Geology topics

Eric Swain

Publications and source records attributed to Eric Swain.

8 recordsLinked to original sources

USGS2024

Insight into sources of benzene, TCE, and PFOA/PFAS in groundwater at Naval Air Station Whiting Field, Florida, through numerical particle-tracking simulations

Past waste-disposal activities at Naval Air Station Whiting Field (NASWF) have led to elevated concentrations of contaminants in the underlying sand and gravel aquifer. Contaminants include two of the most commonly detected chemicals in groundwater in many countries (benzene and trichloroethylene (TCE)) and the “forever chemicals” per- and poly-fluoroalkyl substances (PFAS) such as perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS). A MODFLOW model (the Whiting Field Groundwater Model (WFGM)) was previously developed for NASWF and the surrounding area to simulate groundwater flow. To obtain insight into groundwater flow pathways for the identification of potential source areas, the MODPATH particle-tracking application was applied to the WFGM for three public supply wells and three monitoring wells at NASWF. The travel time to recharge areas was estimated using concentrations of the groundwater age-dating solutes tritium (as helium ingrowth) and chlorofluorocarbons detected in the monitoring wells. Simulated travel times agree with the groundwater ages and indicate that the calibrated WFGM reasonably represents groundwater flow velocities and pathways. The MODPATH simulations confirm suspected on-base source areas to explain chemical detection in the monitoring wells. In contrast, the particle-tracking simulations indicate that potential source areas to the public supply wells include both on- and off-base sources. This is important because PFAS chemicals can have multiple sources, including land application of sludge-based fertilizers. This approach that combines groundwater age dating with particle-tracking simulations can be applied at similar sites characterized by benzene-, TCE-, and PFAS-contaminated groundwater.

Florida↗

USGS2023

Forecasting water levels using machine (deep) learning to complement numerical modelling in the southern Everglades, USA

Water level is an important guide for water resource management and wetland ecosystems, defining one of the most basic processes in hydrology. This research seeks to investigate the possibility of complementing numerical modeling with a Machine Learning (ML) model to forecast daily water levels in the southern Everglades in Florida, USA. An exact analytical solution to water level may not be possible, but using the computational methods afforded by ML, the traditional numerical techniques may be enhanced to generate more robust, scalable predictions. Five locations were chosen for application of the Time-Delayed Neural Network (TDNN) and Long-Short Term Memory Recurrent Neural Network (LSTM-RNN) ML models, which were built to estimate water level with 1, 2, 3, 7 and 10 day forecasts using a simulation step of 1 day. The results showed that rainfall forecasts from weather models could improve water-level forecasts if the accuracy and performance of the weather models can be improved. The ML models presented here improve water-level predictions from a historical hydrologic model for a 24 hour forecast horizon.

Florida↗

USGS2022

Insight into Hurricane Maria peak flows from the development and application of the Precipitation-Runoff Modeling System (PRMS): Including Río Grande de Arecibo, Puerto Rico, 1981–2017

The Precipitation-Runoff Modeling System (PRMS) was used to develop a simulation of watershed hydrology on the island of Puerto Rico for the period 1981–2017, concentrating on the Río Grande de Arecibo, a river with some of the highest streamflows on the island. This development is part of the U.S. Geological Survey’s (USGS) National Hydrologic Model (NHM) infrastructure which supports coordinated, comprehensive, and consistent hydrologic modeling at the watershed scale for the coterminous United States (CONUS). A goal of the NHM program is to expand the domain outside of CONUS, leading to a PRMS application in Puerto Rico. This model was used to simulate the effects of Hurricane Maria on daily streamflow and provide information at locations where streamgages were damaged by the hurricane. Comparisons with streamflow estimates made by indirect methods in the field, up to ten times higher than simulated values, lends insight into the uncertainties in both the indirect methods and model simulated values and helps to identify potential error in the daily streamflow estimates. The PRMS can be applied to look at the effects of changes in climate and land use, water management, industrial and public water usage, and many other factors that affect hydrology on the island of Puerto Rico. The model is also designed as a support tool for the USGS National Water Census which provides comprehensive reporting of national information on withdrawal, conveyance, consumptive use, and return flow by water-use category.

Puerto Rico↗

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↗

USGS2014

Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model

Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.

Florida↗

USGS2013

Internet-based Modeling, Mapping, and Analysis for the Greater Everglades (IMMAGE; Version 1.0): web-based tools to assess the impact of sea level rise in south Florida

South Florida's Greater Everglades area is particularly vulnerable to sea level rise, due to its rich endowment of animal and plant species and its heavily populated urban areas along the coast. Rising sea levels are expected to have substantial impacts on inland flooding, the depth and extent of surge from coastal storms, the degradation of water supplies by saltwater intrusion, and the integrity of plant and animal habitats. Planners and managers responsible for mitigating these impacts require advanced tools to help them more effectively identify areas at risk. The U.S. Geological Survey's (USGS) Internet-based Modeling, Mapping, and Analysis for the Greater Everglades (IMMAGE) Web site has been developed to address these needs by providing more convenient access to projections from models that forecast the effects of sea level rise on surface water and groundwater, the extent of surge and resulting economic losses from coastal storms, and the distribution of habitats. IMMAGE not only provides an advanced geographic information system (GIS) interface to support decision making, but also includes topic-based modules that explain and illustrate key concepts for nontechnical users. The purpose of this report is to familiarize both technical and nontechnical users with the IMMAGE Web site and its various applications.

Florida↗

USGS2012

Stochastic analyses to identify wellfield withdrawal effects on surface-water and groundwater in Miami-Dade County, Florida

Several stochastic analyses were conducted in Miami-Dade County, Florida, to evaluate the effects of wellfield withdrawal on aquifer water levels, canal stage, and canal flow. Multiyear data for withdrawals at four water-supply wellfields, water levels at the S-121 canal control structure and groundwater head at a nearby monitoring well were used to determine the interrelation between wellfield withdrawals and water levels in the canal and aquifer. A spectral analysis was performed first on the wellfield withdrawals, showing similar patterns of fluctuations, but no well-defined seasonality. In order to compare water-level response with withdrawals at each wellfield, the intercorrelation effects between wellfields was removed through a ‘causal chain’ approach where the inter-wellfield correlation is used to isolate the wellfield/water-level correlation. Most computed correlations have magnitudes less than 5 percent, but with statistical significance above 90 percent. Results indicate that withdrawals from the wellfields most distant from the canal had no significant correlation to the canal levels. However the highest correlation was not at the wellfield closest to the canal, but at the two wellfields at the intermediate distance that have higher withdrawal rates. The hydraulic interconnectivity of the canal with the rest of the canal network, covering the study area, allows the canal equalizes with all connected canals. This explains why proximity to a particular canal location does not appear to be as important a factor as the withdrawal rate. Groundwater levels are more highly correlated to a wellfield on the same side of the canal, and to pumping wells in the same wellfield on the same side of the canal. This indicates that canals are an effective barrier and source/sink for the groundwater. Further nonlinear correlation analysis indicates that high withdrawal rates disproportionally affect water levels and are the predominant effect on the canal.

Florida↗

USGS2010

Measurement-derived heat-budget approaches for simulating coastal wetland temperature with a hydrodynamic model

Numerical modeling is needed to predict environmental temperatures, which affect a number of biota in southern Florida, U.S.A., such as the West Indian manatee (Trichechus manatus), which uses thermal basins for refuge from lethal winter cold fronts. To numerically simulate heat-transport through a dynamic coastal wetland region, an algorithm was developed for the FTLOADDS coupled hydrodynamic surface-water/ground-water model that uses formulations and coefficients suited to the coastal wetland thermal environment. In this study, two field sites provided atmospheric data to develop coefficients for the heat flux terms representing this particular study area. Several methods were examined to represent the heat-flux components used to compute temperature. A Dalton equation was compared with a Penman formulation for latent heat computations, producing similar daily-average temperatures. Simulation of heat-transport in the southern Everglades indicates that the model represents the daily fluctuation in coastal temperatures better than at inland locations; possibly due to the lack of information on the spatial variations in heat-transport parameters such as soil heat capacity and surface albedo. These simulation results indicate that the new formulation is suitable for defining the existing thermohydrologic system and evaluating the ecological effect of proposed restoration efforts in the southern Everglades of Florida.

Florida↗