Search USGS⌕ Search

Geology topics

Craig J. Brown

Publications and source records attributed to Craig J. Brown.

At least 19 recordsLinked to original sources

Simulated biogeochemical effects of seawater restoration on diked salt marshes, Cape Cod National Seashore, Massachusetts, U.S.

Efforts have been underway worldwide to reintroduce seawater to many historically diked salt marshes for restoration of tidal flow and associated estuarine habitat. Seawater restoration to a diked Cape Cod marsh was simulated using the computer program PHREEQC based on previously conducted microcosm experiments to better understand the associated timing and sequence of multiple biogeochemical reactions and their implications to aquatic health. Model simulations show that acidic, reducing waters with high concentrations of sorbed ferrous iron (Fe[II]), aluminum (Al), sulfide (S 2− ), ammonia (NH 4 + + NH 3 ), and phosphate (PO 4 3− ) are released through desorption and sediment weathering following salination that can disrupt aquatic habitat. Models were developed for one-dimensional reactive transport of solutes in diked, flooded (DF) marsh sediments and subaerially exposed, diked, drained (DD) sediments by curve matching porewater solute concentrations and adjusting the sedimentary organic matter (SOM) degradation rates based on the timing and magnitude of Fe(II) and S 2− concentrations. Simulated salination of the DD sediments, in particular, showed a large release of Al, Fe(II), NH 4 + , and PO 4 3− ; the redox shift to reductive dissolution provided higher rates of SOM oxidation. The sediment type, iron source, and seasonal timing associated with seawater restoration can affect the chemical speciation and toxicity of constituents to aquatic habitat. The constituents of concern and their associated complex biogeochemical reactions simulated in this study are directly relevant to the increasingly common coastal marsh salination, either through tidal restoration or rising sea level.

Massachusetts↗

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water↗

Prioritizing US Geological Survey science on salinization and salinity in candidate and selected priority river basins

The US Geological Survey (USGS) is selecting and prioritizing basins, known as Integrated Water Science basins, for monitoring and intensive study. Previous efforts to aid in this selection process include a scientifically defensible and quantitative assessment of basins facing human-caused water resource challenges (Van Metre et al. in Environmental Monitoring and Assessment , 192(7), 458 2020). In the present work, we explore this ranking process based on water quality considerations, specifically salinity and salinization. We selected top candidate basins to study salinity and salinization issues in 18 hydrologic regions that include 163 candidate basins. Our prioritization is based on quantitative assessment of sources of salinity, drivers of change, and receptors that must respond to those sources and drivers. Source terms represented in the prioritization include geology, depth to brackish groundwater, stream conductivity, chloride in precipitation, urban and agricultural land use, application of road salt as a deicer, and irrigation. Drivers represented in prioritization include changes in chemical weathering as a result of changes in rainwater chemistry. Receptors include measures of water stress, measurements of stream ecological health, and socioeconomic factors. In addition, we present research activities for the USGS on salinity and salinization that can be pursued in these basins including assessment of sources, pathways, and loadings; predicting and understanding changes in sources, peaks, and trends; understanding the components of salinity and mobilization of contaminants; understanding the relationship between salinization and changing ecosystems; and developing knowledge on the causes and distribution of groundwater salinity, brackish water resources, and challenges related to desalination.

Enviornmental Monitoring and Assessment↗

Prioritizing water availability study settings to address geogenic contaminants and related societal factors

Water availability for human and ecological uses depends on both water quantity and water quality. The U.S. Geological Survey (USGS) is developing strategies for prioritizing regional-scale and watershed basin-scale studies of water availability across the nation. Previous USGS ranking processes for basin-scale studies incorporated primarily water quantity factors but are now considering additional water quality factors. This study presents a ranking based on the potential impacts of geogenic constituents on water quality and consideration of societal factors related to water quality. High-concentration geogenic constituents, including trace elements and radionuclides, are among the most prevalent contaminants limiting water availability in the USA and globally. Geogenic constituents commonly occur in groundwater because of subsurface water–rock interactions, and their distributions are controlled by complex geochemical processes. Geogenic constituent mobility can also be affected by human activities (e.g., mining, energy production, irrigation, and pumping). Societal factors and relations to drinking water sources and water quality information are often overlooked when evaluating research priorities. Sociodemographic characteristics, data gaps resulting from historical data-collection disparities, and infrastructure condition/age are examples of factors to consider regarding environmental justice. This paper presents approaches for ranking and prioritizing potential basin-scale study areas across the contiguous USA by considering a suite of conventional physical and geochemical variables related to geogenic constituents, with and without considering variables related to societal factors. Simultaneous consideration of societal and conventional factors could provide decision makers with more diverse, interdisciplinary tools to increase equity and reduce bias in prioritizing focused research areas and future water availability studies.

Environmental Monitoring and Assessment↗

Estimating lithium concentrations in groundwater used as drinking water for the conterminous United States

Lithium (Li) concentrations in drinking-water supplies are not regulated in the United States; however, Li is included in the 2022 U.S. Environmental Protection Agency list of unregulated contaminants for monitoring by public water systems. Li is used pharmaceutically to treat bipolar disorder, and studies have linked its occurrence in drinking water to human-health outcomes. An extreme gradient boosting model was developed to estimate geogenic Li in drinking-water supply wells throughout the conterminous United States. The model was trained using Li measurements from ∼13,500 wells and predictor variables related to its natural occurrence in groundwater. The model predicts the probability of Li in four concentration classifications, ≤4 μg/L, >4 to ≤10 μg/L, >10 to ≤30 μg/L, and >30 μg/L. Model predictions were evaluated using wells held out from model training and with new data and have an accuracy of 47–65%. Important predictor variables include average annual precipitation, well depth, and soil geochemistry. Model predictions were mapped at a spatial resolution of 1 km 2 and represent well depths associated with public- and private-supply wells. This model was developed by hydrologists and public-health researchers to estimate Li exposure from drinking water and compare to national-scale human-health data for a better understanding of dose–response to low (<30 μg/L) concentrations of Li.

conterminous United States↗

Occurrence and sources of lead in private wells, Sturbridge, Massachusetts

Lead (Pb) occurrence and sources and aqueous geochemistry were assessed in private wellhead and tap water at a targeted area of concern for possible exceedances and at a control area in the same geologic formation, and in wells at a nearby landfill in south-central Massachusetts (MA). Total Pb concentrations were below the U.S. Environmental Protection Agency (USEPA) Action Level of 15 μg/L in all samples, and about 6% of unfiltered samples contained Pb concentrations that exceeded 1.0 μg/L. Pb concentrations were higher under conditions that are acidic and oxic (pH ≤ 6.5 and dissolved oxygen [DO] ≥ 2 mg/L), in which minerals that could sequester lead or manganese typically are undersaturated, and adsorption by hydrous ferric oxide is limited. Under more neutral to alkaline conditions, the precipitation of Pb in solid solution series minerals such as (Ca,Pb)CO 3 and (Ba,Pb)SO 4 −2 , and adsorption by amorphous ferric hydroxides, could limit Pb solubility in the bedrock aquifer or in the plumbing. The low Pb concentrations and the absence of distinctive Pb and strontium (Sr) isotope ratio patterns in samples indicate that a nearby landfill is not likely a significant Pb source. Dissolved concentrations of Pb, copper (Cu), and zinc (Zn) in tap samples were significantly greater than those in wellhead samples, indicating that some Pb is derived from plumbing. Wellhead or tap samples with the highest Pb concentrations also had the greatest corrosivity potential based on the calcite saturation index and the PPGC (Potential to Promote Galvanic Corrosion) and supports the premise that Pb concentrations in tap samples were derived partly from corrosion of plumbing. Concentrations of other constituents, including arsenic (As), uranium (U), Sr, boron (B), and lithium (Li) were not statistically different between the tap and wellhead samples but, apart from Sr, all were statistically higher in the control area than in the target area. This variation in constituent concentrations suggests geochemical variation within the host Paxton Formation, possibly related to faulting and contact with the Ayer granite east of the control area.

Massachusetts↗

Machine learning predicted redox conditions in the glacial aquifer system, northern continental United States

Groundwater supplies 50% of drinking water worldwide and 30% in the United States. Geogenic and anthropogenic contaminants can, however, compromise water quality, thus limiting groundwater availability. Reduction/oxidation (redox) processes and redox conditions affect groundwater quality by influencing the mobility and transport of common geogenic and anthropogenic contaminants. In the glacial aquifer system, northern United States (GLAC, 1.87 million km 2 ), groundwater with high arsenic or manganese concentration is associated with reducing conditions and high nitrate with oxidizing conditions. This study uses machine learning to identify the relative influence of drivers of redox conditions (e.g., residence time vs. reactivity) across the glacial landscape. We developed three‐dimensional boosted regression tree models to predict redox conditions using the likelihood of low dissolved oxygen or high iron as indicators of anoxic conditions. Results indicate that variation in redox condition is controlled primarily by residence time (e.g., groundwater age and relative depth) and to a lesser extent by geochemical reactivity (e.g., subsurface contact time, soil carbon). Older water and deeper wells, along with more water storage or slower water movement was associated with higher probability of anoxic conditions. Mapped model results illustrate regions where anoxic redox conditions may mobilize geogenic contaminants or oxic conditions may limit denitrification potential. Results may also provide simplified redox input for process or predictive models of, for example, arsenic, manganese, or nitrate. Machine learning modeling methods can lead to improved understanding of contaminant occurrence and what drives redox conditions, and the methods may be transferable to other settings.

Northern Continental United States↗

Machine-learning predictions of high arsenic and high manganese at drinking water depths of the glacial aquifer system, northern continental United States

Globally, over 200 million people are chronically exposed to arsenic (As) and/or manganese (Mn) from drinking water. We used machine-learning (ML) boosted regression tree (BRT) models to predict high As (>10 μg/L) and Mn (>300 μg/L) in groundwater from the glacial aquifer system (GLAC), which spans 25 states in the northern United States and provides drinking water to 30 million people. Our BRT models’ predictor variables (PVs) included recently developed three-dimensional estimates of a suite of groundwater age metrics, redox condition, and pH. We also demonstrated a successful approach to significantly improve ML prediction sensitivity for imbalanced data sets (small percentage of high values). We present predictions of the probability of high As and high Mn concentrations in groundwater, and uncertainty, at two nonuniform depth surfaces that represent moving median depths of GLAC domestic and public supply wells within the three-dimensional model domain. Predicted high likelihood of anoxic condition (high iron or low dissolved oxygen), predicted pH, relative well depth, several modeled groundwater age metrics, and hydrologic position were all PVs retained in both models; however, PV importance and influence differed between the models. High-As and high-Mn groundwater was predicted with high likelihood over large portions of the central part of the GLAC.

Environmental Science & Technology↗

Machine learning predictions of pH in the Glacial Aquifer System, Northern USA

A boosted regression tree model was developed to predict pH conditions in three dimensions throughout the glacial aquifer system of the contiguous United States using pH measurements in samples from 18,386 wells and predictor variables that represent aspects of the hydrogeologic setting. Model results indicate that the carbonate content of soils and aquifer materials strongly controls pH and, when coupled with long flowpaths, results in the most alkaline conditions. Conversely, in areas where glacial sediments are thin and carbonate‐poor, pH conditions remain acidic. At depths typical of drinking‐water supplies, predicted pH >7.5—which is associated with arsenic mobilization—occurs more frequently than predicted pH <6—which is associated with water corrosivity and the mobilization of other trace elements. A novel aspect of this model was the inclusion of numerically based estimates of groundwater flow characteristics (age and flowpath length) as predictor variables. The sensitivity of pH predictions to these variables was consistent with hydrologic understanding of groundwater flow systems and the geochemical evolution of groundwater quality. The model was not developed to provide precise estimates of pH at any given location. Rather, it can be used to more generally identify areas where contaminants may be mobilized into groundwater and where corrosivity issues may be of concern to prioritize areas for future groundwater monitoring.

Groundwater↗

Arsenic and uranium occurrence in private wells in Connecticut, 2013–18—A spatially weighted and bedrock geology assessment

The U.S. Geological Survey, in cooperation with the Connecticut Department of Public Health, conducted a study to determine the presence of arsenic and uranium in private drinking water wells in Connecticut. Samples were collected during 2013–18 from wells completed in 115 geologic units, with 2,433 samples analyzed for arsenic and 2,191 samples analyzed for uranium. The study concluded four major findings. In a spatially weighted analysis of groundwater samples collected from more than 2,000 private wells in bedrock aquifers in Connecticut, 3.9 percent of collected samples contained arsenic concentrations greater than the U.S. Environmental Protection Agency’s (EPA) maximum contaminant level (MCL) of 10 micrograms per liter (µg/L), and 4.7 percent of collected samples contained uranium concentrations greater than the EPA MCL of 30 µg/L. Of the 2,433 water samples collected and analyzed from bedrock aquifers in Connecticut, 4.2 percent (102) contained arsenic concentrations at greater than 10 µg/L, and of the 2,191 water samples collected and analyzed from bedrock aquifers in Connecticut, 5.4 percent (118) contained uranium concentrations greater than 30 µg/L. Uranium concentrations greater than or equal to 1 µg/L are relatively ubiquitous across the State of Connecticut, with these concentrations present in 44.9 percent of the State, according to spatially weighted statewide-scale proportion analysis. Of the 115 geologic units studied, 44 had at least one sample with arsenic or uranium concentrations that exceeded the respective constituent’s EPA MCL.

Connecticut↗

A multi-model approach toward understanding iron fouling at rock-fill drainage sites along roadways in New Hampshire, USA

Factors affecting iron fouling in wet areas adjacent to roadways were investigated by collecting field rock cut and aqueous physicochemical data; developing exploratory predictive models; and developing geochemical models. Basic data included the identification of iron fouling from aerial imagery and field visits at 374 New Hampshire rock cut locations, and their associated rock-fill sites. Based on field water quality measurements from wet areas at 36 of the rock-fill sites, the occurrence of iron fouling was associated with higher values of specific conductance, lower concentrations of dissolved oxygen and lower pH compared to areas without iron fouling. A statistical model, using boosted regression trees, was developed to predict the occurrence of iron fouling in wet areas adjacent to roadways where rock-fill from nearby rock cuts was used in roadway construction. The model was used to develop a continuous iron fouling probability map for the state of New Hampshire that can be used to better understand the occurrence of iron fouling. Geochemical models illustrate how iron fouling of waters increases along roadways built with fill from sulfidic rock cuts as a result of acid generation from pyrite dissolution and ferrous iron (Fe 2+ ) oxidation and increases in areas with greater specific conductance from deicing runoff caused by cation exchange. More iron is precipitated as goethite in simulations that include pyrite, and in simulations with deicing salts added, indicating that rock-fill sites with rocks that contain pyrite and water with greater salt content could have enhanced iron fouling.

New Hampshire↗

Fluoride occurrence in United States groundwater

Data from 38,105 wells were used to characterize fluoride (F) occurrence in untreated United States (U.S.) groundwater. For domestic wells (n = 11,032), water from which is generally not purposely fluoridated or monitored for quality, 10.9% of the samples have F concentrations >0.7 mg/L (U.S. Public Health Service recommended optimal F concentration in drinking water for preventing tooth decay) (87% are <0.7 mg/L); 2.6% have F > 2 mg/L (EPA Secondary Maximum Contaminant Level, SMCL); and 0.6% have F > 4 mg/L (EPA MCL). The data indicate the biggest concern with F in domestic wells at the national scale could be one of under consumption of F with respect to the oral-health benchmark (0.7 mg/L). Elevated F concentrations relative to the SMCL and MCL are regionally important, particularly in the western U.S. Statistical comparisons of potentially important controlling factors in four F-concentration categories (<0.1–0.7 mg/L; >0.7–2 mg/L; >2–4 mg/L; >4 mg/L) at the national scale indicate the highest F-concentration category is associated with groundwater that has significantly greater pH values, TDS and alkalinity concentrations, and well depths, and lower Ca/Na ratios and mean annual precipitation, than the lowest F-concentration category. The relative importance of the controlling factors appears to be regionally variable. Three case studies illustrate the spatial variability in controlling factors using groundwater-age (groundwater residence time), water-isotope (evaporative concentration), and water-temperature (geothermal processes) data. Populations potentially served by domestic wells with F concentrations <0.7, >0.7, >2, and >4 mg/L are estimated to be ~28,200,000, ~3,110,000; ~522,000; and ~172,000 people, respectively, in 40 principal aquifers with at least 25 F analyses per aquifer.

Science of the Total Environment↗

Factors affecting the occurrence of lead and manganese in untreated drinking water from Atlantic and Gulf Coastal Plain aquifers, eastern United States—Dissolved oxygen and pH framework for evaluating risk of elevated concentrations

Groundwater samples collected during 2012 and 2013 from public-supply wells screened in the Atlantic and Gulf Coastal Plain aquifers of the eastern and southeastern U.S. rarely contained lead or manganese concentrations that exceeded drinking-water limits, despite having corrosive characteristics. Data indicate that the occurrence of dissolved lead and manganese in sampled groundwater, prior to its distribution or treatment, was related to several explanatory factors including the presence of source minerals, hydrologic position along the flow path, water-rock interactions, and associated geochemical conditions such as pH and dissolved oxygen (DO) concentrations. Elevated concentrations of lead compared to health-based benchmarks were associated with groundwater that is acidic (pH ≤ 6.5), oxygenated (DO ≥ 2 mg/L), and closer to recharge zones (relatively young water). Elevated concentrations of manganese were associated with groundwater that is acidic to neutral (pH ≤ 7.5), has low DO (<2 mg/L), and further from recharge zones (relatively old). Under these geochemical conditions, minerals that could sequester lead or manganese tended to be undersaturated, and adsorption by hydrous ferric oxide was limited. Under neutral to alkaline pH conditions, precipitation of impure calcium carbonate or phosphate compounds containing traces of lead or manganese (solid solutions) could maintain low concentrations of the trace elements. Additionally, adsorption of lead or manganese cations by hydrous ferric oxides (HFO) could be another attenuating factor where conditions are oxidizing and dissolved inorganic carbon concentrations are relatively low. A DO/pH framework was developed as a screening tool for evaluating risk of elevated lead or manganese, based on the occurrence of elevated lead and manganese concentrations and the corresponding distributions of DO and pH in the Atlantic and Gulf Coastal Plain aquifers. Validation of the DO/pH framework was accomplished using an independent national dataset that showed consistent results for elevated lead (pH ≤ 6.5; DO ≥ 2 mg/L) and manganese (pH ≤ 7.5; DO < 2 mg/L).

Atlantic and Gulf Coastal Plain aquifers↗

Arsenic and uranium in private wells in Connecticut, 2013-15

The occurrence of arsenic and uranium in groundwater at concentrations that exceed drinking-water standards is a concern because of the potential adverse effects on human health. Some early studies of arsenic occurrence in groundwater considered anthropogenic causes, but more recent studies have focused on sources of naturally occurring arsenic to groundwater, such as minerals within aquifer materials that are in contact with groundwater. Arsenic and uranium in groundwater in New England have been shown to have a strong association to the geologic setting and nearby streambed sediment concentrations. In New Hampshire and Massachusetts, arsenic and uranium concentrations greater than human-health benchmarks have shown distinct spatial patterns when related to the bedrock units mapped at the local scale. The Connecticut Department of Public Health (DPH) reported that there are about 322,600 private wells in Connecticut serving approximately 823,000 people, or 23 percent of the State’s population. The State does not require that existing private wells be routinely tested for arsenic, uranium, or other contaminants; consequently, private wells are only sampled at the well owner’s discretion or when they are newly constructed. The U.S. Geological Survey (USGS), in cooperation with the DPH, completed an assessment in 2016 on the distribution of concentrations of arsenic and uranium in groundwater from bedrock in Connecticut. This report presents the major findings for arsenic and uranium concentrations from water samples collected from 2013 to 2015 from private wells.

Connecticut↗

Brackish groundwater in the United States

For some parts of the Nation, large-scale development of groundwater has caused decreases in the amount of groundwater that is present in aquifer storage and that discharges to surface-water bodies. Water supply in some areas, particularly in arid and semiarid regions, is not adequate to meet demand, and severe drought is affecting large parts of the United States. Future water demand is projected to heighten the current stress on groundwater resources. This combination of factors has led to concerns about the availability of freshwater to meet domestic, agricultural, industrial, mining, and environmental needs. To ensure the water security of the Nation, currently [2016] untapped water sources may need to be developed. Brackish groundwater is an unconventional water source that may offer a partial solution to current and future water demands. In support of the national census of water resources, the U.S. Geological Survey completed the national brackish groundwater assessment to better understand the occurrence and characteristics of brackish groundwater in the United States as a potential water resource. Analyses completed as part of this assessment relied on previously collected data from multiple sources; no new data were collected. Compiled data included readily available information about groundwater chemistry, horizontal and vertical extents and hydrogeologic characteristics of principal aquifers (regionally extensive aquifers or aquifer systems that have the potential to be used as a source of potable water), and groundwater use. Although these data were obtained from a wide variety of sources, the compiled data are biased toward shallow and fresh groundwater resources; data representing groundwater that is at great depths and is saline were not as readily available. One of the most important contributions of this assessment is the creation of a database containing chemical characteristics and aquifer information for the known areas with brackish groundwater in the United States. Previously published digital data relating to brackish groundwater resources were limited to a small number of State- and regional-level studies. Data sources for this assessment ranged from single publications to large datasets and from local studies to national assessments. Geochemical data included concentrations of dissolved solids, major ions, trace elements, nutrients, and radionuclides as well as physical properties of the water (pH, temperature, and specific conductance). Additionally, the database provides selected well information (location, yield, depth, and contributing aquifer) necessary for evaluating the water resource. The assessment was divided into national-, regional-, and aquifer-scale analyses. National-scale analyses included evaluation of the three-dimensional distribution of observed dissolved-solids concentrations in groundwater, the three-dimensional probability of brackish groundwater occurrence, and the geochemical characteristics of saline (greater than or equal to 1,000 mg/L of dissolved solids) groundwater resources. Regional-scale analyses included a summary of the percentage of observed grid cell volume in the region that was occupied by brackish groundwater within the mixture of air, water, and rock for multiple depth intervals. Aquifer-scale analyses focused primarily on four regions that contained the largest amounts of observed brackish groundwater and included a generalized description of hydrogeologic characteristics from previously published work; the distribution of dissolved-solids concentrations; considerations for developing brackish groundwater resources, including a summary of other chemical characteristics that may limit the use of brackish groundwater and the ability of sampled wells producing brackish groundwater to yield useful amounts of water; and the amount of saline groundwater being used in 2010.

Professional Paper↗

Chloride concentrations, loads, and yields in four watersheds along Interstate 95, southeastern Connecticut, 2008-11: factors that affect peak chloride concentrations during winter storms

Chloride (Cl - ) concentrations and loads and other water chemistry characteristics were assessed to evaluate potential effects of road-deicer applications on streamwater quality in four watersheds along Interstate 95 (I&ndash;95) in southeastern Connecticut from November 1, 2008, through September 30, 2011. Streamflow and water quality were studied in the Four Mile River, Oil Mill Brook, Stony Brook, and Jordan Brook watersheds, where developed land ranged from 9 to 32 percent. Water-quality samples were collected and specific conductance was measured continuously at paired water-quality monitoring sites, upstream and downstream from I&ndash;95. Specific conductance values were related to Cl - concentrations to assist in determining the effects of road-deicing operations on the levels of Cl - in the streams. Streamflow and water-quality data were compared with weather data and with the timing, amount, and composition of deicers applied to State highways. Grab samples were collected during winter stormwater-runoff events, such as winter storms or periods of rain or warm temperatures in which melting takes place. Grab samples were also collected periodically during the spring and summer and during base-flow conditions. The estimated Cl - concentrations at the eight water-quality monitoring sites during winter storms peaked as high as 270 milligrams per liter (mg/L) and were well below the U.S. Environmental Protection Agency (EPA) recommended acute chloride toxicity criterion of 860 mg/L and the chronic 4-day average toxicity criterion of 230 mg/L. Cl - concentrations in streams, particularly at sites downstream from I&ndash;95, peaked during increased streamflow in the winter and early spring as a result of deicers applied to roads and washed off by stormwater or meltwater. Cl - concentrations during most of the nonwinter seasons decreased during increases in streamflow because storm runoff was more dilute than base flow. However, peaks in specific conductance and estimated chloride concentrations at streams in more urbanized watersheds corresponded to peaks in streamflow well after winter snow or ice events; these delayed peaks in Cl - concentration likely resulted from deicer residue that remained in melting snow piles and on roadsides and (or) that were flushed from soils and shallow groundwater, then discharged downstream. Estimated peak Cl - concentrations varied with the type of winter storm event and were highest during or after winter storms of frozen precipitation and rain, in which the rain or meltwater effectively washed off the deicers. Estimated peak Cl - concentrations correlated positively with the duration of deicer application but generally not with streamflow. Estimated peak Cl - concentrations during the winter season were highest during low streamflow at most sites. Chloride concentrations varied considerably in shallow groundwater as a result of land-use differences. Cl - concentrations were very high (as high as 800 mg/L) in shallow groundwater downstream from I&ndash;95 at the Four Mile River site. Chloride/bromide mass concentration ratios and the proximity of a former landfill and sewage lagoon upstream indicate a likely source of Cl - is landfill leachate and possibly sewage leachate. Cl - loads in streams generally were highest in the winter and early spring. The estimated daily Cl - yield for the four monitoring sites downstream from I&ndash;95 ranged from 0.0004 ton per day per square mile for one of the least developed watersheds to 0.052 ton per day per square mile for the watershed with the highest percentage of urban development and impervious area. The estimated median contribution of Cl - load from atmospheric deposition was small and ranged from 0.07 percent of Cl - load at the Jordan Brook watershed to 0.57 percent at the Oil Mill Brook watershed. The Cl - loads in streams (outputs) were compared with Cl - load inputs, which include atmospheric deposition and deicer applications; Cl - load inputs were slightly larger than the Cl - load outputs at most of the sites during most years but do not account for the Cl - load in groundwater leaving the watersheds. A multiple linear regression model was developed to describe the variability of the natural log of peak specific conductance, as well as estimated Cl - concentrations. Five significant variables best explained the variability in the natural log of the peak specific conductance after deicing events: (1) snow on ground before deicing event; (2) winter precipitation with rain; (3) specific conductance in base flow; (4) State-operated road lane miles divided by watershed area; and (5) amount of Cl - from deicers applied to State-operated roads per lane mile. In this report, winter precipitation is defined as any type of precipitation, including frozen precipitation and rain, that occurs during the active deicing season, typically November through March. Frozen precipitation is defined here as snow, sleet, freezing rain, or any winter precipitation except rain. The addition of a lane mile in both directions on I&ndash;95 would result in an estimate of approximately 2 to 11 percent increase in Cl - input from deicers applied to I&ndash;95 and other roads maintained by Connecticut Department of Transportation. The largest estimated increase in Cl - load was in the watersheds with the greatest number miles of I&ndash;95 corridor relative to the total lane miles maintained by Connecticut Department of Transportation. On the basis of these estimates and the estimated peak Cl - concentrations during the study period, it is unlikely that the increased use of deicers on the additional lanes would lead to Cl - concentrations that exceed the aquatic habitat criteria.

Connecticut↗

Major and trace element geochemistry and background concentrations for soils in Connecticut

Soil samples were collected throughout Connecticut (CT) to determine the relationship of soil chemistry with the underlying geology and to better understand background concentrations of major and trace elements in soils. Soil samples were collected (1) from the upper 5 cm of surficial soil at 100 sites, (2) from the A horizon at 86 of these sites, and (3) from the deeper horizon, typically the C horizon, at 79 of these sites. The <2-millimeter fraction of each sample was analyzed for 44 elements by methods that yield the total or near-total elemental content. Sample sites were characterized by glacial setting, underlying bedrock geology, and soil type. These spatial data were used with element concentrations in the C-horizon to relate geologic factors to soil chemistry. Concentrations of elements in C-horizon soils varied with grain size in surficial glacial materials and with underlying rock types, as determined using nonparametric statistical procedures. Concentrations of most elements in C-horizon soils showed a positive correlation with silt and (or) clay content and were higher in surficial materials mapped as till, thick till, and (or) fines. Element concentrations in C-horizon soils showed significant differences among the underlying geologic provinces and were highest overlying the Grenville Belt and (or) the Grenville Shelf Sequence Provinces in western CT. These rocks consist mainly of carbonates and the relatively high element concentrations in overlying soils likely result from less influence of dilution by quartz compared to other provinces. Element concentrations in C-horizon soils in CT were compared with those in samples from other New England states overlying similar lithologic bedrock types. The upper range of As concentrations in C-horizon soils overlying the New Hampshire-Maine (NH-ME) Sequence in CT was 15 mg/kg, lower than the upper range of 24 mg/kg in C-horizon soils overlying the same sequence in ME. In CT, U concentration means were significantly higher in C-horizon soils overlying Avalonian granites, and U concentrations ranged as high as 14 mg/kg, compared to those in C-horizon soil samples collected from other New England states, which ranged as high as 6.1 mg/kg in a sample in NH overlying the NH-ME Sequence. Element concentrations in C-horizon soils in CT were compared with those in samples collected from shallower depths. Concentrations of most major elements were highest in C-horizon soil samples, including Al, Ca, Fe, K, Na, and Ti, but element concentrations showed a relatively similar pattern in A-horizon and surficial soil samples among the underlying geologic provinces. Trace element concentrations, including Ba, W, Ga, Ni, Cs, Rb, Sr, Th, Sc, and U, also were higher in C-horizon soil samples than in overlying soil samples. Concentrations of Mg, and several trace elements, including Mn, P, As, Nb, Sn, Be, Bi, Hg, Se, Sb, La, Co, Cr, Pb, V, Y, Cu, Pb, and Zn were highest in some A-horizon or surficial soils, and indicate possible contributions from anthropogenic sources. Because element concentrations in soils above the C horizon are more likely to be affected by anthropogenic factors, concentration ranges in C-horizon soils and their spatially varying geologic associations should be considered when estimating background concentrations of elements in CT soils.

Connecticut↗

Mapping bedrock surface contours using the horizontal-to-vertical spectral ratio (HVSR) method near the middle quarter srea, Woodbury, Connecticut

The bedrock surface contours in Woodbury, Connecticut, were determined downgradient of a commercial zone known as the Middle Quarter area (MQA) using the novel, noninvasive horizontal-to-vertical (H/V) spectral ratio (HVSR) passive seismic geophysical method. Boreholes and monitoring wells had been drilled in this area to characterize the shallow subsurface to within 20 feet (ft) of the land surface, but little was known about the deep subsurface, including sediment thicknesses and depths to bedrock (Starn and Brown, 2007; Brown and others, 2009). Improved information on the altitude of the bedrock surface and its spatial variation was needed for assessment and remediation of chlorinated solvents that have contaminated the overlying glacial aquifer that supplies water to wells in the area.

Connecticut↗