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USGS2001

Transboundary movement of airborne pollutants — A methodology for integrating spaceborne images and ground based data

The availability of relevant and accurate environmental information is essential for environmental policy-makers. Recent improvements in satellite remote sensing technologies, groundbased monitors, and data access have resulted in the ability to observe and assess major atmospheric and ecological events around the world on a timely basis Each of these monitoring technologies reveals different and useful information, yet rarely are the resulting data sets used together in an integrated manner. The U.S. Environmental Protection Agency (EPA) and the United Nations Environment Programme (UNEP) Global Resource Information Database (GRID) office in Sioux Falls identified an environmental issue of global interest as a test case for applying an integrated approach: the transboundary movement of atmospheric pollutants. Transboundary movement of atmospheric pollutants has ramifications for human and environmental health, as well as economic impacts. As a result, it is the focus of many bilateral, regional, and international policy efforts. A central question with atmospheric pollutant transport is how to monitor pollutant movement and how to merge different monitoring datasets into useful information. Highly visible regional plumes of dust, smoke, and urban haze can be seen with satellite sensors, while ground-based monitoring of air pollutants such as fine particulates, SO2 , and toxics occurs at the local level. Integration of these two kinds of measurements allows the user to remotely observe large environmental effects in many areas of the world, while obtaining more detailed information from ground-based monitors. Hence, the combination of satellite-based sensor data and ground-based monitoring data promotes greater understanding of the movement of pollutants than either data set alone. Combined data sets are important for use by both scientists and international policy-makers. A standard methodology did not exist to guide and encourage integrated use of satellite images and ground-based data to monitor and understand major pollution events, such as air pollution. Thus, a small team was assembled to develop a methodology for the integration of satellite images and ground-based data. First, we conducted a literature and project review covering past and current integrated remote and ground-based data projects, a literature search of published work, and a search of data sets and technologies that could be used in a combined form. Second, based on this search and documentation, a general methodology was developed for using integrated spaceborne and ground-based data sets, intended as a guide for general scientists and policy-makers. Third, we found an existing project that was willing to be a pilot for testing the methodology: a U.S. EPANOAA project that was using aerial and ground-based sampling to learn more about the airborne sources of mercury deposition in the Florida Everglades. This document presents the results of the literature and project review, the complete methodology, and the outcome of the Florida Everglades pilot project.

Report↗

USGS2011

Quality of volatile organic compound data from groundwater and surface water for the National Water-Quality Assessment Program, October 1996–December 2008

This report describes the quality of volatile organic compound (VOC) data collected from October 1996 to December 2008 from groundwater and surface-water sites for the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program. The VOC data described were collected for three NAWQA site types: (1) domestic and public-supply wells, (2) monitoring wells, and (3) surface-water sites. Contamination bias, based on the 90-percent upper confidence limit (UCL) for the 90th percentile of concentrations in field blanks, was determined for VOC samples from the three site types. A way to express this bias is that there is 90-percent confidence that this amount of contamination would be exceeded in no more than 10 percent of all samples (including environmental samples) that were collected, processed, shipped, and analyzed in the same manner as the blank samples. This report also describes how important native water rinsing may be in decreasing carryover contamination, which could be affecting field blanks. The VOCs can be classified into four contamination categories on the basis of the 90-percent upper confidence limit (90-percent UCL) concentration distribution in field blanks. Contamination category 1 includes compounds that were not detected in any field blanks. Contamination category 2 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is about an order of magnitude lower than the concentration distribution of the environmental samples. Contamination category 3 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is within an order of magnitude of the distribution in environmental samples. Contamination category 4 includes VOCs that have a 90-percent UCL concentration distribution in field blanks that is at least an order of magnitude larger than the concentration distribution of the environmental samples. Fifty-four of the 87 VOCs analyzed in samples from domestic and public-supply wells were not detected in field blanks (contamination category 1), and 33 VOC were detected in field blanks. Ten of the 33 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than the concentration distribution in environmental samples (contamination category 2). These 10 VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative of the sources of contamination bias affecting the environmental samples for these 10 VOCs. Seven VOCs had a 90-percent UCL concentration distribution of the field blanks that was within an order of magnitude of the concentration distribution of the environmental samples (contamination category 3). Sixteen VOCs had a 90-percent UCL concentration distribution in the field blanks that was at least an order of magnitude greater than the concentration distribution of the environmental samples (contamination category 4). Field blanks for these 16 VOCs appear to be nonrepresentative of the sources of contamination bias affecting the environmental samples because of the larger concentration distributions (and sometimes higher frequency of detection) in field blanks than in environmental samples. Forty-three of the 87 VOCs analyzed in samples from monitoring wells were not detected in field blanks (contamination category 1), and 44 VOCs were detected in field blanks. Eight of the 44 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than concentrations in environmental samples (contamination category 2). These eight VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative. Seven VOCs had a 90-percent UCL concentration distribution in field blanks that was of the same order of magnitude as the concentration distribution of the environmental samples (contamination category 3). Twenty-nine VOCs had a 90-percent UCL concentration distribution in the field blanks that was an order of magnitude greater than the distribution of the environmental samples (contamination category 4). Field blanks for these 29 VOCs appear to be nonrepresentative of the sources of contamination bias to the environmental samples. Fifty-four of the 87 VOCs analyzed in surface-water samples were not detected in field blanks (category 1), and 33 VOC were detected in field blanks. Sixteen of the 33 VOCs had a 90-percent UCL concentration distribution in field blanks that was at least an order of magnitude lower than the concentration distribution in environmental samples (contamination category 2). These 16 VOCs may have had some contamination bias associated with the environmental samples, but the potential contamination bias was negligible in comparison to the environmental data; therefore, the field blanks were assumed to be representative. Ten VOCs had a 90-percent UCL concentration distribution in field blanks that was similar to the concentration distribution of environmental samples (contamination category 3). Seven VOCs had a 90-percent UCL concentration distribution in the field blanks that was greater than the concentration distribution in environmental samples (contamination category 4). Field-blank samples for these seven VOCs appear to be nonrepresentative of the sources of contamination bias to the environmental samples. The relation between the detection of a compound in field blanks and the detection in subsequent environmental samples appears to be minimal. The median minimum percent effectiveness of native water rinsing is about 79 percent for the 19 VOCs detected in more than 5 percent of field blanks from all three site types. The minimum percent effectiveness of native water rinsing (10 percent) was for toluene in surface-water samples, likely because of the large detection frequency of toluene in surface-water samples (about 79 percent) and in the associated field-blank samples (46.5 percent). The VOCs that were not detected in field blanks (contamination category 1) from the three site types can be considered free of contamination bias, and various interpretations for environmental samples, such as VOC detection frequency at multiple assessment levels and comparisons of concentrations to benchmarks, are not limited for these VOCs. A censoring level for making comparisons at different assessment levels among environmental samples could be applied to concentrations of 9 VOCs in samples from domestic and public-supply wells, 16 VOCs in samples from monitoring wells, and 9 VOCs in surface-water samples to account for potential low-level contamination bias associated with these selected VOCs. Bracketing the potential contamination by comparing the detection and concentration statistics with no censoring applied to the potential for contamination bias on the basis of the 90-percent UCL for the 90th-percentile concentrations in field blanks may be useful when comparisons to benchmarks are done in a study. The VOCs that were not detected in field blanks (contamination category 1) from the three site types can be considered free of contamination bias, and various interpretations for environmental samples, such as VOC detection frequency at multiple assessment levels and comparisons of concentrations to benchmarks, are not limited for these VOCs. A censoring level for making comparisons at different assessment levels among environmental samples could be applied to concentrations of 9 VOCs in samples from domestic and public-supply wells, 16 VOCs in samples from monitoring wells, and 9 VOCs in surface-water samples to account for potential low-level contamination bias associated with these selected VOCs. Bracketing the potential contamination by comparing the detection and concentration statistics with no censoring applied to the potential for contamination bias on the basis of the 90-percent UCL for the 90th-percentile concentrations in field blanks may be useful when comparisons to benchmarks are done in a study.

Scientific Investigations Report↗

USGS2016

Ecoregions of California

Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000). The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014). California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014). The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities. The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.

California↗

USGS1999

Strategies for ensuring global consistency/comparability of water-quality data

In the past 20 years the water quality of the United States has improved remarkably-the waters are safer for drinking, swimming, and fishing. However, despite many accomplishments, it is still difficult to answer such basic questions as: 'How clean is the water?' and 'How is it changing over time?' These same questions exist on a global scale as well. In order to focus water-data issues in the United States, a national Intergovernmental Task Force on Monitoring Water Quality (ITFM) was initiated for public and private organizations, whereby key elements involved in data collection, analysis, storage, and management could be made consistent and comparable. The ITFM recommended and its members are implementing a nationwide strategy to improve water-quality monitoring, assessment, and reporting activities. The intent of this paper is to suggest that a voluntary effort be initiated to ensure the comparability and utility of hydrological data on a global basis. Consistent, long-term data sets that are comparable are necessary in order to formulate ideas regarding regional and global trends in water quantity and quality. The author recommends that a voluntary effort similar to the ITFM effort be utilized. The strategy proposed would involve voluntary representation from countries and international organizations (e.g. World Health Organization) involved in drinking-water assessments and/or ambient water-quality monitoring. Voluntary partnerships such as this will improve curability to reduce health risks and achieve a better return on public and private investments in monitoring, environmental protection, and natural resource management, and result in a collaborative process that will save millions of dollars.In this work it is suggested that a voluntary effort be initiated to ensure the comparability and utility of hydrological data on a global basis. The strategy proposed would involve voluntary representation from countries and international organizations involved in drinking-water assessments and/or ambient water-quality monitoring.

Conference Paper↗

USGS2016

Environmental factors influence lesser scaup migration chronology and population monitoring

Identifying environmental metrics specific to lesser scaup ( Aythya affinis ; scaup) spring migration chronology may help inform development of conservation, management and population monitoring. Our objective was to determine how environmental conditions influence spring migration of lesser scaup to assess the effectiveness of the Waterfowl Breeding Population and Habitat Survey in accurately estimating scaup populations. We first compared peak timing of mallard ( Anas platyrhynchos ) and scaup migration from weekly ground surveys in North Dakota, USA because the Waterfowl Breeding Population and Habitat Survey is designed to capture annual mallard migration. As predicted, we detected that peak timing of scaup and mallard migrations differed in 25 of 36 years investigated (1980–2010). We marked scaup with satellite transmitters ( n = 78; 7,403 locations) at Long Point, Lake Erie, Ontario, Canada; Pool 19 of the Mississippi River, Iowa and Illinois, USA; and Presque Isle Bay, Lake Erie, Pennsylvania, USA. We tested the assumption that our marked scaup were representative of the continental population using the traditional survey area by comparing timing of migration of marked birds and scaup counted in the North Dakota Game and Fish Department survey. We detected a strong positive correlation between marked scaup and the survey data, which indicated that marked scaup were representative of the population. We subsequently used our validated sample of marked scaup to investigate the effects of annual variation in temperature, precipitation, and ice cover on spring migration chronology in the traditional and eastern survey areas of the Waterfowl Breeding Population and Habitat Survey, 2005–2010. We evaluated competing environmental models to explain variation in timing and rate of scaup migration at large-scale and local levels. Spring migration of scaup occurred earlier and faster during springs with warmer temperatures and greater precipitation, variables known to influence energy budgets and wetland availability. Our results suggest that surveys designed to index abundance of breeding mallards is imprecise for estimating scaup abundance, and inaccurate at estimating breeding population size by survey stratum.

Journal of Wildlife Management↗

USGS2019

Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network

This study explores the feasibility and utility of integrating environmental DNA (eDNA) assessments of species occurrences into the United States (U.S.) Geological Survey’s national streamgage network. We used an existing network of five gages in southwest Idaho to explore the type of information that could be gained as well as the associated costs and limitations. Hydrologic technicians were trained in eDNA sampling protocols and they collected samples during routine monthly visits to streamgages over an entire water year (2016). We analyzed the eDNA in the filtered water samples to determine the presence of two fish species: bull trout and rainbow trout. We then modeled the spatiotemporal distribution of each species using discharge and temperature data. To assess the influence of the spatial distribution of the gages on the biological information obtained, we also collected eDNA samples from locations between the gages three times during the water year. We found eDNA monitoring at the five gages provided meaningful information about the distribution of both species, especially when detection probabilities accounted for variations in temperature and discharge. Sampling between the gages provided additional information about bull trout distribution — the rarer of the two species. Our study suggests the integration of eDNA sampling into a streamgage network is feasible and could provide a novel and powerful source of biological information for riverine ecosystems in the U.S.

Idaho, Nebraska↗

USGS2016

Estimation of a Trophic State Index for selected inland lakes in Michigan, 1999–2013

A 15-year estimated Trophic State Index (eTSI) for Michigan inland lakes is available, and it spans seven datasets, each representing 1 to 3 years of data from 1999 to 2013. On average, 3,000 inland lake eTSI values are represented in each of the datasets by a process that relates field-measured Secchi-disk transparency (SDT) to Landsat satellite imagery to provide eTSI values for unsampled inland lakes. The correlation between eTSI values and field-measured Trophic State Index (TSI) values from SDT was strong as shown by R 2 values from 0.71 to 0.83. Mean eTSI values ranged from 42.7 to 46.8 units, which when converted to estimated SDT (eSDT) ranged from 8.9 to 12.5 feet for the datasets. Most eTSI values for Michigan inland lakes are in the mesotrophic TSI class. The Environmental Protection Agency (EPA) Level III Ecoregions were used to illustrate and compare the spatial distribution of eTSI classes for Michigan inland lakes. Lakes in the Northern Lakes and Forests, North Central Hardwood Forests, and Southern Michigan/Northern Indiana Drift Plains ecoregions are predominantly in the mesotrophic TSI class. The Huron/Erie Lake Plains and Eastern Corn Belt Plains ecoregions, had predominantly eutrophic class lakes and also the highest percent of hypereutrophic lakes than other ecoregions in the State. Data from multiple sampling programs—including data collected by volunteers with the Cooperative Lakes Monitoring Program (CLMP) through the Michigan Department of Environmental Quality (MDEQ), and the 2007 National Lakes Assessment (NLA)—were compiled to compare the distribution of lake TSI classes between each program. The seven eTSI datasets are available for viewing and download with eSDT from the Michigan Lake Water Clarity Interactive Map Viewer at http://mi.water.usgs.gov/projects/RemoteSensing/index.html .

Michigan↗

USGS2014

Ecoregions of Arizona (poster)

Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources; they are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The Arizona ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity. These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions. At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions. Level IV is a further subdivision of level III ecoregions. Arizona contains arid deserts and canyonlands, semiarid shrub- and grass-covered plains, woodland- and shrubland-covered hills, lava fields and volcanic plateaus, forested mountains, glaciated peaks, and river alluvial floodplains. Ecological diversity is remarkably high. There are 7 level III ecoregions and 52 level IV ecoregions in Arizona and many continue into ecologically similar parts of adjacent states. This poster is part of a collaborative project primarily between the U.S. Geological Survey (USGS), USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), USEPA Region IX, U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), The Nature Conservancy, and several Arizona state agencies. The project is associated with an interagency effort to develop a common national framework of ecological regions. Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service, the USEPA, and the NRCS. As each of these frameworks is further refined, their differences are becoming less discernible. Collaborative ecoregion projects, such as this one in Arizona, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.

Arizona↗

USGS2019

Assessing rangeland health under climate variability and change

RANGELAND HEALTH IN A CHANGING WORLD Rangeland health is an integrated metric that describes a complex suite of ecosystem properties and processes as applied to resource management. While the concept of “healthy” landscapes has a long history, the term “rangeland health” was codified in the US in 1994 as part of an effort to move towards a national, data driven, rangeland condition assessment (National Research Council 1994). Rangeland health encompasses the status of both soils and ecological processes as well as the condition of those ecosystems relative to ecological thresholds (e.g. “healthy”, “at-risk”, or “unhealthy"; National Research Council 1994). This latter application ensures that rangeland health assessments not only evaluate the conditions of plants and soils, but also gauge those conditions with respect to known or hypothesized ecological dynamics (Bestelmeyer et al. 2013) for a given set of abiotic constraints (climate, soil, and topographic setting). Thus, an assessment of rangeland health should identify the “degree to which the integrity of the soil and the ecological processes are sustained” (National Research Council 1994, Us Department of Agriculture 1997). Rangeland health attributes and assessment procedures have become widely utilized tools for measuring and monitoring dryland ecosystems, and they may provide valuable perspectives on rangeland response to climate change, although long-term directional change in environmental conditions represents a challenge for traditional rangeland health assessment frameworks.

Book chapter↗

USGS2015

Dust control products at Hagerman National Wildlife Refuge, Texas: environmental safety and performance

Controlling fugitive dust while protecting natural resources is a challenge faced by all managers of unpaved roads. Unfortunately, road managers choosing between dust control products often have little objective environmental information to aid their decisions. To address this information gap, the U.S. Geological Survey and the U.S. Fish and Wildlife Service collaborated on a field test of three dust control products with the objectives of ( a ) evaluating product performance under real-world conditions, ( b ) verifying the environmental safety of products identified as practically nontoxic in laboratory tests, and ( c ) testing the feasibility of several environmental monitoring techniques for use in dust control tests. In cooperation with refuge staff and product vendors, three products (one magnesium chloride plus binder, one cellulose, and one synthetic fluid plus binder) were applied in July 2012 to replicated road sections at the Hagerman National Wildlife Refuge in Texas. These sections were monitored periodically for 12 months after application. Product performance was assessed by mobile-mounted particulate-matter meters measuring production of fugitive dust and by observations of road conditions. Environmental safety was evaluated through on-site biological observations and leaching tests with samples of treated aggregate. All products reduced dust and improved surface condition during those 12 months. Planned environmental measurements were not always compatible with day-to-day refuge management actions; this incompatibility highlighted the need for flexible biological monitoring plans. As one of the first field tests of dust suppressants that explicitly incorporated biological endpoints, this effort provides valuable information for improving field tests and for developing laboratory or semifield alternatives.

Texas↗

USGS2025

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado↗

USGS2009

Remote sensing of global croplands for food security: Way forward

This book opens a new pathway for global mapping that is focused on a specific land use theme, such as irrigated or rain-fed croplands and classes within these themes. Since croplands use most of the water consumed by humans, specific knowledge of irrigated and rain-fed croplands will be critical for precise estimates of water use. At present and in the coming decades, irrigated and rain-fed cropland area mapping is crucial for food security studies. Throughout this book, various subjects pertaining to global croplands are discussed comprehensively.

Book chapter↗

USGS2015

Water data to answer urgent water policy questions: Monitoring design, available data and filling data gaps for determining the effectiveness of agricultural management practices for reducing tributary nutrient loads to Lake Erie

Throughout its history, the United States has made major investments in assessing natural resources, such as soils, timber, oil and gas, and water. These investments allow policy makers, the private sector and the American public to make informed decisions about cultivating, harvesting or conserving these resources to maximize their value for public welfare, environmental conservation and the economy. As policy issues evolve, new priorities and challenges arise for natural resource assessment, and new approaches to monitoring are needed. For example, informed conservation and use of the nation’s finite fresh water resources in the context of increasingly intensive land development is a priority for today’s policy decisionmakers. There is a need to evaluate whether today’s water monitoring programs are generating the information needed to answer questions surrounding these new policy priorities. The Northeast-Midwest Institute (NEMWI), in cooperation with the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program, initiated this project to explore the types and amounts of water data needed to address water-quality related policy questions of critical concern to today’s policy makers. The collaborating entities identified two urgent water policy questions and conducted case studies in the Northeast-Midwest region to determine the water data needed, water data available, and the best ways to fill the data gaps relative to those questions. This report details the output from one case study and focuses on the Lake Erie drainage basin, a data-rich area expected to be a best-case scenario in terms of water data availability.

Indiana, Michigan, New York, Ohio, Pennsylvania↗

USGS2016

Water data to answer urgent water policy questions: Monitoring design, available data, and filling data gaps for determining whether shale gas development activities contaminate surface water or groundwater in the Susquehanna River Basin

Throughout its history, the United States has made major investments in assessing natural resources, such as soils, timber, oil and gas, and water. These investments allow policy makers, the private sector and the American public to make informed decisions about cultivating, harvesting or conserving these resources to maximize their value for public welfare, environmental conservation and the economy. As policy issues evolve, new priorities and challenges arise for natural resource assessment, and new approaches to monitoring are needed. For example, new technologies for oil and gas development or alternative energy sources may present new risks for water resources both above and below ground. There is a need to evaluate whether today’s water monitoring programs are generating the information needed to answer questions surrounding these new policy priorities. The Northeast-Midwest Institute (NEMWI), in cooperation with the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program, initiated this project to explore the types and amounts of water data needed to address water-quality related policy questions of critical concern to today’s policy makers and whether those data are currently available. The collaborating entities identified two urgent water policy questions and conducted case studies in the Northeast-Midwest region to determine the water data needed, water data available, and the best ways to fill the data gaps relative to those questions. This report details the output from one case study and focuses on the Susquehanna River Basin, a data-rich area expected to be a best-case scenario in terms of water data availability.

Maryland, New York, Pennsylvania↗

USGS2009

Low-flow frequency and flow duration of selected South Carolina streams in the Pee Dee River basin through March 2007

Part of the mission of the South Carolina Department of Health and Environmental Control and the South Carolina Department of Natural Resources is to protect and preserve South Carolina's water resources. Doing so requires an ongoing understanding of streamflow characteristics of the rivers and streams in South Carolina. A particular need is information concerning the low-flow characteristics of streams; this information is especially important for effectively managing the State's water resources during critical flow periods such as the severe drought that occurred between 1998 and 2002 and the most recent drought that occurred between 2006 and 2009. In 2008, the U.S. Geological Survey, in cooperation with the South Carolina Department of Health and Environmental Control, initiated a study to update low-flow statistics at continuous-record streamgaging stations operated by the U.S. Geological Survey in South Carolina. Under this agreement, the low-flow characteristics at continuous-record streamgaging stations will be updated in a systematic manner during the monitoring and assessment of the eight major basins in South Carolina as defined and grouped according to the South Carolina Department of Health and Environmental Control's Watershed Water Quality Management Strategy. Depending on the length of record available at the continuous-record streamgaging stations, low-flow frequency characteristics are estimated for annual minimum 1-, 3-, 7-, 14-, 30-, 60-, and 90-day average flows with recurrence intervals of 2, 5, 10, 20, 30, and 50 years. Low-flow statistics are presented for 18 streamgaging stations in the Pee Dee River basin. In addition, daily flow durations for the 5-, 10-, 25-, 50-, 75-, 90-, and 95-percent probability of exceedance also are presented for the stations. The low-flow characteristics were computed from records available through March 31, 2007. The last systematic update of low-flow characteristics in South Carolina occurred more than 20 years ago and included data through March 1987. Of the 17 streamgaging stations included in this study, 15 had low-flow characteristics that were published in previous U.S. Geological Survey reports. A comparison of the low-flow characteristic for the minimum average flow for a 7-consecutive-day period with a 10-year recurrence interval from this study with the most recently published values indicated that 10 of the 15 streamgaging stations had values that were within ±25 percent of each other. Nine of the 15 streamgaging stations had negative percentage differences indicating the low-flow statistic had decreased since the previous study, 4 streamgaging stations had positive percent differences indicating that the low-flow statistic had increased since the previous study, and 2 streamgaging stations had a zero percent difference indicating no change since the previous study. The low-flow characteristics are influenced by length of record, hydrologic regime under which the record was collected, techniques used to do the analysis, and other changes that may have occurred in the watershed.

North Carolina, South Carolina↗

USGS2026

Per- and polyfluoroalkyl substances and pesticides in black bears (Ursus americanus) and grizzly bears (Ursus arctos horribilis) from Montana's Cabinet-Yaak ecosystem: A baseline assessment of emerging and legacy contaminants

Per- and polyfluoroalkyl substances (PFAS) and pesticides are globally distributed contaminants that persist in terrestrial food webs, yet baseline data for large omnivores in the continental U.S. remain limited. This study quantified PFAS and pesticides in whole blood from free-ranging black bears ( Ursus americanus , n = 15) and grizzly bears ( Ursus arctos horribilis , n = 9) in the Cabinet-Yaak Ecosystem of northwestern Montana. Using high-resolution mass spectrometry-based methods (GC-MS/MS and LC-MS/MS), 52 PFAS and 186 pesticides were analyzed. PFAS were detected in all bears, with total PFAS concentrations ranging from 79.5 to 317 pg/mL. PFAS profiles were dominated by long-chain perfluoroalkyl carboxylic acids, particularly PFOA, PFDA, and PFUnDA, with minimal contribution from short-chain compounds. Species was the strongest ecological predictor of PFAS concentrations, although variability across age, sex, and capture location were observed. Only two pesticides, piperonyl butoxide and permethrin, were detected at quantifiable concentrations (2070–12,600 pg/mL), and no correlations were observed between pesticide and PFAS concentrations, indicating independent exposure pathways. The predominance of long-chain PFAS suggests diffuse environmental sources and bioaccumulation within terrestrial food webs. Although measured concentrations were generally low relative to other wildlife toxicological studies, the persistence and protein-binding properties of long-chain PFAS warrant continued monitoring, particularly for long-lived omnivores. These results establish baseline contaminant concentrations for two apex omnivores in a remote ecosystem and highlight the utility of large mammals as integrative sentinels of environmental contaminant exposure for regional monitoring and wildlife conservation. Continued monitoring in the Cabinet-Yaak and across western North America will be critical for assessing temporal trends, identifying new contaminant sources, and evaluating ecological health in bear populations.

Montana↗

USGS2006

Environmental contaminant exposure data and monitoring priorities for wild terrestrial vertebrates at national parks in coastal and estuarine habitat

The Biomonitoring of Environmental Status and Trends (BEST) Project of the U.S. Geological Survey (USGS) assesses the exposure and effects of environmental contaminants on select species and habitats in the United States. One of the many BEST Project activities entails the development of decision-support tools to assist in the identification of chemical threats to species and lands under the stewardship of the Department of the Interior. Although there are many ecotoxicological monitoring programs that focus on aquatic species and habitats, there are currently no large-scale efforts that are focused on terrestrial vertebrates in the United States. Nonetheless, organochlorine contaminants, metals, and new pollutants continue to pose hazards to terrestrial vertebrates at many spatial scales (ranging from small hazardous-waste-site point sources to entire watersheds). To evaluate and prioritize pollutant hazards for terrestrial vertebrates, a ?Contaminant Exposure and EffectsTerrestrial Vertebrates? (CEE-TV) database (www.pwrc.usgs.gov/contaminants-online) was developed. The CEE-TV database has been used to conduct simple searches for exposure and biological effects information for a given species or location, identification of temporal contaminant exposure trends, information gap analyses for national wildlife refuge and national park units, and ranking of terrestrial vertebrate ecotoxicological information needs based on data density and water quality problems. Despite widespread concerns about environmental contamination, during the past decade only about one-half of the coastal National Park units appear to have terrestrial vertebrate ecotoxicological data. Based upon known environmental contaminant hazards, it is recommended that regionalized monitoring programs or efforts focused on lands managed by the Department of the Interior should be undertaken to prevent serious natural resource problems.

Book chapter↗

USGS2012

National assessment of shoreline change: Historical shoreline change in the Hawaiian Islands

Sandy beaches of the United States are some of the most popular tourist and recreational destinations. Coastal property constitutes some of the most valuable real estate in the country. Beaches are an ephemeral environment between water and land with unique and fragile natural ecosystems that have evolved in equilibrium with the ever-changing winds, waves, and water levels. Beachfront lands are the site of intense residential and commercial development even though they are highly vulnerable to several natural hazards, including marine inundation, flooding and drainage problems, effects of storms, sea-level rise, and coastal erosion. Because the U.S. population continues to shift toward the coast where valuable coastal property is vulnerable to erosion, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change. One aspect of this effort, the National Assessment of Shoreline Change, uses shoreline position as a proxy for coastal change because shoreline position is one of the most commonly monitored indicators of environmental change (for example, Fletcher, 1992; Dolan and others, 1991; Douglas and others, 1998; Galgano and others, 1998). Additionally, the National Research Council (1990) recommended the use of historical shoreline analysis in the absence of a widely accepted model of shoreline change. A principal purpose of the USGS shoreline change research is to develop a common methodology so that shoreline change analyses for the continental U.S., portions of Hawaii, and Alaska can be updated periodically in a consistent and systematic manner. The primary objectives of this study were to (1) develop and implement improved methods of assessing and monitoring shoreline movement, and (2) improve current understanding of the processes controlling shoreline movement. Achieving these ongoing long-term objectives requires research that (1) examines the original sources of shoreline data (for example, maps, air photos, global positioning system (GPS), Light Detection and Ranging (lidar)); (2) evaluates the utility of different shoreline proxies (for example, geomorphic feature, water mark, tidal datum, elevation), including the errors associated with each; (3) investigates bias and potential errors associated with integrating different shoreline proxies from different sources; (4) develops standard, uniform methods of shoreline change analysis; (5) examines the effects of human activities on shoreline movement and rates of change; and (6) investigates alternative mathematical methods for calculating historical rates of change and uncertainties associated with them. This report summarizes historical shoreline changes on the three most densely populated islands of the eight main Hawaiian Islands: Kauai, Oahu, and Maui. The report emphasizes the hazard from “chronic” (decades to centuries) erosion at regional scales and strives to relate this hazard to the body of knowledge regarding coastal geology of Hawaii because of its potential impact on natural resources, the economy, and society. Results are organized by coastal regions (island side) and sub-regions (common littoral characteristics). This report of Hawaii coasts is part of a series of reports that include text summarizing methods, results, and implications of the results. In addition, geographic information system (GIS) data used in the analyses are made available for download (Romine and others, 2012). The rates of shoreline change and products presented in this report are not intended for site-specific analysis of shoreline movement, nor are they intended to replace any official source of shoreline change information identified by local or State government agencies, or other Federal entities that are used for regulatory purposes. Rates of shoreline change presented herein may differ from other published rates, and differences do not necessarily indicate that the other rates are inaccurate. Some discrepancies are to be expected, considering the many possible ways of determining shoreline positions and rates of change, and the inherent uncertainty in calculating these rates. Rates of shoreline change presented in this report represent shoreline movement under past conditions and are not intended for use in predicting future shoreline positions or future rates of shoreline change.

Hawai'i↗