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Research about Georgia, North Carolina, South Carolina

Source-linked reports with geographic coverage including Georgia, North Carolina, South Carolina.

At least 19 recordsLinked to original sources
USGS2026

Methods for estimating selected low-flow frequency and mean annual flow statistics at gaged and ungaged locations on streams in Georgia, North Carolina, and South Carolina

The U.S. Geological Survey, in cooperation with the Georgia Department of Natural Resources (Environmental Protection Division), North Carolina Department of Environmental Quality (Division of Water Resources), North Carolina Department of Public Safety (Office of Recovery and Resiliency), and South Carolina Department of Environmental Services, updated low-flow frequency, mean annual flow, and flow-duration statistics at 843 streamgages in and near Georgia, North Carolina, and South Carolina. The low-flow frequency statistics are annual minimum 1-day average flow with a 10-year recurrence interval (1Q10), annual minimum 7-day average flow for 2- and 10-year recurrence intervals (7Q2 and 7Q10, respectively), and annual minimum 30-day average flow with 2- and 3-year recurrence intervals (30Q2 and 30Q3, respectively). Monthly 1Q10 and 7Q10, and W7Q10 flow statistics for the winter period (November–March) also are presented. By using data from 604 of the streamgages on streams with streamflows that are not substantially affected by regulation or diversion and are not tidally influenced, regional regression equations were developed to predict flow statistics with prediction intervals at ungaged locations on streams with those same criteria. The regional regression analysis included data from 132 streamgages from adjacent States Alabama, Florida, Tennessee, and Virginia. The final regional regression equations include variables such as drainage area, streamflow variability, precipitation, percentage of impervious area, and percentage of the basin in various ecoregions. The low-flow statistics for the streamgages analyzed and the regional regression equations will be integrated into the U.S. Geological Survey StreamStats application ( https://www.usgs.gov/streamstats ) for Georgia, North Carolina, and South Carolina. StreamStats generates basin characteristics needed to compute low-flow frequency statistics for ungaged locations. A trend analysis of annual minimum 7-day average flows was done for 78 streamgages with at least 30 years of continuous record. Trends were evaluated for 30-, 50‑, 70-, and 90-year periods, ending in climate year 2021, and independence and short- and long-term persistence assumptions were considered. For all trend analysis assumptions, most streamgages did not exhibit significant trends in annual minimum 7-day average flows. Trends in annual precipitation and air temperature were similarly evaluated for the period 1895–2021 to assess the variability of climate for Georgia, North Carolina, and South Carolina.

Georgia, North Carolina, South Carolina↗
USGS2026

Habitat and landscape variables affecting Corbicula fluminea presence in the upper Savannah River drainage (USA)

Aquatic invasive species ( AIS ) are amongst the greatest threats to native aquatic biodiversity. These introduced species often thrive in human-altered environments and spread through human-mediated pathways to invade new watersheds. Corbicula fluminea is a freshwater bivalve native to southeastern Asia first introduced in North America in Seattle, WA, in 1938 and has spread to nearly every major watershed in the southeastern United States. In the present study, we use an information theoretic framework to compare landscape and stream habitat variables associated with C. fluminea presence across five HUC10 watersheds in the upper Savannah River basin of South Carolina and Georgia, USA. Predictive models included landscape-level and site-level habitat variables associated with agricultural, developed, and forested landscapes. Models with variables associated with forested and developed landscapes were the top performing models based on AICc values. In top performing models C. fluminea presence was positively correlated with increased stream width, but negatively correlated with substrates dominated by cobble. Lower performing models highlight positive correlations with the presence of upstream reservoirs and increased developed landscape surrounding the site. Identification of habitat and landscape correlates with invasive species presence may lead to more efficient introduction monitoring efforts for conservation managers.

Georgia, North Carolina, South Carolina↗
USGS2025

Timing of and pressure-temperature constraints on deformation in the Toxaway dome, eastern Blue Ridge: Evidence for continuous deformation from the Neoacadian orogeny to the Alleghanian orogeny

Many mountain belts are built through repeated collision, and in the case of orogenies closely spaced in time, determining when one orogeny ends and another begins can be challenging. The southern Appalachian mountains were formed by three mountain-building events closely spaced in time, including the Taconic (ca. 480–440 Ma), Neoacadian (ca. 375–340 Ma), and Alleghanian (ca. 330–265 Ma) orogenies. Notably, the end of the Neoacadian and the beginning of the Alleghanian are only separated by ~10 m.y., and some published dates record deformation and metamorphism in the eastern Blue Ridge during this interval, blurring the boundary between these two discrete events. The Toxaway dome, located along the North Carolina–South Carolina, USA, border at the eastern edge of the eastern Blue Ridge, is a structural dome cored by Mesoproterozoic Toxaway Gneiss and surrounded by the younger Tallulah Falls Formation. Previous ages constraints from the Toxaway dome (343 and 338 Ma U-Pb zircon ages) make it an ideal location to explore whether there was continuous deformation during this period of supposed quiescence between the Neoacadian and Alleghanian orogenies. We used optical microscopy and electron backscatter diffraction in quartz to determine deformation temperatures, thermobarometry to determine metamorphic pressure-temperature conditions, and monazite petrochronology to determine the timing of deformation. Quartz and feldspar recrystallization fabrics parallel to dome-defining fabrics indicate deformation occurred at amphibolite-facies conditions, which is corroborated by our pressure-temperature estimates of 0.67–0.8 ± 0.12 GPa and 661–689 ± 25 °C. Monazite grains that record the timing of reactions of garnet growth and breakdown range from 342 ± 4.8 Ma to 296 ± 10.8 Ma, bridging the interval between the Neoacadian and Alleghanian orogenies. Three samples from the nearby Tallulah Falls dome, which occupies a similar structural position along the edge of the eastern Blue Ridge in Georgia, record monazite dates of 334 ± 4.2 Ma to 304 ± 4.8 Ma, indicating there was tectonic activity in this region before the commonly defined beginning of the Alleghanian orogeny. We propose (1) there was no period of quiescence between the Neoacadian and Alleghanian orogenies in the eastern Blue Ridge, and (2) deformation during this time was at higher temperatures and pressures than previously reported.

Georgia, North Carolina, South Carolina↗
USGS2023

Effects of impoundments on selected flood-frequency and daily mean streamflow characteristics in Georgia, South Carolina, and North Carolina

The U.S. Geological Survey (USGS) has a long history of working cooperatively with the South Carolina Department of Transportation to develop methods for estimating the magnitude and frequency of floods for rural and urban streams that have minimal to no regulation or tidal influence. As part of those previous investigations, flood-frequency estimates also have been generated for selected streamgages on regulated streams. This report assesses the effects of impoundments on flood-frequency characteristics by comparing annual exceedance probability (AEP) streamflows from pre- and post-regulated (before and after impoundment) periods at 18 long-term USGS streamgages, which is defined as a streamgage with 30 or more years of record, in Georgia, South Carolina, and North Carolina. For an assessment of how differences in such statistics can be influenced by period of record and hydrologic conditions captured in those records, which could be considered as natural variability, AEP streamflows at an additional 18 long-term USGS streamgages that represent unregulated conditions in those three States were computed and compared for the first and last half of those records. Of the 18 long-term streamgages with pre- and post-regulated periods of record, 17 streamgages had both peak streamflows and daily mean streamflows available. To further assess how impoundments may influence a broader range of streamflow characteristics, The Nature Conservancy’s Indicators of Hydrologic Alteration software was used to compare selected streamflow characteristics generated from daily mean streamflows for pre- and post-regulated periods of record at 16 of those long-term streamgages. For comparison of the natural variability of such streamflow statistics, two periods of record (first half and last half) also were compared at 17 of the 18 long-term streamgages on unregulated streams. The remaining long-term streamgage on an unregulated stream included in this report had only annual peak streamflows and, therefore, was not included in the hydrologic alteration analysis. In a separate USGS investigation completed in 2023, flood-frequency statistics for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP streamflows (also known as the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence interval streamflows, respectively) were computed for 72 streamgages on regulated streams in Georgia, South Carolina, and North Carolina. Of those 72 streamgages, 29 streamgages were found to be redundant, which is a situation where the drainage basin of one streamgage is contained inside another (nested) and the two basins are of similar size. For the remaining 43 streamgages, 39 had basins where 75 percent or more of the drainage area was above the Fall Line. Those 39 streamgages were included in this investigation to develop regional regression equations that can be used to estimate the flood-frequency statistics at ungaged locations on regulated streams in Georgia, South Carolina, and North Carolina in which 75 percent or more of the drainage basin is located above the Fall Line. The flood-frequency regression equations are functions of drainage area and maximum storage index computed for upstream reservoirs.

Georgia, North Carolina, South Carolina↗
USGS2023

Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Summary

Reliable flood-frequency estimates are important for hydraulic structure design and floodplain management in Georgia, South Carolina, and North Carolina. Annual peak streamflows (hereafter, referred to as peak flows) measured at 965 U.S. Geological Survey streamgages were used to compute flood-frequency estimates with annual exceedance probabilities (AEPs) of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent. These AEPs correspond to flood-recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A subset of these streamgages (801) were used to develop equations to predict the AEP flood flows at ungaged stream locations. This study was completed by the USGS in cooperation with the Georgia, South Carolina, and North Carolina Departments of Transportation and the North Carolina Department of Crime Control and Public Safety, and the results are summarized in this fact sheet. The complete results and the supporting data are presented in the companion scientific investigations report and data release.

Georgia, North Carolina, South Carolina↗
USGS2023

Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Results

Reliable estimates of the magnitude and frequency of floods are an important part of the framework for hydraulic-structure design and flood-plain management in Georgia, South Carolina, and North Carolina. Annual peak flows measured at U.S. Geological Survey streamgages are used to compute flood‑frequency estimates at those streamgages. However, flood‑frequency estimates also are needed at ungaged stream locations. A process known as regionalization was used to develop regression equations to estimate the magnitude and frequency of floods at ungaged locations. A multistate approach was used to update estimates of the magnitude and frequency of floods in rural, ungaged basins in Georgia, South Carolina, and North Carolina. Annual peak-flow data through September 2017 were analyzed for 965 streamgages with 10 or more years of data on rural streams in Georgia, South Carolina, North Carolina, and adjacent parts of Alabama, Florida, Tennessee, and Virginia. Flood‑frequency estimates of the 50‑, 20‑, 10‑, 4‑, 2‑, 1‑, 0.5‑, and 0.2‑percent annual exceedance probability streamflows, which correspond to flood-recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively, were computed for the 965 streamgages following national guidelines. As part of the computation of flood‑frequency estimates for the streamgages, an updated value for the regional skew coefficient (0.048) was developed using a Bayesian generalized least squares regression model. The new regional skew has a mean square error or average variance of prediction of 0.092. Additionally, basin characteristics for these stations were computed using a geographical information system. Exploratory analyses on the 965 streamgages confirmed the five hydrologic regions for Georgia, South Carolina, and North Carolina defined in a previous rural flood‑frequency study. From the 965 streamgages, streamgages with 30 or more years of record were used to complete a peak-flow trend analysis. Of the 965 streamgages, 164 streamgages were found to be redundant and were excluded from the regional regression analyses. Data from the remaining 801 streamgages (292 in Georgia, 75 in South Carolina, 303 in North Carolina, 15 in Alabama, 12 in Florida, 39 in Tennessee, and 65 in Virginia) were used in a regional regression analysis relating basin characteristics to flood‑frequency estimates. This analysis, based on generalized least squares regression, was used to develop a set of predictive equations to estimate the 50‑, 20‑, 10‑, 4‑, 2‑, 1‑, 0.5‑, and 0.2‑percent annual exceedance probability streamflows for rural, ungaged basins in Georgia, South Carolina, and North Carolina. The final set of predictive equations are all functions of drainage area and percentage of the drainage basin within each of the five hydrologic regions. Average errors of prediction for these regression equations range from 35.8 to 44.4 percent. Flood‑frequency estimates also were computed for 72 regulated (for example, a streamgage where flow is altered by a dam or weir) streamgages in Georgia, South Carolina, and North Carolina with 20 or more years of post-regulation record using data through water year 2019. The water year is the annual period from October 1 through September 30 and is designated by the year in which the period ends. Of the 72 regulated streamgages, 18 had pre-regulated periods of record that also were analyzed as part of this study. Flow adjustments were applied to historic peaks and large floods from the pre-regulated period, if available, for use in the post-regulation frequency analysis. Estimates of large floods provide valuable information in frequency analysis and, thus, were included in the post-regulation frequency analysis.

Georgia, North Carolina, South Carolina↗
USGS2021

Modeling distribution of endemic Bartram’s Bass Micropterus sp. cf. coosae: Disturbance and proximity to invasion source increase hybridization with invasive Alabama Bass

“Bartram’s Bass” Micropterus sp. cf. coosae is endemic to the upper Savannah River basin of the southeastern United States and is threatened by hybridization with invasive Alabama Bass Micropterus henshalli . Bartram’s Bass have been functionally extirpated from reservoirs, and hybrid individuals have been detected in several tributaries. However, the extent of introgression in tributaries is currently unknown. Our objectives were to (1) assess the distribution of Bartram’s Bass, native Largemouth Bass M . salmoides , invasive Alabama Bass, and their hybrids in streams of the upper Savannah River basin and (2) quantify effects of abiotic variables on the distribution of each species. We sampled 154 locations in 2017 and 2018 and assigned genetic identity using hydrolysis probes and microsatellites. We used conditional inference trees to quantify variables affecting the occurrence of each species and hybrids. We observed widespread hybridization across the basin. Pure Bartram’s Bass were collected at 27% (42) of sites, among which only 12 sites contained pure Bartram’s Bass and no other congeners. Thirty sites where pure Bartram’s Bass were collected contained hybrids. In the montane Blue Ridge ecoregion, occurrence of pure Bartram’s Bass was negatively affected by low levels of local-scale developed land cover. In the lower-relief Piedmont ecoregion, pure Bartram’s Bass were positively associated with watershed-scale forest land cover and stream gradient. Distance from a reservoir was positively associated with occurrence of pure Bartram’s Bass in both ecoregions. Pure Bartram’s Bass are likely to occur with high probability in only 16% of nonimpounded stream segments; this represents a conservative estimate, and the true number is likely lower. However, future work accounting for incomplete detection of Bartram’s Bass will help to improve confidence in true extirpations. Conservation efforts may be more successful if implemented on stream segments farther from reservoirs or upstream of dispersal barriers preventing colonization of Alabama Bass.

Georgia, North Carolina, South Carolina↗
USGS2015

Decision support system for optimally managing water resources to meet multiple objectives in the Savannah River Basin

Managers of large river basins face conflicting demands for water resources such as wildlife habitat, water supply, wastewater assimilative capacity, flood control, hydroelectricity, and recreation. The Savannah River Basin, for example, has experienced three major droughts since 2000 that resulted in record low water levels in its reservoirs, impacting dependent economies for years. The Savannah River estuary contains two municipal water intakes and the ecologically sensitive freshwater tidal marshes of the Savannah National Wildlife Refuge. The Port of Savannah is the fourth busiest in the United States, and modifications to the harbor to expand ship traffic since the 1970s have caused saltwater to migrate upstream, reducing the freshwater marsh’s acreage more than 50 percent. A planned deepening of the harbor includes flow-alteration features to minimize further migration of salinity, whose effectiveness will only be known after all construction is completed. One of the challenges of large basin management is the optimization of water use through ongoing regional economic development, droughts, and climate change. This paper describes a model of the Savannah River Basin designed to continuously optimize regulated flow to meet prioritized objectives set by resource managers and stakeholders. The model was developed from historical data using machine learning, making it more accurate and adaptable to changing conditions than traditional models. The model is coupled to an optimization routine that computes the daily flow needed to most efficiently meet the water-resource management objectives. The model and optimization routine are packaged in a decision support system that makes it easy for managers and stakeholders to use. Simulation results show that flow can be regulated to substantially reduce salinity intrusions in the Savannah National Wildlife Refuge, while conserving more water in the reservoirs. A method for using the model to assess the effectiveness of the flow-alteration features after the deepening also is demonstrated.

Georgia, North Carolina, South Carolina↗
USGS2014

Estimating flood magnitude and frequency for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011

Reliable estimates of the magnitude and frequency of floods are essential for the design of transportation and water-conveyance structures, flood insurance studies, and flood-plain management. Flood-frequency estimates are particularly important in densely populated urban areas. The U.S. Geological Survey (USGS) used a multistate approach to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina (Feaster and others, 2014). The multistate approach has the advantage over a single state approach of increasing the number of streamflow-gaging station (streamgages) available for analysis, expanding the geographical coverage that would allow for application of regional regression equations across state boundaries, and building on a previous flood-frequency investigation of rural streamgages in the Southeastern United States. This investigation was funded as part of a cooperative program of water-resources investigations between the USGS, the South Carolina Department of Transportation, and the North Carolina Department of Transportation. In addition, much of the data and information for the Georgia streamgages was funded through a similar cooperative program with the Georgia Department of Transportation.

Georgia, North Carolina, South Carolina↗
USGS2014

Methods for estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina, 2011

Reliable estimates of the magnitude and frequency of floods are essential for the design of transportation and water-conveyance structures, flood-insurance studies, and flood-plain management. Such estimates are particularly important in densely populated urban areas. In order to increase the number of streamflow-gaging stations (streamgages) available for analysis, expand the geographical coverage that would allow for application of regional regression equations across State boundaries, and build on a previous flood-frequency investigation of rural U.S Geological Survey streamgages in the Southeast United States, a multistate approach was used to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina. The at-site flood-frequency analysis of annual peak-flow data for urban and small, rural streams (through September 30, 2011) included 116 urban streamgages and 32 small, rural streamgages, defined in this report as basins draining less than 1 square mile. The regional regression analysis included annual peak-flow data from an additional 338 rural streamgages previously included in U.S. Geological Survey flood-frequency reports and 2 additional rural streamgages in North Carolina that were not included in the previous Southeast rural flood-frequency investigation for a total of 488 streamgages included in the urban and small, rural regression analysis. The at-site flood-frequency analyses for the urban and small, rural streamgages included the expected moments algorithm, which is a modification of the Bulletin 17B log-Pearson type III method for fitting the statistical distribution to the logarithms of the annual peak flows. Where applicable, the flood-frequency analysis also included low-outlier and historic information. Additionally, the application of a generalized Grubbs-Becks test allowed for the detection of multiple potentially influential low outliers. Streamgage basin characteristics were determined using geographical information system techniques. Initial ordinary least squares regression simulations reduced the number of basin characteristics on the basis of such factors as statistical significance, coefficient of determination, Mallow’s Cp statistic, and ease of measurement of the explanatory variable. Application of generalized least squares regression techniques produced final predictive (regression) equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability flows for urban and small, rural ungaged basins for three hydrologic regions (HR1, Piedmont–Ridge and Valley; HR3, Sand Hills; and HR4, Coastal Plain), which previously had been defined from exploratory regression analysis in the Southeast rural flood-frequency investigation. Because of the limited availability of urban streamgages in the Coastal Plain of Georgia, South Carolina, and North Carolina, additional urban streamgages in Florida and New Jersey were used in the regression analysis for this region. Including the urban streamgages in New Jersey allowed for the expansion of the applicability of the predictive equations in the Coastal Plain from 3.5 to 53.5 square miles. Average standard error of prediction for the predictive equations, which is a measure of the average accuracy of the regression equations when predicting flood estimates for ungaged sites, range from 25.0 percent for the 10-percent annual exceedance probability regression equation for the Piedmont–Ridge and Valley region to 73.3 percent for the 0.2-percent annual exceedance probability regression equation for the Sand Hills region.

Georgia, North Carolina, South Carolina↗
USGS2014

Estimating the magnitude and frequency of floods for urban and small, rural streams in Georgia, South Carolina, and North Carolina

Reliable estimates of the magnitude and frequency of floods are essential for such things as the design of transportation and water-conveyance structures, Flood Insurance Studies, and flood-plain management. The flood-frequency estimates are particularly important in densely populated urban areas. A multistate approach was used to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia, South Carolina, and North Carolina. The multistate approach has the advantage over a single state approach of increasing the number of stations available for analysis, expanding the geographical coverage that would allow for application of regional regression equations across state boundaries, and building on a previous flood-frequency investigation of rural streamflow-gaging stations (streamgages) in the Southeastern United States. In addition, streamgages from the inner Coastal Plain of New Jersey were included in the analysis. Generalized least-squares regression techniques were used to generate predictive equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability flows for urban and small, rural ungaged basins for three hydrologic regions; the Piedmont-Ridge and Valley, Sand Hills, and Coastal Plain. Incorporation of urban streamgages from New Jersey also allowed for the expansion of the applicability of the predictive equations in the Coastal Plain from 2.1 to 53.5 square miles. Explanatory variables in the regression equations included drainage area (DA) and percent of impervious area (IA) for the Piedmont-Ridge and Valley region; DA and percent of developed land for the Sand Hills; and DA, IA, and 24-hour, 50-year maximum precipitation for the Coastal Plain. An application spreadsheet also was developed that can be used to compute the flood-frequency estimates along with the 95-percent prediction intervals for an ungaged location.

Georgia, North Carolina, South Carolina↗
USGS2009

Methods for Estimating Magnitude and Frequency of Floods in Rural Basins in the Southeastern United States: South Carolina

For more than 50 years, the U.S. Geological Survey (USGS) has been developing regional regression equations that can be used to estimate flood magnitude and frequency at ungaged sites. Flood magnitude relates to the volume of flow that occurs over some period of time and usually is presented in cubic feet per second. Flood frequency relates to the probability of occurrence of a flood; that is, on average, what is the likelihood that a flood with a specified magnitude will occur in any given year (1 percent chance, 10 percent chance, 50 percent chance, and so on). Such flood estimates are needed for the efficient design of bridges, highway embankments, levees, and other structures near streams. In addition, these estimates are needed for the effective planning and management of land and water resources, to protect lives and property in flood-prone areas, and to determine flood-insurance rates.

Georgia, North Carolina, South Carolina↗
USGS1996

Hydrology of the southeastern Coastal Plain aquifer system in South Carolina and parts of Georgia and North Carolina

The wedge of sediments present beneath the Coastal Plain of South Carolina and adjacent parts of Georgia and North Carolina consists of sand, silt, clay, and limestone. These strata have been subdivided into six regional aquifers: the surficial aquifer, the Floridan aquifer system, the Tertiary sand aquifer, the Black Creek aquifer, the Middendorf aquifer, and the Cape Fear aquifer. Intervening confining units separate the aquifers, except for the Floridan aquifer system and the Tertiary sand aquifer, which together function as a single hydrologic unit. The quality of ground water from the Coastal Plain aquifers of South Carolina generally is acceptable for most uses in most areas. The water in most aquifers under most of the Coastal Plain contains low concentrations of dissolved solids (less than 500 milligrams per liter) and no dominant constituents in the recharge areas. Downgradient, the water is a calcium bicarbonate or sodium bicarbonate type throughout most of the Coastal Plain. Sodium-chloride-type water is present still farther downgradient, near the coast. A quasi-three-dimensional, finite-difference digital ground-water flow model was constructed to simulate flow in the Coastal Plain aquifers prior to development. The model also was used to evaluate the hydraulic responses to pumping that have occurred up to November 1982. The model consisted of five layers and a 48 by 63 node grid with a uniform square grid cell of 4 miles on a side. The Coastal Plain aquifers are recharged primarily by precipitation in their outcrop areas. Discharge is primarily as base flow to upper Coastal Plain rivers, to overlying aquifers by leakage through confining units, and to wells. Total simulated flow in the deep ground-water system was 967 cubic feet per second at the end of the transient simulation (1982). Recharge to the deep flow system simulated by the model was 793 cubic feet per second in the study area in 1982. Simulated aquifer discharge to large rivers was 660 cubic feet per second. Discharge to smaller rivers was not simulated because of the scale of the model. Changes resulting from ground-water pumping were significant as of 1982. The simulated water budget indicates that in 1982, 249 cubic feet per second were discharged from the aquifer system by wells. This pumping was balanced by the following changes from predevelopment conditions: 110 cubic feet per second derived from storage, 67 cubic feet per second decrease in aquifer-to-river discharge, 44 cubic feet per second increase in net inflow from source-sinks, and a net increase in inflow of 28 cubic feet per second across boundaries. Head declines in the Black Creek and Middendorf aquifers have occurred throughout much of the eastern part of the Coastal Plain of South Carolina as a result of pumping in the Myrtle Beach and Florence areas. Simulation indicates that the dominant sources of water for upper Coastal Plain pumping centers such as the city of Florence are decrease in flow to rivers in the upper Coastal Plain and water derived from storage. The dominant sources of water for pumping centers in the Myrtle Beach area are water derived from storage, leakage from overlying aquifers, and net increases in inflow across boundaries. Transmissivity values used in the flow simulation range from less than 1,000 feet squared per day near the updip limit of most aquifers to about 30,000 feet squared per day in the Middendorf aquifer in the Savannah River Plant area. Vertical hydraulic conductivity values used in simulation of confining units range from about 6x10 -7 feet per day for the confining unit between the Middendorf and Black Creek aquifers in coastal areas to 3x10 -2 feet per day for most of the confining units near their updip limits. Storage coefficients used in transient simulations were 0.15 where unconfined conditions exist and 0.0005 where confined conditions exist.

Georgia, North Carolina, South Carolina↗
USGS1994

Mines, prospects, and occurrences of metallic (excluding gold), pegmatite, and rare-earth mineral commodities in the Greenville 1° x 2° quadrangle, South Carolina, Georgia, and North Carolina

All of the known mines, prospects, and occurrences of metallic (excluding gold, pegmatite, and rare-earth mineral commodities for the Greenville 1° x 2° quadrangle are tabulated in this report. The table lists, in consecutive order for each county (fig. 1), the map number of each item, which correlates and locates the item on the accompanying Greenville 1° x 2° quadrangle map. The known name of the feature; the 7.5' topographic map on the which the commodity site is located; the Universal Transverse Mercator (UTM) northing and easting grid coordinates from the appropriate 7.5' topographic map; the commodity; remarks; and references are also listed. Some locations are known, but many sites are not verified and their locations are only approximate. References are listed in References Cited and referred to by number to save space.

Georgia, North Carolina, South Carolina↗
USGS1994

Gold occurrences in the Greenville 1° x 2° quadrangle, South Carolina, Georgia, and North Carolina

All of the gold mines, prospects, placers, and occurrences known in the Greenville 1° x 2° quadrangle are tabulated in this report. The table lists, in consecutive order by county (fig. 1), the map number of each feature, which is located either on the accompanying Greenville 1° x 2° quadrangle map or figure 2. The known name of the feature; the 7.5' topographic map on the which the gold site is located (if known, within 25 ft or 7.6 m), the Universal Transverse Mercator (UTM) northing and easting grid coordinates from the appropriate 7.5' topographic map; the commodity; remarks; and references are also listed. Some locations are known, but many sites are not verified and their locations are only approximate. References are listed in References Cited and referred to by number to save space.

Georgia, North Carolina, South Carolina↗
USGS1994

Mines, prospects, and occurrences of nonmetallic mineral commodities in the Greenville 1° x 2° quadrangle, South Carolina, Georgia, and North Carolina

Mines, prospects, and occurrences of nonmetal mineral commodities in the Greenville 1° x 2° quadrangle are tabulated in this report. There are 488 symbols representing 579 mines, prospects, and occurrences located in the quadrangle. There are 379 symbols used for 466 features in Georgia, 106 symbols for 110 features in South Carolina, and 3 symbols for 3 features in North Carolina. The table lists, in consecutive orders for each county (fig. 1), the map number of each feature, which correlates and locates the item on the accompanying Greenville 1° x 2° quadrangle map. Also listed are the known name of the feature; the 7.5 topographic map on which the commodity site is located; the Transverse Mercator (UTM) northing and easting grid coordinates from the appropriate 7.5’ topographic map; the commodity; remarks; and references. Some locations are known, but many sites are not verified and their locations are only approximate. Reference are listed in References Cited and referred to by number to save space. The generalized tectonic framework for the quadrangle is shown in figure 2.

Georgia, North Carolina, South Carolina↗