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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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State and local county health departments have detected per- and polyfluoroalkyl substances (PFAS) in groundwater downgradient of airports and military and firefighting training areas in Long Island, New York. However, the occurrence and spatial distribution of PFAS throughout the surficial aquifer is not well established. Shallow groundwater samples were collected in 2018 from two observation well networks; the Sentinel network and Wastewater Treatment Plant groundwater (WTPGW) network. The Sentinel network is an island-wide group of wells screened within the shallow upper glacial (surficial, <100 feet deep) aquifer, which were sampled to assess the occurrence of PFAS in different land-use settings. The WTPGW network...
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This model archive makes available the Soil-Water-Balance (SWB) model (Westenbroek and others, 2010) and input data used to estimate the potential amount of annual groundwater recharge to the Long Island aquifer system from 1900 to 2019 as described in U.S. Geological Survey Scientific Investigations Report 2021-5143. Input data for two SWB simulations are included in the archive. The first simulation uses existing land-use/land-cover datasets to estimate changes in recharge with changing land use from 1900-2019 (referred to as the post-development simulation). The second simulation assumed a forested, undeveloped (pre-development simulation) condition across Long Island for the same period. The same soil coverages...
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This dataset has been archived; it has been superseded by version 1.1 (December 2022) which can be found at https://doi.org/10.5066/P9KODN4C. This U.S. Geological Survey data release provides surface-water quality, streamflow, and groundwater-elevation data collected within the Central Pine Barrens (CPB) Region of Suffolk County, New York. The data were collected in cooperation with the Central Pine Barrens Commission and the Town of Brookhaven as part of a five-year comprehensive water-resources monitoring program. Water quality and quality-assurance data from seven sites on two rivers (Carmans River- 5 sites and Peconic River - 2 sites) in the CPB are included. Carmans River sites were sampled four times throughout...
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This data release contains meteorological sensor data (6-minute intervals) collected at Great South Bay at Watch Hill on Fire Island (USGS station number, 01305575), New York, from 2017 to 2022. Measured parameters include: air pressure, air temperature, precipitation, relative humidity, solar radiation, wind direction and speed, and wind-gust direction and speed. Data users are encouraged to review the metadata for information on data quality and screening prior to use.
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This data release contains model simulation results of a particle tracking analysis to delineate areas that provide recharge to surface waters and public-supply wells on Long Island, NY. The analysis partitions the recharge areas based on particle travel times of greater than or less than 10 years to reach the receiving surface water or well. The simulation was performed using a regional-scale numerical model of the Long Island aquifer system (Walter and others, 2020a and 2020b) for average 2005-2015 conditions. The model implements MODFLOW-NWT (Niswonger and others, 2011) to represent steady-state groundwater pumping and aquifer recharge conditions; recharge areas were identified and partitioned using the particle-tracking...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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This U.S. Geological Survey (USGS) data release provides surface water quality and groundwater elevation data collected by USGS personnel within the Central Pine Barrens (CPB) Region of Suffolk County, New York, from October 1, 2021 through September 30, 2022. The data were collected in cooperation with the Central Pine Barrens Commission and the Town of Brookhaven as part of a comprehensive water resources monitoring program during 2017 to 2023. Water quality and quality assurance data from seven sites on two rivers (Carmans River- five sites and Peconic River- two sites) in the CPB are included. Carmans River sites were sampled four times throughout the year (fall, winter, spring, and summer) and Peconic River...
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Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, Shinnecock Inlet, and southwest of Montauk Point were about 1 kilometer (km) wide and 10 km long. The area was mapped by the U.S. Geological Survey with support from the Canadian Hydrographic Service and the University...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
This data release contains geospatial data defining estimates of the depth to water and water-table altitude in the upper glacial and Magothy Aquifers, the potentiometric surface of the confined Magothy and Jameco Aquifers, and the potentiometric surface of the Lloyd and North Shore Aquifers on Long Island, New York. Estimates are based on 502 water-level measurements made in wells across Long Island during March-April 2006. Water-table contours were interpolated using measurements from 341 wells screened in the upper glacial aquifer or shallow Magothy Aquifer. Potentiometric-surface contours in the confined Magothy and hydraulically connected Jameco Aquifer were interpolated using measurements from 102 wells. Potentiometric-surface...
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This document provides a summary of surface water-quality, streamflow, and groundwater data collected by the U.S. Geological Survey (USGS) within the Central Pine Barrens (CPB) Region of Suffolk County, New York. The data were collected in cooperation with the Central Pine Barrens Commission and the Town of Brookhaven under a five-year comprehensive water resources monitoring program. The surface water-quality data within the CPB for the 2018 water year (October 1, 2017 to September 30, 2018) includes data from the Carmans River and the Peconic River. The streams were sampled several times throughout the year at seven pre-determined locations. The Carmans River was sampled at five locations: 1) CARMANS RIVER AT...
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Groundwater samples collected between 2016 and 2018 from 56 shallow (<40 m depth) monitoring wells in Long Island, N.Y., were collected in support of the Long Island Pesticide Pollution Prevention Strategy. Each well was sampled at least once and analyzed for over 200 pesticides and pesticide degradates as part of this study. Results presented here also include field and inorganic analysis data, as well as neonicotinoid (LC9045) and glyphosate pesticide data collected from select monitoring wells. Data collection and analysis was supported by the New York State Department of Environmental Conservation, Suffolk County Department of Health Services, and Long Island Commission for Aquifer Protection. The results presented...
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This data release contains the input, output, and model code used to run a transient simulation of a previously published (Walter and others, 2020) steady-state regional model of Long Island, N.Y. The original model code was updated to MODFLOW 6 (version 6.3.0) and incorporates monthly transient stress periods to simulate conditions from 2005-2019 following methods described in Walter and others (2020). Selected remedial stresses (groundwater extraction and return) were incorporated for select locations in southeastern Nassau County. No modifications were made to the hydrologic boundaries, model layers, or hydraulic properties specified in the original model. A uniform value of 0.25 was used to represent specific...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...


map background search result map search result map GeoTIFF image of shaded-relief bathymetry of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84) 2018 Hydrologic Data Summary for the Central Pine Barrens Region, Suffolk County, New York (ver. 2.0, February 2024) Occurrence of per- and polyfluoroalkyl substances, Long Island and New York City, New York DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012 Development: Development delineation: Fire Island, NY, 2014–2015 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2010 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012 2019 Hydrologic Data Summary for the Central Pine Barrens Region, Suffolk County, New York Soil-water-balance model archive for Long Island, NY, 1900-2019 Meteorological Data from Great South Bay at Watch Hill on Fire Island, New York, 2017 to 2022 Simulated Recharge Areas to Surface Waters and Public-Supply Wells with Travel Times Greater Than and Less Than 10 Years For Average 2005-2015 Conditions, Long Island, NY 2022 Hydrologic Data Summary for the Central Pine Barrens Region, Suffolk County, New York MODFLOW 6 Model Scenario used to Simulate Transient Stresses, Heads, and Flows in the Regional Aquifer System of Long Island, New York, 2005-2019 Meteorological Data from Great South Bay at Watch Hill on Fire Island, New York, 2017 to 2022 GeoTIFF image of shaded-relief bathymetry of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84) DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2010 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012 SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011 Development: Development delineation: Fire Island, NY, 2014–2015 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012 ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012 2018 Hydrologic Data Summary for the Central Pine Barrens Region, Suffolk County, New York (ver. 2.0, February 2024) 2019 Hydrologic Data Summary for the Central Pine Barrens Region, Suffolk County, New York 2022 Hydrologic Data Summary for the Central Pine Barrens Region, Suffolk County, New York Occurrence of per- and polyfluoroalkyl substances, Long Island and New York City, New York Soil-water-balance model archive for Long Island, NY, 1900-2019 Simulated Recharge Areas to Surface Waters and Public-Supply Wells with Travel Times Greater Than and Less Than 10 Years For Average 2005-2015 Conditions, Long Island, NY MODFLOW 6 Model Scenario used to Simulate Transient Stresses, Heads, and Flows in the Regional Aquifer System of Long Island, New York, 2005-2019