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USGS2026

Sampling and analysis plan for the water-quality monitoring program in Lake Koocanusa and upper Kootenai River, Montana, water years 2022–23

The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, collected water-quality samples and environmental data in Lake Koocanusa (also known as “Koocanusa Reservoir”), the Kootenai River, and the Tobacco River during water years 2022–23. The transboundary Lake Koocanusa is in southeastern British Columbia, Canada, and northwestern Montana, United States. It was formed by constructing Libby Dam on the Kootenai River 26 kilometers upstream from Libby, Montana. One of the lake sites and the Kootenai River site, in the Libby Dam tailwater (the outflow of the lake flow into the Kootenai River), were equipped with automated, high-frequency ServoSipper water samplers. At the lake site, these samplers were mounted to pontoon platforms during the summer, and a submersible ServoSipper sipper was deployed with ice buoys during the winter. Samples were automatically collected from multiple depths. At the Kootenai River site, these samplers were housed in the gage house. In water year 2022, discrete water-quality samples were collected every 4–6 weeks, year round, at all four lake sites in the Kootenai River between April and November. In water year 2023, discrete water-quality samples were collected at three lake sites and the Kootenai and Tobacco River sites every 4–6 weeks. The goal of this project was to collect multidepth, high-frequency vertical and temporal water-quality samples and data to understand the limnological and biological processes that control variations and trends in selenium concentrations and loads throughout Lake Koocanusa and in the Libby Dam tailwater at the southern end of the lake. This sampling and analysis plan documents the organization, sampling and data-collection scheme and design, pre- and post-collection processes, and quality-assurance and quality-control procedures of the Koocanusa/Kootenai water-quality monitoring program during water years 2022–23.

Montana↗
USGS2013

Distribution of late Pleistocene ice-rich syngenetic permafrost of the Yedoma Suite in east and central Siberia, Russia

This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.

Siberia↗
USGS2002

Intensity distribution and isoseismal maps for the Nisqually, Washington, earthquake of 28 February 2001

We present isoseismal maps, macroseismic intensities, and community summaries of damage for the MW=6.8 Nisqually, Washington, earthquake of 28 February, 2001. For many communities, two types of macroseismic intensity are assigned, the traditional U.S. Geological Survey Modified Mercalli Intensities (USGS MMI) and a type of intensity newly introduced with this paper, the USGS Reviewed Community Internet Intensity (RCII). For most communities, the RCII is a reviewed version of the Community Internet Intensity (CII) of Wald and others (1999). For some communities, RCII is assigned from such non-CII sources as press reports, engineering reports, and field reconnaissance observations. We summarize differences between procedures used to assign RCII and USGS MMI, and we show that the two types of intensity are nonetheless very similar for the Nisqually earthquake. We do not see evidence for systematic differences between RCII and USGS MMI that would approach one intensity unit, at any level of shaking, but we document a tendency for the RCII to be slightly lower than MMI in regions of low intensity and slightly higher than MMI in regions of high intensity. The highest RCII calculated for the Nisqually earthquake is 7.6, calculated for zip code 98134, which includes the ?south of downtown? (Sodo) area of Seattle and Harbor Island. By comparison, we assigned a traditional USGS MMI 8 to the Sodo area of Seattle. In all, RCII of 6.5 and higher were assigned to 58 zip-code regions. At the lowest intensities, the Nisqually earthquake was felt over an area of approximately 350,000 square km (approximately 135,000 square miles) in Washington, Oregon, Idaho, Montana, and southern British Columbia, Canada. On the basis of macroseismic effects, we infer that shaking in the southern Puget Sound region was somewhat less for the 2001 Nisqually earthquake than for the Puget Sound earthquake of April 13, 1949, which had nearly the same hypocenter and magnitude. Allowing for differences in hypocenter, shaking in the 2001 earthquake was very similar to that produced by the Puget Sound earthquake of April 25, 1965. First-person accounts of the effects of the 2001 earthquake on individual households are given for some communities.

Open-File Report↗
USGS2013

2010 Joint United States-Canadian Program to explore the limits of the Extended Continental Shelf aboard U.S. Coast Guard Cutter Healy--Cruise HLY1002

In August and September 2010, the U.S. Geological Survey, in cooperation with Natural Resources Canada, Geological Survey of Canada, conducted bathymetric and geophysical surveys in the Beaufort Sea and eastern Arctic Ocean aboard the U.S. Coast Guard Cutter Healy. The principal objective of this mission to the high Arctic was to acquire data in support of a delineation of the outer limits of the U.S. and Canadian Extended Continental Shelf in the Arctic Ocean, in accordance with the provisions of Article 76 of the United Nations Convention on the Law of the Sea. The Healy was accompanied by the Canadian Coast Guard icebreaker Louis S. St-Laurent. The scientific parties on board the two vessels consisted principally of staff from the U.S. Geological Survey (Healy), and the Geological Survey of Canada and the Canadian Hydrographic Service (Louis). The crew also included marine-mammal observers, Native-community observers, ice observers, and biologists conducting research of opportunity in the Arctic Ocean. Despite interruptions necessitated by three medical emergencies, the joint survey proved largely successful. The Healy collected 7,201 trackline-kilometers of swath (multibeam) bathymetry (47,663 square kilometers) and CHIRP subbottom data, with accompanying marine gravity measurements, and expendable bathythermograph data. The Louis acquired 3,673 trackline-kilometers of multichannel seismic (airgun) deep-penetration reflection data along 25 continuous profiles, as well as 34 sonobuoy refraction stations and 9,500 trackline-kilometers of single-beam bathymetry. The coordinated efforts of the two vessels resulted in seismic-reflection-profile data that were of much higher quality and continuity than if the data had been acquired with a single vessel alone. The equipment-failure rate of the seismic equipment aboard the Louis was greatly reduced when the Healy led as the ice breaker. When ice conditions proved too severe to deploy the seismic system, the Louis led the Healy, resulting in much improved quality of the swath bathymetric and CHIRP subbottom data in comparison with data collected either by the Healy in the lead or the Healy working alone. During periods when the Healy was operating alone (principally when the Louis was diverted for emergency medical evacuations or ship repairs), the Healy was able to deploy a piston-core-sampler (10 meters maximum potential recovery depending on configuration). The coring operations resulted in recovery of cores at five locations ranging from 2.4 to 5.7 meters in length from water depths ranging from 1,157 to 3,700 meters. One of these cores sited on the Alaskan margin recovered the first reported occurrence of methane hydrate from the Arctic Ocean. Ancillary science objectives, including ice observations and deployment of ice-monitoring buoys and water-column sampling to measure acidification of Arctic waters were successfully conducted. The water-column sampling included using 10 full-ocean-depth, water-sampling casts with accompanying conductivity-temperature-depth measurements. Except for the data deemed proprietary, data from the cruise have been archived and are available for download at the National Geophysical Data Center and at cooperating organizations. Outreach staff and guest teachers aboard the two vessels provided near-real-time connection between the research activities and the public through online blogs, web pages, and other media.

Open-File Report↗
USGS2013

The U.S. Geological Survey Bird Banding Laboratory: an integrated scientific program supporting research and conservation of North American birds

The U.S. Geological Survey (USGS) Bird Banding Laboratory (BBL) was established in 1920 after ratification of the Migratory Bird Treaty Act with the United Kingdom in 1918. During World War II, the BBL was moved from Washington, D.C., to what is now the USGS Patuxent Wildlife Research Center (PWRC). The BBL issues permits and bands to permittees to band birds, records bird band recoveries or encounters primarily through telephone and Internet reporting, and manages more than 72 million banding records and more than 4.5 million records of encounters using state-of-the-art technologies. Moreover, the BBL also issues bands and manages banding and encounter data for the Canadian Bird Banding Office (BBO). Each year approximately 1 million bands are shipped from the BBL to banders in the United States and Canada, and nearly 100,000 encounter reports are entered into the BBL systems. Banding data are essential for regulatory programs, especially migratory waterfowl harvest regulations. The USGS BBL works closely with the U.S. Fish and Wildlife Service (USFWS) to develop regulations for the capture, handling, banding, and marking of birds. These regulations are published in the Code of Federal Regulations (CFR). In 2006, the BBL and the USFWS Division of Migratory Bird Management (DMBM) began a comprehensive revision of the banding regulations. The bird banding community has three major constituencies: Federal and State agency personnel involved in the management and conservation of bird populations that include the Flyway Councils, ornithological research scientists, and avocational banders. With increased demand for banding activities and relatively constant funding, a Federal Advisory Committee (Committee) was chartered and reviewed the BBL program in 2005. The final report of the Committee included six major goals and 58 specific recommendations, 47 of which have been addressed by the BBL. Specifically, the Committee recommended the BBL continue to support science, conservation, and management of birds through the use of banding and banding data and that the BBL be managed by the USGS and located at the USGS Patuxent Wildlife Research Center (PWRC) in Laurel, Maryland. Recommendations that have not been implemented include those already addressed by other organizations, as well as lower priority, such as developing a BBL business plan. The comprehensive review and recommendations of the Committee, the response of the BBL to address the Committee’s recommendations, and other improvements to its operations have positioned the BBL to provide a high level of service to the banding community. As new technologies are developed and incorporated into BBL operations, further efficiencies are expected to enable the BBL to continue to meet emerging scientific needs.

Open-File Report↗
USGS2008

Assessment of Appalachian Basin Oil and Gas Resources: Utica-Lower Paleozoic Total Petroleum System

The Utica-Lower Paleozoic Total Petroleum System (TPS) is an important TPS identified in the 2002 U.S. Geological Survey (USGS) assessment of undiscovered, technically recoverable oil and gas resources in the Appalachian basin province (Milici and others, 2003). The TPS is named for the Upper Ordovician Utica Shale, which is the primary source rock, and for multiple lower Paleozoic sandstone and carbonate units that are the important reservoirs. Upper Cambrian through Upper Silurian petroleum-bearing strata that constitute the Utica-Lower Paleozoic TPS thicken eastward from about 2,700 ft at the western margin of the Appalachian basin to about 12,000 ft at the thrust-faulted eastern margin of the Appalachian basin. The Utica-Lower Paleozoic TPS covers approximately 170,000 mi2 of the Appalachian basin from northeastern Tennessee to southeastern New York and from central Ohio to eastern West Virginia. The boundary of the TPS is defined by the following geologic features: (1) the northern boundary (from central Ontario to northeastern New York) extends along the outcrop limit of the Utica Shale-Trenton Limestone; (2) the northeastern boundary (from southeastern New York, through southeastern Pennsylvania-western Maryland-easternmost West Virginia, to northern Virginia) extends along the eastern limit of the Utica Shale-Trenton Limestone in the thrust-faulted eastern margin of the Appalachian basin; (3) the southeastern boundary (from west-central and southwestern Virginia to eastern Tennessee) extends along the eastern limit of the Trenton Limestone in the thrust-faulted eastern margin of the Appalachian basin; (4) the southwestern boundary (from eastern Tennessee, through eastern Kentucky, to southwestern Ohio) extends along the approximate facies change from the Trenton Limestone with thin black shale interbeds (on the east) to the equivalent Lexington Limestone without black shale interbeds (on the west); (5) the northern part of the boundary in southwestern Ohio to the Indiana border extends along an arbitrary boundary between the Utica Shale of the Appalachian basin and the Utica Shale of the Sebree trough (Kolata and others, 2001); and (6) the northwestern boundary (from east-central Indiana, through northwesternmost Ohio and southeasternmost Michigan, to central Ontario) extends along the approximate southeastern boundary of the Michigan Basin. Although the Utica-Lower Paleozoic TPS extends into northwestern Ohio, southeastern Michigan, and northeastern Indiana, these areas have been assigned to the Michigan Basin (Swezey and others, 2005) and are outside the scope of this report. Furthermore, although the northern part of the Utica-Lower Paleozoic TPS extends across the Great Lakes (Lake Erie and Lake Ontario) into southern Ontario, Canada, only the undiscovered oil and gas resources in the U.S. waters of the Great Lakes have been included in the USGS assessment of the Utica-Lower Paleozoic TPS. This TPS is similar to the Point Pleasant-Brassfield petroleum system previously identified by Drozd and Cole (1994) in the Ohio part of the Appalachian basin.

Open-File Report↗
USGS2006

Petroleum system modeling capabilities for use in oil and gas resource assessments

Summary: Petroleum resource assessments are among the most highly visible and frequently cited scientific products of the U.S. Geological Survey. The assessments integrate diverse and extensive information on the geologic, geochemical, and petroleum production histories of provinces and regions of the United States and the World. Petroleum systems modeling incorporates these geoscience data in ways that strengthen the assessment process and results are presented visually and numerically. The purpose of this report is to outline the requirements, advantages, and limitations of one-dimensional (1-D), two-dimensional (2-D), and three-dimensional (3-D) petroleum systems modeling that can be applied to the assessment of oil and gas resources. Primary focus is on the application of the Integrated Exploration Systems (IES) PetroMod? software because of familiarity with that program as well as the emphasis by the USGS Energy Program on standardizing to one modeling application. The Western Canada Sedimentary Basin (WCSB) is used to demonstrate the use of the PetroMod? software. Petroleum systems modeling quantitatively extends the 'total petroleum systems' (TPS) concept (Magoon and Dow, 1994; Magoon and Schmoker, 2000) that is employed in USGS resource assessments. Modeling allows integration of state-of-the-art analysis techniques, and provides the means to test and refine understanding of oil and gas generation, migration, and accumulation. Results of modeling are presented visually, numerically, and statistically, which enhances interpretation of the processes that affect TPSs through time. Modeling also provides a framework for the input and processing of many kinds of data essential in resource assessment, including (1) petroleum system elements such as reservoir, seal, and source rock intervals; (2) timing of depositional, hiatus, and erosional events and their influences on petroleum systems; (3) incorporation of vertical and lateral distribution and lithologies of strata that compose the petroleum systems; and (4) calculations of pressure-volume-temperature (PVT) histories. As digital data on petroleum systems continue to expand, the models can integrate these data into USGS resource assessments by building and displaying, through time, areas of petroleum generation, migration pathways, accumulations, and relative contributions of source rocks to the hydrocarbon components. IES PetroMod? 1-D, 2-D, and 3-D models are integrated such that each uses the same variables for petroleum systems modeling. 1-D burial history models are point locations, mainly wells. Maps and cross-sections model geologic information in two dimensions and can incorporate direct input of 2-D seismic data and interpretations using various formats. Both 1-D and 2-D models use data essential for assessments and, following data compilation, they can be completed in hours and retested in minutes. Such models should be built early in the geologic assessment process, inasmuch as they incorporate the petroleum system elements of reservoir, source, and seal rock intervals with associated lithologies and depositional and erosional ages. The models can be used to delineate the petroleum systems. A number of 1-D and 2-D models can be constructed across a geologic province and used by the assessment geologists as a 3-D framework of processes that control petroleum generation, migration, and accumulation. The primary limitation of these models is that they only represent generation, migration, and accumulation in two dimensions. 3-D models are generally built at reservoir to basin scales. They provide a much more detailed and realistic representation of petroleum systems than 1-D or 2-D models because they portray more fully the temporal and physical relations among (1) burial history; (2) lithologies and associated changes through burial in porosity, permeability, and compaction; (3) hydrodynamic effects; and (4) other parameters that influence petroleum gen

Open-File Report↗
USGS2005

Quality-assurance data for routine water analyses by the U.S. Geological Survey Laboratory in Troy, New York—July 1995 through June 1997

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) office in Troy, N.Y. analyzes samples collected by USGS projects in the Northeast. The laboratory’s quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures developed to ensure proper sample collection, processing, and analysis. For the time period addressed in this report, the quality-assurance/quality-control data were stored in the laboratory’s SAS data-management system, which provides efficient review, compilation, and plotting of quality-assurance/quality-control data. This report presents and discusses samples analyzed from July 1995 through June 1997. Quality-control results for 19 analytical procedures were evaluated for bias and precision. Control charts show that data from ten of the analytical procedures were biased throughout the analysis period for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, ammonium, calcium, chloride, dissolved organic carbon, magnesium, nitrate (ion chromatography), nitrate (colorimetric method), and sulfate. Four of the analytical procedures were occasionally biased but were within control limits; they were: fluoride, pH, silicon, and sodium. Results from the filter-blank and analytical-blank analyses indicate that all analytical procedures in which blanks were run were within control limits, although values for a few blanks were outside the control limits. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in 14 of the 19 procedures. Data-quality objectives (DQO’s) were met by at least 92 percent of the samples analyzed in all procedures except acid neutralizing capacity (80 percent of samples met objectives), total monomeric aluminum (87 percent of samples met objectives), organic monomeric aluminum (89 percent of samples met objectives), and chloride (89 percent of samples met objectives). The data are insufficient to evaluate the DQO’s for total aluminum. Results of the USGS interlaboratory Standard Reference Sample Program indicated acceptable data quality for most constituents over the time period. The results of the P-sample (low-ionic strength constituent) analysis indicated high data quality with good ratings in all studies. The T-sample (trace constituent) had unacceptable ratings in two studies, but received satisfactory ratings in the others. The N-sample (nutrient constituent) studies had an unacceptable rating in one and an excellent rating in the other. Environment Canada’s NWRI program results indicated that at least 90 percent of the samples met data-quality objectives in 9 of the 12 analyses; exceptions were calcium, chloride, and silicon. Data-quality objectives were not met for calcium samples in two NWRI studies, but all of the samples analyzed were within control limits for the remaining studies. Data-quality objectives were not met for 32 percent of samples analyzed for chloride and 27 percent of samples analyzed for silicon. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 90 percent of the calcium, pH, potassium, and sodium samples. Data-quality objectives were met by 77 percent of the chloride samples, 83 percent of the magnesium samples, and 80 percent of the sulfate samples. There is insufficient data to evaluate the specific conductance samples.

Open-File Report↗
USGS2004

Migration stopover ecology of western avian populations: A southwestern migration workshop

The importance of migration stopover sites in ensuring that migratory birds successfully accomplish their journeys between breeding and non-breeding ranges has come to the forefront of avian research. Migratory birds that breed in western United States (US) and Canada and overwinter primarily in western Mexico migrate across the arid region of northern Mexico and southwestern US. Many of these migrants use lowland riparian stopover habitats, which comprise less than 0.1% of the western U.S. landscape. These habitats represent a significant conservation priority. Recognizing the importance of migration stopover habitats in the arid southwest, the U.S. Fish and Wildlife Service (USFWS) Region 6 partnered with the U.S. Geological Survey (USGS) to support a project---“Migration stopover ecology of western avian populations: patterns of geographic and habitat distribution.” A primary objective of the project was to convene a workshop for avian researchers, conservation professionals, and land managers involved in stopover needs of migratory birds that breed in western North America. The workshop included presentations on our current state of knowledge regarding passerine migration in western North America, techniques and technologies potentially useful in researching migration, and efforts that agencies and other partners are conducting within the realm of migration. Workshop presentations provided a backdrop for subsequent discussions, the goals of which were to identify research needs and initiate a coordinated approach to research of western migration stopover ecology. Workshop presentations spanned a wide range of concerns and interests. Highlights included indications that mid- and high-elevation riparian and montane shrubland habitats may be as crucial to western migrants in fall migration as lowland riparian habitats are in spring migration. Comparisons of eastern versus western migration systems elucidated large differences in stopover habitats used and the intensity with which certain types are used, underscoring the potential need to develop separate management approaches for eastern and western stopover sites. Presentations on techniques and technology for migration research revealed that rate of lipid deposition can serve as an indicator of habitat quality; that genetics and stable isotope analyses of feathers can be valuable tools to elucidate linkages between breeding and wintering areas; that radar imagery can be used to track large-scale movement patterns and habitat use; and that there are analytical options for combining multiple sources of information. Other presentations focused on partnership perspectives (USFWS and Sonoran Joint Venture), the genesis of a western migration monitoring network, premises of Coordinated Bird Monitoring, and how collaborative efforts could benefit migration research (e.g., combined bird and bat migration studies; linking avian researchers with fluvial geomorphologists; linking research throughout western North America; linking surveys and banding). Priority research needs and questions identified during the open discussions fell into three main categories: (1) habitat/landscape/climate relationships, (2) en route bird distribution patterns, and (3) general migration ecology. Tasks within these categories included: define the relative importance of various habitat types to migrants in spring and fall, determine what distinguishes high- from poor-quality stopover habitat; determine geographic patterns of loss in stopover habitats; model landscape attributes associated with species richness and abundance; identify effects of climate change and current climate anomalies on plant phonologies, associated insect flushes, and timing of migration; and determine effects of hydrologic changes on riparian vegetation, food availability, and stopover habitat quality. Workshop participants discussed a coordinated approach for addressing immediate research needs regarding migration patterns and crucial stopover sites and types. They envisioned a three­-tiered, coordinated approach: (1) long-term research to address effects of climate change and other large-scale patterns, (2) intensive, short-term survey and monitoring efforts using a stratified random design within habitats of interest to elucidate regional patterns of distribution and habitat use, and (3) research conducted at existing survey and banding sites to address more in-depth questions (e.g., rates of lipid deposition, microhabitat use, isotope analyses). There was considerable interest in developing common research proposals to blend the broad expertise represented at this workshop. A second meeting is recommended to build on the momentum of these discussions, to facilitate collaborations, and further the goals of integrated approaches to broadscale research on migration stopover ecology.

Open-File Report↗
USGS2020

Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada

Modeling of ecosystems is a part of the U.S. Environmental Protection Agency’s protocol for developing site-specific selenium guidelines for protection of aquatic life. Selenium as an environmental contaminant is known to bioaccumulate and cause reproductive effects in fish and wildlife. Here we apply a modeling methodology—ecosystem-scale selenium modeling—to understand and document the scientific basis for predicting and validating ecological protection for Lake Koocanusa, a transboundary reservoir between Montana and British Columbia. A comprehensive set of site-specific data compiled from public databases (Federal, State, and Provincial) and reports by Teck Coal Ltd., is available in a companion U.S. Geological Survey data release. The tissue guideline used within modeling here to assess protection is the U.S. Environmental Protection Agency’s national selenium guideline for whole-body fish (dry weight); however, other numeric values for a whole-body guideline or other tissue types may be assumed if applicable tissue-to-tissue conversion factors are available. We consider the report assembled here as a working document that presents a model that can effectively address and structure the needs of (1) scientific understanding in representing the lake’s ecosystem and selenium biodynamics and (2) policy and management development during a decision-making process, but it is open to modification and updating as more ecologically detailed data become available. The approach brings together the main concerns involved in selenium toxicity: likelihood of high exposure, inherent species sensitivity, and close connectivity of ecosystem characteristics and behavioral ecology of predators. Detailed site-specific modeling equations are provided to document the linked factors that determine the responses of ecosystems to selenium. A series of scenarios quantifies the implications of choices of site-specific variables including food-web species, bioavailability of particulate material, and partitioning between the dissolved and particulate phases at the base of food webs. A gradient mapping tool applied to Lake Koocanusa provides a precedent for ecosystem-scale modeling of lakes by recognizing the importance of lake strata and hydrodynamics as components of modeling. Data requirements for ecosystem modeling, including ecological and hydrological process information fundamental to the dietary biodynamics of selenium in site-specific food webs, were assessed as a precursor to model validation for Lake Koocanusa. Understanding these relationships is necessary to connect modeling outcomes to reproductive effects and establish boundaries, in the case of Lake Koocanusa, for the influences of dam operation, fish-community viability, and its Clean Water Act impaired 303(d)-listing status on ecosystem function. We find that an assemblage of conditions affects the representation of Lake Koocanusa’s ecosystem within modeling scenarios but that the constructed gradient maps, mechanistic model, and associated bioaccumulation potentials portray and quantify the variables that are determinative to protection of predator species. Ecological and hydrological sorting of compiled individual data points on a site- and species-specific basis helps identify and address model uncertainties. Sources of uncertainty include (1) the scarcity of data for some environmental media compartments across time and locations, (2) the complexity of hydrodynamic conditions that can lead to seasonal ecological disconnects such as in selenium partitioning from water into particulates, and (3) the functional status of Lake Koocanusa’s ecosystem because of cumulative effects of various environmental stresses (for example, fish-community changes, flow regime changes, parasites, gonadal dysfunction, and increasing mining input-selenium concentrations since 1984). To this last point, it is important to determine where Lake Koocanusa is in an impairment-restoration cycle so as not to base protection on survivor bias, the maintenance of a currently degraded ecosystem, or normalized toxicity. In a broader context, one of the overall consequences of revised selenium regulations is that their derivation is now dependent on being able to define and understand the status of the ecosystem on which protection is based.

Montana, British Columbia↗
USGS2006

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York-July 1997 through June 1999

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance/quality-control data for the time period addressed in this report were stored in the laboratory's SAS data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality- control samples analyzed from July 1997 through June 1999. Results for the quality-control samples for 18 analytical procedures were evaluated for bias and precision. Control charts indicate that data for eight of the analytical procedures were occasionally biased for either high-concentration and (or) low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, total aluminum, ammonium, calcium, chloride, specific conductance, and sulfate. The data from the potassium and sodium analytical procedures are insufficient for evaluation. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 11 of 13 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. Blank analysis results for chloride showed that 22 percent of blanks did not meet data-quality objectives and results for dissolved organic carbon showed that 31 percent of the blanks did not meet data-quality objectives. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 14 of the 18 analytes. At least 90 percent of the samples met data-quality objectives for all analytes except total aluminum (70 percent of samples met objectives) and potassium (83 percent of samples met objectives). Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality for most constituents over the time period. The P-sample (low-ionic-strength constituents) analysis had good ratings in two of these studies and a satisfactory rating in the third. The results of the T-sample (trace constituents) analysis indicated high data quality with good ratings in all three studies. The N-sample (nutrient constituents) studies had one each of excellent, good, and satisfactory ratings. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 80 percent of the samples met data-quality objectives for 9 of the 13 analytes; the exceptions were dissolved organic carbon, ammonium, chloride, and specific conductance. Data-quality objectives were not met for dissolved organic carbon in two NWRI studies, but all of the samples were within control limits for the last study. Data-quality objectives were not met in 41 percent of samples analyzed for ammonium, 25 percent of samples analyzed for chloride, and 30 percent of samples analyzed for specific conductance. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 84 percent of the samples analyzed for calcium, chloride, magnesium, pH, and potassium. Data-quality objectives were met by 73 percent of those analyzed for sulfate. The data-quality objective was not met for sodium. The data are insufficient for evaluation of the specific conductance results.

Open-File Report↗
USGS2006

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York--July 1999 through June 2001

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's LabMaster data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality-control samples analyzed from July 1999 through June 2001. Results for the quality-control samples for 18 analytical procedures were evaluated for bias and precision. Control charts indicate that data for eight of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, total aluminum, calcium, chloride and nitrate (ion chromatography and colormetric method) and sulfate. The total aluminum and dissolved organic carbon procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits. The calcium and specific conductance procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The magnesium procedure was biased for the high-concentration and low concentration samples, but was within control limits. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 14 of 15 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for dissolved organic carbon. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 17 of the 18 analytes. At least 90 percent of the samples met data-quality objectives for all analytes except ammonium (81 percent of samples met objectives), chloride (75 percent of samples met objectives), and sodium (86 percent of samples met objectives). Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality over the time period, with most ratings for each sample in the good to excellent range. The P-sample (low-ionic-strength constituents) analysis had one satisfactory rating for the specific conductance procedure in one study. The T-sample (trace constituents) analysis had one satisfactory rating for the aluminum procedure in one study and one unsatisfactory rating for the sodium procedure in another. The remainder of the samples had good or excellent ratings for each study. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 89 percent of the samples met data-quality objectives for 10 of the 14 analytes; the exceptions were ammonium, total aluminum, dissolved organic carbon, and sodium. Results indicate a positive bias for the ammonium procedure in all studies. Data-quality objectives were not met in 50 percent of samples analyzed for total aluminum, 38 percent of samples analyzed for dissolved organic carbon, and 27 percent of samples analyzed for sodium. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 91 percent of the samples analyzed for calcium, chloride, fluoride, magnesium, pH, potassium, and sulfate. Data-quality objectives were met by 75 percent of the samples analyzed for sodium and 58 percent of the samples analyzed for specific conductance.

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USGS2009

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2005 through June 2007

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2005 through June 2007. Results for the quality-control samples for 19 analytical procedures were evaluated for bias and precision. Control charts indicate that data for eight of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: total aluminum, calcium, magnesium, nitrate (colorimetric method), potassium, silicon, sodium, and sulfate. Eight of the analytical procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits; these procedures were: total aluminum, calcium, dissolved organic carbon, chloride, nitrate (ion chromatograph), potassium, silicon, and sulfate. The magnesium and pH procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The acid-neutralizing capacity, total monomeric aluminum, nitrite, and specific conductance procedures were biased for the high-concentration and low-concentration samples, but were within control limits. Results from the filter-blank and analytical-blank analyses indicated that the procedures for 16 of 17 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for dissolved organic carbon. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 21 analytes. At least 93 percent of the samples met data-quality objectives for all analytes except acid-neutralizing capacity (85 percent of samples met objectives), total monomeric aluminum (83 percent of samples met objectives), total aluminum (85 percent of samples met objectives), and chloride (85 percent of samples met objectives). The ammonium and total dissolved nitrogen did not meet the data-quality objectives. Results of the USGS interlaboratory Standard Reference Sample (SRS) Project met the Troy Laboratory data-quality objectives for 87 percent of the samples analyzed. The P-sample (low-ionic-strength constituents) analysis had two outliers each in two studies. The T-sample (trace constituents) analysis and the N-sample (nutrient constituents) analysis had one outlier each in two studies. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 85 percent of the samples met data-quality objectives for 11 of the 14 analytes; the exceptions were acid-neutralizing capacity, total aluminum and ammonium. Data-quality objectives were not met in 41 percent of samples analyzed for acid-neutralizing capacity, 50 percent of samples analyzed for total aluminum, and 44 percent of samples analyzed for ammonium. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 86 percent of the samples analyzed for calcium, magnesium, pH, potassium, and sodium. Data-quality objectives were met by 76 percent of the samples analyzed for chloride, 80 percent of the samples analyzed for specific conductance, and 77 percent of the samples analyzed for sulfate.

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USGS2001

Quality-assurance data for routine water quality analyses by the U. S. Geological Survey laboratory in Troy, New York; July 1993 through June 1995

A laboratory for analysis of low-ionic strength water has been developed at the U.S. Geological Survey (USGS) office in Troy, N.Y., to analyze samples collected by USGS projects in the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures developed to ensure proper sample collection, processing, and analysis. The quality-assurance/quality-control data are stored in the laboratory's SAS data-management system, which provides efficient review, compilation, and plotting of quality-assurance/quality-control data. This report presents and discusses samples analyzed from July 1993 through June 1995. Quality-control results for 18 analytical procedures were evaluated for bias and precision. Control charts show that data from seven of the analytical procedures were biased throughout the analysis period for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, dissolved inorganic carbon, dissolved organic carbon (soil expulsions), chloride, magnesium, nitrate (colorimetric method), and pH. Three of the analytical procedures were occasionally biased but were within control limits; they were: calcium (high for high-concentration samples for May 1995), dissolved organic carbon (high for highconcentration samples from January through September 1994), and fluoride (high in samples for April and June 1994). No quality-control sample has been developed for the organic monomeric aluminum procedure. Results from the filter-blank and analytical-blank analyses indicate that all analytical procedures in which blanks were run were within control limits, although values for a few blanks were outside the control limits. Blanks were not analyzed for acid-neutralizing capacity, dissolved inorganic carbon, fluoride, nitrate (colorimetric method), or pH. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in 14 of the 18 procedures. Data-quality objectives were met by more than 90 percent of the samples analyzed in all procedures except total monomeric aluminum (85 percent of samples met objectives), total aluminum (70 percent of samples met objectives), and dissolved organic carbon (85 percent of samples met objectives). Triplicate samples were not analyzed for ammonium, fluoride, dissolved inorganic carbon, or nitrate (colorimetric method). Results of the USGS interlaboratory Standard Reference Sample Program indicated high data quality with a median result of 3.6 of a possible 4.0. Environment Canada's LRTAP interlaboratory study results indicated that more than 85 percent of the samples met data-quality objectives in 6 of the 12 analyses; exceptions were calcium, dissolved organic carbon, chloride, pH, potassium, and sodium. Data-quality objectives were not met for calcium samples in one LRTAP study, but 94 percent of samples analyzed were within control limits for the remaining studies. Data-quality objectives were not met by 35 percent of samples analyzed for dissolved organic carbon, but 94 percent of sample values were within 20 percent of the most probable value. Data-quality objectives were not met for 30 percent of samples analyzed for chloride, but 90 percent of sample values were within 20 percent of the most probable value. Measurements of samples with a pH above 6.0 were biased high in 54 percent of the samples, although 85 percent of the samples met data-quality objectives for pH measurements below 6.0. Data-quality objectives for potassium and sodium were not met in one study (only 33 percent of the samples analyzed met the objectives), although 85 percent of the sample values were within control limits for the other studies. Measured sodium values were above the upper control limit in all studies. Results from blind reference-sample analyses indicated that data

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USGS2009

Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2001 through June 2003. Results for the quality-control samples for 19 analytical procedures were evaluated for bias and precision. Control charts indicate that data for six of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, chloride, magnesium, nitrate (ion chromatography), potassium, and sodium. The calcium procedure was biased throughout the analysis period for the high-concentration sample, but was within control limits. The total monomeric aluminum and fluoride procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum, pH, specific conductance, and sulfate procedures were biased for the high-concentration and low-concentration samples, but were within control limits. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 16 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for the dissolved organic carbon or specific conductance procedures. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 21 analytes. At least 90 percent of the samples met data-quality objectives for all procedures except total monomeric aluminum (83 percent of samples met objectives), total aluminum (76 percent of samples met objectives), ammonium (73 percent of samples met objectives), dissolved organic carbon (86 percent of samples met objectives), and nitrate (81 percent of samples met objectives). The data-quality objective was not met for the nitrite procedure. Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated satisfactory or above data quality over the time period, with most performance ratings for each sample in the good-to-excellent range. The N-sample (nutrient constituents) analysis had one unsatisfactory rating for the ammonium procedure in one study. The T-sample (trace constituents) analysis had one unsatisfactory rating for the magnesium procedure and one marginal rating for the potassium procedure in one study and one unsatisfactory rating for the sodium procedure in another. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 90 percent of the samples met data-quality objectives for 10 of the 14 analytes; the exceptions were acid-neutralizing capacity, ammonium, dissolved organic carbon, and sodium. Data-quality objectives were not met in 37 percent of samples analyzed for acid-neutralizing capacity, 28 percent of samples analyzed for dissolved organic carbon, and 30 percent of samples analyzed for sodium. Results indicate a positive bias for the ammonium procedure in one study and a negative bias in another. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 90 percent of the samples analyzed for calcium, chloride, magnesium, pH, potassium, and sodium. Data-quality objectives were met by 78 percent of

Open-File Report↗
USGS2009

Quality-assurance data for routine water analyses by the U.S. Geological Survey laboratory in Troy, New York - July 2003 through June 2005

The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2003 through June 2005. Results for the quality-control samples for 20 analytical procedures were evaluated for bias and precision. Control charts indicate that data for five of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, pH, silicon, and sodium. Seven of the analytical procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits; these procedures were: dissolved organic carbon, chloride, nitrate (ion chromatograph), nitrite, silicon, sodium, and sulfate. The calcium and magnesium procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum and specific conductance procedures were biased for the high-concentration and low-concentration samples, but were within control limits. Results from the filter-blank and analytical-blank analyses indicate that the procedures for 17 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for dissolved organic carbon. Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 22 analytes. At least 85 percent of the samples met data-quality objectives for all analytes except total monomeric aluminum (82 percent of samples met objectives), total aluminum (77 percent of samples met objectives), chloride (80 percent of samples met objectives), fluoride (76 percent of samples met objectives), and nitrate (ion chromatograph) (79 percent of samples met objectives). The ammonium and total dissolved nitrogen did not meet the data-quality objectives. Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality over the time period, with ratings for each sample in the satisfactory, good, and excellent ranges or less than 10 percent error. The P-sample (low-ionic-strength constituents) analysis had one marginal and two unsatisfactory ratings for the chloride procedure. The T-sample (trace constituents)analysis had two unsatisfactory ratings and one high range percent error for the aluminum procedure. The N-sample (nutrient constituents) analysis had one marginal rating for the nitrate procedure. Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 84 percent of the samples met data-quality objectives for 11 of the 14 analytes; the exceptions were ammonium, total aluminum, and acid-neutralizing capacity. The ammonium procedure did not meet data quality objectives in all studies. Data-quality objectives were not met in 23 percent of samples analyzed for total aluminum and 45 percent of samples analyzed acid-neutralizing capacity. Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 86 percent of the samples analyzed for calcium, chloride, fluoride, magnesium, pH, potassium, sodium, and sulfate. Data-quality objectives were not met by samples analyzed for fluoride.

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