Geology topics

J. Curtis Weaver

Publications and source records attributed to J. Curtis Weaver.

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↗

USGS2024

State of science, gap analysis, and prioritization for southeastern United States water-quality impacts from coastal storms—Fiscal year 2023 program report to the Water Resources Mission Area from the Water Availability Impacts of Extreme Events Program—Hurricanes

Tropical cyclones (coastal storm events that include tropical depressions, tropical storms, and hurricanes) cause landscape-scale disturbances that can lead to impaired water quality and thus reduce water availability for use. Stakeholders and scientists at local and national scales have illustrated a need for understanding these risks to water quality. A regional and comprehensive understanding of the impacts of tropical storms and hurricanes on surface-water and groundwater quality—and thus water availability—is lacking for potentially impacted coastal and inland areas. As the U.S. Geological Survey considers development of tools to predict the extent to which water-quality impacts of hurricanes affect water availability, an assessment of the state of the science of hurricane impacts is needed, including a gap analysis and prioritization of data and science needs. This assessment focuses on the southeastern coastal States.

southeastern United States↗

USGS2023

Development of the North Carolina stormwater-treatment decision-support system by using the Stochastic Empirical Loading and Dilution Model (SELDM)

The Federal Highway Administration and State departments of transportation nationwide need an efficient method to assess potential adverse effects of highway stormwater runoff on receiving waters to optimize stormwater-treatment decisions. To this end, the U.S. Geological Survey, in cooperation with the Federal Highway Administration and the North Carolina Department of Transportation (NCDOT), developed a decision-support software tool based on a statewide version of the Stochastic Empirical Loading and Dilution Model (SELDM). This decision-support tool is designed to identify potential adverse effects of highway runoff by using a criterion based on a measurable change in water quality from a surrogate pollutant. The NCDOT worked with the North Carolina Department of Environmental Quality to select a 25-percent change in suspended sediment concentration as the decision-rule criterion for identifying measurable downstream water-quality change; this selection was based on available data and widely accepted stormwater monitoring uncertainties. Development of the statewide tool and its application to the Piedmont ecoregion are described in this report. Because SELDM can be applied to build a similar decision-support tool in any State, this report describes practice-ready methods that other State departments of transportation and municipal permittees can use to streamline environmental permitting and project delivery while protecting the environment. Hydraulic design engineers can use this decision-support tool to establish stormwater-treatment goals for highway construction or improvement projects without having to learn SELDM or interpret its statistical output. The tool is a spreadsheet that determines if a selected highway segment can directly discharge highway runoff, if the highway segment can discharge runoff following treatment using a basic vegetated conveyance best management practice (BMP), or if treatment using an advanced BMP is needed to minimize effects of discharges on downstream water quality. To use the tool, hydraulic design engineers obtain upstream-basin characteristics from the U.S. Geological Survey StreamStats application and highway-site characteristics from preliminary design plans. They then enter these characteristics in the decision-support tool, which identifies the necessary stormwater-treatment goal. The Piedmont ecoregion was used as a case study to demonstrate the type of information the decision-support tool can provide. In this ecoregion, 100 percent of direct discharges meet the water-quality criterion when the drainage-area ratio is less than about 0.007 acres of highway per square mile of upstream basin. Advanced BMPs are needed in 100 percent of basins with drainage-area ratios greater than about 50 acres per square mile. Between these drainage-area ratios, the selection of direct discharge, a basic vegetated conveyance BMP, or an advanced BMP is a function of highway-site and upstream-basin properties.

North 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↗

USGS2019

Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM)

In 2015, the U.S. Geological Survey (USGS) entered into a cooperative agreement with the North Carolina Department of Transportation (NCDOT) to develop a North Carolina-enhanced variation of the national Stochastic Empirical Loading and Dilution Model (SELDM) with available North Carolina-specific streamflow and water-quality data and to demonstrate use of the model by documenting selected simulation scenarios. The USGS developed the national SELDM in cooperation with the Federal Highway Administration (FHWA) to provide the tools and techniques necessary for performing stormwater-quality simulations. SELDM uses a stochastic mass-balance approach to estimate combinations of flows, concentrations, and loads of stormwater constituents from the site of interest (often a highway catchment; nonhighway areas, such as a large impervious area at a shopping center complex, also can be used) and the basin upstream from the stormwater outfall to assess the risk for adverse effects of runoff. SELDM also can be used to simulate the effectiveness of volume reduction, hydrograph extension, and water-quality concentration reductions by stormwater best management practices (BMPs), which are designed to help mitigate the effects of runoff on receiving water bodies. Some of the statistical inputs needed for the North Carolina-enhanced SELDM were either calculated or augmented using local or regional data from North Carolina. Streamflow statistics used by SELDM were determined for 266 streamgages across North Carolina on the basis of data available through the 2015 water year. Recession ratio statistics used for triangular hydrographs were also developed for 30 streamgages across the State. The NCDOT identified previous research reports on highway-runoff and BMP studies in North Carolina for review of potential data addition to the national FHWA Highway-Runoff Database (HRDB). Following USGS review of these data, a total of 25,087 event mean concentration values and 1,140 storm events for 39 highway-runoff sites and 195 analytes were uploaded to the national HRDB from six North Carolina highway-runoff research reports and a recent USGS bridge deck runoff study. Using data for 27 streamgages in North Carolina, a total of 57 water-quality transport curves were developed for seven constituents for use in simulating water-quality conditions in the upstream basin. Performance data for three BMPs (bioretention, grass strip or swale, and wetland channel) from NCDOT research data were incorporated into the North Carolina-enhanced SELDM for volume-reduction statistics, including the effectiveness of treating four water-quality constituents (total suspended solids, total nitrogen, total phosphorus, nitrate plus nitrite) and turbidity. Simulations using the North Carolina-enhanced SELDM are presented for two hypothetical upstream basins in the Piedmont ecoregion and one hypothetical highway site to demonstrate how simulations can be used to provide risk-based information about potential effects of stormwater runoff on downstream water quality and the potential for mitigating those risks by using BMPs. The first group of simulations explores the stochastic variability in dilution factors (the ratio of the highway runoff to the total downstream stormflow) for a hypothetical Piedmont rural creek having drainage areas ranging from 1 to 100 square miles. The second group of simulations examines dilution factors based on variations in precipitation, streamflow, and recession ratios for two hypothetical Piedmont upstream basins (rural and urban) where the drainage area was held constant at 25 square miles. These simulations indicate the sensitivity of results to variations in each of the three variables. The third group of simulations examines the effects of varied concentrations in the upstream basin on water-quality conditions downstream from the highway crossing. Variations in upstream water-quality conditions for three constituents (suspended sediment concentration, total nitrogen, and total phosphorus) are based on water-quality transport curves selected from among the 57 curves developed as part of this study to represent low-, medium-, and high-concentration statistics. Simulations completed for this third group also examine the potential effects of grass swale and bioretention BMP treatment on total nitrogen and total phosphorus concentrations in highway runoff. The BMP performance data from the NCDOT research reports were applied in this group of simulations. The stochastic mass-balance approach used in SELDM analyses and simulations provides a strong tool for engineers and water-resource managers to use in exploring a wide range of possible hydrologic and water-quality inputs and their effects on downstream water quality. The results of this study can not only aid engineers and managers in planning for potential adverse effects of runoff at site-specific locations, they can also help the USGS and other Federal and State agencies with oversight responsibilities in stormwater-quality issues to continue gathering data on potential water-quality effects in receiving streams.

North Carolina↗

USGS2018

Preliminary peak stage and streamflow data for selected U.S. Geological Survey streamgaging stations in North and South Carolina for flooding following Hurricane Florence, September 2018

Hurricane Florence made landfall as a Category 1 hurricane at Wrightsville Beach, North Carolina, shortly after dawn on September 14, 2018. Once over land, the forward motion of the hurricane slowed to about 2 to 3 miles per hour. Over the next several days, the hurricane delivered historic amounts of rainfall across North and South Carolina, causing substantial flooding in many communities across both States. For the Hurricane Florence event, a new record rainfall total of 35.93 inches was set in Elizabethtown, N.C. Many other locations throughout North Carolina set new records for rainfall, exceeding the previous State record for rainfall from a tropical system of 24.06 inches, which was set over a 4-day period in Southport, N.C., during Hurricane Floyd in 1999. In South Carolina, the highest reported total rainfall of 23.63 inches was in Loris, S.C., which was the highest total rainfall in South Carolina from a tropical cyclone, replacing the previous total of 17.45 inches associated with Tropical Storm Beryl in 1994. During the October 2015 flood in South Carolina, a 4-day total rainfall of 26.88 inches was recorded in Mount Pleasant; however, because that total rainfall was a combination of a tropical storm system and another front that was centered over the State, it is not considered the largest rainfall event from a tropical storm. Peak streamflow and stage data at 84 U.S. Geological Survey streamflow gaging stations (referred to hereafter as streamgages) in North and South Carolina with at least 10 years of systematic record and for which the flooding following Hurricane Florence resulted in a peak in the top 5 for the period of record are included in this report. New peak streamflows of record were recorded at 18 sites in North Carolina and 10 sites in South Carolina. Another 49 streamgages recorded peak streamflows in the top 5 for their record (45 in North Carolina and 4 in South Carolina). Peak streamflow data following Hurricane Florence were not available for three additional streamgages prior to the publication of this report. Of those three streamgages, two recorded a new peak stage of record and one recorded the second highest peak stage of record. An additional four stage-only streamgages having at least 10 years of systematic record also had new peak stages (also referred to as gage height) of record. For 11 of the 28 streamgages for which the September 2018 peak streamflow was the peak of record, the October 2016 peak following Hurricane Matthew was the second largest peak, and for another four streamgages the September 1999 peak following Hurricane Floyd was the second largest peak. For the 28 streamgages for which a new peak streamflow of record was recorded, a flood-frequency analysis was done using available systematic record through September 2017 and the peak streamflow from the Hurricane Florence event. Of the 28 streamgages analyzed, the estimated annual exceedance probability for the Hurricane Florence peak streamflow at 9 of the streamgages was less than 0.2 percent, which in terms of recurrence intervals is greater than a 500-year flood event. At three streamgages, the estimated annual exceedance probability was equal to 0.2 percent, and at six streamgages, it was between 0.2 and 1 percent (between a 500- and 100-year recurrence interval, respectively). For the remaining 10 streamgages, the estimated annual exceedance probability was between 1.5 and 7.1 percent, which in terms of recurrence intervals is approximately a 67- to 14-year event, respectively.

North Carolina, South Carolina↗

USGS2016

Preliminary peak stage and streamflow data at selected streamgaging stations in North Carolina and South Carolina for flooding following Hurricane Matthew, October 2016

The passage of Hurricane Matthew across the central and eastern regions of North Carolina and South Carolina during October 7–9, 2016, resulted in heavy rainfall that caused major flooding in parts of the eastern Piedmont in North Carolina and coastal regions of both States. Rainfall totals of 3 to 8 inches and 8 to more than 15 inches were widespread throughout the central and eastern regions, respectively. U.S. Geological Survey streamgages recorded peaks of record at 26 locations, including 11 sites with long-term periods of 30 or more years of record. A total of 44 additional locations had peak streamflows that ranked in the top 5 for the period of record. Additionally, among 23 U.S. Geological Survey streamgages within the affected basins in North Carolina where stage-only data are collected, new peak stages were recorded at 5 locations during the flooding. U.S. Geological Survey personnel made 102 streamflow measurements at 60 locations in both States to verify, update, or extend existing rating curves (which are used to determine stage-discharge relations) during the October 2016 flood event.

North Carolina, South Carolina↗

USGS2015

Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012

In 2013, the U.S. Geological Survey, in cooperation with the North Carolina Division of Water Resources, compiled updated low-flow characteristics and flow-duration statistics for selected continuous-record streamgages in North Carolina. The compilation of updated streamflow statistics provides regulators and planners with relevant hydrologic information reflective of the recent droughts, which can be used to better manage the quantity and quality of streams in North Carolina. Streamflow records available through the 2012 water year1 were used to determine the annual (based on climatic year2) and winter 7-day, 10-year (7Q10, W7Q10) low-flow discharges, the 30-day, 2-year (30Q2) low-flow discharge, and the 7-day, 2-year (7Q2) low-flow discharge. Consequently, streamflow records available through March 31, 2012 (or the 2011 climatic year) were used to determine the updated low-flow characteristics. Low-flow characteristics were published for 177 unregulated sites, 56 regulated sites, and 33 sites known or considered to be affected by varying degrees of minor regulation and (or) diversions upstream from the streamgages (266 sites total). The updated 7Q10 discharges were compared for 63 streamgages across North Carolina where (1) long-term streamflow record consisted of 30 or more climatic years of data available as of the 1998 climatic year, and (2) streamflows were not known to be regulated. The 7Q10 discharges did not change for 3 sites, whereas increases and decreases were noted at 5 and 55 sites, respectively. Positive changes (increases) ranged from 4.3 percent (site 362) to 34.1 percent (site 112) with a median of 13.2 percent. Negative percentage changes (decreases) ranged from –3.3 percent (site 514) to –80.0 percent (site 308) with a median of –22.2 percent. The median percentage change for all 63 streamgages was –18.4 percent. Streamflow statistics determined as a part of this compilation included minimum, mean, maximum, and flow-duration statistics of daily mean discharges for categorical periods. Flow-duration statistics based on the daily mean discharge records were compiled in this study for the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. Flow-duration statistics were determined for each complete water year of record at a streamgage as well as the available period of record (or selected periods if flows were regulated) and selected seasonal, monthly, and calendar day periods. In addition to the streamflow statistics compiled for each of the water years, the number of days the daily mean discharge was at or below the 10th percentile was summed for each water year as well as the number of events during the water year when streamflow was consistently at or below the 10th percentile. All low-flow characteristics for the streamgages were added into the StreamStatsDB, which is a database accessible to users through the recently released USGS StreamStats application for North Carolina. The minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record were updated in the North Carolina StreamStatsDB. However, for the selected seasonal, monthly, calendar day, and annual water year periods, tab-delimited American Standard Code for Information Interchange (ASCII) tables of the streamflow statistics are available online to users from a link provided in the StreamStats application. 1The annual period from October 1 through September 30, designated by the year in which the period ends. 2The annual period from April 1 through March 31, designated by the year in which the period begins.

North 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↗

USGS2013

Determination of flow losses in the Cape Fear River between B. Everett Jordan Lake and Lillington, North Carolina, 2008-2010

During 2008-2010, the U.S. Geological Survey conducted a hydrologic investigation in cooperation with the Triangle J Council of Governments Cape Fear River Flow Study Committee and the North Carolina Division of Water Resources to collect hydrologic data in the Cape Fear River between B. Everett Jordan Lake and Lillington in central North Carolina to help determine if suspected flow losses occur in the reach. Flow loss analyses were completed by summing the daily flow releases at Jordan Lake Dam with the daily discharges at Deep River at Moncure and Buckhorn Creek near Corinth, then subtracting these values from the daily discharges at Cape Fear River at Lillington. Examination of long-term records revealed that during 10,227 days of the 1983-2010 water years, 408 days (4.0 percent) had flow loss when conditions were relatively steady with respect to the previous day's records. The flow loss that occurred on these 40 days ranged from 0.49 to 2,150 cubic feet per second with a median flow loss of 37.2 cubic feet per second. The months with the highest number of days with flow losses were June (16. percent), September (16.9 percent), and October (19.4 percent). A series of synoptic discharge measurements made on six separate days in 2009 provided "snapshots" of overall flow conditions along the study reach. The largest water diversion is just downstream from the confluence of the Haw and Deep Rivers, and discharges substantially decrease in the main stem downstream from the intake point. Downstream from Buckhorn Dam, minimal gain or loss between the dam and Raven Rock State Park was noted. Analyses of discharge measurements and ratings for two streamgages-one at Deep River at Moncure and the other at Cape Fear River at Lillington-were completed to address the accuracy of the relation between stage and discharge at these sites. The ratings analyses did not indicate a particular time during the 1982-2011 water years in which a consistent bias occurred in the computations of discharge records that would indicate false flow losses. A total of 34 measured discharges at a streamgage on the Haw River below B. Everett Jordan Lake near Moncure were compared with the reported hourly flow releases from Jordan Lake Dam. Because 28 of 34 measurements were within plus or minus 10 percent of the hourly flow releases reported by the U.S Army Corps of Engineers, use of the current discharge computation tables for reporting Jordan Lake Dam flow releases is generally supported. A stage gage was operated on the Cape Fear River at Buckhorn Dam near Corinth to collect continuous stage-only records. Throughout the study period, flow over the dam was observed along its length, and flow loss within the study reach is not attributed to river-level fluctuations at the dam. Water-use information and (or) data were obtained for five industrial facilities, a regional power utility, two municipalities, one small hydropower facility on the Deep River, and one quarry operation also adjacent to the Deep River. The largest water users are the regional power producer, a small hydropower operation, and the two municipalities. The total water-use diversions for these facilities range from almost 25.5 to 38.5 cubic feet per second (39.5 to 59.5 million gallons per day) during the winter and summer periods, respectively. This range is equivalent to 69 to 104 percent of the 37 cubic feet per second median flow loss. The Lockville hydropower station is on the Deep River about 1 mile downstream from the streamgage near Moncure. Run-of-river operations at the facility do not appear to affect flow losses in the study reach. The largest water user in the study area is a regional power producer at a coal-fired power-generation plant located immediately adjacent to the Cape Fear River just downstream from the confluence of the Haw an Deep Rivers. Comparisons of daily water withdrawals, sup-plied by the regional power producer, and discharge records at a streamgage on the diversion canal indicated many days when consumption exceeded the producer's estimates for the cooling towers. Uncertainty surrounding reasonable estimates of consumption remained in effect at the end of the study. Data concerning evaporative losses were compiled using two approaches-an analysis of available pan-evaporation data from a National Weather Service cooperative observer station in Chapel Hill, North Carolina; and a compilation of reference open-water evaporation computed by the State Climate Office of North Carolina. The potential flow loss by evaporation from the main stem and the Deep River was estimated to be in the range of 4 to 14 cubic feet per second during May through October, equivalent to 10 to 38 percent of the 37 cubic feet per second median flow loss. Daily water-use diversions and evaporation losses were compared to flow-loss occurrences during the period April 2008 through September 2010. In comparing the surface-water, water-use, and evaporation data compiled for 2008-2010, it is evident that documented water diversions combined with flow losses by open-water evaporation can exceed the net flow gain in the study area and result in flow losses from the reach. Analysis of data from a streamgage downstream from the regional power plant on the diversion canal adjacent to the Cape Fear River provided insight into the occurrence of an apparent flow loss at the streamgage at Lillington. Assessment of the daily discharges and subsequent hydrographs for the canal streamgage indicated at least 24 instances during the study when the flows suddenly changed by magnitudes of 100 to more that 200 cubic feet per second, resulting in a noted time-lag effect on the downstream discharges at the Lillington streamgage, beginning 8 to 16 hours after the sudden flow change. A fiber-optic distributed temperature-sensing survey was conducted on the Cape Fear River at the Raven Rock State Park reach August 12-14, 2009, to determine if the presence of diabase dikes were preferentially directing groundwater discharge. No temperature anomalies of colder water were measured during the survey, which indicated that at the time of the survey that particular reach of the Cape Fear River was a "no-flow" or losing stream. An aerial thermal-infrared survey was conducted on the Haw and Cape Fear Rivers on February 27, 2010, from Jordan Lake Dam to Lillington to qualitatively delineate areas of groundwater discharge on the basis of the contrast between warm groundwater discharge and cold surface-water temperatures. Dis-charge generally was noted as diffuse seepage, but in a few cases springs were detected as inflow at a discrete point of discharge. Two reaches of the Cape Fear River (regional power plant and Bradley Road reaches) were selected for groundwater monitoring with a transect of piezometers installed within the flood plain. Groundwater-level altitudes at these reaches were analyzed for 1 water year (October 1, 2009, to September 30, 2010). Data collected as part of this study represent only a brief period of time and may not represent all conditions and all years; however, the data indicate that, during the dry summer months, the Cape Fear River within the study area is losing an undetermined quantity of water through seepage. Analyses completed during this investigation indicate a study reach with complex flow patterns affected by numerous concurrent factors resulting in flow losses. The causes of flow loss could not be solely attributed to any one factor. Among the factors considered, the occurrences of water diversions and evaporative losses were determined to be sufficient on some days (particularly during the base-flow period) to exceed the net gain in flows between the upstream and downstream ends of the study area. Losses by diversions and evaporation can exceed the median flow loss of 3 cubic feet per second, which indicates that flow loss from the study reach is real. Groundwater data collected during 2009-2010 indicate the possibility of localized flow loss during the summer, particularly in the impounded reach above Buckhorn Dam. However, no indication of unusual patterns was noted that would cause substantial flow loss by groundwater and surface-water interaction at the river bottom.

North Carolina↗

USGS2012

StreamStats in North Carolina: A water-resources Web application

A statewide StreamStats application for North Carolina was developed in cooperation with the North Carolina Department of Transportation following completion of a pilot application for the upper French Broad River basin in western North Carolina (Wagner and others, 2009). StreamStats for North Carolina, available at http://water.usgs.gov/osw/streamstats/north_carolina.html, is a Web-based Geographic Information System (GIS) application developed by the U.S. Geological Survey (USGS) in consultation with Environmental Systems Research Institute, Inc. (Esri) to provide access to an assortment of analytical tools that are useful for water-resources planning and management (Ries and others, 2008). The StreamStats application provides an accurate and consistent process that allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS data-collection sites and user-selected ungaged sites. In the North Carolina application, users can compute 47 basin characteristics and peak-flow frequency statistics (Weaver and others, 2009; Robbins and Pope, 1996) for a delineated drainage basin. Selected streamflow statistics and basin characteristics for data-collection sites have been compiled from published reports and also are immediately accessible by querying individual sites from the web interface. Examples of basin characteristics that can be computed in StreamStats include drainage area, stream slope, mean annual precipitation, and percentage of forested area (Ries and others, 2008). Examples of streamflow statistics that were previously available only through published documents include peak-flow frequency, flow-duration, and precipitation data. These data are valuable for making decisions related to bridge design, floodplain delineation, water-supply permitting, and sustainable stream quality and ecology. The StreamStats application also allows users to identify stream reaches upstream and downstream from user-selected sites and obtain information for locations along streams where activities occur that may affect streamflow conditions. This functionality can be accessed through a map-based interface with the user’s Web browser, or individual functions can be requested remotely through Web services (Ries and others, 2008).

North 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↗

USGS2009

Magnitude and frequency of rural floods in the southeastern United States, 2006: Volume 1, Georgia

A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in Georgia, South Carolina, and North Carolina that are not substantially affected by regulation, tidal fluctuations, or urban development. Annual peak-flow data through September 2006 were analyzed for 943 streamgaging stations having 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 were computed for the 943 stations by fitting the logarithms of annual peak flows for each station to a Pearson Type III distribution. As part of the computation of flood-frequency estimates for these streamgaging stations, a new value for the generalized-skew coefficient was developed by using a Bayesian generalized least-squares regression model. Additionally, basin characteristics for the streamgaging stations were computed by using a geographical information system and automated computer algorithms. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged basins in Georgia, South Carolina, and North Carolina. Flood-frequency estimates and basin characteristics for 828 stream-gaging stations were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for Georgia, South Carolina, and North Carolina. The final predictive equations are all functions of drainage area and percentage of the drainage basin within each hydrologic region. Average standard errors of prediction for these regression equations range from 34.5 to 47.7 percent.

Georgia↗

USGS2009

Magnitude and Frequency of Rural Floods in the Southeastern United States, 2006: Volume 3, South Carolina

A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in South Carolina, Georgia, and North Carolina that are not substantially affected by regulation, tidal fluctuations, or urban development. Annual peak-flow data through September 2006 were analyzed for 943 streamgaging stations having 10 or more years of data on rural streams in South Carolina, Georgia, North Carolina, and adjacent parts of Alabama, Florida, Tennessee, and Virginia. Flood-frequency estimates were computed for the 943 stations by fitting the logarithms of annual peak flows for each station to a Pearson Type III distribution. As part of the computation of flood-frequency estimates for the stations, a new value for the generalized skew coefficient was developed using a Bayesian generalized least-squares regression model. Additionally, basin characteristics for these stations were computed by using a geographical information system and automated computer algorithms. Exploratory regression analyses using ordinary least-squares regression completed on the initial database of 943 gaged stations resulted in defining five hydrologic regions for South Carolina, Georgia, and North Carolina. Stations with drainage areas less than 1 square mile were removed from the database, and a procedure to examine for basin redundancy (based on drainage area and periods of record) also resulted in the removal of some stations from the regression database. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged basins in Georgia, South Carolina, and North Carolina. Flood-frequency estimates and basin characteristics for 828 streamgaging stations were combined to form the final database used in the regional regression analysis. The final predictive equations are all functions of drainage area and percentage of the drainage basin within each hydrologic region. Average errors of prediction for these regression equations range from 34.0 to 47.7 percent. Peak-flow records at 25 regulated stations were assessed to determine if a flood-frequency analysis was appropriate. Based on those assessments, flood-frequency estimates are provided for three regulated stations. Annual peak-flow data are provided for the regulated stations in an appendix.

South Carolina↗

USGS2009

Magnitude and Frequency of Rural Floods in the Southeastern United States, through 2006: Volume 2, North Carolina

Reliable estimates of the magnitude and frequency of floods are required for the economical and safe design of transportation and water-conveyance structures. A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in North Carolina, South Carolina, and Georgia that are not substantially affected by regulation, tidal fluctuations, or urban development. In North Carolina, annual peak-flow data available through September 2006 were available for 584 sites; 402 of these sites had a total of 10 or more years of systematic record that is required for at-site, flood-frequency analysis. Following data reviews and the computation of 20 physical and climatic basin characteristics for each station as well as at-site flood-frequency statistics, annual peak-flow data were identified for 363 sites in North Carolina suitable for use in this analysis. Among these 363 sites, 19 sites had records that could be divided into unregulated and regulated/ channelized annual peak discharges, which means peak-flow records were identified for a total of 382 cases in North Carolina. Considering the 382 cases, at-site flood-frequency statistics are provided for 333 unregulated cases (also used for the regression database) and 49 regulated/channelized cases. The flood-frequency statistics for the 333 unregulated sites were combined with data for sites from South Carolina, Georgia, and adjacent parts of Alabama, Florida, Tennessee, and Virginia to create a database of 943 sites considered for use in the regional regression analysis. Flood-frequency statistics were computed by fitting logarithms (base 10) of the annual peak flows to a log-Pearson Type III distribution. As part of the computation process, a new generalized skew coefficient was developed by using a Bayesian generalized least-squares regression model. Exploratory regression analyses using ordinary least-squares regression completed on the initial database of 943 sites resulted in defining five hydrologic regions for North Carolina, South Carolina, and Georgia. Stations with drainage areas less than 1 square mile were removed from the database, and a procedure to examine for basin redundancy (based on drainage area and periods of record) also resulted in the removal of some stations from the regression database. Flood-frequency estimates and basin characteristics for 828 gaged stations were combined to form the final database that was used in the regional regression analysis. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations that can be used for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged, basins in North Carolina, South Carolina, and Georgia. The final predictive equations are all functions of drainage area and the percentage of drainage basin within each of the five hydrologic regions. Average errors of prediction for these regression equations range from 34.0 to 47.7 percent. Discharge estimates determined from the systematic records for the current study are, on average, larger in magnitude than those from a previous study for the highest percent chance exceedances (50 and 20 percent) and tend to be smaller than those from the previous study for the lower percent chance exceedances when all sites are considered as a group. For example, mean differences for sites in the Piedmont hydrologic region range from positive 0.5 percent for the 50-percent chance exceedance flow to negative 4.6 percent for the 0.2-percent chance exceedance flow when stations are grouped by hydrologic region. Similarly for the same hydrologic region, median differences range from positive 0.9 percent for the 50-percent chance exceedance flow to negative 7.1 percent for the 0.2-percent chance exceedance flow. However, mean and median percentage differences between the estimates from the previous and curre

North Carolina↗