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At least 901 records · Page 50Linked to original sources

USGS2015

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies. Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11). To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R 2 ) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Florida↗

USGS2017

Evaluation and use of U.S. Environmental Protection Agency Clean Watersheds Needs Survey data to quantify nutrient loads to surface water, 1978–2012

Changes in municipal and industrial point-source discharges over time have been an important factor affecting nutrient trends in many of the Nation’s streams and rivers. This report documents how three U.S. Environmental Protection Agency (EPA) national datasets—the Permit Compliance System, the Integrated Compliance Information System, and the Clean Watersheds Needs Survey—were evaluated for use in the U.S. Geological Survey National Water-Quality Assessment project to assess the causes of nutrient trends. This report also describes how a database of total nitrogen load and total phosphorous load was generated for select wastewater treatment facilities in the United States based on information reported in the EPA Clean Watersheds Needs Survey. Nutrient loads were calculated for the years 1978, 1980, 1982, 1984, 1986, 1988, 1990, 1992, 1996, 2000, 2004, 2008, and 2012 based on average nitrogen and phosphorous concentrations for reported treatment levels and on annual reported flow values. The EPA Permit Compliance System (PCS) and Integrated Compliance Information System (ICIS), which monitor point-source facility discharges, together are the Nation’s most spatially comprehensive dataset for nutrients released to surface waters. However, datasets for many individual facilities are incomplete, the PCS/ICIS historical data date back only to 1989, and historical data are available for only a limited number of facilities. Additionally, inconsistencies in facility reporting make it difficult to track or identify changes in nutrient discharges over time. Previous efforts made by the U.S. Geological Survey to “fill in” gaps in the PCS/ICIS data were based on statistical methods—missing data were filled in through the use of a statistical model based on the Standard Industrial Classification code, size, and flow class of the facility and on seasonal nutrient discharges of similar facilities. This approach was used to estimate point-source loads for a single point in time; it was not evaluated for use in generating a consistent data series over time. Another national EPA dataset that is available is the Clean Watersheds Needs Survey (CWNS), conducted every 4 years beginning 1973. The CWNS is an assessment of the capital needs of wastewater facilities to meet the water-quality goals set in the Clean Water Act. Data collected about these facilities include location and contact information for the facilities; population served; flow and treatment level of the facility; estimated capital needs to upgrade, repair, or improve facilities for water quality; and nonpoint-source best management practices. Total nitrogen and total phosphorous load calculations for each of the CWNS years were based on treatment level information and average annual outflow (in million gallons per day) from each of the facilities that had reported it. Treatment levels categories (such as Primary, Secondary, or Advanced) were substituted with average total nitrogen and total phosphorous concentrations for each treatment level based on those reported in literature. The CWNS dataset, like the PCS/ICIS dataset, has years where facilities did not report either a treatment level or an annual average outflow, or both. To fill in the data gaps, simple linear assumptions were made based on each facility’s responses to the survey in years bracketing the data gap or immediately before or after the data gap if open ended. Treatment level and flow data unique to each facility were used to complete the CWNS dataset for that facility.

Scientific Investigations Report↗

USGS2019

User’s manual for the Draper climate-distribution software suite with data‑evaluation tools

Development of a time series of spatially distributed climate data is an important step in the process of developing physically based environmental models requiring distributed inputs of climate data beyond what is available from observations collected at climate stations. To prepare inputs required for model-mapping units across the study area, climate data (temperature and precipitation) are distributed by combining data from gridded surfaces of mean-monthly climate-data values with (often) widely spaced daily point observations. Examples of climate-data files used to develop PRMS-formatted input files for the Merced River Basin Precipitation-Runoff Modeling System (PRMS) are included in this manual. The Draper Climate-Distribution Software Suite (Draper Suite) consists of the Draper climate-distribution program (Draper) and several supporting pre- and post-processing applications. Draper combines spatially distributed input in the form of monthly averaged values for precipitation, maximum temperature, and minimum temperature with daily observed data from climate stations to estimate distributed climate-data values at predefined locations across a study area (typically a drainage basin) on a daily time step. Alternative methods are used when station data are limited or missing for a particular day. Draper uses a set of required and optional input and output files with defined formats and naming conventions. A shell application also is available to manage multiple runs of the Draper application. Other applications in the Draper Suite include (1) a tool to find and interactively remove outliers in the input data, (2) a tool to check and enforce a minimum daily temperature range, and (3) a tool to view output diagnostic information as time-series graphs. These tools can be used iteratively to evaluate and improve the results from Draper as part of a workflow involving physically based environmental models, such as the Precipitation-Runoff Modeling System (PRMS).

Techniques and Methods↗

USGS2004

Water-quality characteristics and trends for selected sites in or near the Earth Resources Observation Systems (EROS) Data Center, South Dakota, 1973-2000

This report presents data on water-quality samples that were collected in and near the Earth Resources Observation Systems (EROS) Data Center from 1973 through 2000. The investigation is a collaborated effort between the U.S. Geological Survey, Water Resources Discipline (WRD), and Geography (formerly National Mapping) Discipline, EROS Data Center. A water-quality monitoring program was initiated in 1973, when the EROS Data Center was constructed, and continues at the present time (2003). Under this program, water-quality samples were collected at various sites on the EROS Data Center's property and in the surrounding area. These sites include 4 wastewater-treatment lagoons, 1 site on EROS Lake located behind the EROS Data Center, 2 stream sites near the EROS Data Center, and 9 ground-water wells surrounding the EROS Data Center. Additionally, 3 sites on EROS Lake, 7 stream sites, and 9 ground-water sites are located within the study area and have been sampled during the period covered in the report. Some of these additional sites were part of the initial water-quality monitoring conducted during and immediately after the construction of the EROS Data Center. For other sites, some special sampling (depth-profile and bottom material) has occurred at times during the sampling history; however, these sites have little water-quality data and were not used for statistical or trend analysis. A trend-analysis program, Estimate TREND (ESTREND), was used to analyze for trends for one surface-water site, the Big Sioux River, which was the only site that had a substantial number of samples collected during an extensive period. The ESTREND trend-analysis program was used to analyze 16 constituents. Specific conductance and dissolved orthophosphate were the only constituents determined to have statistically significant trends. Results showed an increasing trend for specific conductance and a decreasing trend for dissolved orthophosphate. Scatter plots with regression smoothing lines for selected constituents are presented for selected surface-water and ground-water sites. Regression analyses using a Lowess (Locally Weighted Scatterplot Smoothing) smoothing line for Split Rock Creek, EROS Lake, the lagoon sites, and the ground-water sites indicated variable results, with some constituents indicating an increasing or decreasing trend, some having varied results, and others indicating no change during the sampling period.

South Dakota↗

USGS1984

Water-data program of the US Geological Survey in Kansas, fiscal year 1983

The U.S. Geological Survey is the principal Federal agency responsible for the collection of hydrologic data needed for the planning, development, use, and management of the water resources in Kansas. Hydrologic-data collection by the U.S. Geological Survey in Kansas began in 1895. The fiscal-year 1983 water-data program, operated in cooperation with several Federal , State, and local agencies, included 270 stations for collection of river, lake, and reservoir data, 1,940 wells for collection of ground-water data; 53 sampling stations and 215 wells for collection of water-quality data. This report provides a detailed description of the water-data program, including coordination and funding, data-collection activities, quality-assurance plans, availability of data, network design, and future needs for water data. (USGS)

Water-Resources Investigations Report↗

USGS1986

Development of a water-use data system in Minnesota

The Minnesota State Legislature passed laws as early as 1937 to regulate use of Minnesota's ground water and surface water through a permit system. Several unsuccessful attempts were made to computerize water-use data reported to the State. The U.S. Geological Survey, through the National Water-Use Information Program, assisted the Minnesota Department of Natural Resources and the Minnesota State Planning Agency, Land Management Information Center, in developing MWUDS (Minnesota Water-Use Data System). The Minnesota Water-Use Data System stores data on the quantity of individual annual water withdrawals and discharges in relation to the water resources affected, provides descriptors for aggregation of data and trend analysis, and enables access to additional data contained in other data bases. MWUDS is stored on a computer at the Land Management Information Center, an agency associated with the State Planning Agency. Interactive menu-driven programs simplify data entry, update, and retrieval and are easy to use. Estimates of unreported water use supplement reported water use to completely describe the stress on the hydrologic system. Links or common elements developed in the MWUDS enable access to data available in other State waterrelated data bases, forming a water-resource information system. Water-use information can be improved by developing methods for increasing accuracy of reported water use and refining methods for estimating unreported water use.

Water-Resources Investigations Report↗

USGS1991

The computer program estimate trend (ESTREND), a system for the detection of trends in water-quality data

Computerized statistical and graphical procedures were developed for use in U.S. Geological Survey (USGS) investigations of trend in stream water-quality data. These procedures, identified as EStimate TREND (ESTREND), are described in this paper to assist USGS investigators involved in multiple-station studies of water-quality trends. Additional discussion focuses on certain statistical and operational decisions required in multiple-station analysis of trends. The statistical methods used in ESTREND overcome common statistical problems encountered by conventional statistical trend techniques in the analysis of water-quality data. The problems include data that are non-normal and seasonally varying and water-quality records with missing values, 'less-than' (censored) values, and outliers, all of which adversely affect the performance of conventional statistical techniques. Parametric and nonparametric statistical trend tests are used in ESTREND. A nonparametric method, the Seasonal Kendall test, is used for data that have few less-than values or data that have been censored at only one reporting limit. A parametric test for trend involving a maximum likelihood estimation method is used for data that have been censored at multiple reporting limits. The Seasonal Kendall test for uncensored data allows for the removal of flow variability in water-quality data which improves the performance of the statistical trend tests. Menu-driven procedures in ESTREND allow the user to easily retrieve water-quality data, analyze data for trend, and view tabular and graphical results of analyses.

Water-Resources Investigations Report↗

USGS1997

Ground-water sampling methods and quality-control data for the Red River of the North basin, Minnesota, North Dakota, and South Dakota, 1993-95

Ground-water-quality samples were collected for the intensive data-collection phase of the Red River of the P Torth Basin study unit, one of 60 study units of the National Water Quality Assessment (NAWQA) Program throughout the United States. The sampling protocols used were designed for the NAWQA Program. The protocols include sampling equipment, cleaning procedures, sample-collection methods, and quality-control plans to monitor the accuracy of the data collected. One of the goals of the NAWQA Program was to collect data using similar methcds to build a nationally consistent water-quality data base. Quality-control data demonstrated that most constituents measured for this study yielded reproducible data, with low to undetectable contamination from the sampling and analytical procedures. Several constituents were occasionally or frequently detected in blank samples at levels similar to low-concentration ground-water-quality samples. For example, iron was detected in 75 percent of the blank samples, with a maximum concentration of 27 [ig/L, indicating that iron contamination may interfere with its determination at low levels in ground waters. Copper, aluminum, and dissolved organic carbon concentrations in blank samples overlap those determined in ground-waterquality samples, thereby precluding quantitative reporting of those constituents. Most pesticide data are reproducible, with minimal bias. Some pesticides had low but consistent recoveries; these data may be useful if spike and surrogate data are carefully considered. Data for some pesticides measured in this study should not be quantitatively reported or used, because they may underestimate the concentrations of those pesticides in ground waters.

Minnesota, North Dakota, South Dakota↗

USGS1997

Water-quality assessment of the Potomac River Basin: Analysis of available pesticide data, 1972-1990

A study of available data for the period from 1972 to 1990 was conducted to characterize the occurrence and distribution of pesticides in sur-face water, bottom material, ground water, and fish tissue in the Potomac River Basin. The study was conducted by the Potomac River study unit of the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) program. Exist-ing data coverage was evaluated to guide future data-collection activities. Data from computer data bases and from published and unpublished reports were obtained from local, State, and Fed-eral agencies in the four Potomac River Basin states and the District of Columbia. Data are available for all environmental media, but geo-graphic and temporal coverage are limited. Clusters of data occur in the north-central parts of the basin, with numerous samples at discrete loca-tions in the Shenandoah and Monocacy River Basins, along the mainstem Potomac River, in the Washington, D.C., area, and in streams along the Potomac Estuary. Much of the available surface-water and bottom-material data are from the ear-lier years of the period of interest, the ground-water data are from the middle years, and the fish-tissue data are distributed over much of the period. Overall, temporal coverage is not sufficient for analysis of trends. Comparisons between different sample media are possible in some areas of the Potomac River Basin, particularly in the northern end of the Great Valley. Residual concentrations of some pesticides have been found in surface water, bottom mate-rial, ground water, and fish tissue. Samples have been analyzed for a total of at least 69 pesticides and related compounds in surface water, bottom material, ground water, and fish tissue. Most con-centrations of the pesticides analyzed during the period from 1972 to 1990 were less than or equal to reporting limits. For surface-water samples, 13 out of 41 pes-ticides and related compounds analyzed had concentrations equal to or greater than the report-ing limits. Compounds reported in surface water included 2,4-D, atrazine, aldrin, chlordane, DDT and related compounds, dieldrin, endrin, lindane, prometone, prometryne, and simazine. For bottom material samples, 19 of 31 pesticides and related compounds analyzed had concentrations equal to or greater than the reporting limits. Compounds reported in bottom material included aldrin, chlor-dane, DDT and related compounds, diazinon, dieldrin, endosulfan, endrin, ethion, heptachlor, heptachlor epoxide, lindane, parathion, and tox-aphene. In ground-water samples, 14 of 39 pesticides and related compounds analyzed had concentrations equal to or greater than the report-ing limits. Compounds reported in ground water included 2,4-D, atrazine, chlordane, cyanazine, DDT and related compounds, diazinon, dieldrin, endosulfan, endrin, heptachlor epoxide, malathion, methyl parathion, simazine. For fish- tissue sam-ples, 30 of the 37 pesticides and related compounds analyzed had concentrations equal to or greater than the reporting limits. Compounds reported included aldrin, chlorpyrifos, dacthal, dieldrin, endrin, HCB, heptachlor, heptachlor epoxide, methoxychlor, mirex, PCA, toxaphene, and those compounds related to chlordane, DDT, and lindane.

Maryland, Pennsylvania, Virginia, West Virginia↗

USGS1999

Fraser River watershed, Colorado — Assessment of available water-quantity and water-quality data through water year 1997

The water-quantity and water-quality data for the Fraser River watershed through water year 1997 were compiled for ground-water and surface-water sites. In order to assess the water-quality data, the data were related to land use/land cover in the watershed. Data from 81 water-quantity and water-quality sites, which consisted of 9 ground-water sites and 72 surface-water sites, were available for analysis. However, the data were limited and frequently contained only one or two water-quality analyses per site. The Fraser River flows about 28 miles from its headwaters at the Continental Divide to the confluence with the Colorado River. Ground-water resources in the watershed are used for residential and municipal drinking-water supplies. Surface water is available for use, but water diversions in the upper parts of the watershed reduce the flow in the river. Land use/land cover in the watershed is predominantly forested land, but increasing urban development has the potential to affect the quantity and quality of the water resources. Analysis of the limited ground-water data in the watershed indicates that changes in the land use/land cover affect the shallow ground-water quality. Water-quality data from eight shallow monitoring wells in the alluvial aquifer show that iron and manganese concentrations exceeded the U.S. Environmental Protection Agency secondary maximum contaminant level. Radon concentrations from these monitoring wells exceeded the U.S. Environmental Protection Agency proposed maximum contaminant level. The proposed radon contaminant level is currently being revised. The presence of volatile organic compounds at two monitoring wells in the watershed indicates that land use affects the shallow ground water. In addition, bacteria detected in three samples are at concentrations that would be a concern for public health if the water was to be used as a drinking supply. Methylene blue active substances were detected in the ground water at some sites and are a possible indication of contamination from wastewater. Age of the alluvial ground water ranged from 10 to 30 years; therefore, results of land-management practices to improve water quality may not be apparent for many years. Surface-water-quality data for the Fraser River watershed are sparse. The surface-water-quality data show that elevated concentrations of selected constituents generally are related to specific land uses in the watershed. For one sample (about 2 percent; 1 of 53), dissolved manganese concentration exceeded the U.S. Environmental Protection Agency secondary maximum contaminant level. Two samples from two surface-water sites in the watershed exceeded the un-ionized ammonia chronic criterion. Spatial distribution of nutrient species (ammonia, nitrite, nitrate, and total phosphorus) shows that elevated concentrations occur primarily downstream from urban areas. Sites with five or more years of record were analyzed for temporal trends in concentration of nutrient species. Downward trends were identified for ammonia and nitrite for three surface-water sites. For nitrate, no trends were observed at two sites and a downward trend was observed at one site. Total phosphorus showed no trend for the site near the mouth of the Fraser River. Downward trends in the nutrient species may reflect changes in the wastewater-treatment facilities in the watershed. Bacteria sampling completed in the watershed indicates that more bacteria are present in the water near urban settings. The limited ground-water and surface-water data for the Fraser River watershed provide a general assessment of the quantity and quality of these resources. Concentrations of most water-quality constituents generally are less than ground- and surface-water-quality standards, but the presence of bacteria, some volatile organic compounds, methylene blue active substances, and increased nutrients in the water may indicate that land use is affecting the water quality.

Colorado↗

USGS1989

Evapotranspiration estimates using remote-sensing data, Parker and Palo Verde valleys, Arizona and California

In 1981 the U.S. Geological Survey established an experimental project to assess the possible and practical use of remote-sensing data to estimate evapotranspiration as an approximation of consumptive use of water in the lower Colorado River flood plain. The project area was in Parker Valley, Arizona. The approach selected was to measure the areas covered by each type of vegetation, using remote-sensing data in various types of analyses, and to multiply each area by a predetermined water-use rate. Two calibration and six remote-sensing methods of classifying crop types were compared for cost, accuracy, consistency, and labor requirements. Included were one method each for field reconnaissance using 1982 data, low-altitude (less than 5,000 feet) aerial photography using 1982 data, and visual photointerpretation of Landsat satellite images using 1981 and 1982 data; two methods for medium-altitude (15,000-18,000 feet) aerial photography using 1982 data; and three methods for digital Landsat satellite images using 1981 data. A test of the most promising digital-processing method, which used three image dates, was made in part of Palo Verde Valley, California, where 1981 crop data were more complete than in Parker Valley. Of the eight methods studied, the two-date digital-processing method was the most consistent and least labor intensive for identifying two or three major crops; visual photointerpretation of Landsat images was the least expensive. Evapotranspiration estimates from crop classifications by all methods differed by a maximum of 6 percent. Total evapotranspiration calculated from crop data and phreatophyte maps in 1981 ranged from 11 percent lower in Palo Verde Valley to 17 percent lower in Parker Valley than consumptive use calculated by water budgets. The difference was greater in Parker Valley because the winter crop data were not included.

Water Supply Paper↗

USGS2022

Landsat data ecosystem case study: Actor perceptions of the use and value of landsat

It is well-known that Earth observation (EO) data plays a critical role in scientific understanding about the global environment. There is also growing support for the use of EO data to provide context-specific insights, with significant implications for their use in decision support systems. Technological development over recent years, including cloud computing infrastructure, machine learning techniques, and rapid expansion of the velocity, volume, and variety of space-borne data sources, offer huge potential to provide solutions to the myriad environmental problems facing society and the planet. The USGS/NASA Landsat Program, the longest continuously gathered source of land surface data, has played a central role in our understanding of environmental change, particularly for its contribution of longitudinal products that offer greater context for present research and decision support activities. The challenge facing the Landsat and EO data community, however, now lies in moving beyond context-specific knowledge generation to translating such knowledge into tangible value for society. Drawing from an open data ecosystem framework and qualitative social science methods, we map the Landsat data ecosystem (LDE) and the relationships linking multiple actors responsible for processing, indexing, analyzing, synthesizing, and translating raw Landsat data into information that is useful, useable, and used by end users in particular social-environmental contexts. Both the role of Big Data and associated technologies are discussed as they relate to the ultimate use of Landsat-derived information products to guide decision-making, and key data ecosystem characteristics that shape the likelihood of these products’ use are highlighted.

Frontiers in Environmental Science↗

USGS2011

OBIS-USA: a data-sharing legacy of the census of marine life

The United States Geological Survey's Biological Informatics Program hosts OBIS-USA, the US node of the Ocean Biogeographic Information System (OBIS). OBIS-USA gathers, coordinates, applies standard formats to, and makeswidely available data on biological collections in marine waters of the United States and other areas where US investigators have collected data and, in some instances, specimens. OBIS-USA delivers its data to OBIS international, which then delivers its data to the Global Biodiversity Information Facility (GBIF) and other Web portals for marine biodiversity data. OBIS-USA currently has 145 data sets from 36 participants, representing over 6.5 million occurrence records of over 83,000 taxa from more than 888,000 locations. OBIS-USA, a legacy of the decade-long (2001-2010) international collaborative Census of Marine Life enterprise, continues to add data, including those from ongoing Census projects. Among the many challenges in creating OBIS, including OBIS-USA, were developing a community of trust and shared valueamong data providers, and demonstrating to providers the value of making their data accessible to others. Challenges also posed by the diversity of data sets relevant tomarine biodiversity stored on thousands of computers, in a variety of formats, not all widely accessible, have been met in OBIS-USA by implementing a uniform standard and publishing platform that is easily accessible to a broad range of users.

Oceanography↗

USGS1968

Hydrogeologic data for the lower Thames and southeastern coastal river basins, Connecticut

This report presents hydrologic and geologic data collected by the U.S. Geological Survey during an investigation of water resources in the lower Thames and southeastern coastal river basins in cooperation with the Connecticut Water Resources Commission. The report area occupies about 440 square miles in the southeastern part of the State; it includes about 5 square miles in southwestern Rhode Island. It includes the towns of Bozrah, Groton, Ledyard, Montville, New London, Stonington, and Waterford, and parts of Columbia, Colchester, East Lyme, Franklin, Lebanon, North Stonington, Norwich, Old Lyme, Preston, Salem, and Voluntown. A companion interpretive report, Connecticut Water Resources Bulletin No. 15, (Thomas and others, in preparation), evaluates the water resources of the area. The data on the following pages serve to document and supplement that report and should be especially useful in planning the development of water resources at specific localities. Data were collected as part of this investigation from 1963 to 1965. Streamflow records from continuous~record gaging stations in the report area for this period have been published annually along with data from other parts of the State in a series of U.S. Geological Survey reports entitled "Surface Water Records of Connecticut." Water-level measurements in wells throughout the State from 1960 through 1966~ including those made as part of this investigations are published in Connecticut Water Resources Bulletin No. 7 (Meikle and Baker~ 1965) and Connecticut Water Resources Bulletin No. 13 (Melklee 1967). Most other data collected during this investigation are tabulated on the following pages. Included are some previously unpublished data collected prior to the start of this study. The locations of sites at which data were collected are shown on Plate A in the pocket at the back of the report. Plate A includes the locations of 42 miscellaneous sites where measurements of streamflow were made during 1963 and 1964 and 6 other sites where continuous records are maintained. Data for 25 of the 42 miscellaneous sites are included in this report: data for the remaining 17 miscellaneous sites and for 5 of the 6 continuous-record sites have already been published in "Surface Water Records of Connecticut." Streamflow records for Pawcatuck River at Westerly~ Rhode Island have been previously published in "Surface Water Records of Massachusetts, New Hampshire, Rhode Island, and Vermont." Data presented, unless otherwise noted, were collected by U.S. Geological Survey personnel.

Connecticut↗

USGS2012

Report on progress at the Center for Engineering Strong Motion Data (CESMD)

Strong-motion data of engineering and scientific importance from the United States and other seismically active countries are served through the Center for Engineering Strong Motion Data (CESMD) at www.strongmotioncenter.org. Recently, the CESMD staff, with cooperation from colleagues at international strong-motion seismic networks, has disseminated strong-motion data from significant earthquakes that occurred in Italy, Haiti, Mexico, New Zealand, Chile, Japan, Turkey, and the United States. The CESMD now automatically posts strong-motion data from an increasing number of seismic stations in California within a few minutes following an earthquake as an Internet Quick Report (IQR). As appropriate, IQRs are updated by more comprehensive Internet Data Reports that include reviewed versions of the data and maps showing, for example, the finite fault rupture along with the distribution of recording stations. Automated processing of strong-motion data will be extended to post the strong-motion records of the regional seismic networks of the Advanced National Seismic System (ANSS) outside California. Transfer of the operational and maintenance responsibilities for the Consortium of Organizations for Strong Motion Observation Systems (COSMOS) Virtual Data Center (VDC) from the University of California at Santa Barbara to the CESMD is nearing completion. The VDC Tagged Format (VTF) file format has been adopted by the CESMD as the standard for converting strong motion data to facilitate the process of uploading data into the VDC database. The CESMD now provides strong-motion records from lower magnitude (<M3.5) and smaller amplitude (<0.5%g) records for use in developing ground motion prediction equations in areas with less frequent earthquakes, such as the Central and Eastern US.

Conference Paper↗

USGS2002

U.S. Geological Survey spatial data access

The U.S. Geological Survey (USGS) has done a progress review on improving access to its spatial data holdings over the Web. The USGS EROS Data Center has created three major Web-based interfaces to deliver spatial data to the general public; they are Earth Explorer, the Seamless Data Distribution System (SDDS), and the USGS Web Mapping Portal. Lessons were learned in developing these systems, and various resources were needed for their implementation. The USGS serves as a fact-finding agency in the U.S. Government that collects, monitors, analyzes, and provides scientific information about natural resource conditions and issues. To carry out its mission, the USGS has created and managed spatial data since its inception. Originally relying on paper maps, the USGS now uses advanced technology to produce digital representations of the Earth’s features. The spatial products of the USGS include both source and derivative data. Derivative datasets include Digital Orthophoto Quadrangles (DOQ), Digital Elevation Models, Digital Line Graphs, land-cover Digital Raster Graphics, and the seamless National Elevation Dataset. These products, created with automated processes, use aerial photographs, satellite images, or other cartographic information such as scanned paper maps as source data. With Earth Explorer, users can search multiple inventories through metadata queries and can browse satellite and DOQ imagery. They can place orders and make payment through secure credit card transactions. Some USGS spatial data can be accessed with SDDS. The SDDS uses an ArcIMS map service interface to identify the user’s areas of interest and determine the output format; it allows the user to either download the actual spatial data directly for small areas or place orders for larger areas to be delivered on media. The USGS Web Mapping Portal provides views of national and international datasets through an ArcIMS map service interface. In addition, the map portal posts news about new map services available from the USGS, many simultaneously published on the Environmental Systems Research Institute Geography Network. These three information systems use new software tools and expanded hardware to meet the requirements of the users. The systems are designed to handle the required workload and are relatively easy to enhance and maintain. The software tools give users a high level of functionality and help the system conform to industry standards. The hardware and software architecture is designed to handle the large amounts of spatial data and Internet traffic required by the information systems. Last, customer support was needed to answer questions, monitor e-mail, and report customer problems.

Journal of Geospatial Engineering↗

USGS2012

Priorities for IOOS ® Data Management and Communications (DMAC)

Dramatic increases in the volume of online data and rapid advances in information technology have transformed many aspects of our society. In the coastal ocean, the amount of data is also growing dramatically due to new sensor and modeling technologies. Lagging behind this deluge of ocean data, however, is an effective framework of standards, protocols, tools and culture needed to transform the way we generate knowledge and value from ocean data. The Data Management and Communications (DMAC) sub-system was envisioned to provide such an information management capability for IOOS®, promoting standards and policies to be implemented by data providers across the IOOS enterprise. DMAC needs to build upon the successes and lessons learned during development of web service standards and promote a set of end-to-end standards and procedures for the entire ocean-data life cycle, including documentation through metadata, quality control and quality assurance, effective data discovery, and stewardship through archiving. Because information technology is constantly changing, a multiyear, top-down design and implementation plan is not workable. DMAC should start by promoting a set of protocols that are functional for specific use cases, creating a modular framework in which modules can be replaced as technologies change. In addition to promoting protocols, DMAC needs to support training, flexible online documentation, support, and social networking that enable users to share code, techniques and experiences. Through this bottom-up approach, trust and understanding will foster adoption by the community. Finally, a compliance and certification process should be developed that allows IOOS to ensure that they meet the needs of customers and other stakeholders while complying with regulatory requirements related to the data. If this approach is followed, we will enable breakthroughs in ocean data–driven technology similar to those common elsewhere in our society, fulfilling the broader mission of IOOS.

Book↗

USGS2010

Data mining for water resource management part 2 - methods and approaches to solving contemporary problems

This is the second of two papers that describe how data mining can aid natural-resource managers with the difficult problem of controlling the interactions between hydrologic and man-made systems. Data mining is a new science that assists scientists in converting large databases into knowledge, and is uniquely able to leverage the large amounts of real-time, multivariate data now being collected for hydrologic systems. Part 1 gives a high-level overview of data mining, and describes several applications that have addressed major water resource issues in South Carolina. This Part 2 paper describes how various data mining methods are integrated to produce predictive models for controlling surface- and groundwater hydraulics and quality. The methods include: - signal processing to remove noise and decompose complex signals into simpler components; - time series clustering that optimally groups hundreds of signals into "classes" that behave similarly for data reduction and (or) divide-and-conquer problem solving; - classification which optimally matches new data to behavioral classes; - artificial neural networks which optimally fit multivariate data to create predictive models; - model response surface visualization that greatly aids in understanding data and physical processes; and, - decision support systems that integrate data, models, and graphics into a single package that is easy to use.

South Carolina↗