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Elise E. Wright

Publications and source records attributed to Elise E. Wright.

2 recordsLinked to original sources

Numerical model of the groundwater-flow system near the southeastern part of Puget Sound, Washington

Groundwater flow in the active model area (AMA) was simulated using a groundwater-flow model. A steady-state model version of the model simulates equilibrium conditions, and a transient model version simulates monthly variability. The model corresponds to the physical and temporal dimensions of the conceptual model and groundwater budget. The steady-state model version represents average conditions for an 11-year period (January 1, 2005–December 31, 2015), and the transient model represents monthly hydrologic variability within that period. The 13-layer model was constructed using MODFLOW-NWT with a uniformly spaced grid consisting of 416 rows, 433 columns, and cells with a horizontal dimension of 500 feet (ft) on a side. The model was calibrated to measured values of water levels in wells and lakes and estimated base flow for selected streamflow measurement stations, commonly referred to as streamgages. Model calibration was accomplished using a combination of manual and automatic methods, including the Model-Independent Parameter Estimation (PEST) program that adjusted model input parameters with the aim of minimizing the difference between estimated and model-simulated values of hydraulic head and base flow. Model boundary conditions consist of all simulated groundwater inflow to and outflow from the AMA. For example, a stream reach that simulates a gain from or loss to groundwater is a boundary condition that allows water to exit or enter, respectively, the groundwater system. Other boundary conditions include springs, seeps, precipitation recharge, groundwater exchange with lakes and Puget Sound, and groundwater pumping. A comparison of the estimated groundwater budget to that simulated by the steady-state model version indicates that the relative percentages of total inflow or total outflow for six major categories of boundary conditions are similar for the two budgets. The model was used to simulate three suites of scenarios of potential drought and water-use changes. Scenario 1 suite consisted of the steady-state model version that was run with 0, 15, 20, and 25 percent reduction of precipitation recharge to assess the corresponding reductions in base flow with decreasing recharge. The last simulation for the scenario 1 suite consisted of the transient model version simulating 3 years of consecutive seasonal drought, defined by the months of May through September, to assess the corresponding base-flow reductions. Scenario 2 suite consisted of the steady-state model version with all simulated groundwater use removed, compared with a simulation that includes current groundwater use to evaluate changes to potentiometric surfaces and base flows. Scenario 3 suite consisted of a transient model version of the model that simulated pumping increases for four different categories of water-supply wells (compared to no pumping increases) to evaluate resulting reductions in base flow. Although, these scenarios provide examples of model applications and useful insights, many other scenarios could be simulated. A description of how to download the model is described in the body of this report. Uncertainty is associated with most model inputs. Groundwater levels, lake levels, and land-surface altitudes are relatively certain; other model inputs are far less certain, including precipitation recharge, base flow, hydraulic properties, water use, and the three-dimensional structure of subsurface hydrogeologic units. Models are useful not because of high levels of accuracy of all model inputs, but because they combine the best information and estimates available, thereby providing the best predictions available related to physical processes. The model described in this report simulates groundwater flow on a regional scale, which has inherent limitations for simulating hydrologic scenarios at local scales. Model structures and inputs were generalized to be consistent with this regional scale. For example, the actual groundwater system has much greater heterogeneity of hydraulic conductivity than is possible within the model’s degrees of freedom. Variations in hydraulic gradients over distances less than 500 ft cannot be simulated. The distances between model features, such as a pumping well and a stream, must be placed at 500-ft intervals and are co-located if both features are within the same model cell.

Washington

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.

Washington