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Alexander O. Headman

Publications and source records attributed to Alexander O. Headman.

6 recordsLinked to original sources

Estimation of impounded sediment volume in the Similkameen River upstream of Enloe Dam, Okanogan County, Washington

The Enloe Dam was built in 1920 for hydropower generation and impounds a steep-banked, narrow reach of the Similkameen River in north-central Washington. During the subsequent century, sediment from the Similkameen River watershed, which includes historical mining operations, accumulated within Enloe Dam’s impoundment. Enloe Dam ceased hydropower production in 1958 and is currently under consideration for removal, but there are concerns that the remobilization of sediments may have harmful impacts on downstream water quality. To complement previously published analyses of heavy metal concentrations within sediments and assess the total volume that may be transported following dam removal, this report presents estimates of the volume of sediment trapped behind Enloe Dam which was measured in 2020. The volume of sediment was estimated by comparing a bathymetric survey, collected using an acoustic Doppler continuous profiler, and a survey of the bedrock-sediment interface, collected using a continuous resistivity profiler. The study area spanned a 2.6-kilometer reach of the Similkameen River upstream from Enloe Dam. The volume of impounded sediment was calculated in 2020 by subtracting the elevation of the bedrock-sediment interface measured using the continuous resistivity profiler from a bathymetric surface measured by the acoustic Doppler current profiler. In 2020, the estimated volume of sediment impounded by Enloe Dam was 2.17±0.04 million cubic meters (Mm 3 ) compared to 1.37 Mm 3 measured in 1971. This equates to a deposition rate of approximately 16,300 cubic meters per year from 1971 to 2020. Continuous resistivity profiles revealed that bedrock within Enloe Dam’s impoundment was deepest (about 20 m) in the southern, downstream end of the profiles and shallowest (less than 5 m) in the northern upstream end of the profiles.

Washington↗

Conceptual hydrogeologic framework and groundwater budget near the southeastern part of Puget Sound, Washington

More than 1 million people live within the active model area (AMA) in the southeastern part of the lowlands surrounding Puget Sound, or Puget Lowland, Washington, and groundwater is the source for approximately one-half of their public, domestic, and irrigation water demands. The 887-square-mile AMA, located in King and Pierce Counties, represents the area of analysis for the conceptual hydrogeologic framework and numerical groundwater-flow models within the study area and includes the Puyallup River and Chambers-Clover Creek watersheds. To assess the potential hydrologic and anthropogenic impacts to groundwater and the connected surface-water resources, conceptual and numerical groundwater-flow models of groundwater flow were developed by the U.S. Geological Survey Washington Water Science Center in close cooperation with 18 water-resource agencies and stakeholders. This report presents information used to characterize the groundwater-flow system and the development of a numerical model in the AMA. Included are descriptions of the geology and conceptual hydrogeologic framework, groundwater levels and flow directions, groundwater recharge and discharge, numerical groundwater-flow model construction and results, and model limitations. The study area encompasses the western part of Pierce County and the southwestern part of King County, Washington. The study area extends south to the Nisqually River, southwest to Tanwax Creek, northeast to the Green River, and north through the valley near Auburn and adjacent uplands. It is bounded on the east by foothills of the Cascade Range, and on the northwest by Puget Sound.

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Evaluation of groundwater resources in the Upper White River Basin within Mount Rainier National Park, Washington State, 2020

The U.S. Geological Survey (USGS), in cooperation with the National Park Service, investigated groundwater gains and losses on the upper White River within Mount Rainier National Park in Washington. This investigation was conducted using stream discharge measurements at 14 locations within 7 reaches over a 6.5-mile river length from near the White River’s origin at the terminus of the Emmons Glacier on Mount Rainier to the White River Entrance near the northeast boundary of Mount Rainier National Park. Locations selected for the stream discharge measurements were on the main channel of the White River and on tributary streams near their confluence with the White River. A soil-water-balance (SWB) model analysis was also performed on the White River basin to estimate groundwater recharge throughout the basin during the time of the study. Analyses were made for the White River basin at the sub-basin (zone) scale to determine groundwater input to the stream for individual stream reaches. The gridded SWB model was simulated at a 10-meter (m) horizontal resolution, where recharge simulations were constructed using five spatially distributed datasets. Daily climate data as input for the simulation included gridded daily precipitation and air temperature. Upon analysis of the seepage run results, three of the seven reaches showed groundwater gains in this study. The SWB model results were used in conjunction with the baseflow gain totals in the reaches to estimate the length of time for recharge to become base flow. Further analysis estimated the rates of groundwater flow in the zones with adjacent gaining reaches. A streamflow gain curve was created from a simple flow model for each of the zones to relate the recharge from the zones to the adjacent reaches on the White River and tributaries. The fit of the streamflow gain curve to the calculated streamflow gain during the seepage run was used to analyze where the recharge from each zone resulted as streamflow gain. Consecutive reach losses from zones D and L were immediately followed downstream by a relatively large gain in zone GH, indicating that the gain in the reach adjacent to zone GH could be from the recharge in zones D and L.

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Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19

The Puget Sound basin encompasses the 13,700-square-mile area that drains to the Puget Sound and the adjacent marine waters of Washington State. Well more than 4 million people live within the basin, with numbers continuing to increase, who rely on the basin’s natural resources including groundwater. The Puget Sound Partnership was created by a Washington State statute to implement a science-based recovery of the Puget Sound to help address impacts to these resources. As part of the recovery, the partnership developed the Puget Sound Vital Signs as measures of ecosystem health that guide the assessment of progress toward Puget Sound recovery goals. The Puget Sound Partnership Leadership Council adopted a Drinking Water Vital Sign associated with human health and quality of life, recognizing certain indicators as integral to the sustainability of Puget Sound recovery efforts. One such Vital Sign indicator was the vulnerability of groundwater throughout the aquifers of the Puget Sound basin to elevated nitrate concentrations as defined by the probability of exceeding 2 milligrams/liter (mg/L) at a specific location and well depth. The U.S. Geological Survey (USGS) led the effort to characterize groundwater vulnerability. For this study, groundwater vulnerability refers to a probability with which a contaminant applied at or near the land surface can migrate to the aquifer of interest for a given set of land-use practices. Nitrate concentration data were selected for evaluation because elevated nitrate concentrations are typically caused by anthropogenic activities and have been associated with deleterious impacts on human health. To identify groundwater vulnerability to elevated nitrate concentrations, logistic regression was used to relate anthropogenic (human associated) and natural variables to the occurrence of elevated nitrate concentrations in untreated groundwater from large public water supply system wells found within the Washington State Department of Health Sentry database. Variables that were analyzed included well depth, soil hydraulic conductivity, precipitation, population density, fertilizer application amounts, and land-use types. Statistically significant models that predicted the probabilities of groundwater nitrate concentrations greater than 2 mg/L based on the predictor variables were created for the time periods 2000–04, 2005–09, 2010–14, and 2015–19. For all time periods, well depth and a measure of the abundance of urban and agricultural land over or near the well consistently helped explain the vulnerability of the well to elevated nitrate concentrations defined as a probability of exceeding 2 mg/L of nitrate. Precipitation and (or) soil hydraulic conductivity were also important predictor variables in the models. The models for each time period were used to create maps of groundwater vulnerability at 150- and 300-foot depths throughout the Puget Sound basin. As expected, the most vulnerable locations were associated with shallower well depths and increased agriculture and urban land cover. Across all four time periods, groundwater vulnerability throughout the Puget Sound was low, with probabilities of exceeding 2 mg/L concentrations of nitrate at depths at 150 and 300 feet typically less than 50 percent. Results also found a slight decrease in probabilities of elevated nitrate concentrations throughout the basin over time. More specifically, additional statistical tests found that groundwater with probabilities of less than about 60 percent declined from 2000 to 2019 and represented more than 75 percent of the modeled Puget Sound basin aquifer. Wells with greater than 60 percent probability increased over the same time period but represented only about 25 percent of the aquifer. The maps and statistical analysis presented in the study provide valuable and informative evaluation of the vulnerability of groundwater in the Puget Sound basin to elevated nitrate concentrations. The probability maps do not represent measured nitrate concentrations in groundwater, but rather they present the probability that nitrate concentrations exceed 2 mg/L. The models and predictions from this study are a viable indicator for the Puget Sound Partnership’s Healthy Human Population—Drinking Water Vital Sign. The logistic regression modeling approach presented here benefits water managers by allowing them to assess temporal trends in a range of probabilities, explore vulnerability changes as new regional land cover and anthropogenic data are generated, and distinguish vulnerabilities at different depths within the aquifer.

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Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery

Knowing subsurface drainage (tile-drain) extent is integral to understanding how landscapes respond to precipitation events and subsequent days of drying, as well as how soil characteristics and land management influence stream response. Consequently, a time series of tile-drain extent would inform one aspect of land management that complicates our ability to explain streamflow and water-quality as a function of climate variability or conservation management. We trained a UNet machine-learning model, a convolutional neural network designed to highlight objects of interest within an image, to delineate tile-drain networks in panchromatic satellite imagery without additional data on soils, topography, or historical tile-drain extent. This was done by training the model to match the accuracy of human experts manually tracing the surface representation of tile drains in satellite imagery. Our approach began with a library of images that were used to train and quantify the accuracy of the model, with model performance tested on imagery from two areas that were not used to train the model. Satellite imagery included acquisition dates from 2008 to 2020. Training imagery was from agricultural areas within the US Great Lakes basin. Validation imagery was from the upper Maumee River, tributary to western Lake Erie, and an Indiana, Ohio-River headwater tributary. Our analysis of the satellite imagery paired with meteorological and soil data found that during spring, a combination of relatively high solar radiation, intermediate soil-water content and bare fields enabled the best model performance. Each area of interest was heavily tile-drained, where better understanding the movement of water, nutrients, and sediment from fields to downstream water bodies is key to managing harmful algal blooms and hypoxia. The trained UNet model successfully identified tile drains visible in the validation imagery with an accuracy of 93%–96% and balanced accuracy of 52%–54%, similar to performance for training data (95% and 63%, respectively). Model performance will benefit from ongoing contributions to the training library.

Indiana, Michigan, Ohio, Wisconsin↗

Variable-density groundwater flow and contaminant transport, Operable Unit 1, Naval Base Kitsap, Keyport, Washington

Chlorinated volatile organic compounds (CVOCs) have migrated to groundwater beneath a former 9-acre landfill at Operable Unit 1 (OU-1) on Naval Base Kitsap, which was active from the 1930s through 1973 on the Keyport Peninsula, in Kitsap County, Washington. Biodegradation of CVOCs at OU-1 limits the mass of dissolved-phase CVOCs in groundwater that discharges to surface water, but contaminant concentrations up to 630 milligrams per liter persist in localized areas, likely from the dissolution of residual, non-aqueous phase liquids. Variable-density groundwater-flow and contaminant-transport models were developed using the SEAWAT-Version 4 computer program to simulate the direction and rate of groundwater flow in a 5.9 square-mile (mi 2 ) - area surrounding the Keyport Peninsula, to estimate the CVOC mass in groundwater and the rate of mass loading, and to assess possible remedial activities at OU-1. The study area is underlain by Quaternary deposits consisting of alternating glacial and interglacial sediments ranging from 500 to 1,500 feet (ft) thick. A hydrogeologic model delineated a sequence of 10 units including a relatively thin package (less than 100 ft) of recent sediments (Vashon Stade and younger) beneath the Keyport Peninsula that are underlain by the much thicker (more than 300 ft) Clover Park Aquitard, which overlies a confined, sea-level aquifer.

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