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At least 1,117 records · Page 62Linked to original sources
USGS2013

Effect of power plant emission reductions on a nearby wilderness area: a case study in northwestern Colorado

This study evaluates the effect of emission reductions at two coal-fired power plants in northwestern Colorado on a nearby wilderness area. Control equipment was installed at both plants during 1999–2004 to reduce SO 2 and NOx emissions. One challenge was separating the effects of local from regional emissions, which also declined during the study period. The long-term datasets examined confirm that emission reductions had a beneficial effect on air and water quality in the wilderness. Despite a 75 % reduction in SO 2 emissions, sulfate aerosols measured in the wilderness decreased by only 20 %. Because the site is relatively close to the power plants (<75 km), the slow rate of conversion of SO 2 to sulfate, particularly under conditions of low relative humidity, might account for this less than one-to-one response. On the clearest days, emissions controls appeared to improve visibility by about 1 deciview, which is a small but perceptible improvement. On the haziest days, however, there was little improvement perhaps reflecting the dominance of regional haze and other components of visibility degradation particularly organic carbon and dust. Sulfate and acidity in atmospheric deposition decreased by 50 % near the southern end of the wilderness of which 60 % was attributed to power plant controls and the remainder to reductions in regional sources. Lake water sulfate responded rapidly to trends in deposition declining at 28 lakes monitored in and near the wilderness. Although no change in the acid–base status was observed, few of the lakes appear to be at risk from chronic or episodic acidification.

Colorado↗
USGS2007

Nitrogen isotopes as indicators of NOx source contributions to atmospheric nitrate deposition across the midwestern and northeastern United States

Global inputs of NO x are dominated by fossil fuel combustion from both stationary and vehicular sources and far exceed natural NO x sources. However, elucidating NO x sources to any given location remains a difficult challenge, despite the need for this information to develop sound regulatory and mitigation strategies. We present results from a regional-scale study of nitrogen isotopes (δ 15 N) in wet nitrate deposition across 33 sites in the midwestern and northeastern U.S. We demonstrate that spatial variations in δ 15 N are strongly correlated with NO x emissions from surrounding stationary sources and additionally that δ 15 N is more strongly correlated with surrounding stationary source NO x emissions than pH, SO 4 2- , or NO 3 - concentrations. Although emission inventories indicate that vehicle emissions are the dominant NO x source in the eastern U.S., our results suggest that wet NO 3 - deposition at sites in this study is strongly associated with NO x emissions from stationary sources. This suggests that large areas of the landscape potentially receive atmospheric NO y deposition inputs in excess of what one would infer from existing monitoring data alone. Moreover, we determined that spatial patterns in δ 15 N values are a robust indicator of stationary NO x contributions to wet NO 3 - deposition and hence a valuable complement to existing tools for assessing relationships between NO 3 - deposition, regional emission inventories, and for evaluating progress toward NO x reduction goals.

Connecticut, Maine, Massachusetts, New Hampshire, ↗
USGS2020

Factors affecting sampling strategies for design of an effects‐directed analysis for endocrine‐active chemicals

Effects‐directed analysis (EDA) is an important tool for identifying unknown bioactive components in a complex mixture. Such an analysis of endocrine‐active chemicals (EACs) from water sources has promising regulatory implications but also unique logistical challenges. We propose a conceptual EDA (framework) based on a critical review of EDA literature and concentrations of common EACs in waste and surface waters. Required water volumes for identification of EACs under this EDA framework were estimated based on bioassay performance (in vitro and in vivo bioassays), limits of quantification by mass spectrometry (MS), and EAC water concentrations. Sample volumes for EDA across the EACs showed high variation in the bioassay detectors, with genistein, bisphenol A, and androstenedione requiring very high sample volumes and ethinylestradiol and 17β‐trenbolone requiring low sample volumes. Sample volume based on the MS detector was far less variable across the EACs. The EDA framework equation was rearranged to calculate detector “thresholds,” and these thresholds were compared with the literature EAC water concentrations to evaluate the feasibility of the EDA framework. In the majority of instances, feasibility of the EDA was limited by the bioassay, not MS detection. Mixed model analysis showed that the volumes required for a successful EDA were affected by the potentially responsible EAC, detection methods, and the water source type, with detection method having the greatest effect on the EDA of estrogens and androgens. The EDA framework, equation, and model we present provide a valuable tool for designing a successful EDA.

Environmental Toxicology and Chemistry↗
USGS2024

Using parentage-based tagging to estimate survival of Chinook salmon fry in a large storage reservoir

Research efforts focusing on salmonid populations have highlighted the need to better understand demographic parameters for the fry and parr life stages. Monitoring these small fish presents a challenge because negative effects from handling and tagging can bias subsequent parameter estimates. Removal models and associated sampling designs represent one class of mark-recapture models with potential to be applied to very small juvenile salmon, yet existing methods associated with removal studies are not well-suited for all study environments. For example, populations residing in large storage reservoirs may yield low capture probabilities when subjected to removal sampling, making unbiased estimation of survival using traditional removal models difficult. To address this limitation, we developed a sampling design and associated model using parentage-based tagging in hatchery-raised juvenile Chinook salmon ( Oncorhynchus tshawytscha ) to estimate survival over a 2-year study period in a large storage reservoir in western Oregon, USA. Individual fish were identified to family groups, serving as replicate batch marks in a robust design removal model framework. Results from a simulation suggested that parameter estimates were unbiased even at very low capture probabilities, although the use of model constraints (i.e., covariates or constant parameter values) was necessary to achieve this. Model fitting to field data supported a trend in survival over time, with survival increasing with time since release in the first study year but decreasing in the second.

Environmental Biology of Fishes↗
USGS2022

Challenges in linking soil health to edge-of-field water quality across the Great Lakes basin

To better understand agricultural nutrient losses, we evaluated relationships between management (e.g., manure and tillage), soil health measurements, and resulting edge-of-field (EOF) surface water quality. This work was conducted before or early into conservation implementation at 14 Great Lakes Restoration Initiative EOF sites spanning Wisconsin, Michigan, Indiana, Ohio, and New York. Analyses of site characteristics (hydroclimate, management, catchment properties) along with 3 yr of soil health measurements (chemical, biological, and physical properties) showed EOF-nutrient export depended on both site and soil properties. A pattern emerged whereby sites not receiving manure and sites with manure defined opposite ends of several gradients for soil and water data. Sites receiving manure had increased microbial activity, organic matter (3.2 vs. 2.7%), and soil test phosphorus (P) (2.8 times more) relative to sites without manure. Suspended sediments (SS), total P (TP), and total nitrogen (TN) in EOF surface runoff varied over three to five orders. Multivariate analysis among sites showed covariant linkages between soil nutrients, soil C, microbial properties, and nutrients in EOF water. There were positive univariate relationships between water-extractable soil P and annual EOF-water concentrations and yields of orthophosphate, TP, TN, and SS ( p < .01). Some soil physical properties (e.g., bulk density and infiltration) also covaried among sites but were not consistently related to runoff index or water yield variables. Given the observed among-site variability, we were not able to isolate desirable soil health signals on EOF surface water quality.

Journal of Environmental Quality↗
USGS2021

Could climate change benefit invasive snakes? Modelling the potential distribution of the California Kingsnake in the Canary Islands

The interaction between climate change and biological invasions is a global conservation challenge with major consequences for invasive species management. However, our understanding of this interaction has substantial knowledge gaps; this is particularly relevant for invasive snakes on islands because they can be a serious threat to island ecosystems. Here we evaluated the potential influence of climate change on the distribution of invasive snakes on islands, using the invasion of the California kingsnake ( Lampropeltis californiae ) in Gran Canaria. We analysed the potential distribution of L. californiae under current and future climatic conditions in the Canary Islands, with the underlying hypothesis that the archipelago might be suitable for the species under these climate scenarios. Our results indicate that the Canary Islands are currently highly suitable for the invasive snake, with increased suitability under the climate change scenarios tested here. This study supports the idea that invasive reptiles represent a substantial threat to near-tropical regions, and builds on previous studies suggesting that the menace of invasive reptiles may persist or even be exacerbated by climate change. We suggest future research should continue to fill the knowledge gap regarding invasive reptiles, in particular snakes, to clarify their potential future impacts on global biodiversity.

Journal of Environmental Management↗
USGS2005

Chemical loading into surface water along a hydrological, biogeochemical, and land use gradient: A holistic watershed approach

Identifying the sources and impacts of organic and inorganic contaminants at the watershed scale is a complex challenge because of the multitude of processes occurring in time and space. Investigation of geochemical transformations requires a systematic evaluation of hydrologic, landscape, and anthropogenic factors. The 1160 km 2 Boulder Creek Watershed in the Colorado Front Range encompasses a gradient of geology, ecotypes, climate, and urbanization. Streamflow originates primarily as snowmelt and shows substantial annual variation. Water samples were collected along a 70-km transect during spring-runoff and base-flow conditions, and analyzed for major elements, trace elements, bulk organics, organic wastewater contaminants (OWCs), and pesticides. Major-element and trace-element concentrations were low in the headwaters, increased through the urban corridor, and had a step increase downstream from the first major wastewater treatment plant (WWTP). Boron, gadolinium, and lithium were useful inorganic tracers of anthropogenic inputs. Effluent from the WWTP accounted for as much as 75% of the flow in Boulder Creek and was the largest chemical input. Under both hydrological conditions, OWCs and pesticides were detected in Boulder Creek downstream from the WWTP outfall as well as in the headwater region, and loads of anthropogenic-derived contaminants increased as basin population density increased. This report documents a suite of potential endocrine-disrupting chemicals in a reach of stream with native fish populations showing indication of endocrine disruption.

Environmental Science & Technology↗
USGS2012

A risk-based approach to evaluating wildlife demographics for management in a changing climate: A case study of the Lewis's Woodpecker

Given the projected threat that climate change poses to biodiversity, the need for proactive response efforts is clear. However, integrating uncertain climate change information into conservation planning is challenging, and more explicit guidance is needed. To this end, this article provides a specific example of how a risk-based approach can be used to incorporate a species' response to climate into conservation decisions. This is shown by taking advantage of species' response (i.e., impact) models that have been developed for a well-studied bird species of conservation concern. Specifically, we examine the current and potential impact of climate on nest survival of the Lewis's Woodpecker ( Melanerpes lewis ) in two different habitats. To address climate uncertainty, climate scenarios are developed by manipulating historical weather observations to create ensembles (i.e., multiple sequences of daily weather) that reflect historical variability and potential climate change. These ensembles allow for a probabilistic evaluation of the risk posed to Lewis's Woodpecker nest survival and are used in two demographic analyses. First, the relative value of each habitat is compared in terms of nest survival, and second, the likelihood of exceeding a critical population threshold is examined. By embedding the analyses in a risk framework, we show how management choices can be made to be commensurate with a defined level of acceptable risk. The results can be used to inform habitat prioritization and are discussed in the context of an economic framework for evaluating trade-offs between management alternatives.

Idaho↗
USGS2018

Rebuttal to “The case of the Biscayne Bay and aquifer near Miami, Florida: density-driven flow of seawater or gravitationally driven discharge of deep saline groundwater?” by Weyer (Environ Earth Sci 2018, 77:1–16)

A recent paper by Weyer (Environ Earth Sci 2018, 77:1–16) challenges the widely accepted interpretation of groundwater heads and salinities in the coastal Biscayne aquifer near Miami, Florida, USA. Weyer (2018) suggests that the body of saltwater that underlies fresh groundwater just inland of the coast is not a recirculating wedge of seawater, but results instead from upward migration of deep saline groundwater driven by regional flow. Perhaps more significantly, Weyer (2018) also asserts that established hydrologic theory is fundamentally incorrect with respect to buoyancy. Instead of acting along the direction of gravity (that is, vertically), Weyer (2018) claims, buoyancy acts instead along the direction of the pressure gradient. As a result, Weyer (2018) considers currently available density-dependent groundwater flow and transport modeling codes, and the analyses based on them, to be in error. In this rebuttal, we clarify the inaccuracies in the main points of Weyer’s (2018) paper. First, we explain that Weyer (2018) has misinterpreted observed equivalent freshwater heads in the Biscayne aquifer and that his alternative hypothesis concerning the source of the saltwater does not explain the observed salinities. Then, we review the established theory of buoyancy to identify the problem with Weyer’s (2018) alternative theory. Finally, we present theory and cite successful benchmark simulations to affirm the suitability of currently available codes for modeling density-dependent groundwater flow and transport.

Environmental Earth Sciences↗
USGS2020

Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data

Stream water temperature ( T s ) is a variable of critical importance for aquatic ecosystem health. T s is strongly affected by groundwater-surface water interactions which can be learned from streamflow records, but previously such information was challenging to effectively absorb with process-based models due to parameter equifinality. Based on the long short-term memory (LSTM) deep learning architecture, we developed a basin-centric lumped daily mean T s model, which was trained over 118 data-rich basins with no major dams in the conterminous United States, and showed strong results. At a national scale, we obtained a median root-mean-square error of 0.69°C, Nash–Sutcliffe model efficiency coefficient of 0.985, and correlation of 0.994, which are marked improvements over previous values reported in literature. The addition of streamflow observations as a model input strongly elevated the performance of this model. In the absence of measured streamflow, we showed that a two-stage model could be used, where simulated streamflow from a pre-trained LSTM model ( Q sim ) still benefited the T s model even though no new information was brought directly into the inputs of the T s model. The model indirectly used information learned from streamflow observations provided during the training of Q sim , potentially to improve internal representation of physically meaningful variables. Our results indicate that strong relationships exist between basin-averaged forcing variables, catchment attributes, and T s that can be simulated by a single model trained by data on the continental scale.

Environmental Research Letters↗
USGS2026

Lost in translation: Reconciling different streamflow permanence data products

The objective of this study is to provide a framework to reconcile streamflow permanence products that provide information on whether a stream is perennial or nonperennial. Accurate classification of streams as perennial or nonperennial is important for a variety of land and water resource management decisions. However, resource managers are challenged with how to reconcile different streamflow permanence information to determine if it is sufficient to avoid field verification, which can be prohibitively costly and time consuming. The study evaluates two datasets for the Pacific Northwest Region, U.S., the National Hydrography Dataset Plus High Resolution (NHDPlus HR) hydrographic classification and the PRObability of Streamflow PERmanence (PROSPER) model output, which differ in structure, output type, and temporal and spatial resolution. The framework includes a two-level evaluation that involves assessing agreement between the two datasets and evaluating the reliability of the two datasets. Summarized at a regional scale, the two datasets agree for 68% of flowlines with higher agreement for nonperennial streams. PROSPER nonperennial stream classifications may be considered generally reliable in arid regions relative to other ecoregions within the Pacific Northwest study area but less reliable for high elevation mountain regions and larger streams and rivers. More than 75% of NHDPlusHR classifications may be considered reliable when evaluating reliability based on approximate climate conditions associated with the year that the NHDPlus HR classification was assigned. The decision procedure is reproducible, flexible to varying criteria of end user applications, and is intended to help provide cost saving opportunities for land managers by providing information for more strategic field verification of streamflow class determination based on available yet imperfect data sources.

California, Idaho, Montana, Nevada, Utah, Washingt↗
USGS2009

NBII-SAIN Data Management Toolkit

The Strategic Plan for the U.S. Geological Survey Biological Informatics Program (2005-2009) recognizes the need for effective data management: Though the Federal government invests more than $600 million per year in biological data collection, it is difficult to address these issues because of limited accessibility and lack of standards for data and information...variable quality, sources, methods, and formats (for example observations in the field, museum specimens, and satellite images) present additional challenges. This is further complicated by the fast-moving target of emerging and changing technologies such as GPS and GIS. Even though these technologies offer new solutions, they also create new informatics challenges (Ruggiero and others, 2005). The USGS National Biological Information Infrastructure program, hereafter referred to as NBII, is charged with the mission to improve the way data and information are gathered, documented, stored, and accessed. The central objective of this project is a direct reflection of the purpose of NBII as described by John Mosesso, Program Manager of the U.S. Geological Survey-Biological Informatics Program-GAP Analysis: At the outset, the reason for bringing about NBII was that there were significant amounts of data and information scattered all over the U.S., not accessible, in incompatible formats, and that NBII was tasked with addressing this problem...NBII's focus is to pull data together that truly matters to someone or communities. Essentially, the core questions are: 1) what are the issues, 2) where is the data, and 3) how can we make it usable and accessible (John Mosesso, U.S. Geological Survey, oral commun., 2006). Redundancy in data collection can be a major issue when multiple stakeholders are involved with a common effort. In 2001 the U.S. General Accounting Office (USGAO) estimated that about 50 percent of the Federal government's geospatial data at the time was redundant. In addition, approximately 80 percent of the cost of a spatial information system is associated with spatial data collection and management (U.S. General Accounting Office, 2003). These figures indicate that the resources (time, personnel, money) of many agencies and organizations could be used more efficiently and effectively. Dedicated and conscientious data management coordination and documentation is critical for reducing such redundancy. Substantial cost savings and increased efficiency are direct results of a pro-active data management approach. In addition, details of projects as well as data and information are frequently lost as a result of real-world occurrences such as the passing of time, job turnover, and equipment changes and failure. A standardized, well documented database allows resource managers to identify issues, analyze options, and ultimately make better decisions in the context of adaptive management (National Land and Water Resources Audit and the Australia New Zealand Land Information Council on behalf of the Australian National Government, 2003). Many environmentally focused, scientific, or natural resource management organizations collect and create both spatial and non-spatial data in some form. Data management appropriate for those data will be contingent upon the project goal(s) and objectives and thus will vary on a case-by-case basis. This project and the resulting Data Management Toolkit, hereafter referred to as the Toolkit, is therefore not intended to be comprehensive in terms of addressing all of the data management needs of all projects that contain biological, geospatial, and other types of data. The Toolkit emphasizes the idea of connecting a project's data and the related management needs to the defined project goals and objectives from the outset. In that context, the Toolkit presents and describes the fundamental components of sound data and information management that are common to projects involving biological, geospatial, and other related data

Open-File Report↗
USGS2025

How do hydrological variability and human activities control the spatiotemporal changes of riverine nitrogen export in the Upper Mississippi River Basin?

Excessive nitrogen export from agricultural watersheds remains a critical water quality challenge, with the Upper Mississippi River Basin (UMRB) significantly contributing to downstream eutrophication and hypoxia in the Gulf. This study investigates the spatiotemporal dynamics of riverine nitrate plus nitrite (NO 3 – + NO 2 – -N) export across the UMRB at high spatial resolution (12-digit Hydrologic Unit Codes or HUC12 subwatershed scale) during 2001–2020 and quantifies the effects of anthropogenic activities and hydrological variability on riverine NO 3 – + NO 2 – -N export changes in the region between 2001–2005 and 2016–2020. Our results revealed hotspots of substantial increases in NO 3 – + NO 2 – -N yields across the UMRB, with distinct regional patterns in driving factors. Over the entire UMRB, NO 3 – + NO 2 – -N yields increased by 9.7 kg/ha/yr on average from 2001–2005 to 2016–2020, with anthropogenic activities contributing 4.8 kg/ha/yr and hydrological variability contributing 4.9 kg/ha/yr. The northern and western UMRB had combined influences from both anthropogenic activities and hydrological variability, while the east-central regions had predominantly hydrologically driven changes. Agricultural sources, including fertilizer, manure, and biological nitrogen fixation, collectively contributed over 80% of NO 3 – + NO 2 – -N loading throughout the basin. This framework for disentangling human and hydrological impacts provides critical insights for developing effective and targeted watershed management strategies to reduce nutrient losses and improve water quality.

Upper Mississippi River Basin↗
USGS2018

Influence of governance structure on green stormwater infrastructure investment

Communities are faced with the challenge of meeting regulatory requirements mandating reductions in water pollution from stormwater and combined sewer overflows (CSO). Green stormwater infrastructure and gray stormwater infrastructure are two types of water management strategies communities can use to address water pollution. In this study, we used long-term control plans from 25 U.S. cities to synthesize: the types of gray and green infrastructure being used by communities to address combined sewer overflows; the types of goals set; biophysical characteristics of each city; and factors associated with the governance of stormwater management. These city characteristics were then used to identify common characteristics of “green leader” cities—those that dedicated >20% of the control plan budget in green infrastructure. Five “green leader” cities were identified: Milwaukee, WI, Philadelphia, PA, Syracuse, NY, New York City, NY, and Buffalo, NY. These five cities had explicit green infrastructure goals targeting the volume of stormwater or percentage of impervious cover managed by green infrastructure. Results suggested that the management scale and complexity of the management system are less important factors than the ability to harness a “policy window” to integrate green infrastructure into control plans. Two case studies—Philadelphia, PA, and Milwaukee, WI—indicated that green leader cities have a long history of building momentum for green infrastructure through a series of phases from experimentation, demonstration, and finally—in the case of Philadelphia—a full transition in the approach used to manage CSOs.

Environmental Science and Policy↗
USGS2013

Overview of groundwater quality in the Piceance Basin, western Colorado, 1946--2009

Groundwater-quality data from public and private sources for the period 1946 to 2009 were compiled and put into a common data repository for the Piceance Basin. The data repository is available on the web at http://rmgsc.cr.usgs.gov/cwqdr/Piceance/index.shtml. A subset of groundwater-quality data from the repository was compiled, reviewed, and checked for quality assurance for this report. The resulting dataset consists of the most recently collected sample from 1,545 wells, 1,007 (65 percent) of which were domestic wells. From those samples, the following constituents were selected for presentation in this report: dissolved oxygen, dissolved solids, pH, major ions (chloride, sulfate, fluoride), trace elements (arsenic, barium, iron, manganese, selenium), nitrate, benzene, toluene, ethylbenzene, xylene, methane, and the stable isotopic compositions of water and methane. Some portion of recharge to most of the wells for which data were available was derived from precipitation (most likely snowmelt), as indicated by δ2H [H2O] and δ18O[H2O] values that plot along the Global Meteoric Water Line and near the values for snow samples collected in the study area. Ninety-three percent of the samples were oxic, on the basis of concentrations of dissolved oxygen that were greater than or equal to 0.5 milligrams per liter. Concentration data were compared with primary and secondary drinking-water standards established by the U.S. Environmental Protection Agency. Constituents that exceeded the primary standards were arsenic (13 percent), selenium (9.2 percent), fluoride (8.4 percent), barium (4.1 percent), nitrate (1.6 percent), and benzene (0.6 percent). Concentrations of toluene, xylenes, and ethylbenzene did not exceed standards in any samples. Constituents that exceeded the secondary standard were dissolved solids (72 percent), sulfate (37 percent), manganese (21 percent), iron (16 percent), and chloride (10 percent). Drinking-water standards have not been established for methane, which was detected in 24 percent of samples. Methane concentrations were greater than or equal to 1 milligram per liter in 8.5 percent of samples. Methane isotopic data for samples collected primarily from domestic wells in Garfield County indicate that methane in samples with relative high methane concentrations were derived from both biogenic and thermogenic sources. Many of the constituents that exceeded standards, such as arsenic, fluoride, iron, and manganese, were derived from rock and sediment in aquifers. Elevated nitrate concentrations were most likely derived from human sources such as fertilizer and human or animal waste. Information about the geologic unit or aquifer in which a well was completed generally was not provided by data sources. However, limited data indicate that Quaternary deposits in Garfield and Mesa Counties, the Wasatch Formation in Garfield County, and the Green River Formation in Rio Blanco County had some of the highest median concentrations of selected constituents. Variations in concentration with depth could not be evaluated because of the general lack of well-depth and water-level data. Concentrations of several important constituents, such as arsenic, manganese, methane, and nitrate, were related to concentrations of dissolved oxygen. Concentrations of arsenic, manganese, and methane were significantly higher in groundwater with low dissolved-oxygen concentrations than in groundwater with high dissolved-oxygen concentrations. In contrast, concentrations of nitrate were significantly higher in groundwater with high dissolved-oxygen concentrations than in groundwater with low dissolved-oxygen concentrations. These results indicate that measurements of dissolved oxygen may be a useful indicator of groundwater vulnerability to some human-derived contaminants and enrichment from some natural constituents. Assessing such a large and diverse dataset as the one available through the repository poses unique challenges for reporting on groundwater quality in the study area. The repository contains data from several studies that differed widely in purpose and scope. In addition to this variability in available data, gaps exist spatially, temporally, and analytically in the repository. For example, groundwater-quality data in the repository were not evenly distributed throughout the study area. Several key water-quality constituents or indicators, such as dissolved oxygen, were underrepresented in the repository. Ancillary information, such as well depth, depth to water, and the geologic unit or aquifer in which a well was completed, was missing for more than 50 percent of samples. Future monitoring could avoid several limitations of the repository by making relatively minor changes to sample- collection and data-reporting protocols. Field measurements for dissolved oxygen could be added to sampling protocols, for example. Information on well construction and the geologic unit or aquifer in which a well was completed should be part of the water-quality dataset. Such changes would increase the comparability of data from different monitoring programs and also add value to each program individually and to that of the regional dataset as a whole. Other changes to monitoring programs could require greater resources, such as sampling for a basic set of constituents that is relevant to major water-quality issues in the regional study area. Creation of such a dataset for the regional study area would help to provide the kinds of information needed to characterize background conditions and the spatial and temporal variability in constituent concentrations associated with those conditions. Without such information, it is difficult to identify departures from background that might be associated with human activities.

Colorado↗
USGS2019

The presence of antibiotic resistance genes in coastal soil and sediment samples from the eastern seaboard of the USA

Infections from antibiotic resistant microorganisms are considered to be one of the greatest global public health challenges that result in huge annual economic losses. While genes that impart resistance to antibiotics (AbR) existed long before the discovery and use of antibiotics, anthropogenic uses of antibiotics in agriculture, domesticated animals, and humans are known to influence the prevalence of these genes in pathogenic microorganisms. It is critical to understand the role that natural and anthropogenic processes have on the occurrence and distribution of antibiotic resistance in microbial populations to minimize health risks associated with exposures. As part of this research, 15 antibiotic resistance genes were analyzed in coastal sediments and soils along the eastern seaboard of the USA using presence/absence quantitative and digital polymerase chain reaction assays. Samples (53 soil and 192 sediment samples including 54 replicates) were collected from a variety of coastal settings where human and wildlife exposure is likely. At least one of the antibiotic resistance genes was detected in 76.4% of the samples. Samples that contained at least five or more antibiotic resistance genes (5.7%) where typically hydrologically down gradient of watersheds influenced by combined sewer outfalls (CSO). The most frequently detected antibiotic resistance target genes were found in 33.2%, 34.4%, and 42.2% of samples (target genes bla SHV , tetO , and aadA2 , respectively). These data provide unique insight into potential exposure of AbR genes over a large geographical region of the eastern seaboard of the USA.

Connecticut, Delaware, District of Columbia, Maine↗
USGS2008

Determination of dominant biogeochemical processes in a contaminated aquifer-wetland system using multivariate statistical analysis

Determining the processes governing aqueous biogeochemistry in a wetland hydrologically linked to an underlying contaminated aquifer is challenging due to the complex exchange between the systems and their distinct responses to changes in precipitation, recharge, and biological activities. To evaluate temporal and spatial processes in the wetland-aquifer system, water samples were collected using cm-scale multi-chambered passive diffusion samplers (peepers) to span the wetland-aquifer interface over a period of 3 yr. Samples were analyzed for major cations and anions, methane, and a suite of organic acids resulting in a large dataset of over 8000 points, which was evaluated using multivariate statistics. Principal component analysis (PCA) was chosen with the purpose of exploring the sources of variation in the dataset to expose related variables and provide insight into the biogeochemical processes that control the water chemistry of the system. Factor scores computed from PCA were mapped by date and depth. Patterns observed suggest that (i) fermentation is the process controlling the greatest variability in the dataset and it peaks in May; (ii) iron and sulfate reduction were the dominant terminal electron-accepting processes in the system and were associated with fermentation but had more complex seasonal variability than fermentation; (iii) methanogenesis was also important and associated with bacterial utilization of minerals as a source of electron acceptors (e.g., barite BaSO 4 ); and (iv) seasonal hydrological patterns (wet and dry periods) control the availability of electron acceptors through the reoxidation of reduced iron-sulfur species enhancing iron and sulfate reduction.

Journal of Environmental Quality↗
USGS2024

Complex hydrology and variability of nitrogen sources in a karst watershed

Streams draining karst areas with rapid groundwater transit times may respond relatively quickly to nitrogen reduction strategies, but the complex hydrologic network of interconnected sinkholes and springs is challenging for determining the placement and effectiveness of management practices. This study aims to inform nitrogen reduction strategies in a representative agricultural karst setting of the Chesapeake Bay watershed (Fishing Creek watershed, Pennsylvania) with known elevated nitrate contamination and a previous documented groundwater residence time of less than a decade. During baseflow conditions, streamflow did not increase with drainage area. Headwaters and the main stem lost substantial flow to sinkholes until eventually discharging along large springs downstream. Seasonal hydrologic conditions shift the flow and nitrogen load spatially among losing and gaining stream sections. A compilation of nitrogen source inputs with the geochemistry and the pattern of enrichment of δ 15 N and δ 18 O suggest that the nitrogen in streams and springs during baseflow represents a mixture of manure, fertilizer, and wastewater sources with low potential for denitrification. The pH and calcite saturation index increased along generalized flow paths from headwaters to springs and indicate shorter groundwater residence times in baseflow during the spring versus summer. Given the substantial investment in management practices, fixed monitoring sites could incorporate synoptic water sampling to properly monitor long-term progress and help inform management actions in karst watersheds. Although karst watersheds have the potential to respond to nitrogen reduction strategies due to shorter groundwater residence times, high nitrogen inputs, effectiveness of conservation practices, and release of legacy nutrients within the karst cavities could confound progress of water quality goals.

Pennsylvania↗