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At least 1,405 records · Page 78Linked to original sources
USGS1982

Water resources data, Pennsylvania water year 1982. Volume 1: Delaware River basin

Water resources data for the 1982 water year for Pennsylvania consist of records of discharge and water quality of streams; elevation and contents of lakes and reservoirs; and elevation of tides; and water levels of ground-water wells. This volume contains records for water discharge at 66 gaging stations; elevation and contents at 11 lakes and reservoirs; elevation of tides at 1 gaging station; water quality at 33 gaging stations; and water levels at 16 observation wells. Also included are data for 34 crest-stage, 80 low-flow, and 43 water-quality partial-record stations. Locations of these sites are shown on figures 6 through 9. Additional water data were collected at various sites not involved in the systematic data-collection program and are published as miscellaneous measurements and analyses. These data together with the data in Volume 2 and 3 represent that part of the National Water Data System operated by the U.S. Geological Survey and cooperating State, local and Federal agencies in Pennsylvania.

Pennsylvania↗
USGS1984

Water resources data, Pennsylvania, water year 1983. Volume 2: Susquehanna and Potomac River basins

Water resources data for the 1983 water year for Pennsylvania consist of records of discharge and water quality of streams; contents of lakes and reservoirs; and water levels, and water quality of ground-water wells. This volume contains records for water discharge at 84 stations; contents at 13 lakes and reservoirs, water quality at 18 gaging stations; and water levels at 26 network observation wells. Also included are data for 12 crest-stage, 98 low flow, and 3 water-quality, and 85 ground water-quality partial-record stations. Locations of these sites are shown on figures 7-10. Additional water data were collected at various sites not involved in-the systematic data-collection program and are published as miscellaneous measurements and analysis. These data together with the data in Volumes 1 and 3 represent that part of the National Water Data System operated by the U.S. Geological Survey and cooperating State, local, and Federal agencies in Pennsylvania.

Pennsylvania↗
USGS1980

Water resources data for Virginia, water year 1979

Water resources data for the 1979 water year for Virginia consist of records of stage, discharge, and water quality of streams; stage, contents, and water quality of lakes and reservoirs; and water levels and water quality of ground-water wells. This volume contains records for water discharge at 200 gaging stations; stage only at 1 gaging station; stage and contents at 9 lakes and reservoirs; water quality at 54 gaging stations and 38 wells; and water levels at 62 observation wells. Also included are data for 64 crest-stage partial-record stations. Locations of these sites are shown on figures 3 and 4. Additional water data were collected at various sites not involved in the systematic data-collection program. Discharge measurements and water-quality analyses were made at 97 coal-monitoring partial-record stations. Miscellaneous data were collected at 220 measuring sites and 64 water-quality sampling sites. These data represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating State and Federal agencies in Virginia.

Virginia↗
USGS1981

Water resources data for Virginia, water year 1980

Water resources data for the 1980 water year for Virginia consist of records of stage, discharge, and water quality of streams; stage, contents, and water quality of lakes and reservoirs; and water levels and water quality of ground-water wells. This volume contains records for water discharge at 210 gaging stations; stage only at 1 gaging station; stage and contents at 10 lakes and reservoirs; water quality at 53 gaging stations and 120 wells; and water levels at 60 observation wells. Also included are data for 63 crest-stage partial-record stations. Locations of these sites are shown on figures 3 and 4. Additional water data were collected at various sites not involved in the systematic data-collection program. Discharge measurements were made at 142 coal-monitoring partial-record stations and 67 low-flow partial-record stations. Miscellaneous data were collected at 311 measuring sites and 186 water-quality sampling sites. These data represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating State and Federal agencies in Virginia.

Virginia↗
USGS1979

Water resources data for Washington, water year 1978; Volume 1. Western Washington

Water resources data for the 1978 water year for Washington consist of records of stage, discharge, and water quality of streams; stage, contents, and water quality of lakes and reservoirs; and water levels and water quality of ground-water wells. This report in two volumes contains records for water discharge at 248 gaging stations; stage only at 4 gaging stations; stage and contents at 44 lakes and reservoirs; water quality at 117 gaging stations (including 6 lakes and reservoirs) and 215 wells; and water levels at 166 observation wells. Also included are data for 96 crest-stage, and 89 water-quality partial-record stations. Additional water data were collected at various sites not involved in the systematic data-collection program and are published as miscellaneous measurements and analyses. These data together with the data in Volume 2 represent that part of the National Water Data System operated by the U.S. Geological Survey and cooperating State, local, and Federal agencies in Washington.

Washington↗
USGS1979

Water resources data for Washington, water year 1978, Vol. 2 - Eastern Washington

Water resources data for the 1978 water year for Washington consist of records of stage, discharge, and water quality of streams; stage, contents, and water quality of lakes and reservoirs; and water levels and water quality of ground-water wells. This volume contains records for water discharge at 248 gaging stations; stage only at 4 gaging stations; stage and contents at 44 lakes and reservoirs; water quality at 117 gaging stations (including 6 lakes and reservoirs) and 215 wells; and water levels at 166 observation wells. Also included are data for 96 crest-stage and 89 water-quality partial-record stations. Locations of these sites are shown on figures 4, 5, and 19. Addition-al water data were collected at various sites not involved in the systematic data-collection program and are published as miscellaneous measurements and and analyses. These data together with the data in Volume 1 represent that part of the national Water Data system operated by the U.S. Geological Survey and cooperating State, local, and Federal agencies in Washington.

Washington↗
USGS1982

Water resources data, West Virginia water year 1981, Appendix - coal areas and special projects

The first section of this report contains data collected during the 1981 water year for the West Virginia Coal Hydrology monitoring project. Records consist of discharge and water-quality data collected at 246 sites in July, at 29 sites in August, and sediment data for 235 sites collected in July. The second section of this report contains data collected during the period January 1978 to December 1981 for the water resources study of the Tug Fork and Twelvepole Creek basins. Records consist of physical data for 347 wells, water level data for two wells, quality analyses of water from 328 wells, and discharge, chemical and biological data for 91 sites sampled several times.

West Virginia↗
USGS1966

Hydrologic and climatologic data, 1965, Salt Lake County, Utah

An investigation of the water resources of Salt Lake County, Utah, was undertaken by the Water Resources Division of the U.S. Geological Survey in July 1963. This investigation is a cooperative project financed equally by the State of Utah and the Federal Government in accordance with an agreement between the State Engineer and the Geological Survey. The Utah Water and Power Board, Utah Fish and Game Commission, Salt Lake County Water Conservancy District, Metropolitan Water District of Salt Lake City, Salt Lake County, Kennecott Copper Corporation, Utah Power and Light Company, Salt Lake City Chamber of Commerce, and the Central Utah Water Conservancy District. contributed funds to the State Engineer's office toward support of the project. The investigation encompasses the collection and interpretation of a large variety of climatologic, hydrologic, and geologic data in and near Salt Lake County. Utah Basic-Data Release No. 11 contains data collected through 1964. This release contains climatologic and surface-water data for the 1965 water year (October 1964 to September 1965) and ground-water data collected during the 1965 calendar year. Similar annual releases will contain data collected during the remainder of the investigation, and interpretive reports will be prepared as the investigation proceeds. Organizations that furnished data are acknowledged in station descriptions and footnotes to tables.

Utah↗
USGS1967

Hydrologic and climatologic data, 1966, Salt Lake County, Utah

An investigation of the water resources of Salt Lake County, Utah, was undertaken by the Water Resources Division of the U.S. Geological Survey in July 1963. This investigation is a cooperative project financed equally by the State of Utah and the Federal Government in accordance with an agreement between the State Engineer and the Geological Survey. The Utah Water and Power Board, Utah Fish and Game Commission, Salt Lake County Water Conservancy District, Metropolitan Water District of Salt Lake City, Salt Lake County, Kennecott Copper Corporation, Utah Power and Light Company, Salt Lake City Chamber of Commerce, and the Central Utah Water Conservancy District contributed funds to the State Engineer's office toward support of the project. The investigation encompasses the collection and interpretation of a large variety of climatologic, hydrologic, and geologic data in and near Salt Lake County. Utah Basic-Data Releases 11 and 12 contain data collected through 1965. This release contains climatologic and surface-water data for the 1966 water year (October 1965 to September 1966) and groundwater data collected during the 1966 calendar year. Similar annual releases will contain data collected during the remainder of the investigation, and interpretive reports will be prepared as the investigation proceeds. Organizations that furnished data are acknowledged in station descriptions and footnotes to tables.

Utah↗
USGS1968

Hydrologic and climatologic data, 1967, Salt Lake County, Utah

An investigation of the water resources of Salt Lake County, Utah, was undertaken by the Water Resources Division of the U.S. Geological Survey in July 1963. This investigation is a cooperative project financed chiefly by equal contributions of the State of Utah and the Federal Government in accordance with an agreement between the Division of Water Rights, Utah Department of Natural Resources, and the Geological Survey. The investigation was financed during the period covered by this report by the following organizations: Utah Division of Water Rights (formerly State Engineer), Utah Division of Water Resources (formerly Water and Power Board), Salt Lake County, Salt Lake County Water Conservancy District, Central Utah Water Conservancy District, Metropolitan Water District of Salt Lake City, City of Murray, Granger-Hunter Improvement District, Taylorsville-Bennion Improvement District, Holladay Water Company, Magna Water and Sewer District, U.S. Bureau of Reclamation, U.S. Geological Survey. The investigation encompasses the collection and interpretation of a large variety of climatologic, hydrologic, and geologic data in and near Salt Lake County. Utah Basic-Data Releases 11-13 contain data collected through 1966. This release contains climatologic and surfacewater data for the 1967 water year (October 1966 to September 1967) and ground-water data collected during the 1967 calendar year. A similar annual release will contain data collected during the remainder of the investigation, and interpretive reports will be prepared as the investigation proceeds. Organizations that furnished data are acknowledged in station descriptions and footnotes to tables.

Utah↗
USGS1969

Hydrologic and climatologic data, 1968, Salt Lake County, Utah

An investigation of the water resources of Salt Lake County, Utah, was undertaken by the Water Resources Division of the U.S. Geological Survey in July 1963. This investigation is a cooperative project financed chiefly by equal contributions of the State of Utah and the Federal Government in accordance with an agreement between the Division of Water Rights, Utah Department of Natural Resources, and the Geological Survey. The investigation was financed during the period covered by this report by the following organizations: Utah Division of Water Rights (formerly State Engineer), Utah Division of Water Resources (formerly Water and Power Board), Salt Lake County, Salt Lake County Water Conservancy District, Central Utah Water Conservancy District, Metropolitan Water District of Salt Lake City, City of Murray, Granger-Hunter Improvement District, Taylorsville-Bennion Improvement District, Holladay Water Company, Magna Water and Sewer District, U.S. Bureau of Reclamation, U.S. Geological Survey The investigation encompasses the collection and interpretation of a large variety of climatologic, hydrologic, and geologic data in and near Salt Lake County. Utah Basic-Data Releases 11-13 and 15 contain data collected through 1967. This release contains climatologic and surface-water data for the 1968 water year (October 1967 to September 1968) and ground-water data collected during the 1968 calendar year. This is the final annual release of basic data for this investigation. Interpretive reports summarizing the results are in preparation. Organizations that furnished data are acknowledged in station descriptions and footnotes to tables.

Utah↗
USGS2023

The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management

Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision-support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision-support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next-generation tools to support agroecosystem management through the 21st century.

Agricultural & Environmental Letters↗
USGS2026

Incorporating data sets with multiple sources of uncertainty in integrated species distribution models

Data integration methods aim to improve species distribution estimates by incorporating multiple sources of uncertainty across datasets. Two major sources of uncertainty are: (1) variation in sampling effort across space and within datasets, and (2) variation in reliability associated with data collection protocols or timing among datasets. Our goal was to evaluate how different approaches to address these uncertainties influence predictive performance of integrated models. We modeled distributions of four bird species using three datasets that differed in sampling design. We examined three strategies to reduce uncertainty: (1) filtering data, (2) incorporating functions that account for uncertainty in observation models, and (3) varying how datasets are integrated into a single estimate. We first examine methods to account for variable effort in observations, focusing on both spatial differences in sampling intensity and effort given to a single observation record. We then examine approaches to account for data sets with differing reliability. Sampling effort was best addressed through conservative filtering, including spatial thinning and excluding observations with highly variable effort. Next, we considered how to account for potential false positive detections—due to either misidentification or changes in distributions. We found that treating less reliable data as a covariate, an approach previously suggested for data integration that can greatly speed up model fitting, performed well. Other effective approaches included directly modeling false positive rates and complete exclusion of less reliable data sets. Our results provide insights into best practices in integrated modeling for handling uncertainty in integrated models. We demonstrate the flexible options available when using integrated models to address uncertainty.

Pennsylvania↗
USGS2014

Inferences about population dynamics from count data using multi-state models: A comparison to capture-recapture approaches

Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers ( Setophaga caerulescens ) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.

New Hampshire↗
USGS2016

Leveraging constraints and biotelemetry data to pinpoint repetitively used spatial features

Satellite telemetry devices collect valuable information concerning the sites visited by animals, including the location of central places like dens, nests, rookeries, or haul‐outs. Existing methods for estimating the location of central places from telemetry data require user‐specified thresholds and ignore common nuances like measurement error. We present a fully model‐based approach for locating central places from telemetry data that accounts for multiple sources of uncertainty and uses all of the available locational data. Our general framework consists of an observation model to account for large telemetry measurement error and animal movement, and a highly flexible mixture model specified using a Dirichlet process to identify the location of central places. We also quantify temporal patterns in central place use by incorporating ancillary behavioral data into the model; however, our framework is also suitable when no such behavioral data exist. We apply the model to a simulated data set as proof of concept. We then illustrate our framework by analyzing an Argos satellite telemetry data set on harbor seals ( Phoca vitulina ) in the Gulf of Alaska, a species that exhibits fidelity to terrestrial haul‐out sites.

Alaska↗
USGS2025

Sparse genetic data limit biodiversity assessments in protected areas globally

Global conservation targets include protecting genetic diversity within species. Yet few studies have assessed whether protected areas (PAs) include genetically diverse populations across species globally. A first step is understanding the availability of population genetic data that could be used in these assessments. We surveyed georeferenced population-level nuclear (as opposed to mitochondrial or plastid-based) genetic data across continents and marine biomes (36,354 populations, 2809 species) and found substantial geographic and taxonomic gaps. Most data were concentrated in Europe and North America, with major gaps in Africa and Asia. For most taxonomic groups, data were available for <1% of described species. Globally, 52.08% of the total areal extent of PAs lacked genetically sampled populations. These gaps in data availability highlight the need for targeted genetic data collection, harmonization, and sharing to improve genetic diversity monitoring and conservation planning. Combined with proxy-based genetic indicators, such data are needed to inform PA assessments, bolster area-based conservation initiatives like 30 × 30, and support achievement of global genetic conservation targets.

Frontiers in Ecology and the Environment↗
USGS2025

Power source, data retrieval method, and attachment type affect success of dorsally mounted tracking tag deployments in 37 species of shorebirds

Animal-borne trackers are commonly used to study bird movements, including in long-distance migrants such as shorebirds. Selecting a tracker and attachment method can be daunting, and methodological advancements often have been made by trial and error and conveyed by word of mouth. We synthesized tracking outcomes across 2745 dorsally mounted trackers on 37 shorebird species around the world. We evaluated how attachment method, power source, data retrieval method, relative tracker mass, and biological traits affected success, where success was defined as whether or not each tag deployment reached its expected tracking duration (i.e. all aspects succeeded for the intended duration of the study: attachment, tracking, data acquisition, and bird survival). We conducted separate analyses for tag deployments with remote data retrieval (‘remote-upload tag deployments') and those that archived data and had to be recovered (‘archival tag deployments'). Among remote-upload tag deployments, those that were a lighter mass relative to the bird, were beyond their first year of production, transmitted data via satellite, or were attached with a leg-loop harness were most often successful at reaching their expected tracking duration. Archival tag deployments were most successful when applied at breeding areas, or when applied to males in any season. Remote-upload tag deployments with solar power, satellite data retrieval, or leg-loop harnesses continued tracking for longer than those with battery power, other types of data retrieval, or glue attachments. However, the majority of tag deployments failed to reach their expected tracking duration (71% of remote-upload, 83% of archival), which could have been due to tracker failure, attachment failure, or bird mortality. Our findings highlight that many tag deployments may fail to meet the goals of a study if tracking duration is crucial. Using our results, we provide guidelines for selecting a tracker and attachment to improve success at meeting study goals.

Journal of Avian Biology↗
USGS2022

Integrating distance sampling survey data with population indices to separate trends in abundance and temporary immigration

Managers rely on accurate estimators of wildlife abundance and trends for management decisions. Despite the focus of contemporary wildlife science on developing methods to improve inference from wildlife surveys, legacy datasets often rely on index counts that lack information about the detection process. Data integration can be a useful tool for combining index counts with data collected under more rigorous designs (i.e., designs that account for the detection process), but care is required when datasets represent different population processes or are mismatched in space and time. This can be particularly problematic in cases where animals aggregate in response to a spatially or temporally limited resource because individuals may temporarily immigrate from outside the study area and be included in the abundance index. Abundance indices based on brown bear ( Ursus arctos ) feeding aggregations within coastal meadows in early summer in Lake Clark National Park and Preserve, Alaska, USA, are one such example. These indices reflect the target population (brown bears residing within the park) and temporary immigrants (i.e., bears drawn from outside the park boundary). To properly account for the effects of temporary immigration, we integrated the index data with abundance data collected via park-wide distance sampling surveys, the latter of which properly addressed the detection process. By assuming that the distance data provide inference on abundance and the index counts represent some combination of abundance and temporary immigration processes, we were able to decompose the relative contribution of each to overall trend. We estimated that the density of brown bears within our study area was 38–54 adults/1,000 km 2 during 2003–2019 and that abundance increased at a rate of approximately 1.4%/year. The contribution of temporary immigrants to overall trend in the index was low, so we created 3 hypothetical scenarios to more fully demonstrate how the integrated approach could be useful in situations where the composite trend in meadow counts may obscure trends in abundance (e.g., opposing trends in abundance and temporary immigration). Our work represents a conceptual advance supporting the integration of legacy index data with more rigorous data streams and is broadly applicable in cases where trends in index values may represent a mixture of population processes.

Alaska↗