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At least 343 records · Page 19Linked to original sources
USGS2015

Median nitrate concentrations in groundwater in the New Jersey Highlands Region estimated using regression models and land-surface characteristics

Nitrate-concentration data are used in conjunction with land-use and land-cover data to estimate median nitrate concentrations in groundwater underlying the New Jersey (NJ) Highlands Region. Sources of data on nitrate in 19,670 groundwater samples are from the U.S. Geological Survey (USGS) National Water Information System (NWIS) and the NJ Private Well Testing Act (PWTA). In a study conducted by the USGS, in cooperation with the New Jersey Department of Environmental Protection, logistic regression was used to relate measured nitrate concentrations to five explanatory variables (percent urban and agricultural land use, septic-system density, total length of streams, and number of known contaminated sites) quantified in 610-meter-square grid cells. A method for calculating the median concentrations of nitrate from a series of logistic regression models was developed. Two calibration and two validation procedures showed that the logistic-regression-based method can estimate groundwater-nitrate concentrations in the Highlands Region accurately to within 0.1 milligram per liter as nitrogen (mg/L as N). Limitations of the logistic-regression-based method include the inability to select a logistic model with exactly 0.5 probability of exceeding the threshold value and lack of an algorithm to directly calculate the median value. Quantile regression was evaluated as a suitable alternative and was slightly less accurate than the logistic-regression method in estimating median groundwater nitrate concentrations in the Highlands Region. Multiple-linear regression with log-transformed nitrate-concentration data and the same five explanatory values was less accurate than either logistic or quantile regression in estimating median nitrate concentrations. On the basis of 4,516 2000 x 2000 foot grid cells that contain wells with data stored in NWIS and the PWTA database, the estimated median nitrate concentration for the entire Highlands Region is about 1.25 mg/L as N, and estimated median concentrations range from about 1.05 to 1.78 mg/L as N among 11 smaller administratively defined areas within the Highlands Region that vary in percentages of urban land use, agricultural land use, and septic-system density. The Kaplan-Meier method of estimating summary statistics from left-censored data was applied in order to include nondetects (left-censored data) in median nitrate-concentration calculations. Median concentrations also were determined using three alternative methods of handling nondetects. Treatment of the 23 percent of samples that were nondetects had little effect on estimated median nitrate concentrations because method detection limits were mostly less than median values.

New Jersey↗
USGS2008

EAARL coastal topography–Northeast Barrier Islands 2007: First surface

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2008

EAARL coastal topography– Northeast barrier islands 2007: Bare earth

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the northeast coastal barrier islands in New York and New Jersey, acquired April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2007

Concentrations and Loads of Organic Compounds and Trace Elements in Tributaries to Newark and Raritan Bays, New Jersey

A study was undertaken to determine the concentrations and loads of sediment and chemicals delivered to Newark and Raritan Bays by five major tributaries: the Raritan, Passaic, Rahway, Elizabeth, and Hackensack Rivers. This study was initiated by the State of New Jersey as Study I-C of the New Jersey Toxics Reduction Workplan for the New York-New Jersey Harbor, working under the NY-NJ Harbor Estuary Program (HEP) Contaminant Assessment and Reduction Program (CARP). The CARP is a comprehensive effort to evaluate the levels and sources of toxic contaminants to the tributaries and estuarine areas of the NY-NJ Harbor, including Newark and Raritan Bays. The Raritan and Passaic Rivers are large rivers (mean daily discharges of 1,189 and 1,132 cubic feet per second (ft3/s), respectively), that drain large, mixed rural/urban basins. The Elizabeth and Rahway Rivers are small rivers (mean daily discharges of 25.9 and 49.1 ft3/s, respectively) that drain small, highly urbanized and industrialized basins. The Hackensack River drains a small, mixed rural/urban basin, and its flow is highly controlled by an upstream reservoir (mean daily discharge of 90.4 ft3/s). These rivers flow into urbanized estuaries and ultimately, to the Atlantic Ocean. Each of these tributaries were sampled during two to four storm events, and twice each during low-flow discharge conditions. Samples were collected using automated equipment installed at stations adjacent to U.S. Geological Survey streamflow-gaging stations near the heads-of-tide of these rivers. Large-volume (greater than 50 liters of water and a target of 1 gram of sediment), flow-weighted composite samples were collected for chemical analysis using filtration to collect suspended particulates and exchange resin (XAD-2) to sequester dissolved contaminants. Composite whole-water samples were collected for dissolved polycyclic aromatic hydrocarbons (PAH) and for trace element analysis. Additional discrete grab samples were collected throughout each event for trace-element analysis, and multiple samples were collected for suspended sediment (SS), particulate carbon (POC), and dissolved organic carbon (DOC) analysis. The suspended sediment and exchange resin were analyzed for 114 polychlorinated biphenyls (PCBs, by US EPA method 1668A, modified), seven 2,3,7,8-substituted chlorinated dibenzo-p-dioxins (CDD) and 10 dibenzo-p-difurans (CDF) (by US EPA method 1613), 24 PAHs (by low-resolution isotope dilution/mass-spectral methods), 27 organo-chlorine pesticides (OCPs) (by high resolution isotope dilution/mass-spectral methods), and the trace elements mercury (Hg), methyl-mercury (MeHg), lead (Pb), and cadmium (Cd). Isotope dilution methods using gas chromatography and high-and low-resolution mass spectral (GC/MS) detection were used to accurately identify and quantify organic compounds in the sediment and water phases. Trace elements were measured using inductively coupled plasma-mass spectrometry and cold-vapor atomic fluorescence spectrometry methods. The loads of sediment, carbon, and chemicals were calculated for each storm and low-flow event sampled. Because only a few storm events were sampled, yearly loads of sediment were calculated from rating curves developed using historical SS and POC data. The average annual loads of sediment and carbon were calculated for the period 1975-2000, along with the loads for the selected water years being modeled as part of the New York New Jersey Harbor Estuary Program CARP. Comparison of loads calculated using the rating curve method to loads measured during the sampled storm events indicated that the rating curve method likely underpredicts annual loads. Average annual loads of suspended sediment in the tributaries were estimated to be 395,000 kilograms per year (kg/yr) in the Hackensack River, 417,000 kg/yr in the Elizabeth River, 882,000 kg/yr in the Rahway River, 22,700,000 kg/yr in the Passaic River, and 93,100,000 kg/yr in the Raritan River. Averag

Scientific Investigations Report↗
USGS1998

Preliminary results from the investigation of the Pymatuning earthquake of September 25, 1998

The Pymatuning earthquake occurred on Friday, September 25, 1998, at 19:52:52 Universal Coordinated Time (UTC), or 3:52:52 p.m. EDT, near Jamestown, Pa., at the southern end of the Pymatuning Reservoir, which straddles the Ohio-Pennsylvania border. The National Earthquake Information Center (NEIC) determined that the event had a magnitude of 5.2 mbLg (a magnitude scale used to measure the size of earthquakes that are regional distances away [100 to 1,000 km, or 60 to 600 mi]), an epicenter of 41.5°N latitude, 80.4°W longitude, and an estimated depth of 5 km (3 mi). One person was reported injured as a result of being thrown to the ground by the earthquake, and it caused minor damage to buildings and seriously disrupted many water wells in the GreenvilleJamestown, Pa., area. The earthquake was generally felt over an area of approximately 200,000 km 2 (77,230 mi 2 ) throughout northern Ohio, western Pennsylvania and New York, and much of southern Ontario, Canada (see map on back cover). It was also felt as far west as Illinois and Wisconsin, as far east as New Jersey, Connecticut, and the District of Columbia, and as far south as Kentucky and Virginia. During the aftershock field investigation that commenced within 12 hours of the main shock, a World Wide Web site, < http://groundmotion.cr.usgs.gov/pym/pym.htm >, was established from the field headquarters. The web site was used not only to transmit investigation results to the world in near real time but also to receive information from the local community as new earthquake effects were reported. As of March 1999, at least 11 aftershocks have occurred, the largest being a magnitude 2.3. The largest recent previous earthquake in the region was the northeastern Ohio (Leroy) earthquake of magnitude 5.0 that occurred on January 31, 1986, about 65 km (40 mi) west-northwest of the Pymatuning shock. This event was also felt by many of those who felt the Pymatuning earthquake. Similar to most of the seismicity east of the Rocky Mountains, earthquakes in the region are probably shallow (5 to 10 km, or 3 to 6 mi), and Seeber and Armbruster (1993) hypothesized that the earthquakes occurred along preexisting zones of weakness in Precambrian rocks. Wegweiser and others (1998) suggested that seismicity in northwestern Pennsylvania may be associated with the northwest-trending “cross-strike discontinuities” that are recognized in Paleozoic rocks and may represent reactivation of faults in the Precambrian basement. Using structure-contour maps constructed on the tops of lower Paleozoic strata, Alexandrowicz and Cole (1999) found evidence of preexisting northwest-striking faults in the epicentral region of the Pymatuning shock. The Harvard focal mechanism for the Pymatuning earthquake (a method used to infer the slip and orientation of the fault that generated an earthquake) indicates thrust faulting on a northwest striking plane, which is consistent with the regional northeast-southwest compressive stress regime observed in the area. Seeber and Armbruster (1993) plotted three prior earthquakes in the epicentral area having magnitudes greater than 3; two were instrumentally located near the Pymatuning earthquake, and the third event occurred 20 to 30 km (12 to 19 mi) to the northeast in 1852 (Figure 1).

Connecticut;District of Columbia;Illinois;Kentucky↗
USGS2021

Distribution of chlorinated volatile organic compounds and per- and polyfluoroalkyl substances in monitoring wells at the former Naval Air Warfare Center, West Trenton, New Jersey, 2014–17

A study was conducted by the U.S. Geological Survey in cooperation with the U.S. Navy (the Navy) to determine the status of volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFASs) in groundwater at the former Naval Air Warfare Center (NAWC) in West Trenton, New Jersey. Wells contaminated with VOCs were sampled in 2014, 2015, 2016, and 2017 as part of the Navy’s long-term monitoring program. The results for trichloroethene (TCE), cis-1,2-dichloroethene (cisDCE), and vinyl chloride (VC) were plotted in map view to determine whether the areal extent of the contamination had changed over the 4-year period. TCE, cisDCE, and VC concentrations were plotted along nine lines of section across the former NAWC site to determine whether the vertical distribution of VOCs had changed during 2014–17. TCE, cisDCE, and VC concentrations over time were plotted on graphs for each well to determine long-term trends and changes in VOC concentrations. Data from 1990 to 2017 were used, if available, to make these graphs. Results show that the areas of VOC concentrations greater than or equal to 1 microgram per liter decreased slightly on the northwestern side and the northeastern side of the NAWC site from 2014 to 2017 under the influence of a pump-and-treat system, natural attenuation processes, and engineered bioaugmentation experiments ongoing at the site. The pump-and-treat system continued to hydraulically contain the VOC contamination and kept it from moving offsite to the south and west of NAWC. One well northeast of the NAWC site, 50BR, was found to have detectable TCE and cisDCE concentrations. These detections indicated that VOC contamination had migrated offsite and that the pump-and-treat system was not containing the VOC contamination on the eastern side of the facility. Detectable VOC concentrations were present in wells as deep as 200 and 221 feet on the eastern and western sides of the NAWC site. TCE concentrations in most wells were found to be stable or to have slowly decreased since the facility closed in 1999. Only 7 wells, including 3 pump-and-treat extraction wells, showed substantial increases in TCE concentration from 2014 to 2017. Continuing sources of TCE to the system are desorption of TCE from organic materials in the aquifer, back diffusion of TCE from the contaminated bedrock matrix, and dissolution of remaining dense nonaqueous phase TCE in the aquifer. Wells at the former NAWC site were sampled for PFASs in 2015, 2016, and 2017. Perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and perfluorononanoic acid (PFNA) results were plotted in map and cross-section views to determine the areal and vertical extent of the PFAS contamination at the site. PFOS, PFOA, and PFNA concentrations greater than their established maximum contaminant levels were detected in 25, 24, and 21 of the 26 wells sampled, respectively, on the eastern side of NAWC in 2017. Vertically, the highest PFAS concentrations were present in shallow wells along the fence near the firehouse and along the railroad tracks where the aqueous film-forming foam discharge reportedly occurred back in 1990. PFAS concentrations were detected in one well (54BR) as deep as 200 feet on the eastern side of the NAWC site. PFASs were present in wells east of the railroad tracks, indicating that PFAS-contaminated groundwater had moved offsite. In a limited test of five wells, samples collected with regenerated cellulose dialysis membrane (RCDM) passive samplers contained PFAS concentrations equal to those in samples from low-flow purging.

New Jersey↗
USGS2008

EAARL coastal topography — Sandy Hook 2007

These remotely sensed, geographically referenced elevation measurements of Lidar-derived topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of Gateway National Recreation Area's Sandy Hook Unit in New Jersey, acquired on May 16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2014

EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for a portion of the New Jersey coastline beachface, acquired pre-Hurricane Sandy on October 26, and post-Hurricane Sandy on November 1 and November 5, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

New Jersey↗
USGS2014

EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012

These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired pre-Hurricane Sandy on October 18, 22, 23, and 26, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

New Jersey↗
USGS2017

Application of at-site peak-streamflow frequency analyses for very low annual exceedance probabilities

The U.S. Geological Survey (USGS), in cooperation with the U.S. Nuclear Regulatory Commission, has investigated statistical methods for probabilistic flood hazard assessment to provide guidance on very low annual exceedance probability (AEP) estimation of peak-streamflow frequency and the quantification of corresponding uncertainties using streamgage-specific data. The term “very low AEP” implies exceptionally rare events defined as those having AEPs less than about 0.001 (or 1 × 10 –3 in scientific notation or for brevity 10 –3 ). Such low AEPs are of great interest to those involved with peak-streamflow frequency analyses for critical infrastructure, such as nuclear power plants. Flood frequency analyses at streamgages are most commonly based on annual instantaneous peak streamflow data and a probability distribution fit to these data. The fitted distribution provides a means to extrapolate to very low AEPs. Within the United States, the Pearson type III probability distribution, when fit to the base-10 logarithms of streamflow, is widely used, but other distribution choices exist. The USGS-PeakFQ software, implementing the Pearson type III within the Federal agency guidelines of Bulletin 17B (method of moments) and updates to the expected moments algorithm (EMA), was specially adapted for an “Extended Output” user option to provide estimates at selected AEPs from 10 –3 to 10 –6 . Parameter estimation methods, in addition to product moments and EMA, include L-moments, maximum likelihood, and maximum product of spacings (maximum spacing estimation). This study comprehensively investigates multiple distributions and parameter estimation methods for two USGS streamgages (01400500 Raritan River at Manville, New Jersey, and 01638500 Potomac River at Point of Rocks, Maryland). The results of this study specifically involve the four methods for parameter estimation and up to nine probability distributions, including the generalized extreme value, generalized log-normal, generalized Pareto, and Weibull. Uncertainties in streamflow estimates for corresponding AEP are depicted and quantified as two primary forms: quantile (aleatoric [random sampling] uncertainty) and distribution-choice (epistemic [model] uncertainty). Sampling uncertainties of a given distribution are relatively straightforward to compute from analytical or Monte Carlo-based approaches. Distribution-choice uncertainty stems from choices of potentially applicable probability distributions for which divergence among the choices increases as AEP decreases. Conventional goodness-of-fit statistics, such as Cramér-von Mises, and L-moment ratio diagrams are demonstrated in order to hone distribution choice. The results generally show that distribution choice uncertainty is larger than sampling uncertainty for very low AEP values.

Scientific Investigations Report↗
USGS2012

Variations in statewide water quality of New Jersey streams, water years 1998-2009

Statistical analyses were conducted for six water-quality constituents measured at 371 surface-water-quality stations during water years 1998-2009 to determine changes in concentrations over time. This study examined year-round concentrations of total dissolved solids, dissolved nitrite plus nitrate, dissolved phosphorus, total phosphorus, and total nitrogen; concentrations of dissolved chloride were measured only from January to March. All the water-quality data analyzed were collected by the New Jersey Department of Environmental Protection and the U.S. Geological Survey as part of the cooperative Ambient Surface-Water-Quality Monitoring Network. Stations were divided into groups according to the 1-year or 2-year period that the stations were part of the Ambient Surface-Water-Quality Monitoring Network. Data were obtained from the eight groups of Statewide Status stations for water years 1998, 1999, 2000, 2001-02, 2003-04, 2005-06, 2007-08, and 2009. The data from each group were compared to the data from each of the other groups and to baseline data obtained from Background stations unaffected by human activity that were sampled during the same time periods. The Kruskal-Wallis test was used to determine whether median concentrations of a selected water-quality constituent measured in a particular 1-year or 2-year group were different from those measured in other 1-year or 2-year groups. If the median concentrations were found to differ among years or groups of years, then Tukey's multiple comparison test on ranks was used to identify those years with different or equal concentrations of water-quality constituents. A significance level of 0.05 was selected to indicate significant changes in median concentrations of water-quality constituents. More variations in the median concentrations of water-quality constituents were observed at Statewide Status stations (randomly chosen stations scattered throughout the State of New Jersey) than at Background stations (control stations that are located on reaches of streams relatively unaffected by human activity) during water years 1998-2009. Results of tests on concentrations of total dissolved solids, dissolved chloride, dissolved nitrite plus nitrate, total phosphorus, and total nitrogen indicate a significant difference in water quality at Statewide Status stations but not at Background stations during the study period. Excluding water year 2009, all significant changes that were observed in the median concentrations were ultimately increases, except for total phosphorus, which varied significantly but in an inconsistent pattern during water years 1998-2009. Streamflow data aided in the interpretation of the results for this study. Extreme values of water-quality constituents generally followed inverse patterns of streamflow. Low streamflow conditions helped explain elevated concentrations of several constituents during water years 2001-02. During extreme drought conditions in 2002, maximum concentrations occurred for four of the six water-quality constituents examined in this study at Statewide Status stations (maximum concentration of 4,190 milligrams per liter of total dissolved solids) and three of six constituents at Background stations (maximum concentration of 179 milligrams per liter of total dissolved solids). The changes in water quality observed in this study parallel many of the findings from previous studies of trends in New Jersey.

New Jersey↗
USGS2014

EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013

These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for part of Barnegat Bay, New Jersey, acquired post-Hurricane Sandy on November 1, 5, 16, 20, and 30, 2012; December 5, 6, and 21, 2012; and January 10, 2013. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site .

New Jersey↗
USGS1971

Geology of the Stroudsburg quadrangle and Adjacent areas, Pennsylvania--New Jersey

The Stroudsburg area is within the Valley and Ridge and Great Valley physiographic provinces, Northampton and Monroe Counties, Pennsylvania, and Warren County, New Jersey. The northeast-trending subparallel valleys and ridges resulted from erosion of folded heterogeneous sedimentary rocks. These are Middle Ordovician to Middle Devonian in age and are more than 17,000 feet thick. Deposition of a thick flysch sequence (Martinsburg Formation of Ordovician age) accompanied onset of Taconic orogenesis. It was followed by deposition of a thick molasse sequence of Silurian and Early Devonian age (continental and marginal-marine clastics--Shawangunk Formation and Bloomsburg Red Beds--overlain by predominantly marginal-marine and subtidal limestone, dolomite, shale, and sandstone--Poxono Island Formation through Oriskany Group). Basin deepening and gradual shallowing occurred during Esopus through Mahantango deposition, heralding the Acadian clastic wedge exposed north of the Stroudsburg area. Interpretation of sedimentary structures and regional stratigraphic relations suggest that the Silurian and Devonian rocks were deposited in the following environments: A1luviated coastal plain (meandering and braided streams), tidal flats (supratidal and intertidal), barrier zone, and neritic zone (upper and lower). The rock stratigraphic units have been grouped into four lithotectonic units, each having a different style of deformation. Folds produced in these rocks are disharmonic, and it is believed that each rock sequence is set off from units above and below by decollements, or zones of detachment. Movement was northwest into the Appalachian basin, primarily by gravitational sliding. The contact between the Shawangunk Formation of Silurian age and Martinsburg Formation of Ordovician age, is one zone of detachment as well as an angular unconformity. Deformational effects of the Middle to Late Ordovician Taconic orogeny are elusive, but it appears that the folds and most minor structures, including the prominent regional cleavage, were produced during the late Paleozoic Appalachian orogeny and are superimposed upon larger Taconic folds and faults. Field relations and microscopic study suggest that the regional cleavage in the Stroudsburg area is due to laminar flow of pelitic material along cleavage folia accompanied by mechanical reorientation of platy and elongate minerals and neocrystallization of mica, quartz, chlorite, and probably albite. Numerous lines of evidence point to the conclusion that cleavage developed after the rock was indurated and formed at, and Just below, conditions of low-grade metamorphism. Intensity of cleavage development increases to the southeast across the area. Second-generation slip cleavage, also believed to be Appalachian in age, formed by mechanical reorientation of minerals as well as by limited new mineral growth. The topography had a profound effect on the direction of movement of the Wisconsin glacier, as well as the manner of its retreat and the deposits that were formed. Till and stratified drift of Wisconsin age and till of Illinoian(?) age are common in the area. Wisconsin deglaciation occurred by northeastward retreat and by stagnation. A conspicuous terminal moraine marks the limit of Wisconsin ice movement. Lake Sciota was dammed between the retreating ice, the moraine, and the surrounding ridges north of Godfrey Ridge. Several deltas mark ice stand positions during the retreat of the ice. Lake-bottom and kame deposits are locally common in Cherry Valley. South of Kittatinny Mountain, on the other hand, melt water was freely discharged to the south. The wind and water gaps in the Stroudsburg area (including Delaware Water Gap and Wind Gap) are structurally controlled; specifically they are located where folds die out in short distances, where folding is locally more intense, or where resistant rocks dip steeply and have a narrow width of outcrop. This conclusion is contrary to

Open-File Report↗
USGS2010

EAARL Coastal Topography-Sandy Hook Unit, Gateway National Recreation Area, New Jersey, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Sandy Hook Unit of Gateway National Recreation Area in New Jersey, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2023

Simulation of flow and eutrophication in the central Salem River, New Jersey

The central Salem River in New Jersey is subject to periods of water-quality impairment, marked by elevated concentrations of phosphorus and chlorophyll- a , and low concentrations of and large diurnal swings in concentrations of dissolved oxygen. These seasonal eutrophic conditions are controlling factors for water quality in lower reaches, where the river is more lacustrine than in upper reaches, as a result of downstream damming. This biological productivity is supported by nutrient wash-off from agricultural areas in the surrounding watershed. To investigate this impairment, flow measurement and water-quality sampling were conducted during 2007–08 in support of development of a one-dimensional surface-water-quality model that simulates nutrient cycling and transformation processes. The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection, used the U.S. Environmental Protection Agency Water Quality Analysis Simulation Program (WASP) to develop a receiving-water-quality model of the central Salem River between Woodstown and Deepwater, New Jersey, from April 2007 to October 2008. The main-stem river and largest tributary were simulated. In the flow model, kinematic wave flow is used to simulate flow in upper reaches and ponded weir flow is used to simulate flow in lower reaches. The water-quality model makes use of a mass-balance equation to simulate the fate and transport of nutrients, phytoplankton chlorophyll- a , dissolved oxygen, and oxygen demands (an indicator rather than a substance) in the river. Model input included channel characteristics, boundary conditions for flow and water quality, environmental parameters, vertical dispersion coefficients, settling rates, and kinetic constants. Inputs were estimated where field data were lacking, notably for tributary flows and nutrient loads. The model was calibrated to observed flow variables and concentrations of dissolved oxygen, chlorophyll- a , and nutrients at sampling locations, with emphasis on growing-season conditions. Calibration was achieved through graphical and statistical comparison of simulated results to observed data. Sensitivity analyses were performed, and model limitations and applicability were evaluated. Simulated results closely matched observed data in most cases, although some were overpredicted slightly. The most important causes of overprediction were estimated tributary flows for the flow model and estimated tributary watershed loads for the water-quality model. Calibration of dissolved-oxygen concentrations was closer, and predicted diurnal variations were consistent with high algal photosynthesis/respiration, although lack of continuous dissolved-oxygen data precluded verifying these predictions. A similar caveat applies to predicted diurnal variations in chlorophyll- a . Simulated limitations on algal growth were consistent with those based on observed data and indicated phosphorus was the main limiting nutrient, except during certain periods when nitrogen was limiting. Two water-quality management scenarios were simulated with the model to assess the effect of point- and nonpoint-source nutrient reductions on water-quality conditions in the river. Scenarios involved (1) a return of watershed land use to predevelopment natural conditions and (2) an extreme reduction in nutrient input. Although the extreme-nutrient-reduction scenario yielded improvements in water quality, the natural-conditions scenario yielded the largest improvements as indicated by minimal violations of surface-water-quality standards or thresholds. However, years may be needed to attain the full benefit of these management scenarios as a result of accumulation of phosphorus and organic carbon in riverbed sediments in lacustrine reaches. The results of this study indicate that the quality of water in the central Salem River will improve if management policies that mitigate the effects of nutrient-loading practices in the watershed, particularly those related to agriculture, are implemented.

New Jersey↗
USGS2008

Recovery of Ground-Water Levels From 1988 to 2003 and Analysis of Potential Water-Supply Management Options in Critical Area 1, East-Central New Jersey

Water levels in four confined aquifers in the New Jersey Coastal Plain within Water Supply Critical Area 1 have recovered as a result of reductions in ground-water withdrawals initiated by the State in the late 1980s. The aquifers are the Wenonah-Mount Laurel, the Upper and Middle Potomac-Raritan-Magothy, and Englishtown aquifer system. Because of increased water demand due to increased development in Monmouth, Ocean, and Middlesex Counties, five base and nine alternate management models were designed for the four aquifers to evaluate the effects resulting from potential reallocation of part of the Critical Area 1 reductions in withdrawals. The change in withdrawals and associated water-level changes in the aquifers for 1988-2003 are discussed. Generally, withdrawals decreased 25 to 30 Mgal/d (million gallons per day), and water levels increased 0 to 80 ft (feet). The Regional Aquifer-System Analysis (RASA) ground-water-flow model of the New Jersey Coastal Plain developed by the U.S. Geological Survey was used to simulate ground-water flow and optimize withdrawals using the Ground-Water Management Process (GWM) for MODFLOW. Results of the model were used to evaluate the effects of several possible water-supply management options in order to provide the information to water managers. The optimization method, which provides a means to set constraints that support mandated hydrologic conditions, then determine the maximum withdrawals that meet the constraints, is a more cost-effective approach than simulating a range of withdrawals to determine the effects on the aquifer system. The optimization method is particularly beneficial for a regional-scale study of this kind because of the large number of wells to be evaluated. Before the model was run, a buffer analysis was done to define an area with no additional withdrawals that minimizes changes in simulated streamflow in aquifer outcrop areas and simulated movement of ground water toward the wells from areas of possible high chloride concentrations in the northern and southern parts of the Critical Area. Five base water-supply management models were developed. Each management model has an objective function, decision variables, and constraints. Two of the five management models were test cases: clean slate option and reallocation from the Wenonah-Mount Laurel aquifer and Englishtown aquifer system to small volume wells for potable water use. Nine other models also were developed as part of a trade-off analysis between withdrawal amounts and constraint values. The 14 management models included current (2003) or regularly spaced well locations with variations on the constraints of ground-water head, drawdown, velocity at the 250-mg/L (milligram per liter) isochlor, and withdrawal rate. Results of each management model were evaluated in terms of withdrawals, heads, saltwater intrusion, and source of water by aquifer. Each trade-off curve was defined by using six to nine separate management model runs. Results of the management models designed in this study indicate that a withdrawal reallocation of 5 to 20 Mgal/d within Critical Area 1 would increase the area of heads below -30 ft and the velocity at the 250-mg/L isochlor by up to 4 times that of the simulated 2003 results; the range of values are 0 to 521 square miles and 1 to 20 feet per year, respectively. The increase in area of heads below -30 ft was larger in the Middle Potomac-Raritan-Magothy aquifer than in other aquifers because that area was negligible in 2003. The range of modeled withdrawals is closely tied to management-model design. Interpretation of management model results is provided as well as a discussion of limitations.

Scientific Investigations Report↗
USGS2011

Arsenic, metals, and nutrients in runoff from two detention basins to Raccoon Creek, New Jersey Coastal Plain, 2008

Arsenic (As) concentrations in the waters of Raccoon Creek in southern New Jersey commonly exceed the State\'s Surface Water Quality Standard (SWQS) for freshwater of 0.017 microgram per liter (mu or ug/L). In order to assess contributions of As from residential runoff to the creek, samples of runoff water were collected from a detention basin in each of two residential developments underlain by different geologic formations and at the outlets of those basins. Samples of streamwater also were collected from Raccoon Creek adjacent to the developments. The samples were analyzed to determine concentrations of As, selected metals, organic carbon, and nutrients. Soil samples in and downgradient from the basins also were collected and analyzed. Concentrations of As in unfiltered water samples of runoff from the basin underlain by glauconitic clays generally were higher (up to 4.35 mu or ug/L) than in runoff from the basin underlain by predominantly quartz sands and silts (up to 2.68 mu or ug/L). Chromium (Cr) concentrations also were higher in runoff from the basin underlain by glauconitic clays than in runoff from the basin underlain by quartz sand and silt. In addition, Cr concentrations were higher in the glauconitic soils than in the quartz-rich soils. Metals such as aluminum (Al), iron (Fe), lead (Pb), and manganese (Mn) in the runoff and in the streamwater were mostly in particulate form. Arsenic, most metals, and phosphorus (P) however, were mostly in dissolved form in runoff but in particulate form in the streamwater. Total organic carbon concentrations in the runoff ranged from about 10 to nearly 16 milligrams per liter (mg/L). Given such levels of organic carbon and strong correlations between concentrations of some metals and organic carbon, it may be that many of the metals were complexed with dissolved organic carbon and transported in that form in the runoff. Although underlying geologic materials and soils appear to be major contributors of As to the streamwater, As also could have been contributed from lead arsenate pesticide residues. The residential development underlain by quartz-rich sediments formerly had been an orchard where such pesticides may have been used. The substantial inputs of As to runoff at this site may be attributable to this former land use, although Pb concentrations were about the same in runoff from both sites. The streamwater at both sites, however, contained Pb concentrations well above those in runoff, indicating that there are additional inputs of Pb, perhaps from roadside soils, upstream from the two sampling sites in this study. Positive relations between concentrations of As and some metals with dissolved organic carbon in runoff and streamwater indicate that complexation with organic carbon may provide a mechanism by which these constituents can be transported. Sorption of As, Pb, and P to Fe hydroxides may be indicated by the observed positive relation of particulate As, Pb, and P to particulate Fe, however, representing an additional mechanism for transport of these constituents.

New Jersey↗
USGS2010

Simulation of Runoff and Reservoir Inflow for Use in a Flood-Analysis Model for the Delaware River, Pennsylvania, New Jersey, and New York, 2004-2006

A model was developed to simulate inflow to reservoirs and watershed runoff to streams during three high-flow events between September 2004 and June 2006 for the main-stem subbasin of the Delaware River draining to Trenton, N.J. The model software is a modified version of the U.S. Geological Survey (USGS) Precipitation-Runoff Modeling System (PRMS), a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The PRMS model simulates time periods associated with main-stem flooding that occurred in September 2004, April 2005, and June 2006 and uses both daily and hourly time steps. Output from the PRMS model was formatted for use as inflows to a separately documented reservoir and riverrouting model, the HEC-ResSim model, developed by the U.S. Army Corps of Engineers Hydrologic Engineering Center to evaluate flooding. The models were integrated through a graphical user interface. The study area is the 6,780 square-mile watershed of the Delaware River in the states of Pennsylvania, New Jersey, and New York that drains to Trenton, N.J. A geospatial database was created for use with a geographic information system to assist model discretization, determine land-surface characterization, and estimate model parameters. The USGS National Elevation Dataset at 100-meter resolution, a Digital Elevation Model (DEM), was used for model discretization into streams and hydrologic response units. In addition, geospatial processing was used to estimate initial model parameters from the DEM and other data layers, including land use. The model discretization represents the study area using 869 hydrologic response units and 452 stream segments. The model climate data for point stations were obtained from multiple sources. These sources included daily data for 22 National Weather Service (NWS) Cooperative Climate Station network stations, hourly data for 15 stations from the National Climatic Data Center, hourly data for 1 station from the NWS Middle Atlantic River Forecast Center records, and daily and hourly data for 7 stations operated by the New York City Department of Environmental Protection. The NWS Multisensor Precipitation Estimate data set for 2001-2007 was used for computing daily precipitation for the model and for computing hourly precipitation for storm simulation periods. Calibration of the PRMS model included regression and optimization algorithms, as well as manual adjustments of model parameters. The general goal of the calibration procedure was to minimize the difference between discharge measured at USGS streamgages and the corresponding discharge simulated by the model. Daily streamflow data from 35 USGS streamgages were used in model calibration. The streamflow data represent areas draining from 20.2 to 6,780 square miles. The PRMS model simulates reservoir inflow and watershed runoff for use as input into HECResSim for the purpose of evaluating and comparing the effects of different watershed conditions on main-stem flooding in the Delaware River watershed draining to Trenton, N.J. The PRMS model is useful as a planning tool to simulate the effects of land-use changes and different antecedent conditions on local runoff and reservoir inflow and, as input to the HEC-ResSim model, on flood flows in the main stem of the Delaware River.

Open-File Report↗