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At least 451 records · Page 25Linked to original sources
USGS2007

The United States Polar Rock Repository: A geological resource for the Earth science community

The United States Polar Rock Repository (USPRR) is a U. S. national facility designed for the permanent curatorial preservation of rock samples, along with associated materials such as field notes, annotated air photos and maps, raw analytic data, paleomagnetic cores, ground rock and mineral residues, thin sections, and microfossil mounts, microslides and residues from Polar areas. This facility was established by the Office of Polar Programs at the U. S. National Science Foundation (NSF) to minimize redundant sample collecting, and also because the extreme cold and hazardous field conditions make fieldwork costly and difficult. The repository provides, along with an on-line database of sample information, an essential resource for proposal preparation, pilot studies and other sample based research that should make fieldwork more efficient and effective. This latter aspect should reduce the environmental impact of conducting research in sensitive Polar Regions. The USPRR also provides samples for educational outreach. Rock samples may be borrowed for research or educational purposes as well as for museum exhibits.

Open-File Report↗
USGS2020

Upper Mississippi River system weighted wind fetch analysis (1989, 2000, 2010/2011)

Wind fetch is defined as the unobstructed distance that wind can travel over water in a constant direction. Fetches are limited by landforms surrounding the body of water. Fetch is an important characteristic of open water because longer fetches can result in larger wind-generated waves. The larger waves, in turn, can increase shoreline erosion and sediment resuspension (Rohweder and others 2012). Increases in sediment resuspension lead to increases in water turbidity, which in turn decreases light penetration and, therefore, create conditions less conducive to aquatic plant growth (Giblin and others 2010). A wind fetch model was developed by David Finlayson, U. S. Geological Survey, Pacific Science Center, while he was a Ph.D. student at the University of Washington (Finlayson 2005). This method calculates effective fetch using the recommended procedure of the Shore Protection Manual (USACE 1984). Scientists at the United States Geological Survey, Upper Midwest Environmental Sciences Center (UMESC) and the United States Army Corps of Engineers (USACE) further refined this model (Rohweder and others 2012) and structured it to operate using the most recent version of the ArcMap Geographic Information System platform (Esri, 2019). At the time the analysis was performed, the version of ArcMap used was 10.7.1. The model refined in 2012 was used for the analyses described in this report. Using this model, UMESC performed an analysis to model weighted wind fetch for the Upper Mississippi River System (UMRS) corresponding to three separate time periods of land cover spatial data acquisition (1989, 2000, and 2010/2011). The purpose of the analysis was to examine how fetch varies over time and space within the UMRS for potential management applications. For more detailed information on the wind fetch model, examine the USGS Open-File Report by Rohweder and others (2012).

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2005

Climate science and famine early warning

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Philosophical Transactions of the Royal Society B:↗
USGS2007

U.S. Geological Survey Mineral Resources Program - Science Supporting Mineral Resource Stewardship

The United States is the world's largest user of mineral resources. We use them to build our homes and cities, fertilize our food crops, and create wealth that allows us to buy goods and services. Individuals rarely use nonfuel mineral resources in their natural state - we buy light bulbs, not the silica, soda ash, lime, coal, salt, tungsten, copper, nickel, molybdenum, iron, manganese, aluminum, and zinc used to convert electricity into light. The USGS Mineral Resources Program (MRP) is the sole Federal source of scientific information and unbiased research on nonfuel mineral potential, production, and consumption, as well as on the environmental effects of minerals. The MRP also provides baseline geochemical, geophysical, and mineral-deposit data used to understand environmental issues related to extraction and use of mineral resources. Understanding how minerals, water, plants, and organisms interact contributes to our understanding of the environment, which is essential for maintaining human and ecosystem health. To support creation of economic and national security policies in a global context, MRP collects and analyzes data on essential mineral commodities from around the world.

Fact Sheet↗
USGS2015

Citizen science contributes to our knowledge of invasive plant species distributions

Citizen science is commonly cited as an effective approach to expand the scale of invasive species data collection and monitoring. However, researchers often hesitate to use these data due to concerns over data quality. In light of recent research on the quality of data collected by volunteers, we aimed to demonstrate the extent to which citizen science data can increase sampling coverage, fill gaps in species distributions, and improve habitat suitability models compared to professionally generated data sets used in isolation. We combined data sets from professionals and volunteers for five invasive plant species ( Alliaria petiolata , Berberis thunbergii , Cirsium palustre , Pastinaca sativa , Polygonum cuspidatum ) in portions of Wisconsin. Volunteers sampled counties not sampled by professionals for three of the five species. Volunteers also added presence locations within counties not included in professional data sets, especially in southern portions of the state where professional monitoring activities had been minimal. Volunteers made a significant contribution to the known distribution, environmental gradients sampled, and the habitat suitability of P. cuspidatum . Models generated with professional data sets for the other four species performed reasonably well according to AUC values (>0.76). The addition of volunteer data did not greatly change model performance (AUC > 0.79) but did change the suitability surface generated by the models, making them more realistic. Our findings underscore the need to merge data from multiple sources to improve knowledge of current species distributions, and to predict their movement under present and future environmental conditions. The efficiency and success of these approaches require that monitoring efforts involve multiple stakeholders in continuous collaboration via established monitoring networks.

Wisconsin↗
USGS2007

Summary of the Ground-Water-Level Hydrologic Conditions in New Jersey 2006

Ground water is one of the Nation's most important natural resources. It provides about 40 percent of our Nation's public water supply. Currently, nearly one-half of New Jersey's drinking-water is supplied by over 300,000 wells that serve more than 4.3 million people (John P. Nawyn, U.S. Geological Survey, written commun., 2007). New Jersey's population is projected to grow by more than a million people by 2030 (U.S. Census Bureau, accessed March 2, 2006, at http://www.census.gov). As demand for water increases, managing the development and use of the ground-water resource so that the supply can be maintained for an indefinite time without causing unacceptable environmental, economic, or social consequences is of paramount importance. This report describes the U.S. Geological Survey (USGS) New Jersey Water Science Center Observation Well Networks. Record low ground-water levels during water year 2006 (October 1, 2005 to September 30, 2006) are listed, and water levels in six selected water-table observation wells and three selected confined wells are shown in hydrographs. The report describes the trends in water levels in various confined aquifers in southern New Jersey and in water-table and fracture rock aquifers throughout the State. Web site addresses to access the data also are included. The USGS has operated a network of observation wells in New Jersey since 1923 for the purpose of monitoring ground-water-level changes throughout the State. Long-term systematic measurement of water levels in observation wells provides the data needed to evaluate changes in the ground-water resource over time. Records of ground-water levels are used to evaluate the effects of climate changes and water-supply development, to develop ground-water models, and to forecast trends.

Fact Sheet↗
USGS2017

Science programs in Kansas

The U.S. Geological Survey (USGS) is a non-regulatory Earth science agency within the Department of the Interior that provides impartial scientific information to describe and understand the health of our ecosystems and environment; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life. The USGS cooperates with Federal, State, tribal, and local agencies in Kansas to deliver long-term data in real-time and interpretive reports describing what those data mean to the public and resource management agencies. USGS science programs in Kansas provide real-time groundwater monitoring at more than 19 locations; streamflow monitoring at more than 216 locations; water-quality and trends in the Little Arkansas and Kansas Rivers; inflows and outflows of sediment to/from reservoirs and in streams; harmful algal bloom research in the Kansas River, Milford Lake, and Cheney Reservoir; water-quantity and water-quality effects of artificial groundwater recharge for the Equus Beds Aquifer Storage and Recovery project near Wichita, Kansas; compilation of Kansas municipal and irrigation water-use data statewide; the occurrence, effects, and movement of environmental pesticides, antibiotics, algal toxins, and taste-and-odor compounds; and funding to the Kansas Water Resources Research Institute to further research and education through Kansas universities.

Kansas↗
USGS2012

The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration

Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policy-makers are faced with countless decisions each year at local, state, tribal, territorial, and national levels on issues as diverse as renewable and non-renewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decision-making is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and well-being of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decision-makers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that USGS scientists and partners can play in building scientific understanding and providing timely information to decision-makers. The strategy underscores the connection between scientific discoveries and the application of new knowledge. The strategy integrates ecosystem science and decision-making, producing new scientific outcomes to assist resource managers and providing public benefits. The USGS is uniquely positioned to play an important role in ecosystem science. With its wide range of expertise, the agency can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the DOI and other partners in the natural sciences, in both conducting science and its application. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework and vision for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected and reinforcing components: • Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. • Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. • Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. • Develop tools, technologies, and capacities to inform decision-making about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. • Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: • Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. • Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. • Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. • Support decision-making. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the strategic approaches are a set of proposed actions that represent a sampling of specific activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct both discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role over the next decade in advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Open-File Report↗
USGS2025

Adapting visitor use management under a changing climate across the U.S. National Park System

Research shows that climate change is already affecting both resources and visitors in U.S. National Parks. We sought to better understand if and how park staff across the National Park Service are adapting to climatic changes that affect visitor use, as well as barriers and challenges to adaptation and information needs. We conducted semi-structured qualitative interviews with 63 staff from 31 representative national park units across the United States. We qualitatively coded interviews for themes using deductive and inductive coding approaches. Results indicate that park staff are already taking action to adapt to changes that are affecting visitor use, including efforts to increase resiliency of infrastructure and to support the health and safety of visitors (e.g., increased communication, preventative search and rescue, changes to programming). Common barriers and challenges include institutional factors (such as funding, staffing capacity, and shifting priorities), uncertainty about future conditions, and difficulties with prioritizing climate adaptation. Data, tool, and information needs varied, but commonly included social science data such as visitor surveys, and tools to help synthesize and standardize information and help translate science into action. These results provide insights into current actions park staff are taking to adapt to climate change and what resources may be helpful in the future to lower the challenges and barriers to adaptation.

Journal of Environmental Management↗
USGS2022

GeoImageNet: A multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

The field of GeoAI or Geospatial Artificial Intelligence has undergone rapid development since 2017. It has been widely applied to address environmental and social science problems, from understanding climate change to tracking the spread of infectious disease. A foundational task in advancing GeoAI research is the creation of open, benchmark datasets to train and evaluate the performance of GeoAI models. While a number of datasets have been published, very few have centered on the natural terrain and its landforms. To bridge this gulf, this paper introduces a first-of-its-kind benchmark dataset, GeoImageNet, which supports natural feature detection in a supervised machine-learning paradigm. A distinctive feature of this dataset is the fusion of multi-source data, including both remote sensing imagery and DEM in depicting spatial objects of interest. This multi-source dataset allows a GeoAI model to extract rich spatio-contextual information to gain stronger confidence in high-precision object detection and recognition. The image dataset is tested with a multi-source GeoAI extension against two well-known object detection models, Faster-RCNN and RetinaNet. The results demonstrate the robustness of the dataset in aiding GeoAI models to achieve convergence and the superiority of multi-source data in yielding much higher prediction accuracy than the commonly used single data source.

GeoInformatica↗
USGS2020

Altitude of the potentiometric surface in the Mississippi River Valley alluvial aquifer, spring 2018

A potentiometric-surface map for spring 2018 was created for the Mississippi River Valley alluvial (MRVA) aquifer using available groundwater-altitude data from 1,126 wells completed in the MRVA aquifer and from the altitude of the top of the water surface in area rivers from 66 streamgages. Personnel from Arkansas Natural Resources Commission, Arkansas Department of Health, Arkansas Geological Survey, Illinois Department of Agriculture, Illinois State Water Survey, Louisiana Department of Natural Resources, Louisiana Department of Transportation and Development, Mississippi Department of Environmental Quality, Missouri Department of Natural Resources, Yazoo Mississippi Delta Joint Water Management District, U.S. Department of Agriculture-Natural Resources Conservation Service, and U.S. Geological Survey (USGS) routinely collect groundwater-level data from wells screened in the MRVA aquifer. The USGS and the U.S. Army Corps of Engineers routinely collect data on river stage and streamflow for the rivers overlying the MRVA aquifer area. The potentiometric-surface map for 2018 was created utilizing existing groundwater and surface-water altitudes to support investigations to characterize the MRVA aquifer as part of the USGS Water Availability and Use Science Program. Sufficient data were available to map the potentiometric surface of the MRVA aquifer for spring 2018 for about 87 percent of the aquifer area. The potentiometric contours ranged from 10 to 340 feet above North American Vertical Datum of 1988. The regional direction of groundwater flow was generally to the south-southwest, except in areas of groundwater-altitude depressions, where groundwater flowed into the depression, and near rivers, where flow can be from aquifer to the river or from the river into the aquifer. There are large depressions in the potentiometric-surface map in the lower one-half of the Cache region and in most of the Grand Prairie and Delta regions.

Mississippi River Valley alluvial aquifer↗
USGS2013

Groundwater ages and mixing in the Piceance Basin natural gas province, Colorado

Reliably identifying the effects of energy development on groundwater quality can be difficult because baseline assessments of water quality completed before the onset of energy development are rare and because interactions between hydrocarbon reservoirs and aquifers can be complex, involving both natural and human processes. Groundwater age and mixing data can strengthen interpretations of monitoring data from those areas by providing better understanding of the groundwater flow systems. Chemical, isotopic, and age tracers were used to characterize groundwater ages and mixing with deeper saline water in three areas of the Piceance Basin natural gas province. The data revealed a complex array of groundwater ages (<10 to >50,000 years) and mixing patterns in the basin that helped explain concentrations and sources of methane in groundwater. Age and mixing data also can strengthen the design of monitoring programs by providing information on time scales at which water quality changes in aquifers might be expected to occur. This information could be used to establish maximum allowable distances of monitoring wells from energy development activity and the appropriate duration of monitoring.

Colorado↗
USGS2022

Deep learning detection and recognition of spot elevations on historic topographic maps

Some information contained in historical topographic maps has yet to be captured digitally, which limits the ability to automatically query such data. For example, U.S. Geological Survey’s historical topographic map collection (HTMC) displays millions of spot elevations at locations that were carefully chosen to best represent the terrain at the time. Although research has attempted to reproduce these data points, it has proven inadequate to automatically detect and recognize spot elevations in the HTMC. We propose a deep learning workflow pretrained using large benchmark text datasets. To these datasets we add manually crafted training image/label pairs, and test how many are required to improve prediction accuracy. We find that the initial model, pretrained solely with benchmark data, fails to predict any HTMC spot elevations correctly, whereas the addition of just 50 custom image/label pairs increases the predictive ability by ~50%, and the inclusion of 350 data pairs increased performance by ~80%. Data augmentation in the form of rotation, scaling and translation (offset) expanded the size and diversity of the training dataset and vastly improved recognition accuracy up to ~95%. Visualization methods, such as heat map generation and salient feature detection are recommended to better understand why some predictions fail.

Frontiers in Environmental Science↗
USGS2006

Influence of dams and habitat condition on the distribution of redhorse (Moxostoma) species in the Grand River watershed, Ontario

Redhorse, Moxostoma spp., are considered to be negatively affected by dams although this assertion is untested for Canadian populations. One hundred and fifty-one sites in the Grand River watershed were sampled to identify factors influencing the distribution of redhorse species. Individual species of redhorse were captured from 3 to 32% of sites. The most widespread species were golden redhorse, M. erythrurum (30%) and greater redhorse, M. valenciennesi (32%), while river redhorse, M. carinatum, was only found along the lower Grand River. Redhorse were absent from the highly fragmented Speed River sub-watershed and upper reaches of the Conestogo River and the Grand River. Redhorse species richness was positively correlated to river fragment size and upstream drainage area. Generalized additive models (GAMs) were applied to evaluate the influence of river fragment length, connectivity and habitat on species distribution. Principal component analysis reduced habitat data to three axes representing: channel structure, substrate, and pool, riffle and run habitats (PC1); gradient and drainage area (PC2); and cover (PC3). GAMs indicate that PC2 was important for predicting black redhorse and greater redhorse site occupancy and PC1 was important for golden redhorse. River fragment length was important for predicting site occupancy for shorthead redhorse, but not other species. ?? 2006 Springer Science+Business Media, Inc.

Environmental Biology of Fishes↗
USGS1998

Inexpensive automated paging system for use at remote research sites

The use of a flow-activated automatic sampler at a remote research site required personnel to periodically visit the site to collect samples and reset the automatic sampler. To reduce site visits, a cellular telephone was modified for activation by a datalogger. The purpose of this study was to demonstrate the use and benefit of the modified telephone. Both the power switch and the speed-dial button on the telephone were bypassed and wired to a relay driver. The datalogger was programmed to compare values of a monitored environmental parameter with a target value. When the target value was reached or exceeded, the datalogger pulsed a relay driver, activating power to the telephone. A separate relay activated the speed dial, dialing the number of a tone-only pager. The use of this system has saved time and reduced travel costs by reducing the number of trips to the site, without the loss of any data.The use of a flow-activated automatic sampler at a remote research site required personnel to periodically visit the site to collect samples and reset the automatic sampler. To reduce site visits, a cellular telephone was modified for activation by a datalogger. The purpose of this study was to demonstrate the use and benefit of the modified telephone. Both the power switch and the speed-dial button on the telephone were bypassed and wired to a relay driver. The datalogger was programmed to compare values of a monitored environmental parameter with a target value. When the target value was reached or exceeded, the datalogger pulsed a relay driver, activating power to the telephone. A separate relay activated the speed dial, dialing the number of a tone-only pager. The use of this system has saved time and reduced travel costs by reducing the number of trips to the site, without the loss of any data.

Soil Science Society of America Journal↗
USGS2020

Moving beyond p<0.05 in ecotoxicology: A guide for practitioners

Statistical inferences play a critical role in ecotoxicology. Historically, Null Hypothesis Significance Testing (NHST) has been the dominant method for inference in ecotoxicology. As a brief and informal definition of the NHST approach, researchers compare (or test) an experimental treatment or observation against a hypothesis of no relationship or effect (the null hypothesis) using the collected data to see if the observed values are statistically significant given predefined error rates. The resulting probability of observing a value equal to or greater than the observed value assuming the null hypothesis is true is the p-value. Historically, criticisms of NHST have existed for almost a century and more recently these have grown to the point where statisticians, including the American Statistical Association, have felt the need to clarify the role of NHST and p-values in science beyond their current, common use. These limitations also exist in ecotoxicology. For example, a review of the 2010 Environmental Toxicology & Chemistry (ET&C) volume found many authors did not correctly report p-values. We repeated this review looking at the 2019 volume of ET&C and the incorrect reporting of p-values still occurred almost a decade later. Problems with NHST and p-values highlight the need for statistical inferences besides NHST, something that has long been known in ecotoxicology and the broader scientific and statistical communities. Furthermore, concerns such as these led the Executive Director of the American Statistical Association to recommend against use of statistical significance in 2019. In light of these criticisms, however, ecotoxicologists require alternative methods. In this paper, we describe some alternative methods including confidence intervals, regression analysis, dose-response curves, Bayes factors, survival analysis, and model selection. Lastly, we provide insights for what ecotoxicology might look like in a post-p-value world.

Environmental Toxicology and Chemistry↗
USGS2014

Methane hydrates in nature - Current knowledge and challenges

Recognizing the importance of methane hydrate research and the need for a coordinated effort, the United States Congress enacted the Methane Hydrate Research and Development Act of 2000. At the same time, the Ministry of International Trade and Industry in Japan launched a research program to develop plans for a methane hydrate exploratory drilling project in the Nankai Trough. India, China, the Republic of Korea, and other nations also have established large methane hydrate research and development programs. Government-funded scientific research drilling expeditions and production test studies have provided a wealth of information on the occurrence of methane hydrates in nature. Numerous studies have shown that the amount of gas stored as methane hydrates in the world may exceed the volume of known organic carbon sources. However, methane hydrates represent both a scientific and technical challenge, and much remains to be learned about their characteristics and occurrence in nature. Methane hydrate research in recent years has mostly focused on: (1) documenting the geologic parameters that control the occurrence and stability of methane hydrates in nature, (2) assessing the volume of natural gas stored within various methane hydrate accumulations, (3) analyzing the production response and characteristics of methane hydrates, (4) identifying and predicting natural and induced environmental and climate impacts of natural methane hydrates, (5) analyzing the methane hydrate role as a geohazard, (6) establishing the means to detect and characterize methane hydrate accumulations using geologic and geophysical data, and (7) establishing the thermodynamic phase equilibrium properties of methane hydrates as a function of temperature, pressure, and gas composition. The U.S. Department of Energy (DOE) and the Consortium for Ocean Leadership (COL) combined their efforts in 2012 to assess the contributions that scientific drilling has made and could continue to make to advance our understanding of methane hydrates in nature. COL assembled a Methane Hydrate Project Science Team with members from academia, industry, and government. This Science Team worked with COL and DOE to develop and host the Methane Hydrate Community Workshop, which surveyed a substantial cross section of the methane hydrate research community for input on the most important research developments in our understanding of methane hydrates in nature and their potential role as an energy resource, a geohazard, and/or as an agent of global climate change. Our understanding of how methane hydrates occur in nature is still growing and evolving, and it is known with certainty that field, laboratory, and modeling studies have contributed greatly to our understanding of hydrates in nature and will continue to be a critical source of the information needed to advance our understanding of methane hydrates.

Journal of Chemical and Engineering Data↗
USGS2015

Sea-level rise modeling handbook: Resource guide for coastal land managers, engineers, and scientists

Global sea level is rising and may accelerate with continued fossil fuel consumption from industrial and population growth. In 2012, the U.S. Geological Survey conducted more than 30 training and feedback sessions with Federal, State, and nongovernmental organization (NGO) coastal managers and planners across the northern Gulf of Mexico coast to evaluate user needs, potential benefits, current scientific understanding, and utilization of resource aids and modeling tools focused on sea-level rise. In response to the findings from the sessions, this sea-level rise modeling handbook has been designed as a guide to the science and simulation models for understanding the dynamics and impacts of sea-level rise on coastal ecosystems. The review herein of decision-support tools and predictive models was compiled from the training sessions, from online research, and from publications. The purpose of this guide is to describe and categorize the suite of data, methods, and models and their design, structure, and application for hindcasting and forecasting the potential impacts of sea-level rise in coastal ecosystems. The data and models cover a broad spectrum of disciplines involving different designs and scales of spatial and temporal complexity for predicting environmental change and ecosystem response. These data and models have not heretofore been synthesized, nor have appraisals been made of their utility or limitations. Some models are demonstration tools for non-experts, whereas others require more expert capacity to apply for any given park, refuge, or regional application. A simplified tabular context has been developed to list and contrast a host of decision-support tools and models from the ecological, geological, and hydrological perspectives. Criteria were established to distinguish the source, scale, and quality of information input and geographic datasets; physical and biological constraints and relations; datum characteristics of water and land components; utility options for setting sea-level rise and climate change scenarios; and ease or difficulty of storing, displaying, or interpreting model output. Coastal land managers, engineers, and scientists can benefit from this synthesis of tools and models that have been developed for projecting causes and consequences of sea-level change on the landscape and seascape.

Professional Paper↗