection, and the developer Range Resources LLC. During the initial cooperative phase, GWERD, with input from the participating agencies, drafted a Quality Assurance Project Plan (QAPP) that proposed much of the objectives, tasks, sampling and analytical procedures, and documentation of results. Later in 2012, the proposed cooperative agreement between the aforementioned partners and the associated land owners for a monitoring program at the drill site was not executed. Therefore, the prospective case study of the RR–MCC site was terminated and no installation of groundwater monitoring wells nor the collection of nearby soil, stream sediment, and surface-water samples were made. Prior to the completion of the QAPP and termination of the perspective case study the geologic framework was rapidly conducted and nearly completed. This was done for three principal reasons. First, there was an immediate need to know the distribution of the relatively undisturbed surface to near-surface bedrock geology and unconsolidated materials for the collection of baseline surface data prior to drill site development (drill pad access road, drill pad leveling) and later during monitoring associated with well drilling, well development, and well production. Second, it was necessary to know the bedrock geology to support the siting of: (1) multiple shallow groundwater monitoring wells (possibly as many as four) surrounding and located immediately adjacent to the drill pad, and (2) deep groundwater monitoring wells (possibly two) located at distance from the drill pad with one possibly being sited along one of the deviated production drill legs. Lastly, the framework geology would provide the lateral extent, thickness, lithology, and expected discontinuities of geologic units (to be parsed or grouped as hydrostratigraphic units) and regional structure trends as inputs into the groundwater model. This report provides the methodology of geologic data accumulation and aggregation, and its integration into a geographic information system (GIS) based program. The GIS program will allow multiple data to be exported in various formats (shapefiles [.shp], database files [.dbf], and Keyhole Markup Language files [.KML]) for use in surface and subsurface geologic site characterization, for sampling strategies, and for inputs for groundwater modeling.

Pennsylvania↗
USGS2014

Executive summary

Fossil fuels from the Appalachian basin region have been major contributors to the Nation’s energy needs over much of the last three centuries. Early records indicate that Appalachian coal was first mined in the middle 1700s (Virginia and Pennsylvania) and was used sparingly to fuel colonial settlements and, later, a fledgling industrial-based economy along the eastern seaboard of the United States (de Witt and Milici, 1989). In 2011, central Appalachian basin coal production accounted for approximately 77 percent of all U.S. metallurgical (or coking) coal and 29 percent of total U.S. production (U.S. Energy Information Administration, 2013). Following initial discoveries and commercial use in western New York (1821) and Ohio and West Virginia (mid-1830s), the Appalachian petroleum (oil and gas) industry began in earnest in 1859 with the discovery of oil at the Drake well in northwestern Pennsylvania. Between 1860 and 1989, the Appalachian basin produced more than 2.5 billion barrels of oil (BBO) and more than 30 trillion cubic feet of gas (TCFG) from more than 500,000 wells (de Witt and Milici, 1989). Although both oil and gas continue to be produced in the Appalachian basin, most new wells in the region are drilled in shale reservoirs to produce natural gas. Appalachian coal and petroleum resources are still available in sufficient quantities to contribute significantly to the Nation’s energy needs. For example, the U.S. Energy Information Administration (2010) estimated that there are 6,484 million short tons of recoverable coal reserves in the Appalachian basin. Similarly, about 14.7 billion barrels of oil equivalent (BBOE) (1.2 BBO+81 TCFG [or 13.5 BBOE]) of recoverable Appalachian basin oil and gas remain available of an estimated ultimate endowment of approximately 25.5 billion BBOE (cumulative production + reserves + estimated recoverable undiscovered resources) (this volume, chap. C.1). U.S. Geological Survey (USGS) Professional Paper 1708 is a modern, indepth collection of reports, cross sections, and maps that describe the geology of the Appalachian basin and its fossil fuel resources. Several of the chapters have been published in outside journals or as other USGS publications. Although this volume is not a comprehensive regional treatment of all notable geologic and fossil fuel localities in the Appalachian basin, the selected study areas and topics presented in the chapters cover large segments of the basin and a wide range of stratigraphic intervals. As the title implies, this volume addresses topics that refer to the locations of coal and petroleum accumulations, the stratigraphic and structural framework, and the geochemical characteristics of the coal beds and petroleum in the basin, as well as the results and documentation of recent USGS assessments of coal, oil, and gas resources in the basin. Many of the maps and accompanying data supporting the reports in this volume are available as downloadable geographic information system (GIS) data files (such as selected coal beds, selected oil and gas fields, locations of oil and gas wells, coal production, coal chemistry, total petroleum system (TPS) boundaries, and bedrock geology). Log ASCII Standard (LAS) files for geophysical (gamma ray) wireline well logs also are included. This publication supplements and updates older USGS regional studies of Appalachian basin coal and petroleum resources such as those by Arndt and others (1968) and the numerous contributors to USGS Miscellaneous Map Series I−917 (for example, Harris and others, 1978), respectively. USGS Professional Paper 1708 is intended primarily for geoscientists in academia, industry, and government who are interested in Appalachian basin geology and its coal and petroleum resources. Other users, however, may find the wide variety of topics, papers, and digital images of value for landuse and policy planning issues. Among the anticipated benefits of the report are improvements in (1) resource assessment estimates and methodology, (2) exploration strategies, (3) basin models, and (4) energy use policies.

Appalachian Basin↗