Geology topics

Toby D. Feaster

Publications and source records attributed to Toby D. Feaster.

46 records · Page 3Linked to original sources

USGS2009

Low-flow frequency and flow duration of selected South Carolina streams in the Pee Dee River basin through March 2007

Part of the mission of the South Carolina Department of Health and Environmental Control and the South Carolina Department of Natural Resources is to protect and preserve South Carolina's water resources. Doing so requires an ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina. A particular need is information concerning the low-flow characteristics of streams; this information is especially important for effectively managing the State's water resources during critical flow periods such as the severe drought that occurred between 1998 and 2002 and the most recent drought that occurred between 2006 and 2009. In 2008, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, initiated a study to update low-flow statistics at continuous-record streamgaging stations operated by the U.S. Geological Survey in South Carolina. Under this agreement, the low-flow characteristics at continuous-record streamgaging stations will be updated in a systematic manner during the monitoring and assessment of the eight major basins in South Carolina as defined and grouped according to the South Carolina Department of Health and Environmental Control's Watershed Water Quality Management Strategy. Depending on the length of record available at the continuous-record streamgaging stations, low-flow frequency characteristics are estimated for annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day average flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years. Low-flow statistics are presented for 18 streamgaging stations in the Pee Dee River basin. In addition, daily flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance also are presented for the stations. The low-flow characteristics were computed from records available through March 31, 2007. The last systematic update of low-flow characteristics in South Carolina occurred more than 20 years ago and included data through March 1987. Of the 17 streamgaging stations included in this study, 15 had low-flow characteristics that were published in previous U.S. Geological Survey reports. A comparison of the low-flow characteristic for the minimum average flow for a 7-consecutive-day period with a 10-year recurrence interval from this study with the most recently published values indicated that 10 of the 15 streamgaging stations had values that were within ±25 percent of each other. Nine of the 15 streamgaging stations had negative percentage differences indicating the low-flow statistic had decreased since the previous study, 4 streamgaging stations had positive percent differences indicating that the low-flow statistic had increased since the previous study, and 2 streamgaging stations had a zero percent difference indicating no change since the previous study. The low-flow characteristics are influenced by length of record, hydrologic regime under which the record was collected, techniques used to do the analysis, and other changes that may have occurred in the watershed.

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↗

USGS2008

The Effects of the Saluda Dam on the Surface-Water and Ground-Water Hydrology of the Congaree National Park Flood Plain, South Carolina

The Congaree National Park was established '... to preserve and protect for the education, inspiration, and enjoyment of present and future generations an outstanding example of a near-virgin, southern hardwood forest situated in the Congaree River flood plain in Richland County, South Carolina' (Public Law 94-545). The resource managers at Congaree National Park are concerned about the timing, frequency, magnitude, and duration of flood-plain inundation of the Congaree River. The dynamics of the Congaree River directly affect ground-water levels in the flood plain, and the delivery of sediments and nutrients is constrained by the duration, extent, and frequency of flooding from the Congaree River. The Congaree River is the southern boundary of the Congaree National Park and is formed by the convergence of the Saluda and Broad Rivers 24 river miles upstream from the park. The streamflow of the Saluda River has been regulated since 1929 by the operation of the Saluda Dam at Lake Murray. The U.S. Geological Survey, in cooperation with the National Park Service, Congaree National Park, studied the interaction between surface water in the Congaree River and ground water in the flood plain to determine the effect Saluda Dam operations have on water levels in the Congaree National Park flood plain. Analysis of peak flows showed the reduction in peak flows after the construction of Lake Murray was more a result of climate variability and the absence of large floods after 1930 than the operation of the Lake Murray dam. Dam operations reduced the recurrence interval of the 2-year to 100-year peak flows by 6.1 to 17.6 percent, respectively. Analysis of the daily gage height of the Congaree River showed that the dam has had the effect of lowering high gage heights (95th percentile) in the first half of the year (December to May) and raising low gage heights (5th percentile) in the second half of the year (June to November). The dam has also had the effect of increasing the 1-, 3-, 7-, 30-, and 90-day minimum gage heights by as much as 23.9 percent and decreasing the 1-, 3-, 7-, 30-, and 90-day maximum gage heights by as much as 7.2 percent. Analysis of the ground-water elevations in the Congaree National Park flood plain shows similar results as the gage-height analysis--the dam has had the effect of lowering high ground-water elevations and increasing low ground-water elevations. Overall, the operation of the dam has had a greater effect on the gage heights within the river banks than gage heights in the flood plain. This result may have a greater effect on the subsurface water levels of the surficial flood-plain aquifer than the frequency and magnitude of inundation of the flood plain.

South Carolina↗

USGS2007

Magnitude and Frequency of Floods in Alabama, 2003

Methods of estimating flood magnitudes for recurrence intervals of 1.5, 2, 5, 10, 25, 50, 100, 200, and 500 years have been developed for rural streams in Alabama that are not affected by regulation or urbanization. Regression relations were developed using generalized least-squares regression techniques to estimate flood magnitude and frequency on ungaged streams as a function of the basin drainage area. These methods are based on flood-frequency characteristics for 169 gaging stations in Alabama and 47 gaging stations in adjacent states having 10 or more years of record through September 2003. Graphical relations of peak flows to drainage areas are presented for sites along the Alabama, Coosa, Tallapoosa, Tennessee, Tombigbee, and Black Warrior Rivers. Equations that account for drainage area and percentage of impervious cover as independent variables also are provided for estimating flood magnitudes on ungaged urban streams (taken from a previous report).

Scientific Investigations Report↗

USGS2004

Computation of Flow Through Water-Control Structures Using Program DAMFLO.2

As part of its mission to collect, analyze, and store streamflow data, the U.S. Geological Survey computes flow through several dam structures throughout the country. Flows are computed using hydraulic equations that describe flow through sluice and Tainter gates, crest gates, lock gates, spillways, locks, pumps, and siphons, which are calibrated using flow measurements. The program DAMFLO.2 was written to compute, tabulate, and plot flow through dam structures using data that describe the physical properties of dams and various hydraulic parameters and ratings that use time-varying data, such as lake elevations or gate openings. The program uses electronic computer files of time-varying data, such as lake elevation or gate openings, retrieved from the U.S. Geological Survey Automated Data Processing System. Computed time-varying flow data from DAMFLO.2 are output in flat files, which can be entered into the Automated Data Processing System database. All computations are made in units of feet and seconds. DAMFLO.2 uses the procedures and language developed by the SAS Institute Inc.

Open-File Report↗

USGS2004

Estimating the Magnitude and Frequency of Floods in Small Urban Streams in South Carolina, 2001

The magnitude and frequency of floods at 20 streamflowgaging stations on small, unregulated urban streams in or near South Carolina were estimated by fitting the measured wateryear peak flows to a log-Pearson Type-III distribution. The period of record (through September 30, 2001) for the measured water-year peak flows ranged from 11 to 25 years with a mean and median length of 16 years. The drainage areas of the streamflow-gaging stations ranged from 0.18 to 41 square miles. Based on the flood-frequency estimates from the 20 streamflow-gaging stations (13 in South Carolina; 4 in North Carolina; and 3 in Georgia), generalized least-squares regression was used to develop regional regression equations. These equations can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence-interval flows for small urban streams in the Piedmont, upper Coastal Plain, and lower Coastal Plain physiographic provinces of South Carolina. The most significant explanatory variables from this analysis were mainchannel length, percent impervious area, and basin development factor. Mean standard errors of prediction for the regression equations ranged from -25 to 33 percent for the 10-year recurrence-interval flows and from -35 to 54 percent for the 100-year recurrence-interval flows. The U.S. Geological Survey has developed a Geographic Information System application called StreamStats that makes the process of computing streamflow statistics at ungaged sites faster and more consistent than manual methods. This application was developed in the Massachusetts District and ongoing work is being done in other districts to develop a similar application using streamflow statistics relative to those respective States. Considering the future possibility of implementing StreamStats in South Carolina, an alternative set of regional regression equations was developed using only main channel length and impervious area. This was done because no digital coverages are currently available for basin development factor and, therefore, it could not be included in the StreamStats application. The average mean standard error of prediction for the alternative equations was 2 to 5 percent larger than the standard errors for the equations that contained basin development factor. For the urban streamflow-gaging stations in South Carolina, measured water-year peak flows were compared with those from an earlier urban flood-frequency investigation. The peak flows from the earlier investigation were computed using a rainfall-runoff model. At many of the sites, graphical comparisons indicated that the variance of the measured data was much less than the variance of the simulated data. Several statistical tests were applied to compare the variances and the means of the measured and simulated data for each site. The results indicated that the variances were significantly different for 11 of the 13 South Carolina streamflow-gaging stations. For one streamflow-gaging station, the test for normality, which is one of the assumptions of the data when comparing variances, indicated that neither the measured data nor the simulated data were distributed normally; therefore, the test for differences in the variances was not used for that streamflow-gaging station. Another statistical test was used to test for statistically significant differences in the means of the measured and simulated data. The results indicated that for 5 of the 13 urban streamflowgaging stations in South Carolina there was a statistically significant difference in the means of the two data sets. For comparison purposes and to test the hypothesis that there may have been climatic differences between the period in which the measured peak-flow data were measured and the period for which historic rainfall data were used to compute the simulated peak flows, 16 rural streamflow-gaging stations with long-term records were reviewed using similar techniques as those used for the measured an

South Carolina↗

USGS2003

Simulation of Temperature, Nutrients, Biochemical Oxygen Demand, and Dissolved Oxygen in the Catawba River, South Carolina, 1996-97

Time-series plots of dissolved-oxygen concentrations were determined for various simulated hydrologic and point-source loading conditions along a free-flowing section of the Catawba River from Lake Wylie Dam to the headwaters of Fishing Creek Reservoir in South Carolina. The U.S. Geological Survey one-dimensional dynamic-flow model, BRANCH, was used to simulate hydrodynamic data for the Branched Lagrangian Transport Model. Waterquality data were used to calibrate the Branched Lagrangian Transport Model and included concentrations of nutrients, chlorophyll a, and biochemical oxygen demand in water samples collected during two synoptic sampling surveys at 10 sites along the main stem of the Catawba River and at 3 tributaries; and continuous water temperature and dissolved-oxygen concentrations measured at 5 locations along the main stem of the Catawba River. A sensitivity analysis of the simulated dissolved-oxygen concentrations to model coefficients and data inputs indicated that the simulated dissolved-oxygen concentrations were most sensitive to watertemperature boundary data due to the effect of temperature on reaction kinetics and the solubility of dissolved oxygen. Of the model coefficients, the simulated dissolved-oxygen concentration was most sensitive to the biological oxidation rate of nitrite to nitrate. To demonstrate the utility of the Branched Lagrangian Transport Model for the Catawba River, the model was used to simulate several water-quality scenarios to evaluate the effect on the 24-hour mean dissolved-oxygen concentrations at selected sites for August 24, 1996, as simulated during the model calibration period of August 23 27, 1996. The first scenario included three loading conditions of the major effluent discharges along the main stem of the Catawba River (1) current load (as sampled in August 1996); (2) no load (all point-source loads were removed from the main stem of the Catawba River; loads from the main tributaries were not removed); and (3) fully loaded (in accordance with South Carolina Department of Health and Environmental Control National Discharge Elimination System permits). Results indicate that the 24-hour mean and minimum dissolved-oxygen concentrations for August 24, 1996, changed from the no-load condition within a range of - 0.33 to 0.02 milligram per liter and - 0.48 to 0.00 milligram per liter, respectively. Fully permitted loading conditions changed the 24-hour mean and minimum dissolved-oxygen concentrations from - 0.88 to 0.04 milligram per liter and - 1.04 to 0.00 milligram per liter, respectively. A second scenario included the addition of a point-source discharge of 25 million gallons per day to the August 1996 calibration conditions. The discharge was added at S.C. Highway 5 or at a location near Culp Island (about 4 miles downstream from S.C. Highway 5) and had no significant effect on the daily mean and minimum dissolved-oxygen concentration. A third scenario evaluated the phosphorus loading into Fishing Creek Reservoir; four loading conditions of phosphorus into Catawba River were simulated. The four conditions included fully permitted and actual loading conditions, removal of all point sources from the Catawba River, and removal of all point and nonpoint sources from Sugar Creek. Removing the point-source inputs on the Catawba River and the point and nonpoint sources in Sugar Creek reduced the organic phosphorus and orthophosphate loadings to Fishing Creek Reservoir by 78 and 85 percent, respectively.

South Carolina↗

USGS2002

Techniques for estimating the magnitude and frequency of floods in rural basins of South Carolina, 1999

Data from 167 streamflow-gaging stations in or near South Carolina with 10 or more years of record through September 30, 1999, were used to develop two methods for estimating the magnitude and frequency of floods in South Carolina for rural ungaged basins that are not significantly affected by regulation. Floodfrequency estimates for 54 gaged sites in South Carolina were computed by fitting the water-year peak flows for each site to a log-Pearson Type III distribution. As part of the computation of flood-frequency estimates for gaged sites, new values for generalized skew coefficients were developed. Flood-frequency analyses also were made for gaging stations that drain basins from more than one physiographic province. The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, updated these data from previous flood-frequency reports to aid officials who are active in floodplain management as well as those who design bridges, culverts, and levees, or other structures near streams where flooding is likely to occur. Regional regression analysis, using generalized least squares regression, was used to develop a set of predictive equations that can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence- interval flows for rural ungaged basins in the Blue Ridge, Piedmont, upper Coastal Plain, and lower Coastal Plain physiographic provinces of South Carolina. The predictive equations are all functions of drainage area. Average errors of prediction for these regression equations ranged from -16 to 19 percent for the 2-year recurrence-interval flow in the upper Coastal Plain to -34 to 52 percent for the 500-year recurrenceinterval flow in the lower Coastal Plain. A region-of-influence method also was developed that interactively estimates recurrence- interval flows for rural ungaged basins in the Blue Ridge of South Carolina. The region-of-influence method uses regression techniques to develop a unique relation between flow and basin characteristics for an individual watershed. This, then, can be used to estimate flows at ungaged sites. Because the computations required for this method are somewhat complex, a computer application was developed that performs the computations and compares the predictive errors for this method. The computer application includes the option of using the region-of-influence method, or the generalized least squares regression equations from this report to compute estimated flows and errors of prediction specific to each ungaged site. From a comparison of predictive errors using the region-of-influence method with those computed using the regional regression method, the region-of-influence method performed systematically better only in the Blue Ridge and is, therefore, not recommended for use in the other physiographic provinces. Peak-flow data for the South Carolina stations used in the regionalization study are provided in appendix A, which contains gaging station information, log- Pearson Type III statistics, information on stage-flow relations, and water-year peak stages and flows. For informational purposes, water-year peak-flow data for stations on regulated streams in South Carolina also are provided in appendix D. Other information pertaining to the regulated streams is provided in the text of the report.

South Carolina↗