USGS Science⌕ Search

SEARCH · USGS Science

Results for “Natural Resource Data Series”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27Linked to original sources

EAARL Coastal Topography-Fire Island National Seashore, New York, 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 Fire Island National Seashore in New York, 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↗

EAARL Coastal Topography and Imagery-Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) topography, first-surface (FS) topography, and canopy-height (CH) datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Naval Live Oaks Area in Florida's Gulf Islands National Seashore, acquired June 30, 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 multispectral 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 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 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↗

EAARL Coastal Topography-Maryland and Delaware, 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 by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL. This project provides highly detailed and accurate datasets of a portion of the eastern Maryland and Delaware coastline beachface, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 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↗

EAARL coastal topography and imagery-Fire Island National Seashore, New York, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and 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 Fire Island National Seashore in New York, acquired on July 9 and August 3, 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 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 Cessna 310 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↗

EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and 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 Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 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↗

EAARL Coastal Topography-Eastern Louisiana Barrier Islands, Post-Hurricane Gustav, 2008: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived 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 Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Louisiana barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 6 and 7, 2008. 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 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 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↗

EAARL Coastal Topography-Eastern Florida, Post-Hurricane Jeanne, 2004: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived 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 Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired post-Hurricane Jeanne (September 2004 hurricane) on October 1, 2004. 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 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 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↗

Hydrology and water quality of Shell Lake, Washburn County, Wisconsin, with special emphasis on the effects of diversion and changes in water level on the water quality of a shallow terminal lake

Shell Lake is a relatively shallow terminal lake (tributaries but no outlets) in northwestern Wisconsin that has experienced approximately 10 feet (ft) of water-level fluctuation over more than 70 years of record and extensive flooding of nearshore areas starting in the early 2000s. The City of Shell Lake (City) received a permit from the Wisconsin Department of Natural Resources in 2002 to divert water from the lake to a nearby river in order to lower water levels and reduce flooding. Previous studies suggested that water-level fluctuations were driven by long-term cycles in precipitation, evaporation, and runoff, although questions about the lake’s connection with the groundwater system remained. The permit required that the City evaluate assumptions about lake/groundwater interactions made in previous studies and evaluate the effects of the water diversion on water levels in Shell Lake and other nearby lakes. Therefore, a cooperative study between the City and U.S. Geological Survey (USGS) was initiated to improve the understanding of the hydrogeology of the area and evaluate potential effects of the diversion on water levels in Shell Lake, the surrounding groundwater system, and nearby lakes. Concerns over deteriorating water quality in the lake, possibly associated with changes in water level, prompted an additional cooperative project between the City and the USGS to evaluate efeffects of changes in nutrient loading associated with changes in water levels on the water quality of Shell Lake. Numerical models were used to evaluate how the hydrology and water quality responded to diversion of water from the lake and historical changes in the watershed. The groundwater-flow model MODFLOW was used to simulate groundwater movement in the area around Shell Lake, including groundwater/surface-water interactions. Simulated results from the MODFLOW model indicate that groundwater flows generally northward in the area around Shell Lake, with flow locally converging toward the lake. Total groundwater inflow to Shell Lake is small (approximately 5 percent of the water budget) compared with water entering the lake from precipitation (83 percent) and surface-water runoff (13 percent). The MODFLOW model also was used to simulate average annual hydrologic conditions from 1949 to 2009, including effects of the removal of 3 billion gallons of water during 2003–5. The maximum decline in simulated average annual water levels for Shell Lake due to the diversion alone was 3.3 ft at the end of the diversion process in 2005. Model simulations also indicate that although water level continued to decline through 2009 in response to local weather patterns (local drought), the effects of the diversion decreased after the diversion ceased; that is, after 4 years of recovery (2006–9), drawdown attributable to the diversion alone decreased by about 0.6 ft because of increased groundwater inflow and decreased lake-water outflow to groundwater caused by the artificially lower lake level. A delayed response in drawdown of less than 0.5 ft was transmitted through the groundwater-flow system to upgradient lakes. This relatively small effect on upgradient lakes is attributed in part to extensive layers of shallow clay that limit lake/groundwater interaction in the area. Data collected in the lake indicated that Shell Lake is polymictic (characterized by frequent deep mixing) and that its productivity is limited by the amount of phosphorus in the lake. The lake was typically classified as oligotrophic-mesotrophic in June, mesotrophic in July, and mesotrophic-eutrophic in August. In polymictic lakes like Shell Lake, phosphorus released from the sediments is not trapped near the bottom of the lake but is intermittently released to the shallow water, resulting in deteriorating water quality as summer progresses. Because the productivity of Shell Lake is limited by phosphorus, the sources of phosphorus to the lake were quantified, and the response in water quality to changes in phosphorus inputs were evaluated by means of eutrophication models. During 2009, the total input of phosphorus to Shell Lake was 1,730 pounds (lb), of which 1,320 lb came from external sources (76 percent) and 414 lb came from internal loading from sediments in the lake (24 percent). The largest external source was from surface-water runoff, which delivered about 52 percent of the total phosphorus load compared with about 13 percent of the water input. The second largest source was from precipitation (wetfall and dryfall), which delivered 19 percent of the load compared to about 83 percent of the water input. Contributions from septic systems and groundwater accounted for about 3 and 2 percent, respectively. Increased runoff raises water levels in the lake but does not necessarily increase phosphorus loading because phosphorus concentrations in the tributaries decline during increased flow, possibly because of shorter retention times in upstream wetlands. Phosphorus loading to the lake in 2009 represented what occurred after a series of dry years; therefore, this information was combined with data from 2011, a wet year, to estimate phosphorus loading during a range of hydrologic conditions by estimating loading from each component of the phosphorus budget for each year from 1949 to 2011. Comparisons of historical water-quality records with historical water levels and applications of a hydrodynamic model (Dynamic Lake Model, DLM) and empirical eutrophication models were used to understand how changes in water level and the coinciding changes in phosphorus loading affect the water quality of Shell Lake. DLM simulations indicate that large changes in water level (approximately 10 ft) affect the persistence of stratification in the lake. During periods with low water levels, the lake is a well-mixed, polymictic system, with water quality degrading slightly as summer progresses. During periods with high water levels, the lake is more stratified, and phosphorus from internal loading is trapped in the hypolimnion and released later in summer, which results in more extreme seasonality in water quality and better clarity in early summer. Results of eutrophication model simulations using a range in external phosphorus inputs illustrate how water quality in Shell Lake (phosphorus and chlorophyll a concentrations and Secchi depths) responds to changes in external phosphorus loading. Results indicate that a 50-percent reduction in external loading from that measured in 2009 would be required to change phosphorus concentrations from 0.018 milligram per liter (mg/L) (measured in 2009) to 0.012 mg/L (estimated for the mid-1800s from analysis of diatoms in sediment cores). Such reductions in phosphorus loading cannot be accomplished by targeting septic systems or internal loading alone because septic systems contribute only about 3 percent of the phosphorus input to the lake, and internal loading from the sediments of Shell Lake contributes only about 25 percent of phosphorus input. Complete elimination of phosphorus from septic systems and internal loading would decrease the phosphorus concentrations in the lake by 0.003–0.004 mg/L. Therefore, reducing phosphorus concentration in the lake more than by 0.004 mg/L requires decreasing phosphorus loading from surface-water contributions, primarily runoff to the lake. Reconstructed changes in water quality from 1860 to 2010, based on changes in the diatom communities archived in the sediments and eutrophication model simulations, suggest that anthropogenic changes in the watershed (sawmill construction in 1881; the establishment of the village of Shell Lake; and land-use changes in the 1920s, including increased agriculture) had a much larger effect on water quality than the natural changes associated with fluctuations in water level. Although the effects of natural changes in water level on water quality appear to be small, changes in water level do have a modest effect on water quality, primarily manifested as small improvements during higher water levels. Fluctuations in water level, however, have a larger effect on the seasonality of water-quality patterns, with better water quality, especially increased Secchi depths, in early summer during years with high water levels.

Wisconsin↗

Community estimate of global glacier mass changes from 2000 to 2023

Glaciers are indicators of ongoing anthropogenic climate change 1 . Their melting leads to increased local geohazards 2 , and impacts marine 3 and terrestrial 4 , 5 ecosystems, regional freshwater resources 6 , and both global water and energy cycles 7 , 8 . Together with the Greenland and Antarctic ice sheets, glaciers are essential drivers of present 9 , 10 and future 11 , 12 , 13 sea-level rise. Previous assessments of global glacier mass changes have been hampered by spatial and temporal limitations and the heterogeneity of existing data series 14 , 15 , 16 . Here we show in an intercomparison exercise that glaciers worldwide lost 273 ± 16 gigatonnes in mass annually from 2000 to 2023, with an increase of 36 ± 10% from the first (2000–2011) to the second (2012–2023) half of the period. Since 2000, glaciers have lost between 2% and 39% of their ice regionally and about 5% globally. Glacier mass loss is about 18% larger than the loss from the Greenland Ice Sheet and more than twice that from the Antarctic Ice Sheet 17 . Our results arise from a scientific community effort to collect, homogenize, combine and analyse glacier mass changes from in situ and remote-sensing observations. Although our estimates are in agreement with findings from previous assessments 14 , 15 , 16 at a global scale, we found some large regional deviations owing to systematic differences among observation methods. Our results provide a refined baseline for better understanding observational differences and for calibrating model ensembles 12 , 16 , 18 , which will help to narrow projection uncertainty for the twenty-first century 11 , 12 , 18 .

Nature↗

EAARL Coastal Topography-Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

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; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Mississippi and Alabama barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 8, 2008. 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 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 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↗

EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and submerged 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 Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Chandeleur Islands, acquired March 3, 2010. 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 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 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↗

Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities

This report is part of the NOAA Mesophotic and Deep Benthic Communities (MDBC) Series of publications that share the results of work conducted by the Deepwater Horizon MDBC restoration projects. The 2010 Deepwater Horizon oil spill was an unprecedented event. Approximately 3.2 million barrels of oil were released into the deep ocean over nearly three months. The plume of oil moved throughout the water column, formed surface slicks that cumulatively covered an area the size of Virginia, and washed oil onto at least 1,300 miles of shoreline habitats. More than 770 square miles (2,000 square kilometers) of deep benthic habitat surrounding the Deepwater Horizon wellhead and 4-square miles of the Pinnacles mesophotic reef complex, located at the edge of the continental shelf, were injured by the oil spill. Under the Oil Pollution Act, state and federal natural resource trustees conducted a Natural Resource Damage Assessment (NRDA). The Trustees assessed damages, quantifying the unprecedented injuries to natural resources and lost services. They also developed a programmatic restoration plan to restore injured resources and compensate the public for lost services. In April 2016, a settlement was finalized that included up to $8.8 billion in funding for the Deepwater Horizon Trustees to restore the natural resource injuries caused by the oil spill as described in their programmatic restoration plan, Final Programmatic Damage Assessment and Restoration Plan and Final Programmatic Environmental Impact Statement. The Deepwater Horizon Open Ocean Trustee Implementation Group is responsible for restoring natural resources and their services within the Open Ocean Restoration Area that were injured by the oil spill. The Open Ocean Trustees include NOAA, Department of the Interior, U.S. Environmental Protection Agency, and U.S. Department of Agriculture. In 2019, the Open Ocean Trustee Implementation Group committed more than $126 million to implement four restoration projects to address the injury to MDBC. The MDBC projects are: mapping, Ground-truthing, and Predictive Habitat Modeling; Habitat Assessment and Evaluation; Coral Propagation Technique Development; and Active Management and Protection. NOAA and the Department of the Interior are implementing the projects, in cooperation with a range of partners, over eight years. Together, the projects take a phased approach to meet the challenges involved in restoring deep-sea habitats. Challenges to restoration include a limited scientific understanding of these communities, limited experience with restoration at the depths at which these communities occur, and remote locations that limit accessibility. More information about Deepwater Horizon restoration and the MDBC restoration projects is available at: www.gulfspillrestoration.noaa.gov.

Gulf of Mexico↗

Hydrogeology of the Cliff House Sandstone in the San Juan structural basin, New Mexico, Colorado, Arizona, and Utah

This report is one in a series resulting from the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) study of the San Juan structural basin that began in October 1984. Previous reports in the series describe the hydrogeology of the Dakota Sandstone (Craigg and others, 1989), Point Lookout Sandstone (Craigg and others, 1990), Morrison Formation (Dam and others, 1990), Gallup Sandstone (Kernodle and others, 1989), and Menefee Formation (Levings and others, 1990) in the San Juan structural basin. The purposes of the RASA (Welder, 1986) are to: (1) Define and evaluate the aquifer system; (2) assess the effects of past, present, and potential ground-water use on aquifers and streams; and (3) determine the availability and quality of ground water. This report summarizes information on the geology and the occurrence and quality of water in the Cliff House Sandstone, one of the primary water-bearing units in the regional aquifer system. Data used in this report were collected during the study or were derived from existing records in the U.S. Geological Survey's computerized National Water Information System (NWIS) data base, the Petroleum Information Corporation's data base, and the Dwight's ENERGYDATA Inc. BRIN data base. Although all data available for the Cliff House Sandstone were considered in formulating the discussions in the text, not all those data could be plotted on the illustrations. The San Juan structural basin is in New Mexico, Colorado, Arizona, and Utah and has an area of about 21,600 square miles (fig. 1). The structural basin is about 140 miles wide and about 200 miles long. The study area is that part of the structural basin that contains rocks of Triassic or younger age and, therefore, is less extensive than the structural basin. Triassic through Tertiary sedimentary rocks are emphasized in this study because the major aquifers in the basin are present in these rocks. The study area is about 140 miles wide (about the same as the structural basin), 180 miles long, and has an area of about 19,400 square miles. Altitudes in the study area range from about 4,500 feet in San Juan County, Utah, to about 11,000 feet in Cibola County, New Mexico. Annual precipitation in the high mountainous areas along the north and east margins of the basin is as much as 45 inches, whereas annual precipitation in the lower altitude, central basin is generally less than 8 inches. Mean annual precipitation in the study area is about 12 inches. Data obtained from documents published by the U.S. Bureau of the Census, 1980 and 1985, were used to estimate the population of the study area. The population of the study area in 1970 was estimated to be about 134,000. The population rose to about 194,000 in 1980, 212,000 in 1982, 221,000 in 1984, and then fell to about 210,000 in 1985. The economy of the basin is supported by exploration and development of petroleum, natural gas, coal, and uranium resources; urban enterprise, farming and ranching; tourism; and recreation. The rise and fall in population were related to changes in the economic strength of the mining, petroleum, and natural-gas industries, and support services. Uranium mining and milling activities grew rapidly until the late 1970's when most uranium-mining activity ended in the study area. Likewise, the oil and gas industry prospered until about 1983 and then declined rapidly, also affecting many jobs in support industries.

Arizona, Colorado, New Mexico, Utah↗

Hydrogeology of the Point Lookout Sandstone in the San Juan structural basin, New Mexico, Colorado, Arizona, and Utah

This report is one in a series resulting from the U.S. Geological Survey's Regional Aquifer-System Analysis (RASA) study of the San Juan structural basin that began in October 1984. Previous reports in the series describe the hydrogeology of the Dakota Sandstone (Craigg and others, 1989), Morrison Formation (Dam and others, 1990), Gallup Sandstone (Kernodle and others, 1989), Menefee Formation (Levings and others, 1990), and Cliff House Sandstone (Thorn and others, 1990), in the San Juan structural basin. The purposes of the RASA (Welder, 1986) are to: (1) Define and evaluate the aquifer system; (2) assess the effects of past, present, and potential ground-water use on aquifers and streams; and (3) determine the availability and quality of ground water. This report summarizes information on the geology and the occurrence and quality of water in the Point Lookout Sandstone, one of the primary water-bearing units in the regional aquifer system. Data used in this report were collected during the study or were derived from existing records in the U.S. Geological Survey's computerized National Water Information System (NWIS) data base, the Petroleum Information Corporation's database, and the Dwight's ENERGYDATA Inc. BRIN data base. Although all data available for the Point Lookout Sandstone were considered in formulating the discussions in the text, not all those data could be plotted on the illustrations. The San Juan structural basin is in New Mexico, Colorado, Arizona, and Utah and has an area of about 21,600 square miles (fig. 1). The structural basin is about 140 miles wide and about 200 miles long. The study area is that part of the structural basin that contains rocks of Triassic or younger age and, therefore, is less areally extensive than the structural basin. Triassic through Tertiary sedimentary rocks are emphasized in this study because the major aquifers in the basin are present in these rocks. The study area is about 140 miles wide (about the same as the structural basin), 180 miles long, and has an area of about 19,400 square miles. Altitudes in the study area range from about 4,500 feet in San Juan County, Utah, to about 11,000 feet in Cibola County, New Mexico. Annual precipitation in the high mountainous areas along the north and east margins of the basin is as much as 45 inches, whereas annual precipitation in the lower altitude, central basin is generally less than 8 inches. Mean annual precipitation in the study area is about 12 inches. Data obtained from documents published by the U.S. Bureau of the Census, 1980 and 1985, were used to estimate the population of the study area. The population of the study area in 1970 was estimated to be about 134,000. The population rose to about 194,000 in 1980, 212,000 in 1982, 221,000 in 1984, and then fell to about 210,000 in 1985. The economy of the basin is supported by exploration and development of petroleum, natural gas, coal, and uranium resources; urban enterprise, farming "and ranching; tourism; and recreation. The rise and fall in population were related to changes in the economic strength of the mining, petroleum, and natural-gas industries, and support services. Uranium mining and milling activities grew rapidly until the late 1970's when most uranium-mining activity ended in the study area. Likewise, the oil and gas industry prospered until about 1983 and then declined rapidly, also affecting many jobs in support industries.

Arizona, Colorado, New Mexico, Utah↗

Data summary report: Unregulated contaminants monitoring project

The Drinking Water Protection Section of the Minnesota Department of Health conducted reconnaissance monitoring of selected public water systems in Minnesota. Funding was obtained primarily from the Environment and Natural Resources Trust Fund. Sampling was conducted in 2019 and 2021. Laboratory analysis of samples was conducted for a variety of different contaminants of emerging concern (CECs), including selected pharmaceuticals, pesticides, PFAS, wastewater indicators and other parameters chosen for the physical and land use setting surrounding the sampling points. Sampling site and parameter selection were designed with several goals, as follows: Characterize occurrence and distribution of selected CECs in settings where such chemicals are most likely to be present; Determine if any such occurrences represent a public health concern; Compare results from coupled source water and finished (i.e., treated) water samples at public water system sites where such sampling is feasible; Assess if results from geologically vulnerable (sensitive subject to rapid recharge) and geologically non-vulnerable settings differ significantly. 306 samples were collected as part of the study, from three networks of public water systems differentiated on the basis of source water type (i.e., surface water or groundwater) and land use environment (agricultural and wastewater influenced). This report provides a preliminary, qualitative evaluation of the results. Additionally, more rigorous research will be conducted on these water quality data to evaluate the below findings in more detail. High-level findings from this assessment include the following: Very few samples exceeded health-based guidance for CECs; o When this occurred, MDH staff conducted follow up sampling at the system and provided technical advice about managing the situation. Only a fraction of the CECs analyzed were detected; o Of the 522 different CECs analyzed in the water samples, 161 were detected in one or more samples; o Additionally, most detections were at low levels; Among the CEC classes included in the analytical work, pesticides and PFAS were generally detected at a greater frequency than other CECs; o See Executive Summary Figure 1. The ten most commonly detected individual compounds include: o Tribromomethane, or bromoform, (a disinfection by-product) (70% of sites where analyzed); o norgestrel (a pharmaceutical) (69% of sites where analyzed); o lithium (68% of sites where analyzed); o Metolachlor SA (52%), Deethylatrazine (49%), atrazine (45%), and deisopropylatrazine (31%) (pesticides); o PFBA (44%) and PFHxS (27%) (PFAS compounds); and o 5-methyl benzotriazole (29%) (a benzotriazole). Some CECs were detected more frequently in samples collected from surface waters than those collected from groundwater sources; CEC concentrations were generally higher in vulnerable settings compared to nonvulnerable settings; Whether CECs were detected more frequently in the source water or finished water varied by CEC class. For example, o Benzotriazoles and pharmaceuticals were more frequently detected in source water samples than finished water samples; and o Tribromomethane, or bromoform, a common disinfection by-product, was more frequently found in finished water samples than in source water samples. This work prompted a series of programmatic changes and innovations: A response framework was established for helping the program and public water systems manage detections of unregulated CECs in drinking water; Results were forwarded to the program within MDH responsible for developing healthbased guidance in order to nominate specific compounds found in drinking water but for which limited or no risk advice is available; MDH is seeking support from the Clean Water Council to support the establishment of permanent capacity within the Drinking Water Protection Section to continue sampling efforts of this type.

Minnesota↗

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Imperviousness

This data set represents the mean percent impervious surface from the Imperviousness Layer of the National Land Cover Dataset 2001 (LaMotte and Wieczorek, 2010), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents imperviousness for the conterminous United States for 2001. The Imperviousness Layer of the National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Data Series↗

Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Land Use and Land Cover

This data set represents the estimated area of land use and land cover from the National Land Cover Dataset 2001 (LaMotte, 2008), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents land use and land cover for the conterminous United States for 2001. The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus dataset is organized by 18 Production Units that cover the conterminous United States. The NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, Crawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains NHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, contains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering the Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production Units 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains NHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, contains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus Production Unit 18.

Data Series↗

User's guide to revised method-of-characteristics solute-transport model (MOC--version 31)

The U.S. Geological Survey computer model to simulate two-dimensional solute transport and dispersion in ground water (Konikow and Bredehoeft, 1978; Goode and Konikow, 1989) has been modified to improve management of input and output data and to provide progressive run-time information. All opening and closing of files are now done automatically by the program. Names of input data files are entered either interactively or using a batch-mode script file. Names of output files, created automatically by the program, are based on the name of the input file. In the interactive mode, messages are written to the screen during execution to allow the user to monitor the status and progress of the simulation and to anticipate total running time. Information reported and updated during a simulation include the current pumping period and time step, number of particle moves, and percentage completion of the current time step. The batch mode enables a user to run a series of simulations consecutively, without additional control. A report of the model's activity in the batch mode is written to a separate output file, allowing later review. The user has several options for creating separate output files for different types of data. The formats are compatible with many commercially available applications, which facilitates graphical postprocessing of model results. Geohydrology and Evaluation of Stream-Aquifer Relations in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern Alabama, Northwestern Florida, and Southwestern Georgia By Lynn J. Torak, Gary S. Davis, George A. Strain, and Jennifer G. Herndon Abstract The lower Apalachieola-Chattahoochec-Flint River Basin is underlain by Coastal Plain sediments of pre-Cretaceous to Quaternary age consisting of alternating units of sand, clay, sandstone, dolomite, and limestone that gradually thicken and dip gently to the southeast. The stream-aquifer system consism of carbonate (limestone and dolomite) and elastic sediments, which define the Upper Floridan aquifer and Intermediate system, in hydraulic connection with the principal rivers of the basin and other surface-water features, natural and man made. Separate digital models of the Upper Flori-dan aquifer and Intermediate system were constructed by using the U.S. Geological Survey's MODular Finite-Element model of two dimensional ground-water flow, based on concep- tualizations of the stream-aquifer system, and calibrated to drought conditions of October 1986. Sensitivity analyses performed on the models indicated that aquifer hydraulic conductivity, lateral and vertical boundary flows, and pumpage have a strong influence on groundwater levels. Simulated pumpage increases in the Upper Floridan aquifer, primarily in the Dougherty Plain physiographic district of Georgia,. caused significant reductions in aquifer discharge to streams that eventually flow to Lake Seminole and the Apalachicola River and Bay. Simulated pumpage increases greater than 3 times the October 1986 rates caused drying ofsome stream reaches and parts of the Upper Floridan aquifer in Georgia. Water budgets prepared from simulation results indicate that ground- water discharge to streams and recharge by horizontal and vertical flow are the principal mechanisms for moving water through the flow system. The potential for changes in ground-water quality is high in areas where chemical constituents can be mobilized by these mechanisms. Less than 2 percent of ground-water discharge to streams comes from the Intermediate system; thus, it plays a minor role in the hydrodynamics of the stream- aquifer system.

Water-Resources Investigations Report↗