Geology topics

Paul Conrads

Publications and source records attributed to Paul Conrads.

45 records · Page 3Linked to original sources

USGS2007

Hydrologic Record Extension of Water-Level Data in the Everglades Depth Estimation Network (EDEN) Using Artificial Neural Network Models, 2000-2006

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface models designed to provide scientists, engineers, and water-resource managers with current (2000-present) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystem Science provides support for EDEN and the goal of providing quality assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. To increase the accuracy of the water-surface models, 25 real-time water-level gaging stations were added to the network of 253 established water-level gaging stations. To incorporate the data from the newly added stations to the 7-year EDEN database in the greater Everglades, the short-term water-level records (generally less than 1 year) needed to be simulated back in time (hindcasted) to be concurrent with data from the established gaging stations in the database. A three-step modeling approach using artificial neural network models was used to estimate the water levels at the new stations. The artificial neural network models used static variables that represent the gaging station location and percent vegetation in addition to dynamic variables that represent water-level data from the established EDEN gaging stations. The final step of the modeling approach was to simulate the computed error of the initial estimate to increase the accuracy of the final water-level estimate. The three-step modeling approach for estimating water levels at the new EDEN gaging stations produced satisfactory results. The coefficients of determination (R2) for 21 of the 25 estimates were greater than 0.95, and all of the estimates (25 of 25) were greater than 0.82. The model estimates showed good agreement with the measured data. For some new EDEN stations with limited measured data, the record extension (hindcasts) included periods beyond the range of the data used to train the artificial neural network models. The comparison of the hindcasts with long-term water-level data proximal to the new EDEN gaging stations indicated that the water-level estimates were reasonable. The percent model error (root mean square error divided by the range of the measured data) was less than 6 percent, and for the majority of stations (20 of 25), the percent model error was less than 1 percent.

Open-File Report↗

USGS2007

Analysis of salinity intrusion in the Waccamaw River and Atlantic Intracoastal Waterway near Myrtle Beach, South Carolina, 1995-2002

Six reservoirs in North Carolina discharge into the Pee Dee River, which flows 160 miles through South Carolina to the coastal communities near Myrtle Beach, South Carolina. During the Southeast's record-breaking drought from 1998 to 2003, salinity intrusions inundated a coastal municipal freshwater intake, limiting water supplies. To evaluate the effects of regulated flows of the Pee Dee River on salinity intrusion in the Waccamaw River and Atlantic Intracoastal Waterway, the South Carolina Department of Natural Resources and a consortium of stakeholders entered into a cooperative agreement with the U.S. Geological Survey to apply data-mining techniques to the long-term time series to analyze and simulate salinity dynamics near the freshwater intakes along the Grand Strand of South Carolina. Salinity intrusion in tidal rivers results from the interaction of three principal forces—streamflow, mean tidal water levels, and tidal range. To analyze, model, and simulate hydrodynamic behaviors at critical coastal gages, data-mining techniques were applied to over 20 years of hourly streamflow, coastal water-quality, and water-level data. Artificial neural network models were trained to learn the variable interactions that cause salinity intrusions. Streamflow data from the 18,300-square-mile basin were input to the model as time-delayed variables and accumulated tributary inflows. Tidal inputs to the models were obtained by decomposing tidal water-level data into a "periodic" signal of tidal range and a "chaotic" signal of mean water levels. The artificial neural network models were able to convincingly reproduce historical behaviors and generate alternative scenarios of interest. To make the models directly available to all stakeholders along the Pee Dee and Waccamaw Rivers and Atlantic Intracoastal Waterway, an easy-to-use decision support system (DSS) was developed as a spreadsheet application that integrates the historical database, artificial neural network models, model controls, streaming graphics, and model output. An additional feature is a built-in optimizer that dynamically calculates the amount of flow needed to suppress salinity intrusions as tidal ranges and water levels vary over days and months. This DSS greatly reduced the number of long-term simulations needed for stakeholders to determine the minimum flow required to adequately protect the freshwater intakes.

South Carolina↗

USGS2007

Visualization and Time-Series Analysis of Ground-Water Data for C-Area, Savannah River Site, South Carolina, 1984-2004

In 2004, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, initiated a study of historical ground-water data of C-Area on the Savannah River Site in South Carolina. The soils and ground water at C-Area are contaminated with high concentrations of trichloroethylene and lesser amounts of tetrachloroethylene. The objectives of the investigation were (1) to analyze the historical data to determine if data-mining techniques could be applied to the historical database to ascertain whether natural attenuation of recalcitrant contaminants, such as volatile organic compounds, is occurring and (2) to determine whether inferential (surrogate) analytes could be used for more cost-effective monitoring. Twenty-one years of data (1984-2004) were collected from 396 wells in the study area and converted from record data to time-series data for analysis. A Ground-Water Data Viewer was developed to allow users to spatially and temporally visualize the analyte data. Overall, because the data were temporally and spatially sparse, data analysis was limited to only qualitative descriptions.

South Carolina↗

USGS2006

Trends of Abutment-Scour Prediction Equations Applied to 144 Field Sites in South Carolina

The U.S. Geological Survey conducted a study in cooperation with the Federal Highway Administration in which predicted abutment-scour depths computed with selected predictive equations were compared with field measurements of abutment-scour depth made at 144 bridges in South Carolina. The assessment used five equations published in the Fourth Edition of 'Evaluating Scour at Bridges,' (Hydraulic Engineering Circular 18), including the original Froehlich, the modified Froehlich, the Sturm, the Maryland, and the HIRE equations. An additional unpublished equation also was assessed. Comparisons between predicted and observed scour depths are intended to illustrate general trends and order-of-magnitude differences for the prediction equations. Field measurements were taken during non-flood conditions when the hydraulic conditions that caused the scour generally are unknown. The predicted scour depths are based on hydraulic conditions associated with the 100-year flow at all sites and the flood of record for 35 sites. Comparisons showed that predicted scour depths frequently overpredict observed scour and at times were excessive. The comparison also showed that underprediction occurred, but with less frequency. The performance of these equations indicates that they are poor predictors of abutment-scour depth in South Carolina, and it is probable that poor performance will occur when the equations are applied in other geographic regions. Extensive data and graphs used to compare predicted and observed scour depths in this study were compiled into spreadsheets and are included in digital format with this report. In addition to the equation-comparison data, Water-Surface Profile Model tube-velocity data, soil-boring data, and selected abutment-scour data are included in digital format with this report. The digital database was developed as a resource for future researchers and is especially valuable for evaluating the reasonableness of future equations that may be developed.

South Carolina↗

USGS2006

Simulation of Water Levels and Salinity in the Rivers and Tidal Marshes in the Vicinity of the Savannah National Wildlife Refuge, Coastal South Carolina and Georgia

The Savannah Harbor is one of the busiest ports on the East Coast of the United States and is located downstream from the Savannah National Wildlife Refuge, which is one of the Nation?s largest freshwater tidal marshes. The Georgia Ports Authority and the U.S. Army Corps of Engineers funded hydrodynamic and ecological studies to evaluate the potential effects of a proposed deepening of Savannah Harbor as part of the Environmental Impact Statement. These studies included a three-dimensional (3D) model of the Savannah River estuary system, which was developed to simulate changes in water levels and salinity in the system in response to geometry changes as a result of the deepening of Savannah Harbor, and a marsh-succession model that predicts plant distribution in the tidal marshes in response to changes in the water-level and salinity conditions in the marsh. Beginning in May 2001, the U.S. Geological Survey entered into cooperative agreements with the Georgia Ports Authority to develop empirical models to simulate the water level and salinity of the rivers and tidal marshes in the vicinity of the Savannah National Wildlife Refuge and to link the 3D hydrodynamic river-estuary model and the marsh-succession model. For the development of these models, many different databases were created that describe the complexity and behaviors of the estuary. The U.S. Geological Survey has maintained a network of continuous streamflow, water-level, and specific-conductance (field measurement to compute salinity) river gages in the study area since the 1980s and a network of water-level and salinity marsh gages in the study area since 1999. The Georgia Ports Authority collected water-level and salinity data during summer 1997 and 1999 and collected continuous water-level and salinity data in the marsh and connecting tidal creeks from 1999 to 2002. Most of the databases comprise time series that differ by variable type, periods of record, measurement frequency, location, and reliability. Understanding freshwater inflows, tidal water levels, and specific conductance in the rivers and marshes is critical to enhancing the predictive capabilities of a successful marsh succession model. Data-mining techniques, including artificial neural network (ANN) models, were applied to address various needs of the ecology study and to integrate the riverine predictions from the 3D model to the marsh-succession model. ANN models were developed to simulate riverine water levels and specific conductance in the vicinity of the tidal marshes for the full range of historical conditions using data from the river gaging networks. ANN models were also developed to simulate the marsh water levels and pore-water salinities using data from the marsh gaging networks. Using the marsh ANN models, the continuous marsh network was hindcasted to be concurrent with the long-term riverine network. The hindcasted data allow ecologists to compute hydrologic parameters?such as hydroperiods and exposure frequency?to help analyze historical vegetation data. To integrate the 3D hydrodynamic model, the marsh-succession model, and various time-series databases, a decision support system (DSS) was developed to support the various needs of regulatory and scientific stakeholders. The DSS required the development of a spreadsheet application that integrates the database, 3D hydrodynamic model output, and ANN riverine and marsh models into a single package that is easy to use and can be readily disseminated. The DSS allows users to evaluate water-level and salinity response for different hydrologic conditions. Savannah River streamflows can be controlled by the user as constant flow, a percentage of historical flows, a percentile daily flow hydrograph, or as a user-specified hydrograph. The DSS can also use output from the 3D model at stream gages near the Savannah National Wildlife Refuge to simulate the effects in the tidal marshes. The DSS is distributed with a two-dimensional (

Georgia, South Carolina↗

USGS2003

Estimating water temperatures in small streams in western Oregon using neural network models

Artificial neural network models were developed to estimate water temperatures in small streams using data collected at 148 sites throughout western Oregon from June to September 1999. The sites were located on 1st-, 2nd-, or 3rd-order streams having undisturbed or minimally disturbed conditions. Data collected at each site for model development included continuous hourly water temperature and description of riparian habitat. Additional data pertaining to the landscape characteristics of the basins upstream of the sites were assembled using geographic information system (GIS) techniques. Hourly meteorological time series data collected at 25 locations within the study region also were assembled. Clustering analysis was used to partition 142 sites into 3 groups. Separate models were developed for each group. The riparian habitat, basin characteristic, and meteorological time series data were independent variables and water temperature time series were dependent variables to the models, respectively. Approximately one-third of the data vectors were used for model training, and the remaining two-thirds were used for model testing. Critical input variables included riparian shade, site elevation, and percentage of forested area of the basin. Coefficient of determination and root mean square error for the models ranged from 0.88 to 0.99 and 0.05 to 0.59 oC, respectively. The models also were tested and validated using temperature time series, habitat, and basin landscape data from 6 sites that were separate from the 142 sites that were used to develop the models. The models are capable of estimating water temperatures at locations along 1st-, 2nd-, and 3rd-order streams in western Oregon. The model user must assemble riparian habitat and basin landscape characteristics data for a site of interest. These data, in addition to meteorological data, are model inputs. Output from the models include simulated hourly water temperatures for the June to September period. Adjustments can be made to the shade input data to simulate the effects of minimum or maximum shade on water temperatures.

Oregon↗

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↗

USGS2000

Characterization of water quality and simulation of temperature, nutrients, biochemical oxygen demand, and dissolved oxygen in the Wateree River, South Carolina, 1996-98

In May 1996, the U.S. Geological Survey entered into a cooperative agreement with the Kershaw County Water and Sewer Authority to characterize and simulate the water quality in the Wateree River, South Carolina. Longitudinal profiling of dissolved-oxygen concentrations during the spring and summer of 1996 revealed dissolved-oxygen minimums occurring upstream from the point-source discharges. The mean dissolved-oxygen decrease upstream from the effluent discharges was 2.0 milligrams per liter, and the decrease downstream from the effluent discharges was 0.2 milligram per liter. Several theories were investigated to obtain an improved understanding of the dissolved-oxygen dynamics in the upper Wateree River. Data suggest that the dissolved-oxygen concentration decrease is associated with elevated levels of oxygen-consuming nutrients and metals that are flowing into the Wateree River from Lake Wateree. Analysis of long-term streamflow and water-quality data collected at two U.S. Geological Survey gaging stations suggests that no strong correlation exists between streamflow and dissolved-oxygen concentrations in the Wateree River. However, a strong negative correlation does exist between dissolved-oxygen concentrations and water temperature. Analysis of data from six South Carolina Department of Health and Environmental Control monitoring stations for 1980.95 revealed decreasing trends in ammonia nitrogen at all stations where data were available and decreasing trends in 5-day biochemical oxygen demand at three river stations. The influence of various hydrologic and point-source loading conditions on dissolved-oxygen concentrations in the Wateree River were determined by using results from water-quality simulations by the Branched Lagrangian Transport Model. The effects of five tributaries and four point-source discharges were included in the model. Data collected during two synoptic water-quality samplings on June 23.25 and August 11.13, 1997, were used to calibrate and validate the Branched Lagrangian Transport Model. The data include dye-tracer concentrations collected at six locations, stream-reaeration data collected at four locations, and water-quality and water-temperature data collected at nine locations. Hydraulic data for the Branched Lagrangian Transport Model were simulated by using the U.S. Geological Survey BRANCH one-dimensional, unsteady-flow model. Data that were used to calibrate and validate the BRANCH model included time-series of water-level and streamflow data at three locations. The domain of the hydraulic model and the transport model was a 57.3- and 43.5-mile reach of the river, respectively. 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 changes in the boundary concentration inputs of water temperature and dissolved oxygen followed by sensitivity to the change in streamflow. A 35-percent increase in streamflow resulted in a negative normalized sensitivity index, indicating a decrease in dissolved-oxygen concentrations. The simulated dissolved-oxygen concentrations showed no significant sensitivity to changes in model input rate kinetics. To demonstrate the utility of the Branched Lagrangian Transport Model of the Wateree River, the model was used to simulate several hydrologic and water-quality scenarios to evaluate the effects on simulated dissolved-oxygen concentrations. The first scenario compared the 24-hour mean dissolved-oxygen concentrations for August 13, 1997, as simulated during the model validation, with simulations using two different streamflow patterns. The mean streamflow for August 13, 1997, was 2,000 cubic feet per second. Simulations were run using mean streamflows of 1,000 and 1,400 cubic feet per second while keeping the water-quality boundary conditions the same as were used during the validation simulations.

South Carolina↗

USGS1994

Ground-water and precipitation data for South Carolina, 1990

Continuous water-level data collected from 53 wells in South Carolina during 1990 provide the basic data for this report. Hydrographs are presented for selected wells to illustrate the effects that changes in ground-water recharge and artificial ground-water discharge have had on the ground-water reservoirs in the State. Daily mean water levels are listed in tables. Monthly mean water levels for 1990 and for the entire period of record at each monitoring well are depicted in hydrographs. Also included are precipitation records from ten National Weather Service stations in South Carolina.

South Carolina↗