Geology topics

Matthew D. Petkewich

Publications and source records attributed to Matthew D. Petkewich.

At least 19 recordsLinked to original sources

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↗

USGS2024

Community for Data Integration 2020 project report

The U.S. Geological Survey Community for Data Integration annually funds small projects focusing on data integration for interdisciplinary research, innovative data management, and demonstration of new technologies. This report provides a summary of the 12 projects funded in fiscal year 2020, outlining their goals, activities, and accomplishments.

Open-File Report↗

USGS2022

Evaluation of the Bushy Park Reservoir three-dimensional hydrodynamic and water-quality model, South Carolina, 2012–15

The Bushy Park Reservoir is a relatively shallow impoundment in southeastern South Carolina. The reservoir, located under a semi-tropical climate, is the principal water supply for the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there was an adequate supply of freshwater in the reservoir in 2022, water-quality concerns are present over taste-and-odor and saltwater-intrusion issues. From 2013 to 2015, the U.S. Geological Survey (USGS), in cooperation with the Charleston Water System, engaged in a multi-year study of the hydrology and hydrodynamics of Bushy Park Reservoir to better understand factors affecting water-quality conditions in the reservoir. As part of this study, Charleston Water System worked with Tetra Tech, Inc., a consulting and engineering firm, to develop a Bushy Park Reservoir hydrodynamic and water-quality modeling framework, built upon earlier efforts by both Tetra Tech and the U.S. Army Corps of Engineers. At the completion of the new modeling framework, the USGS was requested to evaluate the calibrated hydrodynamic and water-quality model. The Bushy Park Reservoir Environmental Fluid Dynamics Code (EFDC) model was calibrated for the time period from January 1, 2012, to December 31, 2015. The general modeling approach for the newly revised modeling framework, as briefly detailed in this report, was developed with EFDC. The EFDC is a grid-based modeling package that can simulate three-dimensional flow, transport, and water quality in surface-water systems. This report evaluated the capacity of Tetra Tech’s Bushy Park EFDC model to simulate water discharge, water circulation, surface elevations, temperature, salinity, and other water-quality parameters. The USGS model review focused specifically on the following criteria: (1) determine if the model, with additional effort, could be developed into an adequate planning tool for Bushy Park Reservoir; (2) assess the capacity of the model to specifically address water-quality issues in the reservoir related to taste-and-odor and saltwater intrusions; and, (3) evaluate three preliminary water-management scenarios related to reduced water withdrawals in the reservoir and the effect on saltwater intrusion. Overall, the model was able to simulate discharge, flow velocity, and water-surface elevations with generally good agreement between the simulated and measured values. Specifically, the model was able to demonstrate good agreement for discharge at two USGS continuous discharge locations (USGS station 02172002; USGS station 02172040), with Wilmott index of agreements of 0.86 and 0.75, respectively. A total of seven USGS streamgages, located on the West Branch of the Cooper River, Durham Canal, and the Cooper River, were available for water-surface elevations, with index of agreements ranging from 0.74 to 0.99. However, model-simulated water-surface elevation ranges were appreciably high (compared to measured ranges) for two locations near Pinopolis Dam, farthest upstream on the West Branch of the Cooper River. This result may indicate that too much simulated tidal energy propagated through the model domain. For water temperature, 16 calibration stations were available for at least part of the 4-year simulation. The index of agreement range for temperature comparisons was from 0.95 to 1.00, indicating excellent agreement between the measured and simulated results. One of the primary future applications for the Bushy Park Reservoir EFDC model is to determine the extent of saltwater intrusions. A wide range in the salinity prediction quality was simulated with the model. The prediction quality ranged from an index of agreement of 0.15 at Cooper River approximately 2.75 miles southeast of the Tee, South Carolina, to 0.92 at West Branch Cooper River near Moncks Corner, South Carolina. Although the model did not accurately simulate some of the larger salinity deviations resulting during individual hydrologic events, the seasonal salinity trends were adequately simulated with the model during the study period (2012–15). Therefore, it may be difficult to simulate extreme hydrologic events, such as during large storms, where high salinity water is exchanged with Bushy Park Reservoir. There was agreement in model simulation with the measured data either on the quantitative index of agreement values or qualitative agreement in the seasonal salinity data trends. For water quality, the index of agreement values were generally low for total nitrogen, ammonia, nitrate, total Kjeldahl nitrogen, total phosphorus, and orthophosphate. Although general trends were adequately simulated at specific stations, particularly for Bushy Park Reservoir, the model-simulated fit was low across all the constituents described above with index of agreements usually below 0.50. A limitation for simulating nutrient concentrations across the model domain was the lack of characterization for the constituents directly entering Bushy Park Reservoir, or the lack of data directly attributed to the boundary condition (for example, the Cooper River). The other two calibrated water-quality constituents (besides the nutrients mentioned above) were dissolved oxygen and chlorophyll a . Dissolved oxygen varied from index of agreement values from 0.58 to 0.94 for 11 stations, generally indicating agreement with the available measured data. Chlorophyll a , calibrated for seven stations, had a wider range from 0.11 to 0.74 for the index of agreement. With the current modeling framework, taste-and-odor events, related to cyanobacterial blooms, cannot be directly simulated. However, indirect estimates of cyanobacteria concentrations may be obtained by using the chlorophyll a model outputs, which represent total phytoplankton biomass, and the phytoplankton biovolume data by group (diatoms, green algae, cyanobacteria and others) collected from 2012 to 2015. For the Bushy Park Reservoir modeling framework to be used directly for taste-and-odor issues, cyanobacteria must be simulated and calibrated based on observations of cyanobacteria biomass concentrations. In addition to the cyanobacteria sampling conducted within the reservoir between 2012 and 2015, the new model calibration would also require new algae biomass data-collection efforts to characterize the external sources of cyanobacteria entering the Bushy Park Reservoir from tributaries, as well as the internal cycling, production, and decay of cyanobacteria in the hydrologic system. Further improvements to the EFDC model would include expanding the collection of boundary condition datasets, such as water-quality monitoring to determine improved nutrient loads into the model domain. Along with improved water-quality monitoring for the major boundary conditions, continuous discharge, for both Foster Creek and the Back River, would further constrain the flow balance and the loads into Bushy Park Reservoir. In addition to better boundary-condition characterization, it is important to better characterize possible shortcomings specifically to the model domain, such as the grid resolution, bathymetry, and numerical hydrodynamic errors. Further consideration of the model may involve a sensitivity analysis to determine if errors in the simulation outputs, such as discharge, water-surface elevations, and salinity, were more likely caused by poor boundary condition characterization or, specifically, the model setup. Three model scenarios were run with the revised Bushy Park Reservoir model: (1) reduced withdrawals from one of the large intake-discharge locations for Bushy Park Reservoir, the Williams Station; (2) elevated (above background levels) ocean water level causing saltwater intrusion from the ocean through Durham Canal into Bushy Park Reservoir; and (3) overtopping of the Back River Dam at the southernmost end of Bushy Park Reservoir. For the reduced withdrawals scenarios, the largest shift in flow resulted near the Williams Station intake, with the next largest flow change at the southern end of Bushy Park Reservoir, and a net increase in flow out of the Bushy Park Reservoir to the Cooper River by way of the Durham Canal. The effect resulting from scenario 3 on water quality and salinity was small, with larger increases for dissolved oxygen than other constituents at several monitoring stations. For the two scenarios related to saltwater intrusion (including dam overtopping), the changes in salinity generally were found to dissipate in the following 2 weeks and generally back to baseline salinity conditions within 3 months. This result did vary depending on the severity of the storm or length of the dam overtopping event.

South Carolina↗

USGS2020

The Everglades Depth Estimation Network (EDEN) surface-water interpolation model, version 3

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that estimate daily water-level data at ungaged locations, and applications that generate derived hydrologic data across the freshwater part of the Greater Everglades landscape. Version 3 (V3) of the EDEN interpolation surface-water model is the most recent update, replacing the version 2 (V2) model released in 2011. The primary revision for the V3 model is the switch to the R programming language to create a more efficient and portable EDEN code relative to V2, without reliance on proprietary software. Using R, the interpolation script runs over 10 times faster and is more easily updated, for example, to accommodate changes in the gage network or to incorporate R software updates. Additional revisions made for the V3 model include updates to the interpolation model, the gage network, and groundwater-level estimations. The EDEN model domain in the Greater Everglades and Big Cypress National Preserve is divided into subdomains that are based on hydrologic boundaries. In the V3 model, the number of subdomains was increased from five to eight, which allows hydrologic boundaries, such as levees and canals, to be better represented in the interpolation scheme. Five pseudogages were added to constrain the water-level surface at subdomain boundaries. Changes made to the water-level gage network between the implementation of the V2 and V3 models are incorporated, and groundwater-level estimations are added, which are important information for hydrologic and ecological studies. Summary model performance statistics indicate similar accuracy in water-level surfaces generated by the V3 and V2 models, with a root mean square error of 4.78 centimeters for both interpolation models against independent water-level measurements. Providing stability and continuity for the EDEN user community, the V3 model closely replicates the V2 model, with a root mean square difference of 3.87 centimeters for interpolated surfaces from April 1, 2014, to March 31, 2018. The additional groundwater levels provide a realistic estimate of the saturated groundwater surface continuous with the surface-water surface for Water Conservation Areas 2A and 2B from 2000 to 2011. This continuous surface is a more accurate estimation of the spatial distribution of water in the hydrologic system than before, providing needed information for ecological studies in areas where depth to water table affects habitats. Development of the EDEN V3 model advances the tools available to scientists and resource managers for guiding large-scale field operations, describing hydrologic changes, and supporting biological and ecological assessments.

Florida↗

USGS2020

Effects of stormwater runoff from selected bridge decks on conditions of water, sediment, and biological quality in receiving waters in South Carolina, 2013 to 2018

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, investigated the effects of stormwater runoff from bridge decks on stream water quality conditions in South Carolina. The investigation assessed 5 bridges in 3 physiographic provinces in South Carolina (Piedmont, Upper Coastal Plain, and Lower Coast Plain) that had a range of bridge, traffic, and hydrologic characteristics. The five selected South Carolina bridge sites (coincident with U.S. Geological Survey stations) and corresponding highways were Lynches River at Effingham (station 02132000; U.S. Highway 52), North Fork Edisto River at Orangeburg (station 02173500; U.S. Highway 301), Turkey Creek above Huger (station 02172035; South Carolina Highway 41), South Fork Edisto River near Denmark (station 02173000; U.S. Highway 321), and Fishing Creek at Highway 5 below York (station 021473415; South Carolina Highway 5). Bridge decks at the selected sites used open chutes, scuppers, and downspouts to drain stormwater directly into the receiving water at evenly spaced intervals. Stream water, sediment, and biological samples were collected and analyzed for a variety of constituents to evaluate the stream conditions for this study. Five to six stream samples were collected at transects upstream and downstream from each selected bridge site using the equal-width-increment technique during observable stormwater runoff. Routine samples of the receiving waters were collected 12 to 14 times at the upstream transect during nonstorm conditions. Samples were analyzed for physical properties, suspended sediment, nutrients, major ions, trace metals, polycyclic aromatic hydrocarbons, and Escherichia coli . Bridge-deck sediment and streambed sediment at upstream and downstream transects were collected once at each bridge site and analyzed for metals and semivolatile organic compounds that include polycyclic aromatic hydrocarbons. Benthic macroinvertebrate community surveys were conducted once using Hester-Dendy multiplate artificial substrate samplers deployed at multiple upstream and downstream transects concurrently. Statistical analysis of the water-quality data determined that stormwater runoff from bridges did not significantly degrade physical properties, nor nutrient, trace-metal, Escherichia coli , and suspended-sediment concentrations at the selected sites beyond the variability at the upstream transect (no bridge influence) during the study period. During storm sampling at the bridge sites, water-quality conditions were statistically similar upstream and downstream from each bridge, except for greater turbidity, total nitrogen, and total organic nitrogen plus ammonia concentrations found downstream from the bridge site on Fishing Creek; higher total chromium concentrations detected downstream from the bridge site on Turkey Creek; and increased Escherichia coli concentrations found downstream from the bridge site on the North Fork Edisto River. Total recoverable lead, cadmium, and copper concentrations were the only trace metals that periodically exceeded the South Carolina Department of Health and Environmental Control freshwater aquatic-life criteria at some bridge sites (lead, copper, and cadmium in Turkey Creek; cadmium and lead in Fishing Creek; lead in the South Fork Edisto River and Lynches River), but the exceedances occurred more frequently during routine sampling upstream from the bridge sites than during storm sampling at upstream and downstream transects. In general, stormwater runoff from the bridge decks did not seem to be the major source of metal enrichment in receiving waters during the study period. North Fork and South Fork Edisto Rivers and Turkey Creek had only one storm sample that exceeded South Carolina Department of Health and Environmental Control recreational criterion for Escherichia coli at both the upstream and downstream locations, while Fishing Creek had more frequent exceedances. Polycyclic aromatic hydrocarbons were detected infrequently in the stream samples. In general, sediment trace-metal concentrations were below the threshold and probable effect concentration at all bridge sites, except for the chromium concentration (45.1 milligrams per kilogram) detected upstream from the bridge site on Fishing Creek that exceeded the threshold effect concentration of 43.4 milligrams per kilogram. Based on enrichment ratios less than 1.5, bridge-deck runoff did not seem to be affecting trace-metal accumulation in the streambed sediment downstream from the bridge sites, except for lead at the bridge site on the Lynches River and manganese at the bridge site on Fishing Creek. Individual polycyclic aromatic compound concentrations and the sum of 18 compounds did not exceed any threshold and probable effect concentrations, indicating polycyclic aromatic hydrocarbon concentrations in the streambed sediment at downstream and upstream transects were not likely to affect the health of benthic macroinvertebrate communities. Although the cumulative polycyclic aromatic hydrocarbon concentrations in downstream sediment at the sites on Turkey and Fishing Creeks were well below the threshold effect concentration of 1,610 micrograms per kilogram, the 3- to 100-fold increase in downstream concentrations indicated a strong probability of a bridge-deck runoff source. Overall, benthic macroinvertebrate community health downstream from the bridge sites did not seem to be affected by bridge-deck runoff based on several multivariate analyses that indicated statistically similar benthic macroinvertebrate communities at upstream and downstream transects. Of the five bridge sites in this study, the site on Turkey Creek seemed to have the least healthy benthic macroinvertebrate communities because of the lowest Ephemeroptera, Plecoptera, and Trichoptera spp. (mayflies, stoneflies, and caddisflies, respectively) taxa, species richness, and diversity; and the highest biotic indices, indicative of poorer ecological health, at upstream and downstream transects. This ecological finding was not unexpected because of seasonal periods of negligible flow when dissolved-oxygen concentrations fell below 4 milligrams per liter during the study period. Of the five bridge sites in this study, the site on the South Fork Edisto River seemed to have healthier benthic macroinvertebrate communities because of the greater mean Ephemeroptera, Plecoptera, and Trichoptera spp. taxa; and lower mean biotic indices at upstream and downstream transects.

Scientific Investigations Report↗

USGS2019

Coastal Salinity Index along the southeastern Atlantic coast and the Gulf of Mexico, 1983 to 2018

Coastal droughts have a different dynamic than upland droughts, which are typically characterized by agricultural, hydrologic, meteorological, and (or) socioeconomic effects. Drought uniquely affects coastal ecosystems because of changes in the salinity conditions of estuarine creeks and rivers. The location of the freshwater-saltwater interface in surface-water bodies is an important factor in the ecological and socioeconomic dynamics of coastal communities. To address the data and information gap for characterizing coastal drought, the Coastal Salinity Index (CSI) was developed by using salinity data. The CSI uses a computational approach similar to the Standardized Precipitation Index. The CSI can be computed for unique time intervals (for example 1-, 6-, 12-, and 24-month intervals) to characterize short- and long-term drought (saline) conditions, as well as wet (high freshwater inflow) conditions. To encourage the use of the CSI in current and future research endeavors, this investigation addressed three activities to enhance the use and application of the CSI. First, a software package was developed for the consistent computation of the CSI that includes preprocessing of salinity data, filling missing data, computing the CSI, post-processing, and generating the supporting metadata. This software package is available for download from the U.S. Geological Survey GitLab repository. Second, the CSI has been computed at sites along the southeastern Atlantic coast (Florida to North Carolina) and the Gulf of Mexico (Texas to Florida) to increase the opportunity for linking the CSI to ecological response data. Third, using telemetered salinity data, the real-time computation of the CSI has been prototyped and disseminated on the web.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗

USGS2018

Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15

The Bushy Park Reservoir is the principal water supply for 400,000 people in the greater Charleston, South Carolina, area, which includes homes as well as businesses and industries in the Bushy Park Industrial Complex. Charleston Water System and the U.S. Geological Survey conducted a cooperative study during 2013–15 to assess the circulation of Bushy Park Reservoir and its effects on water-quality conditions, specifically, recurring taste-and-odor episodes. This report describes the water-quality data collected for the study that included a combination of discrete water-column sampling at seven locations in the reservoir and longitudinal water-quality profiling surveys of the reservoir and tributaries to characterize the temporal and spatial water-quality dynamics of Bushy Park Reservoir. Water-quality profiling surveys were conducted with an autonomous underwater vehicle equipped with a multiparameter water-quality-sonde bulkhead. Data collected by the autonomous underwater vehicle included water temperature, dissolved oxygen, pH, specific conductance, turbidity, total chlorophyll as fluorescence (estimate of algal biomass), and phycocyanin as fluorescence (estimate of cyanobacteria biomass) data. Characterization of the water-quality conditions in the reservoir included comparison to established State nutrient guidelines, identification of any spatial and seasonal variation in water-quality conditions and phytoplankton community structures, and assessment of the degree of influence of water-quality conditions related to Foster Creek and Durham Canal inflows, especially during periods of elevated taste-and-odor concentrations. Depth-profile and autonomous underwater vehicle survey data were used to identify areas within the reservoir where greater phytoplankton and cyanobacteria densities were most likely occurring. Water-quality survey results indicated that Bushy Park Reservoir tended to stratify thermally at a depth of about 20 feet from June to early October. The stratification was limited to the deeper portions of the reservoir near the dam and often dissipated within the reservoir near the CWS intake less than a mile upstream from the dam. Where thermally stratified, a corresponding depletion of dissolved oxygen also occurred at about the same depth and resulted in an anoxic hypolimnion below the 25-foot depth and an increase in specific conductance, likely due to re-mobilized metals and phosphorus under reducing conditions. In general, chlorophyll estimated from fluorescence exhibited some spatial variation, but no strong consistent pattern or “hot spot” was observed. Phycocyanin, estimated from relative fluorescence unit output as blue-green algae cell density, periodically seemed to be greater in the upper portion of the reservoir, but those differences may be attributed to increased turbidity and the potential change in phytoplankton community structure that affects fluorescence. Increased phycocyanin was observed at about the 10-foot depth during the summer months. A constant production of 2-methylisoborneol (MIB) near the dam and geosmin in the middle and upper portions of the reservoir appears to be occurring during the summer and early fall in the reservoir, but concentrations of these compounds tend to be between 10 and 15 nanograms per liter, which is at the Charleston Water System treatment threshold. At the Bushy Park Reservoir intake, the dominant taste-and-odor compound tended to be MIB, measured at a 2- or 3-to-1 ratio with geosmin during the summer and fall. During springtime episodes, however, when taste-and-odor compound concentrations typically are elevated above the Charleston Water System treatment threshold, the spatial distribution of geosmin concentrations greater than 15 nanograms per liter (28 to 38 nanograms per liter) was best explained by in situ production in the lower portion of the Bushy Park Reservoir near the dam rather than transport from Foster Creek. This pattern seems to indicate a possible shift in phytoplankton communities (or, at least, cyanobacteria communities) from MIB producers to geosmin producers. The spatial and seasonal assessment of water-quality conditions in Bushy Park Reservoir identified seasonal differences in water chemistry and spatial differences between the upper and lower portions of the reservoir that correspond to the location of elevated geosmin concentrations. On the basis of the spatial and seasonal assessment of actinomycetes concentrations compared to taste-and-odor compound concentrations, cyanobacteria production likely was the dominant source of the taste-and-odor episodes rather than actinomycetes. The lack of spatial and seasonal patterns in actinomycetes concentrations did not correspond to the springtime geosmin concentrations that were elevated above the Charleston Water System treatment threshold in the lower portion of the reservoir. Additionally, actinomycetes concentrations, although ubiquitous, had a median of about 9 and maximum of about 20 colonies per milliliter, which can be considered low for elevated taste-and-odor compound production. Nonetheless, the potential exists for actinomycetes to be a secondary source of taste-and-odor production and could explain some of the ubiquitous occurrence of low-level taste-and-odor production, such as MIB concentrations, observed throughout the summer and early fall months. When evaluated by biovolume, cyanobacteria were not the dominant phytoplankton group in Bushy Park Reservoir during the study period. Dolichospermum planctonicum (previously Anabaena planktonica ) was the dominant genera of the cyanobacteria group during spring periods. The geosmin-producing genera that were identified in the 2014 and 2015 spring communities in Bushy Park Reservoir were not observed in the 1999 and 2000 algal taxonomic data. A more robust examination of phytoplankton species was conducted by using a multivariate analysis that identified seasonal changes in phytoplankton community structure. These seasonal phytoplankton communities appeared to be explained by seasonal changes in water chemistry and may be responsible for episodes of taste-and-odor occurrence, especially geosmin. The most probable source of geosmin identified during the study was D. planctonicum . In a synoptic sampling event during a taste-and-odor episode in April 2015, cyanobacteria, not acinomycetes, also was indicated to be the more prevalent source of the geosmin. Although the Edisto River intake and its associated supply tunnel to the treatment facility had relatively high actinomycetes concentrations (130 and 140 colonies per milliliter, respectively) compared to the Bushy Park intake and tunnel (2 colonies per milliliter), corresponding geosmin concentrations were below 5 nanograms per liter for source water from the Edisto River intake and tunnel. Elevated geosmin concentrations above the Charleston Water System treatment threshold were identified in source waters from the Bushy Park Reservoir. The cyanobacteria community at the sampled sites in April 2015 was statistically similar to the community in the Bushy Park Reservoir in April 2014, when geosmin concentrations also were elevated. The only geosmin-producing genus identified at the Bushy Park intake, however, was D. planctonicum .

South Carolina↗

USGS2017

Simulation of groundwater flow and pumping scenarios for 1900–2050 near Mount Pleasant, South Carolina

Groundwater withdrawals from the Upper Cretaceous-age Middendorf aquifer in South Carolina have created a large, regional cone of depression in the potentiometric surface of the Middendorf aquifer in Charleston and Berkeley Counties, South Carolina. Groundwater-level declines of as much as 249 feet have been observed in wells over the past 125 years and are a result of groundwater use for public water supply, irrigation, and private industry. To address the concerns of users of the Middendorf aquifer, the U.S. Geological Survey, in cooperation with Mount Pleasant Waterworks (MPW), recalibrated an existing groundwater-flow model to incorporate additional groundwater-use and water-level data since 2008. This recalibration process consisted of a technique of parameter estimation that uses regularized inversion and employs “pilot points” for spatial hydraulic property characterization. The groundwater-flow system of the Coastal Plain physiographic province of South Carolina and parts of Georgia and North Carolina was simulated using the U.S. Geological Survey finite-difference computer code MODFLOW-2000. After the model recalibration, the following six predictive water-management scenarios were created to simulate potential changes in groundwater flow and groundwater-level conditions in the Mount Pleasant, South Carolina, area: Scenario 1—maximize MPW reverse-osmosis plant capacity by increasing groundwater withdrawals from the Middendorf aquifer from 3.9 million gallons per day (Mgal/d), which was the amount withdrawn in 2015, to 8.58 Mgal/d; Scenario 2—same as Scenario 1, but with the addition of a 0.5 Mgal/d supply well in the Middendorf aquifer near Moncks Corner, South Carolina; Scenario 3—same as Scenario 1, but with the addition of a 1.5 Mgal/d supply well in the Middendorf aquifer near Moncks Corner, South Carolina; Scenario 4—maximize MPW well capacity by increasing withdrawals from the Middendorf aquifer from 3.9 Mgal/d (in 2015) to 10.16 Mgal/d; Scenario 5—minimize MPW surface-water purchase from the Charleston Water System by adding supply wells and increasing withdrawals from the Middendorf aquifer from 3.9 Mgal/d (in 2015) to 12.16 Mgal/d; and Scenario 6—same as Scenario 1, but with he addition of quarterly model stress periods to simulate seasonal variations in the groundwater withdrawals. Results from the simulations indicated further decline of groundwater levels creating cones of depressions near pumping wells in the Middendorf aquifer in the Mount Pleasant, South Carolina, area between 2015 and 2050 for all six scenarios. Simulation results from Scenario 1 showed an average decline of about 150 feet in the groundwater levels of the MPW production wells. Simulated hydrographs for two area observation wells illustrate the gradual decline in groundwater levels with overall changes in water-level altitudes of –92 and –33 feet, respectively. Simulated groundwater altitudes at a hypothetical observation well located in the MPW well field declined 121 feet between 2015 and 2050. Scenarios 2 and 3 have the same pumping rates as Scenario 1 for the MPW production wells; however, a single hypothetical pumping well was added in the Middendorf aquifer near the town of Moncks Corner, South Carolina. This hypothetical pumping well has a withdrawal rate of 0.5 Mgal/d for Scenario 2 and 1.5 Mgal/d for Scenario 3. A comparison to the 2050 Scenario 1 simulation indicates groundwater altitudes for Scenarios 2 and Scenario 3 are 3 feet and 8 feet lower, respectively, at the MPW production wells. Scenario 4 simulates the maximum pumping capacity of 10.16 Mgal/d for the MPW network of production wells. Simulated 2050 groundwater altitudes for this simulation declined to –359 feet. Simulated hydrographs for two observation wells show groundwater-level declines of 116 and 41 feet, respectively. Simulated differences in groundwater altitudes at a hypothetical observation well located in the MPW well field indicate a water-level decline of 164 feet between 2015 and 2050. Scenario 5 is a modification of Scenario 4 with the addition of two new MPW production wells. For this scenario, the MPW network of production wells were simulated the same as in Scenario 4, but withdrawals from the two new production wells were added in 2020. Simulated 2050 groundwater altitudes for this simulation declined to – 405 feet. Simulated hydrographs for two observation wells show groundwater-level declines of 143 and 51 feet, respectively. Simulated groundwater altitudes at a hypothetical observation well located in the MPW well field declined 199 feet between 2015 and 2050. Scenario 6 is a modification of Scenario 1, in which 140 additional quarterly stress periods were added to simulate MPW seasonal demands. Simulated groundwater altitudes for Scenario 6 declined to –353 feet during 2050. For Scenario 6, simulated hydrographs for two observation wells and the hypothetical observation well show similar groundwater-level declines as seen in Scenario 1, but with seasonal fluctuations of as much as 56 feet in the hypothetical observation well. Water budgets for the model area immediately surrounding Mount Pleasant, South Carolina, were calculated for 2015 and for 2050. The water budget for 2015 is equal for all of the scenarios because it represents the year prior to the hypothetical pumping beginning in 2016. The largest flow component in the 2015 water budget for the Mount Pleasant area is discharge to wells at a rate of 4.17 Mgal/d. Additionally, 0.23 Mgal/d flows laterally out of the Middendorf aquifer in this area of the model due to the regional horizontal hydraulic gradient. Flow into this zone consists predominantly of lateral flow within the Middendorf aquifer at 4.08 Mgal/d. Additionally, 0.02 Mgal/d is released into this zone from aquifer storage. Vertically, 0.06 Mgal/d flows down from the Middendorf confining unit located above the Middendorf aquifer, and 0.25 Mgal/d flows up from the Cape Fear confining unit below. The largest flow component in the 2050 water budget for all six scenarios is discharge to wells in the Mount Pleasant area at rates between 8.89 and 12.47 Mgal/d. Flow into this zone consists mostly of lateral flow between 8.47 and 11.77 Mgal/d within the Middendorf aquifer. Between 0.003 and 0.46 Mgal/d is released into this zone from aquifer storage. Between 0.004 and 0.15 Mgal/d flows laterally out of this zone into adjacent areas of the Middendorf aquifer due to the regional horizontal hydraulic gradient. Finally, between 0.15 and 0.22 Mgal/d flows vertically into this zone from confining units above and below the Middendorf aquifer.

South Carolina↗

USGS2017

Hydrologic characterization of Bushy Park Reservoir, South Carolina, 2013–15

The Bushy Park Reservoir is a relatively shallow impoundment in a semi-tropical climate and is the principal water supply for the 400,000 people of the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there is an adequate supply of freshwater in the reservoir, taste-and-odor water-quality issues are a concern. The U.S. Geological Survey conducted an investigation in cooperation with the Charleston Water System to study the hydrology and hydrodynamics of the Bushy Park Reservoir to identify factors affecting water-quality conditions. Specifically, five areas for monitoring and (or) analysis were addressed: (1) hydrologic monitoring of the reservoir to establish a water budget, (2) flow monitoring in the tunnels to compute flow from Bushy Park Reservoir and at critical distribution junctions, (3) water-quality sampling, profiling, and continuous monitoring to identify the causes of taste-and-odor occurrence, (4) technical evaluation of appropriate hydrodynamic and water-quality simulation models for the reservoir, and (5) preliminary evaluation of alternative reservoir operations scenarios. This report describes the hydrodynamic and hydrologic data collected from 2013 to 2015 to support the application and calibration of a three-dimensional hydrodynamic model and the water-quality monitoring and analysis to gain insight into the principal causes of the Bushy Park Reservoir taste-and-odor episodes. The existing U.S. Geological Survey real-time network on the West Branch of the Cooper River was augmented with a tidal flow gage on Durham Canal Back River, and Foster Creek. The Charleston Water System intake structure was instrumented to collect water-level, water temperature (top and bottom probes), specific conductance (top and bottom probes), wind speed and direction, and photosynthetically active radiation data. In addition to the gages attached to fixed structures, four bottom-mounted velocity profilers were deployed at six locations over different periods. The deployment period for the velocity profiler ranged from 2 weeks to 4 months. During the investigation, tidal cycle (13-hour) streamflow measurements were made at 30-minute intervals at five locations. The Williams Station is a coal-fired powerplant that withdraws water from Bushy Park Reservoir for cooling purposes. The magnitude of the withdrawal (approximately 550 million gallons per day) is the major factor controlling the circulation in the reservoir. The net flow in Durham Canal to the reservoir is comparable to the withdrawal rates of the powerplant. When the Williams Station is not withdrawing water, the net flow in Durham Canal quickly goes to zero or reverses with a net flow away from the reservoir and to the Cooper River. Plan views of the velocity vectors for the tidal cycle streamflow measurements and rose diagram of the velocity profilers created with the Williams Station withdrawing and not withdrawing water show substantial effects of the distribution of magnitude and direction of the water velocities.

South Carolina↗

USGS2016

User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data

The generation of Everglades Depth Estimation Network (EDEN) daily water-level and water-depth maps is dependent on high quality real-time data from over 240 water-level stations. To increase the accuracy of the daily water-surface maps, the Automated Data Assurance and Management (ADAM) tool was created by the U.S. Geological Survey as part of Greater Everglades Priority Ecosystems Science. The ADAM tool is used to provide accurate quality-assurance review of the real-time data from the EDEN network and allows estimation or replacement of missing or erroneous data. This user’s manual describes how to install and operate the ADAM software. File structure and operation of the ADAM software is explained using examples.

Open-File Report↗

USGS2016

Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data

The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data. The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.

Florida↗

USGS2015

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies. Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11). To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R 2 ) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Florida↗

USGS2014

Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida

The urbanization of central Florida has progressed substantially in recent decades, and the total population in Lake, Orange, Osceola, Polk, and Seminole Counties more than quadrupled from 1960 to 2010. The Floridan aquifer system is the primary source of water for potable, industrial, and agricultural purposes in central Florida. Despite increases in groundwater withdrawals to meet the demand of population growth, recharge derived by infiltration of rainfall in the well-drained karst terrain of central Florida is the largest component of the long-term water balance of the Floridan aquifer system. To complement existing physics-based groundwater flow models, artificial neural networks and other data-mining techniques were used to simulate historical lake water level, groundwater level, and spring flow at sites throughout the area. Historical data were examined using descriptive statistics, cluster analysis, and other exploratory analysis techniques to assess their suitability for more intensive data-mining analysis. Linear trend analyses of meteorological data collected by the National Oceanic and Atmospheric Administration at 21 sites indicate 67 percent of sites exhibited upward trends in air temperature over at least a 45-year period of record, whereas 76 percent exhibited downward trends in rainfall over at least a 95-year period of record. Likewise, linear trend analyses of hydrologic response data, which have varied periods of record ranging in length from 10 to 79 years, indicate that water levels in lakes (307 sites) were about evenly split between upward and downward trends, whereas water levels in 69 percent of wells (out of 455 sites) and flows in 68 percent of springs (out of 19 sites) exhibited downward trends. Total groundwater use in the study area increased from about 250 million gallons per day (Mgal/d) in 1958 to about 590 Mgal/d in 1980 and remained relatively stable from 1981 to 2008, with a minimum of 559 Mgal/d in 1994 and a maximum of 773 Mgal/d in 2000. The change in groundwater-use trend in the early 1980s and the following period of relatively slight trend is attributable to the concomitant effects of increasing public-supply withdrawals and decreasing use of water by the phosphate industry and agriculture. On the basis of available historical data and exploratory analyses, empirical lake water-level, groundwater-level, and spring-flow models were developed for 22 lakes, 23 wells, and 6 springs. Input time series consisting of various frequencies and frequency-band components of daily rainfall (1942 to 2008) and monthly total groundwater use (1957 to 2008) resulted in hybrid signal-decomposition artificial neural network models. The final models explained much of the variability in observed hydrologic data, with 43 of the 51 sites having coefficients of determination exceeding 0.6, and the models matched the magnitude of the observed data reasonably well, such that models for 32 of the 51 sites had root-mean-square errors less than 10 percent of the measured range of the data. The Central Florida Artificial Neural Network Decision Support System was developed to integrate historical databases and the 102 site-specific artificial neural network models, model controls, and model output into a spreadsheet application with a graphical user interface that allows the user to simulate scenarios of interest. Overall, the data-mining analyses indicate that the Floridan aquifer system in central Florida is a highly conductive, dynamic, open system that is strongly influenced by external forcing. The most important external forcing appears to be rainfall, which explains much of the multiyear cyclic variability and long-term downward trends observed in lake water levels, groundwater levels, and spring flows. For most sites, groundwater use explains less of the observed variability in water levels and flows than rainfall. Relative groundwater-use impacts are greater during droughts, however, and long-term trends in water levels and flows were identified that are consistent with historical groundwater-use patterns. The sensitivity of the hydrologic system to rainfall is expected, owing to the well-drained karst terrain and relatively thin confinement of the Floridan aquifer system in much of central Florida. These characteristics facilitate the relatively rapid transmission of infiltrating water from rainfall to the water table and contribute to downward leakage of water to the Floridan aquifer system. The areally distributed nature of rainfall, as opposed to the site-specific nature of groundwater use, and the generally high transmissivity and low storativity properties of the semiconfined Floridan aquifer system contribute to the prevalence of water-level and flow patterns that mimic rainfall patterns. In general, the data-mining analyses demonstrate that the hydrologic system in central Florida is affected by groundwater use differently during wet periods, when little or no system storage is available (high water levels), compared to dry periods, when there is excess system storage (low water levels). Thus, by driving the overall behavior of the system, rainfall indirectly influences the degree to which groundwater use will effect persistent trends in water levels and flows, with groundwater-use impacts more prevalent during periods of low water levels and spring flows caused by low rainfall and less prevalent during periods of high water levels and spring flows caused by high rainfall. Differences in the magnitudes of rainfall and groundwater use during wet and dry periods also are important determinants of hydrologic response. An important implication of the data-mining analyses is that rainfall variability at subannual to multidecadal timescales must be considered in combination with groundwater use to provide robust system-response predictions that enhance sustainable resource management in an open karst aquifer system. The data-driven approach was limited, however, by the confounding effects of correlation between rainfall and groundwater use, the quality and completeness of the historical databases, and the spatial variations in groundwater use. The data-mining analyses indicate that available historical data when used alone do not contain sufficient information to definitively quantify the related individual effects of rainfall and groundwater use on hydrologic response. The knowledge gained from data-driven modeling and the results from physics-based modeling, when compared and used in combination, can yield a more comprehensive assessment and a more robust understanding of the hydrologic system than either of the approaches used separately.

Florida↗

USGS2013

Estimation of missing water-level data for the Everglades Depth Estimation Network (EDEN), 2013 update

The Everglades Depth Estimation Network is an integrated network of real-time water-level gaging stations, a ground-elevation model, and a water-surface elevation model designed to provide scientists, engineers, and water-resource managers with water-level and water-depth information (1991-2013) for the entire freshwater portion of the Greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for the Everglades Depth Estimation Network in order for the Network to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. In a previous study, water-level estimation equations were developed to fill in missing data to increase the accuracy of the daily water-surface elevation model. During this study, those equations were updated because of the addition and removal of water-level gaging stations, the consistent use of water-level data relative to the North American Vertical Datum of 1988, and availability of recent data (March 1, 2006, to September 30, 2011). Up to three linear regression equations were developed for each station by using three different input stations to minimize the occurrences of missing data for an input station. Of the 667 water-level estimation equations developed to fill missing data at 223 stations, more than 72 percent of the equations have coefficients of determination greater than 0.90, and 97 percent have coefficients of determination greater than 0.70.

Florida↗

USGS2012

Fluvial transport of mercury, organic carbon, suspended sediment, and selected major ions in contrasting stream basins in South Carolina and New York, October 2004 to September 2009

A spatially extensive assessment of the environmental controls on mercury transport and bioaccumulation in stream ecosystems in New York and South Carolina was conducted as part of the U.S. Geological Survey National Water-Quality Assessment Program and included the determination of fluvial transport of mercury and associated constituents during water years 2005–2009. (A water year extends from October of one calendar year to September of the next calendar year.) In the Coastal Plain region of South Carolina, the study area included the Edisto River and its headwater tributary, McTier Creek. In the Adirondack region of New York, the study area included the upper Hudson River and its headwater tributary, Fishing Brook. Median concentrations of filtered total mercury rangedfrom 1.55 nanograms per liter (ng/L) at the Hudson River site to 2.77 ng/L at the Edisto River site. The Edisto River site had the greatest median filtered methylmercury concentration, at 0.32 ng/L, and the Hudson River site had the least median filtered methylmercury concentration, at 0.07 ng/L.

New York, South Carolina↗

USGS2010

Groundwater Hydrology and Chemistry in and near an Emulsified Vegetable-Oil Injection Zone, Solid Waste Management Unit 17, Naval Weapons Station Charleston, North Charleston, South Carolina, 2004-2009

The U.S. Geological Survey and the Naval Facilities Engineering Command Southeast investigated the hydrology and groundwater chemistry in the vicinity of an emulsified vegetable-oil injection zone at Solid Waste Management Unit (SWMU) 17, Naval Weapons Station Charleston, North Charleston, South Carolina. In May 2004, Solutions-IES initiated a Phase-I pilot-scale treatability study at SWMU17 involving the injection of an edible oil emulsion into the aquifer near wells 17PS-01, 17PS-02, and 17PS-03 to treat chlorinated solvents. The Phase-I injection of emulsified vegetable oil resulted in dechlorination of trichloroethene (TCE) to cis-1,2-dichloroethene (cDCE), but the dechlorination activity appeared to stall at cDCE, with little further dechlorination of cDCE to vinyl chloride (VC) or to ethene. The purpose of the present investigation was to examine the groundwater hydrology and chemistry in and near the injection zone to gain a better understanding of the apparent remediation stall. It is unlikely that the remediation stall was due to the lack of an appropriate microbial community because groundwater samples showed the presence of Dehalococcoides species (sp.) and suitable enyzmes. The probable causes of the stall were heterogeneous distribution of the injectate and development of low-pH conditions in the injection area. Because groundwater pH values in the injection area were below the range considered optimum for dechlorination activity, a series of tests was done to examine the effect on dechlorination of increasing the pH within well 17PS-02. During and following the in-well pH-adjustment tests, VC concentrations gradually increased in some wells in the injection zone that were not part of the in-well pH-adjustment tests. These data possibly reflect a gradual microbial acclimation to the low-pH conditions produced by the injection. In contrast, a distinct increase in VC concentration was observed in well 17PS-02 following the in-well pH increase. Adjustment of the pH to near-neutral values in well 17PS-02 may have made that well relatively favorable to VC production compared with much of the rest of the injection zone, possibly accounting for acceleration of VC production at that well. Following a Phase-II injection in which Solutions-IES, Inc., injected pH-buffered emulsified vegetable oil with an improved efficiency injection approach, 1,1-dichloroethene, TCE, and cDCE rapidly decreased in concentration and are now (2009) undetectable in the injection zone, with the exception of a low concentration (43 micrograms per liter, August 2009) of cDCE in well 17PS-01. In August 2009, VC was still present in groundwater at the test wells in concentrations ranging from 150 to 640 micrograms per liter. The Phase-II injection, however, appears to have locally decreased aquifer permeability, possibly resulting in movement of contamination around, rather than through, the treatment area.

North Carolina↗

USGS2010

Contamination movement around a permeable reactive barrier at Solid Waste Management Unit 12, Naval Weapons Station Charleston, North Charleston, South Carolina, 2009

The U.S. Geological Survey and the Naval Facilities Engineering Command Southeast investigated natural and engineered remediation of chlorinated volatile organic compound groundwater contamination at Solid Waste Management Unit 12 at the Naval Weapons Station Charleston, North Charleston, South Carolina, beginning in 2000. In early 2004, groundwater contaminants began moving around the southern end of a permeable reactive barrier (PRB) installed by a consultant in December 2002. The PRB is a 130-foot-long and 3-foot-wide barrier consisting of varying amounts of zero-valent iron with or without sand mixture. Contamination moving around the PRB probably has been transported at least 75 feet downgradient from the PRB at a rate of about 15 to 29 feet per year. The diversion of contamination around the southern end of the PRB may be due to construction difficulties associated with the PRB installation or to reduced permeability in the PRB. An event that took place during installation of the PRB, which may have caused permeability loss, was the collapse and subsequent abandonment of a 110-foot-long trench originally designed to be the PRB on November 11, 2002, approximately 25 feet upgradient (west) from the final PRB. Guar gum with antimicrobial preservative in a polymer slurry had been used to stabilize the abandoned trench prior to collapse and was only partially recovered. Residual guar gum can cause permeability reduction in a PRB. It also is possible that permeability reduction took place within the PRB by slow degradation of the guar gum slurry or mineral precipitation. Despite the likely permeability reduction in and near the PRB immediately following installation, there is evidence that contaminants moved through the PRB and were degraded, consistent with the planned purpose of the PRB. Volatile organic compound contamination in groundwater downgradient from the PRB is subject to attenuation by phytovolatilization, sorption, and biodegradation. Pulses of contamination increases have been observed in some monitoring wells downgradient from the PRB. The pulses may reflect downgradient transport of contaminant pulses; however, lateral shifting of the plume is a more likely explanation for the concentration changes at well 12MW-12S. The ability to monitor the fate and behavior of the plume in the forest is severely limited because the present axis of maximum contamination in that area bypasses all but one of the existing monitoring wells (12MW-12S). Moreover, the 2009 data indicate that there are no optimally placed sentinel wells in the probable path of contaminant transport. Thus the monitoring network is no longer adequate to monitor the groundwater contamination downgradient from the PRB.

South Carolina↗

USGS2009

Estimation of Missing Water-Level Data for the Everglades Depth Estimation Network (EDEN)

The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level gaging stations, ground-elevation models, and water-surface elevation models designed to provide scientists, engineers, and water-resource managers with current (2000-2009) water-depth information for the entire freshwater portion of the greater Everglades. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN and their 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 daily water-surface elevation model, water-level estimation equations were developed to fill missing data. To minimize the occurrences of no estimation of data due to missing data for an input station, a minimum of three linear regression equations were developed for each station using different input stations. Of the 726 water-level estimation equations developed to fill missing data at 239 stations, more than 60 percent of the equations have coefficients of determination greater than 0.90, and 92 percent have an coefficient of determination greater than 0.70.

Open-File Report↗