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Anthony J. Gotvald

Publications and source records attributed to Anthony J. Gotvald.

29 records · Page 2Linked to original sources
USGS2010

Epic Flooding in Georgia, 2009

Metropolitan Atlanta-September 2009 Floods The epic floods experienced in the Atlanta area in September 2009 were extremely rare. Eighteen streamgages in the Metropolitan Atlanta area had flood magnitudes much greater than the estimated 0.2-percent (500-year) annual exceedance probability. The Federal Emergency Management Agency (FEMA) reported that 23 counties in Georgia were declared disaster areas due to this flood and that 16,981 homes and 3,482 businesses were affected by floodwaters. Ten lives were lost in the flood. The total estimated damages exceed $193 million (H.E. Longenecker, Federal Emergency Management Agency, written commun., November 2009). On Sweetwater Creek near Austell, Ga., just north of Interstate 20, the peak stage was more than 6 feet higher than the estimated peak stage of the 0.2-percent (500-year) flood. Flood magnitudes in Cobb County on Sweetwater, Butler, and Powder Springs Creeks greatly exceeded the estimated 0.2-percent (500-year) floods for these streams. In Douglas County, the Dog River at Ga. Highway 5 near Fairplay had a peak stage nearly 20 feet higher than the estimated peak stage of the 0.2-percent (500-year) flood. On the Chattahoochee River, the U.S. Geological Survey (USGS) gage at Vinings reached the highest level recorded in the past 81 years. Gwinnett, De Kalb, Fulton, and Rockdale Counties also had record flooding. South Georgia March and April 2009 Floods The March and April 2009 floods in South Georgia were smaller in magnitude than the September floods but still caused significant damage. No lives were lost in this flood. Approximately $60 million in public infrastructure damage occurred to roads, culverts, bridges and a water treatment facility (Joseph T. McKinney, Federal Emergency Management Agency, written commun., July 2009). Flow at the Satilla River near Waycross, exceeded the 0.5-percent (200-year) flood. Flows at seven other stations in South Georgia exceeded the 1-percent (100-year) flood.

Fact Sheet↗
USGS2010

Historic Flooding in Georgia, 2009

Heavy rains in southern Georgia during March 27-April 3, 2009, and in northern Georgia during September 16-22, 2009, caused severe flooding and widespread damages to residential, public, and commercial structures. Of the 159 counties in Georgia, 69 were declared disaster areas because of flooding. The heavy rainfall in southern Georgia resulted in severe flooding in the Satilla-St. Marys and upper Ochlockonee Basins and caused approximately $60 million in damages to the public infrastructure. The heavy rainfall in northern Georgia resulted in severe flooding on many streams within the upper Chattahoochee, Altamaha, and Coosa-Tallapoosa Basins and caused 10 deaths, evacuation of thousands of residents, and approximately $500 million in damages. The U.S. Geological Survey computed annual exceedance probabilities of the peak flows in 2009 at 238 streamgages throughout the State. Record peak flows were recorded at 40 streamgages for the respective periods of record as a result of the heavy rainfall during the two multiday events. The peak flows at 33 streamgages exceeded the 1-percent annual exceedance probability (100-year recurrence interval), and 19 of these exceeded the 0.2-percent annual exceedance probability (500-year recurrence interval).

Georgia↗
USGS2010

Surface-water quality-assurance plan for the USGS Georgia Water Science Center, 2010

The U.S. Geological Survey requires that each Water Science Center prepare a surface-water quality-assurance plan to describe policies and procedures that ensure high quality surface-water data collection, processing, analysis, computer storage, and publication. The Georgia Water Science Center's standards, policies, and procedures for activities related to the collection, processing, analysis, computer storage, and publication of surface-water data are documented in this Surface-Water Quality-Assurance Plan for 2010.

Georgia↗
USGS2009

Acoustic Doppler current profiler applications used in rivers and estuaries by the U.S. Geological Survey

The U.S. Geological Survey (USGS) has collected streamflow information for the Nation's streams since 1889. Streamflow information is used to predict floods, manage and allocate water resources, design engineering structures, compute water-quality loads, and operate water-control structures. The current (2007) size of the USGS streamgaging network is over 7,400 streamgages nationwide. The USGS has progressively improved the streamgaging program by incorporating new technologies and techniques that streamline data collection while increasing the quality of the streamflow data that are collected. The single greatest change in streamflow measurement technology during the last 100 years has been the development and application of high frequency acoustic instruments for measuring streamflow. One such instrument, the acoustic Doppler current profiler (ADCP), is rapidly replacing traditional mechanical current meters for streamflow measurement (Muste and others, 2007). For more information on how an ADCP works see Simpson (2001) or visit http://hydroacoustics.usgs.gov/. The USGS has used ADCPs attached to manned or tethered boats since the mid-1990s to measure streamflow in a wide variety of conditions (fig. 1). Recent analyses have shown that ADCP streamflow measurements can be made with similar or greater accuracy, efficiency, and resolution than measurements made using conventional current-meter methods (Oberg and Mueller, 2007). ADCPs also have the ability to measure streamflow in streams where traditional current-meter measurements previously were very difficult or costly to obtain, such as streams affected by backwater or tides. In addition to streamflow measurements, the USGS also uses ADCPs for other hydrologic measurements and applications, such as computing continuous records of streamflow for tidally or backwater affected streams, measuring velocity fields with high spatial and temporal resolution, and estimating suspended-sediment concentrations. An overview of these applications is provided in the fact sheet.

Fact Sheet↗
USGS2009

Historic Flooding in South Georgia, March 27-April 3, 2009

A primary mission of the U.S. Geological Survey (USGS) is the measurement and documentation of the magnitude and extent of hydrologic hazards, such as floods, droughts, and hurricane storm surge. USGS personnel were deployed for historic widespread flooding that occurred throughout South Georgia from a storm event beginning in the late evening of March 27 and continuing through April 3, 2009. Data collected by USGS personnel and a network of automated real-time streamgages are critical to emergency management officials so that informed decisions can be made before, during, and after an event to assist in the protection of life and property. According to the Federal Emergency Management Agency (FEMA), 46 counties in Georgia were declared disaster areas due to flooding. FEMA reported that 1,875 homes and 29 businesses were affected by floodwaters. No lives were lost in this flood. Approximately $60 million in public infrastructure damage occurred to roads, culverts, bridges and a water treatment facility (Joseph T. McKinney, Federal Emergency Management Agency, written commun., July 2009).

Georgia↗
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↗