Geology topics

Shaun Wicklein

Publications and source records attributed to Shaun Wicklein.

8 recordsLinked to original sources

USGS2022

Summary of the midchannel springflows in Jackson River below Gathright Dam between April 24, 2010, and May 7, 2019

Between April 2010 and May 2019, springflow was determined for a midchannel spring in Jackson River below Gathright Dam near Hot Springs, Virginia. The springflow was measured to assess if the spring was influenced by the elevation of Lake Moomaw. Local precipitation was also reviewed to determine whether variations in springflow were influenced by rainfall. The spring is approximately 250 feet downstream from the dam’s discharge race channel, where the water is carried away from the base of the dam, and its flow was determined by the gain in streamflow between concurrent measurements made upstream and downstream from the spring. Throughout the study period, the springflow showed little variation over time, and no direct correlations were determined between the observed springflow and the elevation of Lake Moomaw or local precipitation data.

Virginia↗

USGS2017

Characteristics of peak streamflows and extent of inundation in areas of West Virginia and southwestern Virginia affected by flooding, June 2016

Heavy rainfall occurred across central and southern West Virginia in June 2016 as a result of repeated rounds of torrential thunderstorms. The storms caused major flooding and flash flooding in central and southern West Virginia with Kanawha, Fayette, Nicholas, and Greenbrier Counties among the hardest hit. Over the duration of the storms, from 8 to 9.37 inches of rain was reported in areas in Greenbrier County. Peak streamflows were the highest on record at 7 locations, and streamflows at 18 locations ranked in the top five for the period of record at U.S. Geological Survey streamflow-gaging stations used in this study. Following the storms, U.S. Geological Survey hydrographers identified and documented 422 high-water marks in West Virginia, noting location and height of the water above land surface. Many of these high-water marks were used to create flood-inundation maps for selected communities of West Virginia that experienced flooding in June 2016. Digital datasets of the inundation areas, mapping boundaries, and water depth rasters are available online.

Virginia, West Virginia↗

USGS2014

Coastal storm monitoring in Virginia

Coastal communities in Virginia are prone to flooding, particularly during hurricanes, nor’easters, and other coastal low-pressure systems. These weather systems affect public safety, personal and public property, and valuable infrastructure, such as transportation, water and sewer, and electric-supply networks. Local emergency managers, utility operators, and the public are tasked with making difficult decisions regarding evacuations, road closures, and post-storm recovery efforts as a result of coastal flooding. In coastal Virginia these decisions often are made on the basis of anecdotal knowledge from past events or predictions based on data from monitoring sites located far away from the affected area that may not reflect local conditions. Preventing flood hazards, such as hurricane-induced storm surge, from becoming human disasters requires an understanding of the relative risks that flooding poses to specific communities. The risk to life and property can be very high if decisions about evacuations and road closures are made too late or not at all.

Virginia↗

USGS2013

Monitoring storm tide and flooding from Hurricane Sandy along the Atlantic coast of the United States, October 2012

The U.S. Geological Survey (USGS) deployed a temporary monitoring network of water-level and barometric pressure sensors at 224 locations along the Atlantic coast from Virginia to Maine to continuously record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Sandy. These records were greatly supplemented by an extensive post-flood high-water mark (HWM) flagging and surveying campaign from November to December 2012 involving more than 950 HWMs. Both efforts were undertaken as part of a coordinated federal emergency response as outlined by the Stafford Act under a directed mission assignment by the Federal Emergency Management Agency (FEMA).

Connecticut, Delaware, Maine, Maryland, Massachuse↗

USGS2006

Water resources data Virginia water year 2005 Volume 1. Surface-water discharge and surface-water quality records

Water-resources data for the 2005 water year for Virginia includes records of stage, discharge, and water quality of streams and stage, contents, and water quality of lakes and reservoirs. This volume contains records for water discharge at 172 gaging stations; stage only at 2 gaging stations; elevation at 2 reservoirs and 2 tide gages; contents at 1 reservoir, and water quality at 25 gaging stations. Also included are data for 50 crest-stage partial-record stations. Locations of these sites are shown on figures 4A-B and 5A-B. Miscellaneous hydrologic data were collected at 128 measuring sites and 19 water-quality sampling sites not involved in the systematic data-collection program. The data in this report represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating State and Federal agencies in Virginia.

Water Data Report↗

USGS2006

Water resources data Virginia water year 2005 Volume 2. Ground-water level and ground-water quality records

Water-resources data for the 2005 water year for Virginia consist of records of water levels and water quality of ground-water wells. This report (Volume 2. Ground-Water-Level and Ground-Water-Quality Records) contains water levels at 349 observation wells and water quality at 29 wells. Locations of these wells are shown on figures 3 through 8. The data in this report represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating State and Federal agencies in Virginia.

Water Data Report↗

USGS2004

Evaluation of Water Quality for Two St. Johns River Tributaries Receiving Septic Tank Effluent, Duval County, Florida

Tributary streamflow to the St. Johns River in Duval County is thought to be affected by septic tank leachate from residential areas adjacent to these tributaries. Water managers and the city of Jacksonville have committed to infrastructure improvements as part of a management plan to address the impairment of tributary water quality. In order to provide data to evaluate the effects of future remedial activities in selected tributaries, major ion and nutrient concentrations, fecal coliform concentrations, detection of wastewater compounds, and tracking of bacterial sources were used to document septic tank influences on the water quality of selected tributaries. The tributaries Fishing Creek and South Big Fishweir Creek were selected because they drain subdivisions identified as high priority locations for septic tank phase-out projects: the Pernecia and Murray Hill B subdivisions, respectively. Population, housing (number of residences), and septic tank densities for the Murray Hill B subdivision are greater than those for the Pernecia subdivision. Water-quality samples collected in the study basins indicate influences from ground water and septic tanks. Estimated concentrations of total nitrogen ranged from 0.33 to 2.86 milligrams per liter (mg/L), and ranged from less than laboratory reporting limit (0.02 mg/L) to 0.64 mg/L for total phosphorus. Major ion concentrations met the State of Florida Class III surface-water standards; total nitrogen and total phosphorus concentrations exceeded the U.S. Environmental Protection Agency Ecoregion XII nutrient criteria for rivers and streams 49 and 96 percent of the time, respectively. Organic wastewater compounds detected at study sites were categorized as detergents, antioxidants and flame retardants, manufactured polycarbonate resins, industrial solvents, and mosquito repellent. The most commonly detected compound was para-nonylphenol, a breakdown product of detergent. Results of wastewater sampling give evidence that stream water in the study basins is affected by septic tank effluent. Fecal coliform bacteria concentrations were measured on a monthly basis; of 115 samples, 63 percent exceeded the State of Florida fecal coliform bacteria standard for Class III surface waters of 800 colonies per 100 milliliters of water on any 1 day. Fecal coliform bacteria concentrations ranged from less than 20 colonies per 100 milliliters of sample to greater than or equal to 160,000 colonies per 100 milliliters of sample. Antibiotic resistance patterns of fecal coliform bacteria were used to identify the sources of fecal coliform bacteria. Significant sources of fecal coliform bacteria included wild animals, dogs, and humans. A majority of the fecal coliform bacteria were classified to be from human sources. Because the primary source of fecal coliform bacteria is from human sources, and most likely septic tank effluent, management of human sources may substantially improve microbiological water quality in both the Fishing Creek and South Branch Big Fishweir Creek basins.

Water-Resources Investigations Report↗

USGS2002

Simulation of runoff and water quality for 1990 and 2008 land-use conditions in the Reedy Creek watershed, east-central Florida

Hydrologic and water-quality data have been collected within the 177-square-mile Reedy Creek, Florida, watershed, beginning as early as 1939, but the data have not been used to evaluate relations among land use, hydrology, and water quality. A model of the Reedy Creek watershed was developed and applied to the period January 1990 to December 1995 to provide a computational foundation for evaluating the effects of future land-use changes on hydrology and water quality in the watershed. The Hydrological Simulation Program-Fortran (HSPF) model was used to simulate hydrology and water quality of runoff for pervious land areas, impervious land areas, and stream reaches. Six land-use types were used to characterize the hydrology and water quality of pervious and impervious land areas in the Reedy Creek watershed: agriculture, rangeland, forest, wetlands, rapid infiltration basins, and urban areas. Hydrologic routing and water-quality reactions were simulated to characterize hydrologic and water-quality processes and the movement of runoff and its constituents through the main stream channels and their tributaries. Because of the complexity of the stream system within the Reedy Creek Improvement District (RCID) (hydraulic structures, retention ponds) and the anticipated difficulty of modeling the system, an approach of calibrating the model parameters for a subset of the gaged watersheds and confirming the usefulness of the parameters by simulating the remainder of the gaged sites was selected for this study. Two sub-watersheds (Whittenhorse Creek and Davenport Creek) were selected for calibration because both have similar land use to watersheds within the RCID (with the exception of urban areas). Given the lack of available rainfall data, the hydrologic calibration of the Whittenhorse Creek and Davenport Creek sub-watersheds was considered acceptable (for monthly data, correlation coefficients, 0.86 and 0.88, and coefficients of model-fit efficiency, 0.72 and 0.74, respectively). The hydrologic model was tested by applying the parameter sets developed for Whittenhorse Creek and Davenport Creek to other land areas within the Reedy Creek watershed, and by comparing the simulated results to observed data sets for Reedy Creek near Vineland, Bonnet Creek near Vineland, and Reedy Creek near Loughman. The hydrologic model confirmation for Reedy Creek near Vineland (correlation coefficient, 0.91, and coefficient of model fit efficiency, 0.78, for monthly flows) was acceptable. Flows for Bonnet Creek near Vineland were substantially under simulated. Consideration of the ground-water contribution to Bonnet Creek could improve the water balance simulation for Bonnet Creek near Vineland. On longer time scales (monthly or over the 72-month simulation period), simulated discharges for Reedy Creek near Loughman agreed well with observed data (correlation coefficient, 0.88). For monthly flows the coefficient of model-fit efficiency was 0.77. On a shorter time scale (less than a month), however, storm volumes were greatly over simulated and low flows (less than 8 cubic feet per second) were greatly under simulated. A primary reason for the poor results at low flows is the diversion of an unknown amount of water from the RCID at the Bonnet Creek near Kissimmee site. Selection of water-quality constituents for simulation was based primarily on the availability of water-quality data. Dissolved oxygen, nitrogen, and phosphorus species were simulated. Representation of nutrient cycling in HSPF also required simulation of biochemical oxygen demand and phytoplankton populations. The correlation coefficient for simulated and observed daily mean dissolved oxygen concentration values at Reedy Creek near Vineland was 0.633. Simulated time series of total phosphorus, phosphate, ammonia nitrogen, and nitrate nitrogen generally agreed well with periodically observed values for the Whittenhorse Creek and Davenport Creek sites. Simulated water-quality constituents at the Bonnet Creek and Reedy Creek near Vineland sites varied as to how well the values agreed with periodically observed constituent concentrations. Simulated water-quality constituent concentrations for the Reedy Creek near Loughman site generally agreed well with observed constituent concentrations. Simulation of a future land-use scenario for the Reedy Creek watershed was based on the hydrologic and water-quality simulations, projected 2008 land use within the RCID, and assuming no change in existing land use for other areas within the Reedy Creek watershed but external to the RCID. The percentages of forest and urban-impervious land use showed the most change between existing and future land use; forest areas decreased by 50 percent and urban-impervious areas increased by 300 percent. Simulated values of mean total phosphorus, phosphate, ammonia nitrogen, and nitrate nitrogen concentrations for existing and future land-use simulations were within 0.01 milligrams per liter of each other. The simulated maximum daily load increased an average of 10 percent for all constituents. Maximum daily nitrate nitrogen load increased about 17 percent, the greatest increase of all daily constituent loads. Duration curves of daily total phosphorus, phosphate, ammonia nitrogen, and nitrate nitrogen load indicated an increase in the likelihood of exceeding a given load throughout the range of daily constituent loads at Reedy Creek near Loughman.

Florida↗