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At least 703 records · Page 39Linked to original sources
USGS2017

Water-quality and lake-stage data for Wisconsin lakes, water years 2012–2013

Introduction The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The locations of water-quality and lake-stage stations in Wisconsin for water year 2012 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 2011 through September 30, 2012, is called “water year 2012.” The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are included for all lakes. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake’s watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published online at http://nwis.waterdata.usgs.gov/wi/nwis . Water-resources data, including stage and discharge data at most streamflow-gaging stations, are available online. The Wisconsin Water Science Center’s home page is at https://www.usgs.gov/centers/wisconsin-water-science-center . Information on the Wisconsin Water Science Center’s Lakes Program is found at http://wi.water.usgs.gov/lakes/index.html and http://wi.water.usgs.gov/projects/index.html .

Wisconsin↗
USGS2019

Arizona hedgehog cactus (Echinocereus triglochidiatus var. arizonicus)—A systematic data assessment in support of recovery

The Arizona hedgehog cactus ( Echinocereus triglochidiatus var . arizonicus ) is endemic to central Arizona in Gila and Pinal Counties, and has been federally listed as endangered by the U.S. Fish and Wildlife Service (FWS) since 1979. Mining, mineral exploration, and highway development have resulted in habitat degradation and loss of individual plants. Therefore, decreases in the population of the cactus are expected to continue. In response to a request from FWS to compile, evaluate, and synthesize data for the cactus, we identified and evaluated existing survey and monitoring data for the cactus and conducted a demographic analysis with suitable data. Systematic surveys for the Arizona hedgehog cactus did not begin until the late 1970s. Early surveys generally were anecdotal descriptions of cactus populations and precisely georeferenced records of individual cactus occurrence did not occur until global positioning systems were widely used. Much of the georeferenced data have been collected by consultants for mining operations, the Arizona Department of Transportation, the U.S. Forest Service, and independent surveyors. Occurrence records have been compiled by the Arizona Game and Fish Department Heritage Data Management System, but submission of these data may be incomplete, and the attributes reported have varied among the contributing entities. The compilation and management of survey data is essential for field-based evidence of the size, distribution, and range extent of the cactus. In support of consistency in future survey data collection, this report makes several suggestions for future surveys. Monitoring for the Arizona hedgehog cactus, defined as repeat observations of the status of cactus individuals, has been done by consulting companies for three mines. Demographic monitoring further involves marking individual cacti in consistently defined plots and recording the fate of each cacti through time, including birth, growth, reproduction, and death. We were able to use demographic monitoring data provided by two consulting companies to calculate survival and population growth rates, using several statistical approaches. Resulting models indicate that larger cacti, as measured by their number of stems, have greater survival rates. Larger individuals also had higher probability of producing more flowers. Small cacti had the lowest survivorship, with potentially only 15–20 percent reaching large size. Most populations monitored by the two companies were stable to increasing. However, there were differences in the growth rates among plots and some plots had negative population growth rates. The demographic monitoring data we used represented relatively dense populations of undisturbed cacti. Hence, overall positive population growth rates were not influenced by any large-scale disturbances. Previous analyses with cacti and other species suggest that more than 10 years of data are necessary to accurately forecast long-term population trajectories. As the monitoring intervals we evaluated were shorter, they represent short-term dynamics only. Several suggestions are made in the report to improve collection of monitoring data to support evidence-based estimates of demographic characteristics of the Arizona hedgehog cactus.

Arizona↗
USGS2022

Opportunities to improve alignment with the FAIR Principles for U.S. Geological Survey data

In 2016, an interdisciplinary, international group of 53 scientists introduced a framework named “the FAIR Principles” for addressing 21st century scientific data challenges. The FAIR Principles are increasingly used as a guide for producing digital scientific products that are findable, accessible, interoperable, and reusable (FAIR), especially to enable use of such products in automated systems. Data aligned with the FAIR Principles can increase the efficiency of science integration capabilities such as those envisioned for the U.S. Geological Survey (USGS) Earth Monitoring, Analyses, and Projections (EarthMAP) initiative. The FAIR Principles clearly define the characteristics of reusable scientific products, but it is less clear how to facilitate consistency in achieving these characteristics across the Bureau. USGS data are produced by local research projects distributed over more than 100 centers in 7 regions. After data are approved for release, they could be managed in numerous repositories and online data systems. The diversity of USGS data is illustrated by the topical range of the USGS mission areas: Core Science Systems, Ecosystems, Energy and Minerals, Natural Hazards, and Water Resources. In the USGS context, realizing the EarthMAP vision for automated, predictive, integrated science that provides timely and actionable results involves providing knowledge and support services and developing the skills, infrastructure, and culture to enable Bureau-wide implementation of the FAIR Principles. In 2019, the USGS Community for Data Integration funded a project to convene a broadly representative workshop and produce recommendations to enable consistency with the FAIR Principles across the USGS. The workshop, held in Fort Collins, Colorado, in September 2019, brought together 28 participants for 3 days to engage with the FAIR Principles, analyze USGS use cases, and discuss the roles of data producers and managers, data storage and catalogs, value-added services, and policy makers in implementing the FAIR Principles. Workshop participants agreed that scientific reproducibility requires the extension of the FAIR Principles beyond measured data to include physical samples, research methods, software, and tools at the USGS. Workshop discussions focused on how the USGS can implement the FAIR Principles by supporting research teams in creating data, metadata, and other scientific products and also by supporting enterprise systems that maintain and leverage the products’ consistency with the FAIR Principles. The resulting FAIR roadmap of recommendations describes nine proposed interdependent strategies that could be achieved by coordinated actions taken by different parts of the USGS. A proposed early action would be the creation of a coordinating council that includes representatives from the groups engaged in activities consistent with better alignment with the FAIR Principles. The nine proposed strategies, which are presented in more detail in this roadmap report, focus on enabling improvements to individual data products, providing infrastructure, and structuring administrative activities to support an organizational culture that values the FAIR Principles.

Open-File Report↗
USGS2023

Gulf Islands National Seashore regional sediment budget research and data needs—Workshop series summary

Executive Summary The National Park Service (NPS), in collaboration with the U.S. Geological Survey (USGS), recognizes the need to quantify the sediment budget of the barrier islands within the Gulf Islands National Seashore (GINS) to understand the coastal processes affecting island resiliency. To achieve this goal, identifying and quantifying the physical parameters that drive long-term change is necessary to model the processes that are both generative and terminal in island evolution and capture island response to long-term human alteration and climatic patterns. For example, measuring change across periods of storminess is more effective at assessing island resiliency than measuring change resulting from a single storm impact. Understanding changes to the physical environment over time is key to successfully predicting island responses to future storm impacts, human alteration, and sea-level rise and is necessary for effective decision making and management response. Yet, the diversity of factors affecting natural and cultural resources necessitates a strategic approach to data collection priorities that can inform sediment budget quantification and integrated resource management. This study sought to advance sediment budget modeling efforts by conducting a “Needs Assessment Workshop” at the GINS. The purpose of the workshop was to identify and prioritize the specific research and data needs regarding the sediment budget at the GINS that can enhance the NPS efforts to conserve the islands’ natural resources, cultural resources, and the facilities and infrastructure that support both conservation and visitor use of those resources. This effort explored two research questions: (1) “what research and data needs exist for the sediment budget at Gulf Islands National Seashore” (research question 1) and (2) “how can research to address these needs capitalize on regional partnerships to advance natural and cultural resource conservation at Gulf Islands National Seashore” (research question 2)? The workshop was conducted virtually in a two-part, two-day series. The workshop series was organized by researchers from North Carolina State University in collaboration with NPS and USGS staff and was facilitated by National Oceanographic and Atmospheric Administration staff. The workshop series (two paired, sequential, partial-day workshops) addressed two target audiences: (1) NPS and USGS staff (April workshop) and (2) regional Federal, State, county, and nongovernmental organization staff, including NPS and USGS staff (May workshop). A total of four workshop sessions were held, comprising two sessions with each target audience. The workshop series intended to identify sediment management research and data needs that could enhance natural and cultural resource stewardship at the GINS. One objective was to share information about regional sediment transport and management, available sediment management plans, and predictive modeling capabilities, including geomorphologic and hydrodynamic predictive models. This information was shared through a series of presentations by park managers and NPS and USGS researchers that identified park issues and available capabilities and data. The second objective was to elicit research and data needs, with a primary goal of assessing the importance and urgency of the identified needs. This assessment was partly determined by requesting that the workshop participants identify and prioritize research themes through polls, comments, and discussion. The polls explicitly asked participants to qualitatively evaluate the importance (not at all, slightly, somewhat, very, or extremely) and urgency (not at all, slightly, somewhat, very, or extremely) of the thematically grouped research and data needs. These evaluations were plotted and shared during the workshop to visualize how the relative importance ( x -axis) and relative urgency ( y -axis) of each “need,” relative to other needs, to identify the most necessary (importance) and time-sensitive (urgent) items, thereby allowing an enhanced, holistic understanding of the sediment budget at GINS. Results of the poll are published as a USGS data release. The assessment results revealed that the most important and urgent research and data needs included mapping (for example, elevation, habitat, and cultural resources), a regional sediment budget and management plan, and the dynamic modeling of sediment processes. During the workshop, these issues were visualized using scatter plots to demonstrate the relative importance and urgency of each theme, provide descriptive statistics, and elicit discussion. This format of iterative presentation, discussion, and prioritization allowed the project team to effectively accomplish their objective of identifying important and urgent research needs for natural and cultural resource stewardship at the GINS. Through the workshop, it was determined that expanded communication with the broader research community was needed to coordinate research activities and streamline potential funding opportunities and that research and policy should be integrated through a structured decision-making process. At the conclusion of the workshop, an administered poll showed that the presentations effectively identified data and research needs and that the goals of the workshop were achieved. The results suggest that this type of needs-assessment workshop can effectively identify existing research capabilities and data, determine and prioritize research and data needs, and address how these efforts can use regional partnerships to aid natural and cultural resource conservation and management at National Parks.

Florida, Mississippi↗
USGS1970

A proposed streamflow data program for South Carolina

An evaluation of the available streamflow data in South Carolina was made to provide guidelines for planning future surface-water data programs. The basic elements in the evaluation procedure were (1) establishment of objectives and goals of the program, (2) examination and analysis of all available data to determine which goals have already been met, (3) consideration of alternate methods of meeting the remaining goals, and (4) identification of elements that should be included in the future program. Four categories of data form the framework of program design. They are: current-purpose data, planning and design data, data to define long-term trends, and stream environment data. An accuracy goal for planning and design data of an equivalent of 25 years of record was specified for principal streams and an equivalent of 10 years of record was specified for minor streams. It was found that many of the goals could be met by generalizing data for gaged basins by regression analysis. Appropriate changes could be made in the present data program based on this fact. A streamflow data program based on the guidelines developed in this study is proposed for the future.

South Carolina↗
USGS1985

U.S. Geological Survey urban-stormwater data base for 22 metropolitan areas throughout the United States

The U.S. Geological Survey has been collecting urban rainfall, runoff, and water-quality data nationally for several decades. These data have been stored in many data bases and locations. A collective urban-stormwater data base has now been assembled on magnetic tape and contains data from the U.S. Geological Survey 's urban-stormwater program, that includes data from the Nationwide Urban Runoff Program. Stations having simultaneous rainfall, runoff, and water-quality data were selected for the data base. Rigorous quality-assurance procedures were followed to ensure that the data were of good quality. The resultant data base contains information for 723 storms from 99 stations in 22 metropolitan areas throughout the United States. Data for five or more storms are available for about two-thirds of the stations. This data base is available to the public in standardized format on magnetic tape. This publication explains the content and format of the tape. (USGS)

Open-File Report↗
USGS1993

Hydrologic data for Block Island, Rhode Island

This report was compiled as part of a study to assess the hydrogeology and the quality and quantity of fresh ground water on Block Island, Rhode Island. Hydrologic data were collected on Block Island during 1988-91. The data are pre- sented in illustrations and tables. Data collec- ted include precipitation, surfae-water, ground- water, lithologic, and well-construction and dis- charge information. Precipitation data include total monthly precipitation values from 11 rain gages and water-quality analyses of 14 precipi- tation samples from one station. Surface-water data include water-level measurements at 12 ponds, water-quality data for five ponds, and field specific-conductance measurements at 56 surface- water sites (streams, ponds, and springs). Ground- water data include water-level measurements at 159 wells, water-quality data at 150 wells, and field specific-conductance data at 52 wells. Lithologic logs for 375 wells and test borings, and construc- tion and location data for 570 wells, springs, and test borings are included. In addition, the data set contains data on water quality of water samples, collected by the Rhode Island Department of Health during 1976-91, from Fresh and Sands Ponds and from wells at the Block Island Water Company well field north of Sands Pond.

Open-File Report↗
USGS1996

Water-quality and lake-stage data for Wisconsin lakes, water year 1995

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The location of surface water-quality and lake-stage stations in Wisconsin for water year 1995 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends and which includes 9 of the 12 months. Thus the period October 1, 1994 through September 30, 1995, is called "water year 1995." The purpose of this report is to provide information about the physical and chemical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected includes measurements of lake stage and in-lake water quality. Graphs of Secchi depths, and surface total-phosphorus and chlorophyll-a concentrations versus time are included for lakes with two or more years of data. Descriptive information for each lake includes: location of the lake, drainage area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: "Water Resources Data-Wisconsin, 1995."

Wisconsin↗
USGS1997

Water-quality and lake-stage data for Wisconsin lakes, water year 1996

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The location of surface water-quality and lake-stage stations in Wisconsin for water year 1996 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends and which includes 9 of the 12 months. Thus the period October 1, 1995 through September 30, 1996, is called "water year 1996." The purpose of this report is to provide information about the physical and chemical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected includes measurements of lake stage and in-lake water quality. Graphs of Secchi depths, surface totalphosphorus and chlorophyll-a concentrations versus time are included for lakes with two or more years of data. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, drainage area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: "Water Resources Data-Wisconsin, 1996."

Wisconsin↗
USGS1998

Water-quality and lake-stage data for Wisconsin lakes, water year 1997

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The location of water-quality and lake-stage stations in Wisconsin for water year 1997 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 1996 through September 30, 1997 is called 'water year 1997'. The purpose of this report is to provide information about the physical and chemical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of lake stage and in-lake water quality. Graphs of Secchi depths, surface total-phosphorus and chlorophyll-a concentrations versus time are usually included for lakes with two or more years of data. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: 'Water Resources Data-Wisconsin, 1997'.

Wisconsin↗
USGS1999

Water-quality and lake-stage data for Wisconsin lakes, water year 1998

The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The location of water-quality and lake-stage stations in Wisconsin for water year 1998 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 1997 through September 30, 1998 is called "water year 1998." The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are usually included for lakes with two or more years of data. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake's watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: "Water Resources Data- Wisconsin, 1998."

Wisconsin↗
USGS2003

Irrigation-induced contamination of water, sediment, and biota in the western United States-synthesis of data from the National Irrigation Water Quality Program

In October 1985 the U.S. Department of the Interior (DOI), through the National Irrigation Water Quality Program (NIWQP), began a series of field investigations at 26 areas in the Western United States to determine whether irrigation drainage has had harmful effects on fish, wildlife, and humans or has reduced beneficial uses of water. In 1992 NIWQP initiated the Data Synthesis Project to evaluate data collected during the field investigations. Geologic, climatologic, and hydrologic data were evaluated and water, sediment, and biota from the 26 areas were analyzed to identify commonalities and dominant factors that result in irrigation-induced contamination of water and biota. Data collected for the 26 area investigations have been compiled and merged into a common data base. The structure of the data base is designed to enable assessment of relations between contaminant concentrations in water, sediment, and biota. The data base is available to the scientific community through the World Wide Web at URL http://www.usbr.gov/niwqp. Analysis of the data base for the Data Synthesis included use of summary statistics, factor analysis, and logistic regression. A Geographic Information System was used to store and analyze spatially oriented digital data such as land use, geology and evaporation rates. In the U.S. Department of the Interior (DOI) study areas, samples of water, bottom sediment, and biota were collected for trace-element and pesticide analysis. Contaminants most commonly associated with irrigation drainage were identified by comparing concentrations in water with established criteria. For surface water, the criteria used were typically chronic criteria for the protection of freshwater aquatic life. Because ground water can discharge to the surface where wildlife can be exposed to it, the criteria used for ground water were both the maximum contaminant levels (MCL's) for drinking water and the chronic criteria for the protection of freshwater aquatic life. Data collected by the NIWQP studies indicated that, in surface water, filtered and unfiltered samples had nearly the same concentrations of arsenic, boron, molybdenum, and selenium for concentrations greater than about 10 micrograms per liter. Therefore, in this concentration range, filtered concentrations can be directly compared to biological-effect levels developed for unfiltered samples. In the range of 1 to 10 micrograms per liter there may be a tendency for unfiltered arsenic concentrations to be greater than filtered concentrations. For selenium, however, the data suggest differences from equality in that range result from analytical imprecision and not a general tendency for unfiltered concentrations to be greater than filtered concentrations. This relation may not be true in lentic, nutrient-rich waters because in such settings algae can bioaccumulate large amounts of selenium and other trace elements. Selenium was the trace element in surface water that most commonly exceeded chronic criteria for the protection of freshwater aquatic life; more than 40 percent of the selenium concentrations in surface-water samples exceeded the U.S. Environmental Protection Agency (USEPA) aquatic-life chronic criterion (5 micrograms per liter). In 12 of the 26 areas at least 25 percent of the surface water-samples had selenium concentrations that either equaled or exceeded the chronic criterion (5 micrograms per liter). More than 28 percent of boron concentrations and almost 17 percent of the molybdenum concentrations exceeded the aquatic life criteria established by the State of California (550 and 19 micrograms per liter, respectively). In ground water, more than 22 percent of the arsenic concentrations and more than 35 percent of the selenium concentrations exceeded the MCL (10 and 50 micrograms per liter, respectively). Few samples of uranium in surface water exceeded a criterion for the protection of aquatic life (300 micrograms per liter), but 44 percent

Professional Paper↗
USGS2015

Reducing cross-sectional data using a genetic algorithm method and effects on cross-section geometry and steady-flow profiles

Reduction of cross-sectional data using a genetic algorithm method, and the effects of data reduction on channel geometry and steady-flow profiles, were analyzed. Two reduction methods─standard and genetic algorithms─were used to reduce cross-sectional data from the Kootenai River in northern Idaho. Cross sections that are representative of meander, straight, braided, and canyon reaches were used to evalutate the reduction methods. Visual and hydraulic analyses were used to assess the methods. The genetic algorithm-reduced cross sections approximated the shape of the original cross sections better than the standard-reduced cross sections. A greater number of cross-sectional data points were needed for reduced cross sections in the straight reach, and even more in the braided reach, because a greater amount of data points are needed to adequately define cross sections that have greater topographic varability. For the genetic algorithm-reduction method, about 40 data points were needed to adequately define the shape of a reduced cross section in the braided reach compared to 10 to 20 data points in the meander and canyon reaches. The standard-reduction method needed about 70 data points for the braided reach and more than 30 points for the meander and canyon reaches. The genetic algorithm can effectively reduce data while staying within the threshold set by the maximum number of points to be included in the reduced dataset. The effects of reduced cross-sectional data points on steady-flow profiles were also determined. Thirty-five cross sections of the original steady-flow model of the Kootenai River were used. These two methods were tested for all cross sections with each cross section resolution reduced to 10, 20 and 30 data points, that is, six tests were completed for each of the thirty-five cross sections. Generally, differences from the original water-surface elevation were smaller as the number of data points in reduced cross sections increased, but this was not always the case, especially in the braided reach. Differences were smaller for reduced cross sections developed by the genetic algorithm method than the standard algorithm method.

Scientific Investigations Report↗
USGS2017

The U.S. Geological Survey Peak-Flow File Data Verification Project, 2008–16

Annual peak streamflow (peak flow) at a streamgage is defined as the maximum instantaneous flow in a water year. A water year begins on October 1 and continues through September 30 of the following year; for example, water year 2015 extends from October 1, 2014, through September 30, 2015. The accuracy, characterization, and completeness of the peak streamflow data are critical in determining flood-frequency estimates that are used daily to design water and transportation infrastructure, delineate flood-plain boundaries, and regulate development and utilization of lands throughout the United States and are essential to understanding the implications of climate and land-use change on flooding and high-flow conditions. As of November 14, 2016, peak-flow data existed for 27,240 unique streamgages in the United States and its territories. The data, collectively referred to as the “peak-flow file,” are available as part of the U.S. Geological Survey (USGS) public web interface, the National Water Information System, at https://nwis.waterdata.usgs.gov/usa/nwis/peak . Although the data have been routinely subjected to periodic review by the USGS Office of Surface Water and screening at the USGS Water Science Center level, these data were not reviewed in a national, systematic manner until 2008 when automated scripts were developed and applied to detect potential errors in peak-flow values and their associated dates, gage heights, and peak-flow qualification codes, as well as qualification codes associated with the gage heights. USGS scientists and hydrographers studied the resulting output, accessed basic records and field notes, and corrected observed errors or, more commonly, confirmed existing data as correct. This report summarizes the changes in peak-flow file data at a national level, illustrates their nature and causation, and identifies the streamgages affected by these changes. Specifically, the peak-flow data were compared for streamgages with peak flow measured as of November 19, 2008 (before the automated scripts were widely applied) and on November 14, 2016 (after several rounds of corrections). There were 659,332 peak-flow values in the 2008 dataset and 731,965 peak-flow values in the 2016 dataset. When compared to the 2016 dataset, 5,179 (0.79 percent) peak-flow values had changed; 36,506 (5.54 percent) of the peak-flow qualification codes had changed; 1,938 (0.29 percent) peak-flow dates had changed; 18,599 (2.82 percent) of the peak-flow gage heights had changed; and 20,683 (3.14 percent) of the gage-height qualification codes had changed—most as a direct result of the peak-flow file data verification effort led by USGS personnel. The various types of changes are summarized and mapped in this report. In addition to this report, a corresponding USGS data release is provided to identify changes in peak flows at individual streamgages. The data release and the procedures to access the data release are described in this report.

Scientific Investigations Report↗
USGS2020

Interpretation of hydrogeologic data to support groundwater management, Bazile Groundwater Management Area, northeast Nebraska, 2019—A case demonstration of the Nebraska Geocloud

Nitrate, age tracer, and continuous groundwater-level data were interpreted in conjunction with airborne electromagnetic (AEM) survey data to understand the movement of nitrate within the Bazile Groundwater Management Area (BGMA) in northeastern Nebraska. Previously published age tracer data and nitrate data indicated vertical stratification of groundwater quality. Younger groundwater sampled within shallow parts of the aquifer had higher concentrations of nitrate, with 70 percent exceeding the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter. In contrast, groundwater sampled from deeper parts of the aquifer indicated that nitrate concentrations were less than 2 milligrams per liter and that groundwater likely recharged prior to widespread use of commercial fertilizer. The hydrostratigraphic interpretation of AEM profiles indicated that shallow and deep monitoring wells were often screened within the same homogenous zone of aquifer material. In contrast, test-hole logs indicated that there often are fine-grained layers within these homogenous zones that separate the shallow and deep monitoring well screens, but these fine-grained layers are not detected by the AEM technique because of decreased resolution of the AEM technique with depth. The stratification of groundwater ages and nitrate concentrations likely was caused by groundwater-flow paths of different length, location and time of recharge, and denitrification. Within paleochannels interpreted from AEM and test-hole data, pesticides detected in groundwater generally coincide with elevated nitrate concentrations. Continuous groundwater-level data from four monitoring well nests indicated that groundwater pumping can impose or increase downward hydraulic gradients and facilitate the downward movement of nitrate into deeper parts of the High Plains aquifer. Given the density of irrigation wells within the BGMA, this effect on the hydraulic gradient is likely prevalent in other areas of the BGMA. Understanding seasonal water-level changes can allow water managers to better predict and assess the hydraulic gradient and the vulnerability of groundwater in deeper parts of the High Plains aquifer. Nitrate, age tracer, and continuous groundwater-level data within the BGMA were interpreted in conjunction with AEM data as a case demonstration of the Nebraska Geocloud. The Nebraska Geocloud was initiated to protect taxpayer investments in AEM data collection and realize maximum benefit of these data by creating a publicly available, online digital database for long-term data storage. The Lower Platte North, Lower Platte South, Papio-Missouri River, Nemaha, Lower Loup, Central Platte, Upper Elkhorn, Lower Elkhorn, Lower Niobrara, and Lewis and Clark Natural Resources Districts; the University of Nebraska-Lincoln Conservation and Survey Division, Nebraska Natural Resources Commission, Nebraska Department of Natural Resources; and the U.S. Geological Survey entered a cooperative agreement to begin a program of data management and research aimed at understanding the best use of AEM for groundwater sustainability and management. Resulting case-study interpretations are provided to guide use of the Nebraska Geocloud to assess water-quality conditions and can be used by water managers and staff to address applicable water resource problems.

Nebraska↗
USGS2015

Design, analysis, and interpretation of field quality-control data for water-sampling projects

The process of obtaining and analyzing water samples from the environment includes a number of steps that can affect the reported result. The equipment used to collect and filter samples, the bottles used for specific subsamples, any added preservatives, sample storage in the field, and shipment to the laboratory have the potential to affect how accurately samples represent the environment from which they were collected. During the early 1990s, the U.S. Geological Survey implemented policies to include the routine collection of quality-control samples in order to evaluate these effects and to ensure that water-quality data were adequately representing environmental conditions. Since that time, the U.S. Geological Survey Office of Water Quality has provided training in how to design effective field quality-control sampling programs and how to evaluate the resultant quality-control data. This report documents that training material and provides a reference for methods used to analyze quality-control data. Quality-control data are those generated from the collection and analysis of quality-control samples, and are used to estimate the magnitude of errors in the process of obtaining environmental data. “Bias” and “variability” are the terms used in this report for the two types of errors in environmental data that are quantified by the data from quality-control samples. Bias is the systematic error inherent in a method or measurement system. Variability is the random error that occurs in independent measurements. The types of field quality-control samples discussed in this report include blanks, spikes, and replicates. Blanks are samples prepared with water that is intended to be free of measurable constituents that will be analyzed by the laboratory; blanks are used to estimate bias caused by contamination. Spiked samples are modified by addition of specific analytes; spikes are used to determine the performance of analytical methods and to estimate the potential bias due to matrix interference or analyte degradation. Replicate samples are two or more samples that are considered to be essentially identical in composition. Replicates are used to evaluate variability in analytical results. Various sub-types of these quality-control samples are defined and discussed in this report, and guidance is provided for incorporating the proper samples into the design for a project. The concept of inference space is introduced to help determine where and when quality-control samples should be collected as well as which environmental samples are related to a set of quality-control samples. The recommended basic quality-control design incorporates project-specific considerations, such as the objectives and scale of the study, and hydrologic and chemical conditions within the study area. The report provides extensive information about statistical methods used to analyze quality-control data in order to estimate potential bias and variability in environmental data. These methods include construction of confidence intervals on various statistical measures, such as the mean, percentiles and percentages, and standard deviation. The methods are used to compare quality-control results with the larger set of environmental data in order to determine whether the effects of bias and variability might interfere with interpretation of these data. Examples from published reports are presented to illustrate how the methods are applied, how bias and variability are reported, and how the interpretation of environmental data can be qualified based on the quality-control analysis.

Techniques and Methods↗
USGS2004

Summary of available state ambient stream-water-quality data, 1990-98, and limitations for national assessment

The investigation described in this report summarized data from State ambient stream-water-quality monitoring sites for 10 water-quality constituents or measurements (suspended solids, fecal coliform bacteria, ammonia as nitrogen, nitrite plus nitrate as nitrogen, total phosphorus, total arsenic, dissolved solids, chloride, sulfate, and pH). These 10 water-quality constituents or measurements commonly are listed nationally as major contributors to degradation of surface water. Water-quality data were limited to that electronically accessible from the U.S. Environmental Protection Agency Storage and Retrieval System (STORET), the U.S. Geological Survey National Water Information System (NWIS), or individual State databases. Forty-two States had ambient stream-water-quality data electronically accessible for some or all of the constituents or measurements summarized during this investigation. Ambient in this report refers to data collected for the purpose of evaluating stream ecosystems in relation to human health, environmental and ecological conditions, and designated uses. Generally, data were from monitoring sites assessed for State 305(b) reports. Comparisons of monitoring data among States are problematic for several reasons, including differences in the basic spatial design of monitoring networks; water-quality constituents for which samples are analyzed; water-quality criteria to which constituent concentrations are compared; quantity and comprehensiveness of water-quality data; sample collection, processing, and handling; analytical methods; temporal variability in sample collection; and quality-assurance practices. Large differences among the States in number of monitoring sites precluded a general assumption that statewide water-quality conditions were represented by data from these sites. Furthermore, data from individual monitoring sites may not represent water-quality conditions at the sites because sampling conditions and protocols are unknown. Because of these factors, a high level of uncertainty exists in a national assessment of water quality. The purpose of this report is to present a summary of electronically available State ambient stream-water-quality data for 10 selected constituents and measurements from monitoring sites with nine or more analyses for 199098 and to discuss limitations for use of the data for national assessment. These analyses were statistiscally summarized by monitoring site and State, and the results presented in tabular format. Most of the selected constituents or measurements have U.S. Environmental Protection Agency criteria or guidelines for aquatic-life or drinking-water purposes. A significant finding of this investigation is that for a large percentage of monitoring sites in the Nation, there are insufficient data to meet U.S. Environmental Protection Agency recommendations for determining if water-quality conditions are degraded and for making informed decisions regarding total maximum daily loads.

Water-Resources Investigations Report↗
USGS1986

Sediment-data sources and estimated annual suspended-sediment loads of rivers and streams in Colorado

Sources of sediment data collected by several government agencies through water year 1984 are summarized for Colorado. The U.S. Geological Survey has collected suspended-sediment data at 243 sites; these data are stored in the U.S. Geological Survey 's water data storage and retrieval system. The U.S. Forest Service has collected suspended-sediment and bedload data at an additional 225 sites, and most of these data are stored in the U.S. Environmental Protection Agency 's water-quality-control information system. Additional unpublished sediment data are in the possession of the collecting entities. Annual suspended-sediment loads were computed for 133 U.S. Geological Survey sediment-data-collection sites using the daily mean water-discharge/sediment-transport-curve method. Sediment-transport curves were derived for each site by one of three techniques: (1) Least-squares linear regression of all pairs of suspended-sediment and corresponding water-discharge data, (2) least-squares linear regression of data sets subdivided on the basis of hydrograph season; and (3) graphical fit to a logarithm-logarithm plot of data. The curve-fitting technique used for each site depended on site-specific characteristics. Sediment-data sources and estimates of annual loads of suspended, bed, and total sediment from several other reports also are summarized. (USGS)

Colorado↗