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At least 667 records · Page 37Linked to original sources
USGS2015

Changes in data sharing and data reuse practices and perceptions among scientists worldwide

The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines. We distributed surveys to a multinational sample of scientific researchers at two different time periods (October 2009 to July 2010 and October 2013 to March 2014) to observe current states of data sharing and to see what, if any, changes have occurred in the past 3–4 years. We also looked at differences across age, geographic, and discipline-based groups as they currently exist in the 2013/2014 survey. Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors. However, there is also increased perceived risk associated with data sharing, and specific barriers to data sharing persist. There are also differences across age groups, with younger respondents feeling more favorably toward data sharing and reuse, yet making less of their data available than older respondents. Geographic differences exist as well, which can in part be understood in terms of collectivist and individualist cultural differences. An examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines. Implications of these findings include the continued need to build infrastructure that promotes data sharing while recognizing the needs of different research communities. Moving into the future, organizations such as DataONE will continue to assess, monitor, educate, and provide the infrastructure necessary to support such complex grand science challenges.

PLoS ONE↗
USGS2020

Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment

The US Fish and Wildlife Service has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of a species’ current status and predicted future status. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, recovery planning, etc. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting species conservation decisions in current data and cutting edge analytical and modeling techniques. Here we describe a novel analysis of available data to assess current condition of eastern black rail across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future conditions under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With results of these data analyses and predictive modeling, the US Fish and Wildlife Service concluded that protections of the Endangered Species Act were warranted for this subspecies.

Endangered Species Research↗
USGS2025

Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

Ecosphere↗
USGS2002

Digital data grids for the magnetic anomaly map of North America

The digital magnetic anomaly database and map for the North American continent is the result of a joint effort by the Geological Survey of Canada (GSC), U. S. Geological Survey (USGS), and Consejo de Recursos Minerales of Mexico (CRM). This integrated, readily accessible, modern digital database of magnetic anomaly data is a powerful tool for further evaluation of the structure, geologic processes, and tectonic evolution of the continent and may also be used to help resolve societal and scientific issues that span national boundaries. The North American magnetic anomaly map derived from the digital database provides a comprehensive magnetic view of continental-scale trends not available in individual data sets, helps link widely separated areas of outcrop, and unifies disparate geologic studies. This open-file report presents three unique, gridded data sets used to make the magnetic anomaly map of North America. Subsets of these three grids that span only the United States were also created, giving a total of six grids. Details on the data processing and compilation procedures used to produce the grids are described in the booklet that accompanies the North American magnetic anomaly map. All three grids have 1-km spacing and are projected to the DNAG projection (spherical transverse mercator, central meridian of 100 o W, base latitude of 0o, scale factor of 0.926 and Earth radius of 6,371,204 m.) More details are given in the metadata files that accompany the gridded data files. These grids are presented in Geosoft binary grid format, with two files describing each of the six grids (suffixes .grd and .gi). This format can be easily converted to numerous other formats using the free conversion software offered by this company at http://www.geosoft.com/. The first grids (NAmag_origmrg.grd and USmag_origmrg.grd) show the magnetic field at 305 m. above terrain. For the second grids (NAmag_hp500.grd and USmag_hp500.grd) we removed long-wavelength anomalies (500 km and greater) from the first grid. This grid was used for the published map. Although the North American merged grid represents a significant upgrade to older compilations, the existing patchwork of surveys is inherently unable to accurately represent anomalies with long (greater than roughly 150 km) wavelengths, particularly in the US and Canada (U.S. Magnetic-Anomaly Data Set Task Group, 1994). The lack of information about long wavelength anomalies is primarily related to datum shifts between merged surveys, caused by data acquisition at widely different times and by differences in merging procedures. Therefore, we removed anomalies with wavelengths greater than 500 km from the merged grid to reduce the effects caused by the spurious long wavelengths but still maintain the continuity of anomalies. The correction was accomplished by transforming the merged grid to the frequency domain, filtering the transformed data with a long-wavelength cutoff at 500 km, and subtracting the long-wavelength data grid from the merged grid. In addition to the 500-km high pass filter, an equivalent source method, based on long-wavelength characterization using satellite data (CHAMP satellite anomalies, Maus and others, 2002), was also used to correct for spurious shifts in the original magnetic anomaly grid (Ravat and others, 2002). These results are presented in the third grids (NAmag_CM.grd and USmag_CM.grd), in which the wavelengths longer than 500 km have been replaced by downward-continued satellite data. The steps used to create the third long-wavelength-corrected grid are: 0. The North American 1-km merged grid was decimated to 5 km. 1. This 5-km grid was converted to a 0.05 degree grid and was low-pass filtered using a Gaussian filter with a 500-km cutoff, then decimated to 1 degree. 2. A joint inversion of this 1-degree low-pass aeromagnetic grid and satellite data, with the aeromagnetic data weighted very low, was used to produce a stabilized downward continuation of the satellite data. 3. The inverted data were interpolated to 0.05 degrees and again low-pass filtered using the same Gaussian 500-km filter to remove short-wavelength artifacts. 4. The low-pass grid from step 1 was subtracted from the original 0.05-degree aeromagnetic grid to create a 500-km high-pass aeromagnetic grid. This grid was added to the low-pass inverted grid from step 3 to get a corrected 0.05-degree aeromagnetic grid. 5. The corrected 0.05-degree aeromagnetic grid was projected to the DNAG projection and regridded to 5 km. This was subtracted from the decimated 5-km aeromagnetic grid to generate a 5-km correction grid. A matched filter was used to remove short-wavelength artifacts resulting from the projection and regridding process. 6. The resulting 5-km correction grid was regridded to the original 1-km grid and subtracted from the original 1-km aeromagnetic grid to generate the final 1-km corrected aeromagnetic grid. The six grids described in this report are available for download. Two metadata files, one for the North American grids and one for the United States grids, are also included with the gridded data.

Open-File Report↗
USGS2002

Of bugs and birds: Markov Chain Monte Carlo for hierarchical modeling in wildlife research

Markov chain Monte Carlo (MCMC) is a statistical innovation that allows researchers to fit far more complex models to data than is feasible using conventional methods. Despite its widespread use in a variety of scientific fields, MCMC appears to be underutilized in wildlife applications. This may be due to a misconception that MCMC requires the adoption of a subjective Bayesian analysis, or perhaps simply to its lack of familiarity among wildlife researchers. We introduce the basic ideas of MCMC and software BUGS (Bayesian inference using Gibbs sampling), stressing that a simple and satisfactory intuition for MCMC does not require extraordinary mathematical sophistication. We illustrate the use of MCMC with an analysis of the association between latent factors governing individual heterogeneity in breeding and survival rates of kittiwakes ( Rissa tridactyla ). We conclude with a discussion of the importance of individual heterogeneity for understanding population dynamics and designing management plans.

Journal of Wildlife Management↗
USGS2000

Data report: Mid-Pliocene diatom assemblages at sites 1016, 1021, and 1022

Diatom assemblages from the middle part of the Pliocene (3.2-2.5 Ma) were investigated from Ocean Drilling Program Sites 1016, 1021, and 1022 in an effort to infer paleotemperature fluctuations off California. Diatoms are very sparse in virtually all of the samples that were examined from Sites 1016 and 1021. This is presumably because these sites were seaward (west) of the coastal zone of diatom productivity during the middle part of the Pliocene. Diatoms are relatively common in the vast majority of samples that were examined from Hole 1022A. Diatom assemblages are dominated by Chaetoceros spores (a coastal upwelling component), the cold-water (subarctic) taxa Neodenticula kamtschatica and its descendant Neodenticula koizumii, and Thalassionema nitzschioides, a temperate taxon that is typically found at the seaward edge of coastal upwelling zones. Paleotemperature interpretations, however, are not possible at this time because of the scarcity of comparative modern core-top data.

Proceedings of the Ocean Drilling Program: Scienti↗
USGS1955

Geology of the Calamity Mesa quadrangle, Colorado

The series of Geologic Quadrangle Maps of the United States continues the series of quadrangle maps begun with the folios of the Geologic Atlas of the United States, which were published from 1894 to 1945. The present series consists of geologic maps, supplemented where possible by structure sections, columnar sections, and other graphic means of presenting geologic data, and accompanied by a brief explanatory text to make the maps useful for general scientific and economic purposes. Full description and interpretation of the geology of the areas shown on these maps are reserved for publication in other channels, such as the Bulletins and Professional Papers of the Geological Survey. Separate maps of the same areas, covering bedrock, surficial, engineering, and other phases of geology, may be published in the geologic quadrangle map series.

Colorado↗
USGS2013

Reconnaissance geologic map of Kodiak Island and adjacent islands, Alaska

Kodiak Island and its adjacent islands, located on the west side of the Gulf of Alaska, contain one of the largest areas of exposure of the flysch and melange of the Chugach terrane of southern Alaska. However, in the past 25 years, only detailed mapping covering small areas in the archipelago has been done. This map and its associated digital files (Wilson and others, 2005) present the best available mapping compiled in an integrated fashion. The map and associated digital files represent part of a systematic effort to release geologic map data for the United States in a uniform manner. The geologic data have been compiled from a wide variety of sources, ranging from state and regional geologic maps to large-scale field mapping. The map data are presented for use at a nominal scale of 1:500,000, although individual datasets (see Wilson and others, 2005) may contain data suitable for use at larger scales.

Alaska↗
USGS2018

Delineation of the hydrogeologic framework of the Big Sioux aquifer near Sioux Falls, South Dakota, using airborne electromagnetic data

The U.S. Geological Survey, in cooperation with the City of Sioux Falls, South Dakota, began developing a groundwater-flow model of the Big Sioux aquifer in 2014 that will enable the City to make more informed water management decisions, such as delineation of areas of the greatest specific yield, which is crucial for locating municipal wells. Innovative tools are being evaluated as part of this study that can improve the delineation of the hydrogeologic framework of the aquifer for use in development of a groundwater-flow model, and the approach could have transfer value for similar hydrogeologic settings. The first step in developing a groundwater-flow model is determining the hydrogeologic framework (vertical and horizontal extents of the aquifer), which typically is determined by interpreting geologic information from drillers’ logs and surficial geology maps. However, well and borehole data only provide hydrogeologic information for a single location; conversely, nearly continuous geophysical data are collected along flight lines using airborne electromagnetic (AEM) surveys. These electromagnetic data are collected every 3 meters along a flight line (on average) and subsequently can be related to hydrogeologic properties. AEM data, coupled with and constrained by well and borehole data, can substantially improve the accuracy of aquifer hydrogeologic framework delineations and result in better groundwater-flow models. AEM data were acquired using the Resolve frequency-domain AEM system to map the Big Sioux aquifer in the region of the city of Sioux Falls. The survey acquired more than 870 line-kilometers of AEM data over a total area of about 145 square kilometers, primarily over the flood plain of the Big Sioux River between the cities of Dell Rapids and Sioux Falls. The U.S. Geological Survey inverted the survey data to generate resistivity-depth sections that were used in two-dimensional maps and in three-dimensional volumetric visualizations of the Earth resistivity distribution. Contact lines were drawn using a geographic information system to delineate interpreted geologic stratigraphy. The contact lines were converted to points and then interpolated into a raster surface. The methods used to develop elevation and depth maps of the hydrogeologic framework of the Big Sioux aquifer are described herein. The final AEM interpreted aquifer thickness ranged from 0 to 31 meters with an average thickness of 12.8 meters. The estimated total volume of the aquifer was 1,060,000,000 cubic meters based on the assumption that the top of the aquifer is the land-surface elevation. A simple calculation of the volume (length times width times height) of a previous delineation of the aquifer estimated the aquifer volume at 378,000,000 cubic meters; thus, the estimation based on AEM data is more than twice the previous estimate. The depth to top of Sioux Quartzite, which ranged in depth from 0 to 90 meters, also was delineated from the AEM data.

South Dakota↗
USGS2005

Potentiometric surface of the Ozark aquifer in northern Arkansas, 2004

The Ozark aquifer in northern Arkansas comprises dolomites, limestones, sandstones, and shales of Late Cambrian to Middle Devonian age, and ranges in thickness from approximately 1,100 feet to more than 4,000 feet. Hydrologically, the aquifer is complex, characterized by discrete and discontinuous flow components with large variations in permeability. The potentiometric-surface map, based on 59 well and 5 spring water-level measurements collected in 2004 in Arkansas and Missouri, indicates maximum water-level altitudes of about 1,188 feet in Benton County and minimum water-level altitudes of about 116 feet in Randolph County. Regionally, the flow within the aquifer is to the south and southeast in the eastern and central part of the study area and to the northwest and north in the western part of the study area. Comparing the 2004 potentiometric- surface map with a predevelopment potentiometricsurface map indicates general agreement between the two surfaces. Potentiometric-surface differences could be attributed to differences in pumping related to changing population from 1990 to 2000, change in source for public supplies, processes or water use outside the study area, or differences in data-collection or map-construction methods.

Scientific Investigations Report↗
USGS2007

Development and Application of Health-Based Screening Levels for Use in Water-Quality Assessments

Health-Based Screening Levels (HBSLs) are non-enforceable water-quality benchmarks that were developed by the U.S. Geological Survey in collaboration with the U.S. Environmental Protection Agency (USEPA) and others. HBSLs supplement existing Federal drinking-water standards and guidelines, thereby providing a basis for a more comprehensive evaluation of contaminant-occurrence data in the context of human health. Since the original methodology used to calculate HBSLs for unregulated contaminants was published in 2003, revisions have been made to the HBSL methodology in order to reflect updates to relevant USEPA policies. These revisions allow for the use of the most recent, USEPA peer-reviewed, publicly available human-health toxicity information in the development of HBSLs. This report summarizes the revisions to the HBSL methodology for unregulated contaminants, and updates the guidance on the use of HBSLs for interpreting water-quality data in the context of human health.

Scientific Investigations Report↗
USGS2012

Regression model development and computational procedures to support estimation of real-time concentrations and loads of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-9

In December 2005, the U.S. Geological Survey (USGS), in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria ( Escherichia coli and total coliform), atrazine, and suspended sediment at two USGS streamflow-gaging stations that represent watersheds contributing to Lake Houston (08068500 Spring Creek near Spring, Tex., and 08070200 East Fork San Jacinto River near New Caney, Tex.). Data from the discrete water-quality samples collected during 2005–9, in conjunction with continuously monitored real-time data that included streamflow and other physical water-quality properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), were used to develop regression models for the estimation of concentrations of water-quality constituents of substantial source watersheds to Lake Houston. The potential explanatory variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, and time (to account for seasonal variations inherent in some water-quality data). The response variables (the selected constituents) at each site were nitrite plus nitrate nitrogen, total phosphorus, total organic carbon, E. coli , atrazine, and suspended sediment. The explanatory variables provide easily measured quantities to serve as potential surrogate variables to estimate concentrations of the selected constituents through statistical regression. Statistical regression also facilitates accompanying estimates of uncertainty in the form of prediction intervals. Each regression model potentially can be used to estimate concentrations of a given constituent in real time. Among other regression diagnostics, the diagnostics used as indicators of general model reliability and reported herein include the adjusted R-squared, the residual standard error, residual plots, and p-values. Adjusted R-squared values for the Spring Creek models ranged from .582–.922 (dimensionless). The residual standard errors ranged from .073–.447 (base-10 logarithm). Adjusted R-squared values for the East Fork San Jacinto River models ranged from .253–.853 (dimensionless). The residual standard errors ranged from .076–.388 (base-10 logarithm). In conjunction with estimated concentrations, constituent loads can be estimated by multiplying the estimated concentration by the corresponding streamflow and by applying the appropriate conversion factor. The regression models presented in this report are site specific, that is, they are specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the general methods that were developed and documented could be applied to most perennial streams for the purpose of estimating real-time water quality data.

Texas↗
USGS2013

Construction of 3-D geologic framework and textural models for Cuyama Valley groundwater basin, California

Groundwater is the sole source of water supply in Cuyama Valley, a rural agricultural area in Santa Barbara County, California, in the southeasternmost part of the Coast Ranges of California. Continued groundwater withdrawals and associated water-resource management concerns have prompted an evaluation of the hydrogeology and water availability for the Cuyama Valley groundwater basin by the U.S. Geological Survey, in cooperation with the Water Agency Division of the Santa Barbara County Department of Public Works. As a part of the overall groundwater evaluation, this report documents the construction of a digital three-dimensional geologic framework model of the groundwater basin suitable for use within a numerical hydrologic-flow model. The report also includes an analysis of the spatial variability of lithology and grain size, which forms the geologic basis for estimating aquifer hydraulic properties. The geologic framework was constructed as a digital representation of the interpreted geometry and thickness of the principal stratigraphic units within the Cuyama Valley groundwater basin, which include younger alluvium, older alluvium, and the Morales Formation, and underlying consolidated bedrock. The framework model was constructed by creating gridded surfaces representing the altitude of the top of each stratigraphic unit from various input data, including lithologic and electric logs from oil and gas wells and water wells, cross sections, and geologic maps. Sediment grain-size data were analyzed in both two and three dimensions to help define textural variations in the Cuyama Valley groundwater basin and identify areas with similar geologic materials that potentially have fairly uniform hydraulic properties. Sediment grain size was used to construct three-dimensional textural models that employed simple interpolation between drill holes and two-dimensional textural models for each stratigraphic unit that incorporated spatial structure of the textural data.

California↗
USGS2017

Evaluation of radon occurrence in groundwater from 16 geologic units in Pennsylvania, 1986–2015, with application to potential radon exposure from groundwater and indoor air

Results from 1,041 groundwater samples collected during 1986‒2015 from 16 geologic units in Pennsylvania, associated with 25 or more groundwater samples with concentrations of radon-222, were evaluated in an effort to identify variations in radon-222 activities or concentrations and to classify potential radon-222 exposure from groundwater and indoor air. Radon-222 is hereafter referred to as “radon.” Radon concentrations in groundwater greater than or equal to the proposed U.S. Environmental Protection Agency (EPA) maximum contaminant level (MCL) for public-water supply systems of 300 picocuries per liter (pCi/L) were present in about 87 percent of the water samples, whereas concentrations greater than or equal to the proposed alternative MCL (AMCL) for public water-supply systems of 4,000 pCi/L were present in 14 percent. The highest radon concentrations were measured in groundwater from the schists, gneisses, and quartzites of the Piedmont Physiographic Province. In this study, conducted by the U.S. Geological Survey in cooperation with the Pennsylvania Department of Health and the Pennsylvania Department of Environmental Protection, groundwater samples were aggregated among 16 geologic units in Pennsylvania to identify units with high median radon concentrations in groundwater. Graphical plots and statistical tests were used to determine variations in radon concentrations in groundwater and indoor air. Median radon concentrations in groundwater samples and median radon concentrations in indoor air samples within the 16 geologic units were classified according to proposed and recommended regulatory limits to explore potential radon exposure from groundwater and indoor air. All of the geologic units, except for the Allegheny (Pa) and Glenshaw (Pcg) Formations in the Appalachian Plateaus Physiographic Province, had median radon concentrations greater than the proposed EPA MCL of 300 pCi/L, and the Peters Creek Schist (Xpc), which is in the Piedmont Physiographic Province, had a median radon concentration greater than the EPA proposed AMCL of 4,000 pCi/L. Median concentrations of radon in groundwater and indoor air were determined to differ significantly among the geologic units (Kruskal-Wallis test, significance probability, p<0.001), and Tukey’s test indicated that radon concentrations in groundwater and indoor air in the Peters Creek Schist (Xpc) were significantly higher than those in the other units. Also, the Peters Creek Schist (Xpc) was determined to be the area with highest potential of radon exposure from groundwater and indoor air and one of two units with the highest percentage of population assumed to be using domestic self-supplied water (81 percent), which puts the population at greater potential of exposure to radon from groundwater. Potential radon exposure determined from classification of geologic units by median radon concentrations in groundwater and indoor air according to proposed and recommended regulatory limits is useful for drawing general conclusions about the presence, variation, and potential radon exposure in specific geologic units, but the associated data and maps have limitations. The aggregated indoor air radon data have spatial accuracy limitations owing to imprecision of geocoded test locations. In addition, the associated data describing geologic units and the public water supplier’s service areas have spatial and interpretation accuracy limitations. As a result, data and maps associated with this report are not recommended for use in predicting individual concentrations at specific sites nor for use as a decision-making tool for property owners to decide whether to test for radon concentrations at specific locations. Instead, the data and maps are meant to promote awareness regarding potential radon exposure in Pennsylvania and to point out data gaps that exist throughout the State.

Pennsylvania↗
USGS2017

Low-flow frequency and flow-duration characteristics of selected streams in Alabama through March 2014

Low-flow statistics are needed by water-resource engineers, planners, and managers to protect and manage the water resources of Alabama. The accuracy of these statistics is influenced by such factors as length of record and specific hydrologic conditions measured in those records. As such, it is generally recommended that flow statistics be updated about every 10 years to provide improved and representative low-flow characteristics. The previous investigation of low-flow characteristics for Alabama included data through September 1990. Since that time, Alabama has experienced several historic droughts highlighting the need to update the low-flow characteristics at U.S. Geological Survey streamgaging stations. Consequently, this investigation was undertaken in cooperation with a number of State and local agencies to update low-flow frequency and flow-duration statistics at 210 continuous-record streamgaging stations in Alabama and 67 stations from basins that are shared with surrounding States. The flow characteristics were computed on the basis of available data through March 2014.

Alabama↗
USGS2020

Spatially referenced models of streamflow and nitrogen, phosphorus, and suspended-sediment loads in streams of the Pacific region of the United States

Although spatial information describing the supply and quality of surface water is critical for managing water resources for human uses and for ecological health, monitoring is expensive and cannot typically be done over large scales or in all streams or waterbodies. To address the need for such data, the U.S. Geological Survey developed SPAtially Referenced Regression On Watershed attributes (SPARROW) for the Pacific region of the U.S. for streamflow and three water-quality constituents–total nitrogen, total phosphorus, and suspended sediment, based on a decadal time frame centered on the year 2012. The domain for these models included the Columbia River basin, the Puget Sound, the coastal drainages of Washington, Oregon, and California, and the Central Valley of California. Landscape runoff (represented by the difference between precipitation and evapotranspiration) was the largest source of streamflow, wastewater discharge, and atmospheric deposition were the largest contributors to total nitrogen yield from the Pacific region, wastewater discharge was the largest contributor to total phosphorus yield, and forest land was the largest contributor to suspended-sediment yield. Watersheds with relatively high water yields also generally had relatively high yields of total nitrogen, total phosphorous, and suspended sediment–except where there were large contributions from developed land and wastewater discharge. The data used in this study, including many that improved upon existing national data or were compiled specifically for the Pacific region, characterized the complex hydrologic and water-quality conditions in the region more completely than previous models. By using these new datasets, this investigation was able to account for the complex network of water diversions and transfers, quantify the contribution of nutrients from different sources of livestock manure, discern a signal from unpaved logging roads in the suspended-sediment yields from forested coastal watersheds, show how recent wildfire disturbance influences phosphorus and sediment delivery to streams, and how sediment delivery to streams is also sensitive to the intensity of cattle grazing. The results from this study could complement research and inform water-quality management activities in the Pacific region. Examples might include identifying potentially impaired waterbodies and guiding remediation efforts where impairment has been documented, explaining the spatial patterns in harmful algal blooms, and providing estimates of sediment and nutrient loadings to Pacific coast estuaries where such data are scarce or non-existent.

Pacific Region↗
USGS2024

External quality-assurance project report for the National Atmospheric Deposition Program National Trends Network and Mercury Deposition Network, 2021–22

The U.S. Geological Survey Precipitation Chemistry Quality Assurance project (PCQA) operated five distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program (NADP) National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2021–22. The NTN programs included (1) a field audit program to evaluate sample contamination and stability, (2) an interlaboratory-comparison program to evaluate analytical laboratory performance, and (3) a colocated sampler program to estimate overall variability of NTN wet-deposition measurements, and the MDN programs included the (4) system blank program to evaluate sample contamination and stability and (5) an interlaboratory-comparison program. The results indicated increased levels of sample contamination compared to previous years for NTN samples and decreased contamination in MDN samples. Strong analytical laboratory performance with low overall variability and bias in concentration data was indicated for the NTN Central Analytical Laboratory. Slight perturbations in contamination levels in NTN samples and in analytical performance for MDN are considered inconsequential. The colocated sampler program results indicated overall variability in NTN data to range from 0 to 30.3 percent for cations, 1.6 to 11.4 percent for ammonium, 0.8 to 20.2 percent for anions, 10.3 to 17.2 percent for hydrogen-ion concentration, and 1.5 to 12.2 percent for specific conductance. The PCQA results indicate that NADP data continue to be of sufficient quality for applications in independent research and NADP data products, including spatial interpolations and time trends for chemical constituents in wet deposition. Small shifts in data quality indicated by the 2021–22 PCQA results are included to be used for interpretation of the NADP data products.

Scientific Investigations Report↗
USGS2018

Separable correlation and maximum likelihood

We consider estimation of the covariance matrix of a multivariate normal distribution when the correlation matrix is separable in the sense that it factors as a Kronecker product of two smaller matrices. A computationally convenient coordinate descent-type algorithm is developed for maximum likelihood estimation. Simulations indicate our method often gives smaller estimation error than some common alternatives when correlation is separable, and that correctly sized tests for correlation separability can be obtained using a parametric bootstrap. Using dissolved oxygen data from the Upper Mississippi River, we illustrate how our model can lead to interesting scientific findings that may be missed when using competing models.

arXiv↗