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At least 73 records · Page 4Linked to original sources
USGS2017

User’s Manual for the National Water Information System of the U.S. Geological Survey: Aggregate Water-Use Data System, Version 3.2

The Aggregate Water-Use Data System (AWUDS) is the database management system used to enter, store, and analyze state aggregate water-use data. It is part of the U.S. Geological Survey National Water Information System. AWUDS has a graphical user interface that facilitates data entry, revision, review, and approval. This document provides information on the basic functions of AWUDS and the steps for carrying out common tasks that are a part of compiling an aggregated dataset. Also included are explanations of terminology and descriptions of user-interface structure, procedures for using the AWUDS operations, and dataset-naming conventions. Information on water-use category definitions, data-collection methods, and data sources are found in the report “Guidelines for preparation of State water-use estimates,” available at https://pubs.er.usgs.gov/publication/ofr20171029 .

Open-File Report↗
USGS2019

Distinguishing recent dispersal from historical genetic connectivity in the coastal California gnatcatcher

Habitat loss and fragmentation are primary threats to biodiversity worldwide. We studied the impacts of habitat loss and fragmentation on genetic connectivity and diversity among local aggregations of the California gnatcatcher ( Polioptila californica californica ) across its U.S. range. With a dataset of 268 individuals genotyped at 19 microsatellite loci, we analyzed genetic structure across the range using clustering analyses, exact tests for population differentiation, and a pedigree analysis to examine the spatial distribution of first-order relatives throughout the study area. In addition, we developed a habitat suitability model and related percent suitable habitat to genetic diversity indices within aggregations at two spatial scales. We detected a single genetic cluster across the range, with weak genetic structure among recently geographically isolated aggregations in the northern part of the range. The pedigree analysis detected closely related individuals across disparate aggregations and across large geographic distances in the majority of the sampled range, demonstrating that recent long-distance dispersal has occurred within this species. Genetic diversity was independent of suitable habitat at a local 5-km scale, but increased in a non-linear fashion with habitat availability at a broader, 30-km scale. Diversity declined steeply when suitable habitat within 30-km fell below 10%. Together, our results suggest that California gnatcatchers retain genetic connectivity across the majority of the current distribution of coastal sage scrub fragments, with the exception of some outlying aggregations. Connectivity may help support long-term persistence under current conservation and management strategies. However, emerging structure among more remote aggregations and associations between available habitat and genetic diversity also suggest that continued loss of habitat could threaten diversity and connectivity in the future.

California↗
USGS2009

The history of aggregate development in the Denver, CO area

At the start of the 20 th century Denver's population was 203,795. Most streets were unpaved. Buildings were constructed of wood frame or masonry. Transport was by horse-drawn-wagon or rail. Statewide, aggregate consumption was less than 0.25 metric tons per person per year. One hundred years later Denver had a population of 2,365,345. Today Denver is a major metropolitan area at the crossroads of two interstates, home to a new international airport, and in the process of expanding its light rail transit system. The skyline is punctuated with skyscrapers. The urban center is surrounded with edge cities. These changes required huge amounts of aggregate. Statewide, aggregate consumption increased 50 fold to over 13 metric tons per person per year. Denver has a large potential supply of aggregate, but sand and gravel quality decreases downstream from the mountain front and potential sources of crushed stone occur in areas prized for their scenic beauty. These issues, along with urban encroachment and citizen opposition, have complicated aggregate development and have paved a new path for future aggregate development including sustainable resource management and reclamation techniques.

Colorado↗
USGS2011

Adaptive management for a turbulent future

The challenges that face humanity today differ from the past because as the scale of human influence has increased, our biggest challenges have become global in nature, and formerly local problems that could be addressed by shifting populations or switching resources, now aggregate (i.e., "scale up") limiting potential management options. Adaptive management is an approach to natural resource management that emphasizes learning through management based on the philosophy that knowledge is incomplete and much of what we think we know is actually wrong. Adaptive management has explicit structure, including careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. It is evident that adaptive management has matured, but it has also reached a crossroads. Practitioners and scientists have developed adaptive management and structured decision making techniques, and mathematicians have developed methods to reduce the uncertainties encountered in resource management, yet there continues to be misapplication of the method and misunderstanding of its purpose. Ironically, the confusion over the term "adaptive management" may stem from the flexibility inherent in the approach, which has resulted in multiple interpretations of "adaptive management" that fall along a continuum of complexity and a priori design. Adaptive management is not a panacea for the navigation of 'wicked problems' as it does not produce easy answers, and is only appropriate in a subset of natural resource management problems where both uncertainty and controllability are high. Nonetheless, the conceptual underpinnings of adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex social-ecological systems, but management decisions must still be made, and whenever possible, we should incorporate learning into management. ?? 2010 .

Journal of Environmental Management↗
USGS2004

Discrimination among spawning aggregations of lake herring from Lake Superior using whole-body morphometric characters

The lake herring ( Coregonus artedi ) was one of the most commercially and ecologically valuable Lake Superior fishes, but declined in the second half of the 20th century as the result of overharvest of putatively discrete stocks. No tools were previously available that described lake herring stock structure and accurately classified lake herring to their spawning stocks. The accuracy of discriminating among spawning aggregations was evaluated using whole-body morphometrics based on a truss network. Lake herring were collected from 11 spawning aggregations in Lake Superior and two inland Wisconsin lakes to evaluate morphometrics as a stock discrimination tool. Discriminant function analysis correctly classified 53% of all fish from all spawning aggregations, and fish from all but one aggregation were classified at greater rates than were possible by chance. Discriminant analysis also correctly classified 66% of fish to nearest neighbor groups, which were groups that accounted for the possibility of mixing among the aggregations. Stepwise discriminant analysis showed that posterior body length and depth measurements were among the best discriminators of spawning aggregations. These findings support other evidence that discrete stocks of lake herring exist in Lake Superior, and fishery managers should consider all but one of the spawning aggregations as discrete stocks. Abundance, annual harvest, total annual mortality rate, and exploitation data should be collected from each stock, and surplus production of each stock should be estimated. Prudent management of stock surplus production and exploitation rates will aid in restoration of stocks and will prevent a repeat of the stock collapses that occurred in the middle of the 20th century, when the species was nearly extirpated from the lake.

Journal of Great Lakes Research↗
USGS2026

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Ohio↗
USGS2013

Research strategies for addressing uncertainties

There is an immense volume of information pertaining to research needs for addressing climate change uncertainties and resolving key information gaps. Fortunately, multiple independent efforts to establish research priorities have yielded similar results. Input on research needs is being used to craft national scientific priorities and strategies that are being implemented regionally by agencies and organizations. A number of regionally based efforts are already underway to aggregate and synthesize climate-related management needs and research priorities. Landscape Conservation Cooperatives and Climate Science Centers, funded by the Department of the Interior, are conducting strategic syntheses of common resource-management priorities and related science needs across the Southwest, and many of these priorities and needs are related to climate variability and change. The present Assessment includes many examples of the types of research that are needed to address key climate science uncertainties. The Assessment also includes examples of information needs related to understanding climate effects on systems (human, biophysical, ecosystems, and others) in the Southwest. Implementation of research strategies will increase understanding and improve the ability of the scientific community to anticipate the direction or magnitude of future climate-related change in these systems. The assembly of experts for the other chapters of this document provided a unique opportunity to draw upon the authors’ collective expertise to share knowledge about priority research strategies. The peer-reviewed information sources assessed in this chapter highlight research strategies and priorities established by the research community. Other sources cover priorities that are based primarily on management and policy needs. In the latter type, the sources represent the consensus of senior leaders of organizations, generally with substantial input and advice from the organizations’ technical and scientific experts.

Book chapter↗
USGS2026

Estimating GPS-based social aggregation metrics using collar data

Understanding social aggregation patterns in ungulate herds is essential for gaining behavioral insights, optimizing resource use, reducing human-wildlife conflict, and managing disease risk. As chronic wasting disease is the preeminent disease-related threat to cervid populations in North America, knowledge of contact between individuals and spatiotemporal patterns of aggregation provides opportunity to understand and potentially reduce disease risk while supporting sustainable population sizes. Herd density metrics, derived from global positioning system (GPS) data, can be used to inform management decisions. To effectively compare aggregation behavior within and between herds, aggregation metrics must be accurate. However, the consistency of metrics across different GPS collar sample sizes remains unclear and robust studies of big game require understanding how these factors may vary in different contexts. We examined the minimum sample size necessary for reliable calculations of three aggregation metrics: pairwise inter-animal distances, daily proximity rates, and kernel density estimate (KDE) areas. We used GPS collar data from the Jackson and West Green River elk herds ( Cervus canadensis ) in western Wyoming, USA, that differ in herd size and group structure (single versus multiple sub-groups), representing common practical contexts. Elk locations were acquired for the Jackson herd between 2016 and 2019 and from 2005 to 2010 for the West Green River herd. Herd-specific characteristics substantially influence the sample size necessary for accurate density measurements. As predicted, larger herds with many groups require more GPS collars than small herds with fewer groups. The sample size needed to accurately estimate aggregation varies by metric, with KDE areas, useful for indexing environmentally transmitted disease risk, generally requiring fewer samples, especially in high-density contexts. The required sample size also varies with seasonal changes in density. During periods of highest density, similar sample sizes are required to estimate inter-animal distances and proximity rates regardless of herd characteristics. Our results have implications for costs associated with studying big game herds, indicating fewer collars may be sufficient in some cases. These insights can aid researchers and managers in determining the appropriate number of GPS collars required for effective herd monitoring and informing relevant aggregation metrics for their management goals.

Wyoming↗
USGS2015

User-interactive sediment budgets in a browser: A web application for river science and management

Decision-support tools providing accurate, near-real-time data and user-friendly interactive visualizations are of critical value to resource managers tasked with planning and carrying out management programs in their domain. Creating a system to continuously aggregate datasets and recompute derived values is difficult and error-prone when attempted by hand. To address this need for river managers in support of sediment budgeting, we have created a web-based, open source suite of tools and processes that 1) continually aggregate data of interest, 2) recompute derived values based upon latest available data, and 3) update visualizations on-demand, providing simple front-end tools available to resource managers and the public. For the first time, engineers and scientists can access these tools freely over the web to assist them with planning and adaptive management decisions.

Conference Paper↗
USGS2003

Statistical, economic and other tools for assessing natural aggregate

Quantitative aggregate resource assessment provides resource estimates useful for explorationists, land managers and those who make decisions about land allocation, which may have long-term implications concerning cost and the availability of aggregate resources. Aggregate assessment needs to be systematic and consistent, yet flexible enough to allow updating without invalidating other parts of the assessment. Evaluators need to use standard or consistent aggregate classification and statistic distributions or, in other words, models with geological, geotechnical and economic variables or interrelationships between these variables. These models can be used with subjective estimates, if needed, to estimate how much aggregate may be present in a region or country using distributions generated by Monte Carlo computer simulations.

Bulletin of Engineering Geology and the Environmen↗
USGS2026

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment↗
USGS2023

Future-proofing the Emergency Recovery Plan for freshwater biodiversity

Freshwater biodiversity loss is accelerating globally, but humanity can change this trajectory through actions that enable recovery. To be successful, these actions require coordination and planning at a global scale. The Emergency Recovery Plan for global freshwater biodiversity aims to reduce the risk for freshwater biodiversity loss through six priority actions: (1) accelerate implementation of environmental flows; (2) improve water quality to sustain aquatic life; (3) protect and restore critical habitats; (4) manage exploitation of freshwater species and riverine aggregates; (5) prevent and control nonnative species invasions in freshwater habitats; and (6) safeguard and restore freshwater connectivity. These actions can be implemented using future-proofing approaches that anticipate future risks (e.g., emerging pollutants, new invaders, and synergistic effects) and minimize likely stressors to make conservation of freshwater biodiversity more resilient to climate change and other global environmental challenges. While uncertainty with respect to past observations is not a new concern for freshwater biodiversity, future-proofing has the distinction of accounting for the uncertainty of future conditions that have no historical baseline. The level of uncertainty with respect to future conditions is unprecedented. Future-proofing of the Emergency Recovery Plan for freshwater biodiversity will require anticipating future changes and developing and implementing actions to address those future changes. Here, we showcase future-proofing approaches likely to be successful using local case studies and examples. Ensuring that response options within the Emergency Recovery Plan are future-proofed will provide decision makers with science-informed choices, even in the face of uncertain and potentially new future conditions. We are at an inflection point for global freshwater biodiversity loss; learning from defeats and successes can support improved actions toward a sustainable future.

Environmental Reviews↗
USGS2013

Aggregation of carbon dioxide sequestration storage assessment units

The U.S. Geological Survey is currently conducting a national assessment of carbon dioxide (CO 2 ) storage resources, mandated by the Energy Independence and Security Act of 2007. Pre-emission capture and storage of CO 2 in subsurface saline formations is one potential method to reduce greenhouse gas emissions and the negative impact of global climate change. Like many large-scale resource assessments, the area under investigation is split into smaller, more manageable storage assessment units (SAUs), which must be aggregated with correctly propagated uncertainty to the basin, regional, and national scales. The aggregation methodology requires two types of data: marginal probability distributions of storage resource for each SAU, and a correlation matrix obtained by expert elicitation describing interdependencies between pairs of SAUs. Dependencies arise because geologic analogs, assessment methods, and assessors often overlap. The correlation matrix is used to induce rank correlation, using a Cholesky decomposition, among the empirical marginal distributions representing individually assessed SAUs. This manuscript presents a probabilistic aggregation method tailored to the correlations and dependencies inherent to a CO 2 storage assessment. Aggregation results must be presented at the basin, regional, and national scales. A single stage approach, in which one large correlation matrix is defined and subsets are used for different scales, is compared to a multiple stage approach, in which new correlation matrices are created to aggregate intermediate results. Although the single-stage approach requires determination of significantly more correlation coefficients, it captures geologic dependencies among similar units in different basins and it is less sensitive to fluctuations in low correlation coefficients than the multiple stage approach. Thus, subsets of one single-stage correlation matrix are used to aggregate to basin, regional, and national scales.

Stochastic Environmental Research and Risk Assessm↗
USGS2017

Estimating linear temporal trends from aggregated environmental monitoring data

Trend estimates are often used as part of environmental monitoring programs. These trends inform managers (e.g., are desired species increasing or undesired species decreasing?). Data collected from environmental monitoring programs is often aggregated (i.e., averaged), which confounds sampling and process variation. State-space models allow sampling variation and process variations to be separated. We used simulated time-series to compare linear trend estimations from three state-space models, a simple linear regression model, and an auto-regressive model. We also compared the performance of these five models to estimate trends from a long term monitoring program. We specifically estimated trends for two species of fish and four species of aquatic vegetation from the Upper Mississippi River system. We found that the simple linear regression had the best performance of all the given models because it was best able to recover parameters and had consistent numerical convergence. Conversely, the simple linear regression did the worst job estimating populations in a given year. The state-space models did not estimate trends well, but estimated population sizes best when the models converged. We found that a simple linear regression performed better than more complex autoregression and state-space models when used to analyze aggregated environmental monitoring data.

Ecological Indicators↗
USGS2024

Groundwater sustainability and land subsidence in California’s Central Valley

The Central Valley of California is one of the most prolific agricultural regions in the world. Agriculture is reliant on the conjunctive use of surface-water and groundwater. The lack of available surface-water and land-use changes have led to pumping-induced groundwater-level and storage declines, land subsidence, changes to streamflow and the environment, and the degradation of water quality. As a result, in part, the Sustainable Groundwater Management Act (SGMA) was developed. An examination of the components of SGMA and contextualizing regional model applications within the SGMA framework was undertaken to better understand and quantify many of the components of SGMA. Specifically, the U.S. Geological Survey (USGS) updated the Central Valley Hydrologic Model (CVHM) to assess hydrologic system responses to climatic variation, surface-water availability, land-use changes, and groundwater pumping. MODFLOW-OWHM has been enhanced to simulate the timing of land subsidence and attribute its inelastic and elastic portions. In addition to extending CVHM through 2019, the new version, CVHM2, includes several enhancements as follows: managed aquifer recharge (MAR), pumping with multi-aquifer wells, inflows from ungauged watersheds, and more detailed water-balance subregions, streamflow network, diversions, tile drains, land use, aquifer properties, and groundwater level and land subsidence observations. Combined with historical approximations, CVHM2 estimates approximately 158 km 3 of storage loss in the Central Valley from pre-development to 2019. About 15% of the total storage loss is permanent loss of storage from subsidence that has caused damage to infrastructure. Climate extremes will likely complicate the efforts of water managers to store more water in the ground. CVHM2 can provide data in the form of aggregated input datasets, simulate climatic variations and changes, land-use changes or water management scenarios, and resulting changes in groundwater levels, storage, and land subsidence to assist decision-makers in the conjunctive management of water supplies.

California↗
USGS2005

Chapter K: Progress in the Evaluation of Alkali-Aggregate Reaction in Concrete Construction in the Pacific Northwest, United States and Canada

The supply of aggregates suitable for use in construction and maintenance of infrastructure in western North America is a continuing concern to the engineering and resources-management community. Steady population growth throughout the region has fueled demand for high-quality aggregates, in the face of rapid depletion of existing aggregate resources and slow and difficult permitting of new sources of traditional aggregate types. In addition to these challenges, the requirement for aggregates to meet various engineering standards continues to increase. In addition to their physical-mechanical properties, other performance characteristics of construction aggregates specifically depend on their mineralogy and texture. These properties can result in deleterious chemical reactions when aggregate is used in concrete mixes. When this chemical reaction-termed 'alkali-aggregate reaction' (AAR)-occurs, it can pose a major problem for concrete structures, reducing their service life and requiring expensive repair or even replacement of the concrete. AAR is thus to be avoided in order to promote the longevity of concrete structures and to ensure that public moneys invested in infrastructure are well spent. Because the AAR phenomenon is directly related to the mineral composition, texture, and petrogenesis of the rock particles that make up aggregates, an understanding of the relation between the geology and the performance of aggregates in concrete is important. In the Pacific Northwest, some aggregates have a moderate to high AAR potential, but many others have no or only a low AAR potential. Overall, AAR is not as widespread or serious a problem in the Pacific Northwest as in other regions of North America. The identification of reactive aggregates in the Pacific Northwest and the accurate prediction of their behavior in concrete continue to present challenges for the assessment and management of geologic resources to the owners and operators of pits and quarries and to the users of the concrete aggregates mined from these deposits. This situation is complicated by the length of time typically required for AAR to become noticeable in concrete construction in the Pacific Northwest, commonly on such a scale that other deterioration mechanisms may have masked the effects of AAR. Distinguishing between the effects of AAR and those related to other problems in concrete is important for understanding the nature and severity of AAR throughout the Pacific Northwest. Furthermore, developing an understanding of the extent of the problem will assist efforts to maximize the intelligent and stewardly use of aggregate resources in the Pacific Northwest. This chapter illustrates the current 'state of the art' of AAR studies in the Pacific Northwest, a region with a common geologic heritage as well as many distinct geologic elements. The optimal use of aggregates in the construction of concrete structures that will achieve their design life is possible through an understanding of the engineering and geologic properties of these aggregates and of their geologic setting.

Bulletin↗
USGS2000

Dataset of aggregate producers in New Mexico

This report presents data, including latitude and longitude, for aggregate sites in New Mexico that were believed to be active in the period 1997-1999. The data are presented in paper form in Part A of this report and as Microsoft Excel 97 and Data Interchange Format (DIF) files in Part B. The work was undertaken as part of the effort to update information for the National Atlas. This compilation includes data from: the files of U.S. Geological Survey (USGS); company contacts; the New Mexico Bureau of Mines and Mineral Resources, New Mexico Bureau of Mine Inspection, and the Mining and Minerals Division of the New Mexico Energy, Minerals and Natural Resources Department (Hatton and others, 1998); the Bureau of Land Management Information; and direct communications with some of the aggregate operators. Additional information on most of the sites is available in Hatton and others (1998).

New Mexico↗