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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 397 records · Page 22Linked to original sources
USGS2013

Ecological prediction with nonlinear multivariate time-frequency functional data models

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Lower Missouri River↗
USGS2014

Organization of marine phenology data in support of planning and conservation in ocean and coastal ecosystems

Among the many effects of climate change is its influence on the phenology of biota. In marine and coastal ecosystems, phenological shifts have been documented for multiple life forms; however, biological data related to marine species' phenology remain difficult to access and is under-used. We conducted an assessment of potential sources of biological data for marine species and their availability for use in phenological analyses and assessments. Our evaluations showed that data potentially related to understanding marine species' phenology are available through online resources of governmental, academic, and non-governmental organizations, but appropriate datasets are often difficult to discover and access, presenting opportunities for scientific infrastructure improvement. The developing Federal Marine Data Architecture when fully implemented will improve data flow and standardization for marine data within major federal repositories and provide an archival repository for collaborating academic and public data contributors. Another opportunity, largely untapped, is the engagement of citizen scientists in standardized collection of marine phenology data and contribution of these data to established data flows. Use of metadata with marine phenology related keywords could improve discovery and access to appropriate datasets. When data originators choose to self-publish, publication of research datasets with a digital object identifier, linked to metadata, will also improve subsequent discovery and access. Phenological changes in the marine environment will affect human economics, food systems, and recreation. No one source of data will be sufficient to understand these changes. The collective attention of marine data collectors is needed—whether with an agency, an educational institution, or a citizen scientist group—toward adopting the data management processes and standards needed to ensure availability of sufficient and useable marine data to understand marine phenology.

Ecological Informatics↗
USGS2011

Social network models predict movement and connectivity in ecological landscapes

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Proceedings of the National Academy of Sciences of↗
USGS2017

PRISM software—Processing and review interface for strong-motion data

Rapidly available and accurate ground-motion acceleration time series (seismic recordings) and derived data products are essential to quickly providing scientific and engineering analysis and advice after an earthquake. To meet this need, the U.S. Geological Survey National Strong Motion Project has developed a software package called PRISM (Processing and Review Interface for Strong-Motion data). PRISM automatically processes strong-motion acceleration records, producing compatible acceleration, velocity, and displacement time series; acceleration, velocity, and displacement response spectra; Fourier amplitude spectra; and standard earthquake-intensity measures. PRISM is intended to be used by strong-motion seismic networks, as well as by earthquake engineers and seismologists.

Techniques and Methods↗
USGS2007

Modeling environmental bias and computing velocity field from data of Terra Nova Bay GPS network in Antarctica by means of a quasi-observation processing approach

A semi-permanent GPS network of about 30 vertices has been installed at Terra Nova Bay (TNB) near Ross Sea in Antarctica. A permanent GPS station TNB1 based on an Ashtech Z-XII dual frequency P-code GPS receiver with ASH700936D_M Choke Ring Antenna has been mounted on a reinforced concrete pillar built on bedrock since October 1998 and has recorded continuously up to the present. The semi-permanent network has been routinely surveyed every summer using high quality dual frequency GPS receivers with 24 hour sessions at 15 sec rate; data, metadata and solutions will be available to the scientific community at (http://www.geodant.unimore.it). We present the results of a distributed session approach applied to processing GPS data of the TNB GPS network, and based on Gamit/Globk 10.2-3 GPS analysis software. The results are in good agreement with other authors' computations and with many of the theoretical models.

Open-File Report↗
USGS2020

Sediments and the sea floor of the continental shelves and coastal waters of the United States—About the usSEABED integrated sea-floor-characterization database, built with the dbSEABED processing system

Since the second half of the 20th century, there has been an increase in scientific interest, research effort, and information gathered on the geologic sedimentary character of the continental margins of the United States. Data and information from thousands of sources have increased our scientific understanding of the character of the margin surface, but rarely have those data been combined and integrated. Initially, the U.S. Geological Survey (USGS), in cooperation with the Institute of Arctic and Alpine Research at the University of Colorado Boulder, created the usSEABED database to provide surficial sea-floor-characterization data for USGS assessments of marine-based aggregates and for studies of sea-floor habitat. Since then, the USGS has continued to build up the database as a nationwide resource for many uses and applications. Previously published data derived from the usSEABED database have been released as three USGS data series publications containing data covering the U.S. Atlantic margin, the Gulf of Mexico and Caribbean regions, and the Pacific coast. An updated USGS data release unifies the three publications, incorporates additional data and sources including data from Alaska, Hawaii, and U.S. overseas territories, and provides revised output files that fix known errors and add known or inferred sampling dates. This report accompanies the data release and contains information on the methodology and products of the usSEABED database.

Open-File Report↗
USGS2026

The Climate Hazards Center Infrared Precipitation with Stations, version 3

The Climate Hazards Center Infrared Precipitation with Stations (CHIRPS) data stream combines: (1) a high-resolution climatology, (2) thermal infrared (TIR) geostationary satellite observations, and (3) station observations. In the past, CHIRPS version 2 (CHIRPS2) has proven to be valuable for drought monitoring, hydrologic modeling, scientific studies and agricultural decision making. Version 3 (CHIRPS3) improves each of these components. The new version, CHIRPS3 extends to 60°S/N, adopts an improved variance-preserving TIR-to-precipitation estimation method, uses many more stations and station sources than the original CHIRPS2 product, and implements gauge-undercatch correction. In this paper, we evaluate the performance of satellite-only CHIRP3, CHIRP2, IMERG, PERSIANN- CCS, and GPI using high quality interpolated data in twelve regions with dense station coverage. CHIRP3 represents both the observed mean and variance more accurately than CHIRP2. A usage section in Morocco shows that CHIRPS3 better captures the observed rainfall variability when compared to CHIRPS2. This section also demonstrates how station data should be gauge-undercatch-corrected when validating CHIRPS3.

Scientific Data↗
USGS2007

Advances through collaboration: sharing seismic reflection data via the Antarctic Seismic Data Library System for Cooperative Research (SDLS)

The Antarctic Seismic Data Library System for Cooperative Research (SDLS) has served for the past 16 years under the auspices of the Antarctic Treaty (ATCM Recommendation XVI-12) as a role model for collaboration and equitable sharing of Antarctic multichannel seismic reflection (MCS) data for geoscience studies. During this period, collaboration in MCS studies has advanced deciphering the seismic stratigraphy and structure of Antarctica’s continental margin more rapidly than previously. MCS data compilations provided the geologic framework for scientific drilling at several Antarctic locations and for high-resolution seismic and sampling studies to decipher Cenozoic depositional paleoenvironments. The SDLS successes come from cooperation of National Antarctic Programs and individual investigators in “on-time” submissions of their MCS data. Most do, but some do not. The SDLS community has an International Polar Year (IPY) goal of all overdue MCS data being sent to the SDLS by end of IPY. The community science objective is to compile all Antarctic MCS data to derive a unified seismic stratigraphy for the continental margin – a stratigraphy to be used with drilling data to derive Cenozoic circum-Antarctic paleobathymetry maps and local-to-regional scale paleoenvironmental histories.

Open-File Report↗
USGS2022

Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model

Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture–recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears ( Ursus maritimus ) in a 28,125 km 2 survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture–recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from <0.75 bears/625 km 2 grid cell/day in nearshore cells to 1.6–2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124–250). Abundance estimates were similar to a previous multiyear integrated population model using capture–recapture and telemetry data (2008–2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR–movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR–movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.

eastern Chukchi Sea↗
USGS2023

Prioritizing science efforts to inform decision making on public lands

Public land management agencies in the US are committed to using science-informed decision making, but there has been little research on the types and topics of science that managers need most to inform their decisions. We used the National Environmental Policy Act to identify four types of science information needed for making decisions relevant to public lands: (1) data on resources of concern, (2) scientific studies relevant to potential effects of proposed actions, (3) methods for quantifying potential effects of proposed actions, and (4) effective mitigation measures. We then used this framework to analyze 70 Environmental Assessments completed by the Bureau of Land Management in Colorado. Commonly proposed actions were oil and gas development, livestock grazing, land transactions, and recreation. Commonly analyzed resources included terrestrial wildlife, protected birds, vegetation, and soils. Focusing research efforts on the intersection of these resources and actions, and on developing and evaluating the effectiveness of mitigation measures to protect these resources, could strengthen the science foundation for public lands decision making.

Frontiers in Ecology and the Environment↗
USGS2011

Geoinformatics in the public service: Building a cyberinfrastructure across the geological surveys

Advanced information technology infrastructure is increasingly being employed in the Earth sciences to provide researchers with efficient access to massive central databases and to integrate diversely formatted information from a variety of sources. These geoinformatics initiatives enable manipulation, modeling and visualization of data in a consistent way, and are helping to develop integrated Earth models at various scales, and from the near surface to the deep interior. This book uses a series of case studies to demonstrate computer and database use across the geosciences. Chapters are thematically grouped into sections that cover data collection and management; modeling and community computational codes; visualization and data representation; knowledge management and data integration; and web services and scientific workflows. Geoinformatics is a fascinating and accessible introduction to this emerging field for readers across the solid Earth sciences and an invaluable reference for researchers interested in initiating new cyberinfrastructure projects of their own.

Book chapter↗
USGS2021

Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty

Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales. We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data. Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product. The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.

Methods in Ecology and Evolution↗
USGS2023

Consolidated Appropriations Act, 2023—USGS disaster emergency recovery activities

Title VII of Division N in the Consolidated Appropriations Act, 2023 (Public Law 117–328), was enacted on December 29, 2022. The U.S. Geological Survey received $41.04 million in disaster emergency supplemental funding for repairing and replacing facilities and equipment, collecting high-resolution elevation data in affected areas, and completing scientific assessments to support direct recovery and rebuilding decisions in the wake of declared disasters related to hurricanes and typhoons in 2022.

Fact Sheet↗
USGS2003

Pallid sturgeon in the Lower Mississippi Region: Hematology and genome information

This project (Project 1448-43270-2M-002) has been coordinated through the Natchitoches National Fish Hatchery (NNFH) and the U.S. Geological Survey’s National Wetlands Research Center (NWRC). From November 2001 to April 2002, over 280 sturgeon of the genus Scaphirhynchus (including pallid sturgeon, shovelnose, and their hybrids) were sampled from the outflow channel of the Old River Control Structure Complex (ORCC) in Concordia Parish, La. In the overall project, several datasets were collected (see Appendix), including species identification by using microsatellites and morphometric characters, food habits, physical anomalies, information on blood cells, and pathologic evidence of iridovirus – the first indication in the lower Mississippi population of pallid sturgeon. In this study, data on blood cells were obtained from the sturgeon collected monthly from approximately 20 different animals at each sampling time. This report presents preliminary information on differential blood cell identifications in sturgeon, data on comparative genomic DNA content and DNA degradation, and summaries and interpretations of data collected in light of available scientific literature addressing blood parameters of fish and sturgeon, in particular. Results obtained from collection and examination of blood and body fluids are often essential in establishing the health of fish (Blaxhall, 1972; Fange, 1992). Blood cells and sperm cells can be obtained nondestructively from fishes, even from small specimens that weigh less than 100 g (Stoskopf, 1992a). For flow cytometry assays, whereby cells are analyzed individually in a fluid stream, less than 1 :L of blood is needed. Examinations of blood by microscopy and flow cytometry were performed at NWRC in assisting in the efforts directed at recovery of the pallid sturgeon population in the Lower Mississippi River Basin.

Open-File Report↗
USGS2014

Documentation for the 2014 update of the United States national seismic hazard maps

The national seismic hazard maps for the conterminous United States have been updated to account for new methods, models, and data that have been obtained since the 2008 maps were released (Petersen and others, 2008). The input models are improved from those implemented in 2008 by using new ground motion models that have incorporated about twice as many earthquake strong ground shaking data and by incorporating many additional scientific studies that indicate broader ranges of earthquake source and ground motion models. These time-independent maps are shown for 2-percent and 10-percent probability of exceedance in 50 years for peak horizontal ground acceleration as well as 5-hertz and 1-hertz spectral accelerations with 5-percent damping on a uniform firm rock site condition (760 meters per second shear wave velocity in the upper 30 m, V S30 ). In this report, the 2014 updated maps are compared with the 2008 version of the maps and indicate changes of plus or minus 20 percent over wide areas, with larger changes locally, caused by the modifications to the seismic source and ground motion inputs.

Open-File Report↗
USGS2012

Water-quality assessment of the Cambrian-Ordovician aquifer system in the northern Midwest, United States

This report provides a regional assessment of groundwater quality of the Cambrian-Ordovician aquifer system, based primarily on raw water samples collected by the NAWQA Program during 1995 through 2007. The NAWQA Program has published findings in local study-unit reports encompassing parts of the Cambrian-Ordovician aquifer system. Data collected from the aquifer system were used in national synthesis reports on selected topics such as specific water-quality constituent classes, well type, or aquifer material; however, a synthesis of groundwater quality at the principal aquifer scale has not been completed and is therefore the major purpose of this report. Water samples collected by the NAWQA Program were analyzed for various classes of characteristics including physical properties, major ions, trace elements, nutrients and dissolved organic carbon, radionuclides (tritium, radon, and radium), pesticides, and volatile organic compounds. Subsequent sections of this report provide discussions on these classes of characteristics. The assessment objectives of this report are to (1) summarize constituent concentrations and compare them to human-health benchmarks and non-health guidelines; (2) determine the geographic distribution of constituent concentrations and relate them to various factors such as confining conditions, well type, land use, and groundwater age; and (3) evaluate near-decadal-scale changes in nitrate concentrations and pesticide detections. The most recent sample collected from each well by the NAWQA Program was used for most analyses. Near-decadal-scale changes in nitrate concentrations and pesticide detections were evaluated for selected well networks by using the most recent sample from each well and comparing it to the results from a sample collected 7 or 11 years earlier. Because some of the NAWQA well networks provide a limited areal coverage of the aquifer system, data for raw water samples from other USGS sources and state agencies were included to expand the data coverage into areas between the NAWQA well networks and into northeastern Missouri. Many of the maps in this report that show concentrations of selected constituents include data from other sources to expand on the geographic area covered by the NAWQA data.

Midwest;Cambrian-ordovician Aquifer System↗
USGS2017

Estimated fecal coliform bacteria concentrations using near real-time continuous water-quality and streamflow data from five stream sites in Chester County, Pennsylvania, 2007–16

Several streams used for recreational activities, such as fishing, swimming, and boating, in Chester County, Pennsylvania, are known to have periodic elevated concentrations of fecal coliform bacteria, a type of bacteria used to indicate the potential presence of fecally related pathogens that may pose health risks to humans exposed through water contact. The availability of near real-time continuous stream discharge, turbidity, and other water-quality data for some streams in the county presents an opportunity to use surrogates to estimate near real-time concentrations of fecal coliform (FC) bacteria and thus provide some information about associated potential health risks during recreational use of streams. The U.S. Geological Survey (USGS), in cooperation with the Chester County Health Department (CCHD) and the Chester County Water Resources Authority (CCWRA), has collected discrete stream samples for analysis of FC concentrations during March–October annually at or near five gaging stations where near real-time continuous data on stream discharge, turbidity, and water temperature have been collected since 2007 (or since 2012 at 2 of the 5 stations). In 2014, the USGS, in cooperation with the CCWRA and CCHD, began to develop regression equations to estimate FC concentrations using available near real-time continuous data. Regression equations included possible explanatory variables of stream discharge, turbidity, water temperature, and seasonal factors calculated using Julian Day with base-10 logarithmic (log) transformations of selected variables. The regression equations were developed using the data from 2007 to 2015 (101–106 discrete bacteria samples per site) for three gaging stations on Brandywine Creek (West Branch Brandywine Creek at Modena, East Branch Brandywine Creek below Downingtown, and Brandywine Creek at Chadds Ford) and from 2012 to 2015 (37–38 discrete bacteria samples per site) for one station each on French Creek near Phoenixville and White Clay Creek near Strickersville. Fecal coliform bacteria data collected by USGS in 2016 (about nine samples per site) were used to validate the equations. The best-fit regression equations included log turbidity and seasonality factors computed using Julian Day as explanatory variables to estimate log FC concentrations at all five stream sites. The adjusted coefficient of determination for the equations ranged from 0.61 to 0.76, with the strength of the regression equations likely affected in part by the limited amount and variability of FC bacteria data. During summer months, the estimated and measured FC concentrations commonly were greater than the Pennsylvania Department of Environmental Protection established standards of 200 and 400 colonies per 100 milliliters for water contact from May through September at the 5 stream sites, with concentrations typically higher at 2 sites (White Clay Creek and West Branch Brandywine Creek at Modena) than at the other 3 sites. The estimated concentrations of FC bacteria during the summer months commonly were higher than measured concentrations and therefore could be considered cautious estimates of potential human-health risk. Additional water-quality data are needed to maintain and (or) improve the ability of regression equations to estimate FC concentrations by use of surrogate data.

Pennsylvania↗