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At least 451 records · Page 25Linked to original sources
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↗
USGS2012

Simulation of climate change in San Francisco Bay Basins, California: Case studies in the Russian River Valley and Santa Cruz Mountains

As a result of ongoing changes in climate, hydrologic and ecologic effects are being seen across the western United States. A regional study of how climate change affects water resources and habitats in the San Francisco Bay area relied on historical climate data and future projections of climate, which were downscaled to fine spatial scales for application to a regional water-balance model. Changes in climate, potential evapotranspiration, recharge, runoff, and climatic water deficit were modeled for the Bay Area. In addition, detailed studies in the Russian River Valley and Santa Cruz Mountains, which are on the northern and southern extremes of the Bay Area, respectively, were carried out in collaboration with local water agencies. Resource managers depend on science-based projections to inform planning exercises that result in competent adaptation to ongoing and future changes in water supply and environmental conditions. Results indicated large spatial variability in climate change and the hydrologic response across the region; although there is warming under all projections, potential change in precipitation by the end of the 21st century differed according to model. Hydrologic models predicted reduced early and late wet season runoff for the end of the century for both wetter and drier future climate projections, which could result in an extended dry season. In fact, summers are projected to be longer and drier in the future than in the past regardless of precipitation trends. While water supply could be subject to increased variability (that is, reduced reliability) due to greater variability in precipitation, water demand is likely to steadily increase because of increased evapotranspiration rates and climatic water deficit during the extended summers. Extended dry season conditions and the potential for drought, combined with unprecedented increases in precipitation, could serve as additional stressors on water quality and habitat. By focusing on the relationship between soil moisture storage and evapotranspiration pressures, climatic water deficit integrates the effects of increasing temperature and varying precipitation on basin conditions. At the fine-scale used for these analyses, this variable is an effective indicator of the areas in the landscape that are the most resilient or vulnerable to projected changes. These analyses have shown that regardless of the direction of precipitation change, climatic water deficit is projected to increase, which implies greater water demand to maintain current agricultural resources or land cover. Fine-scale modeling provides a spatially distributed view of locations in the landscape that could prove to be resilient to climatic changes in contrast to locations where vegetation is currently living on the edge of its present-day bioclimatic distribution and, therefore, is more likely to perish or shift to other dominant species under future warming. This type of modeling and the associated analyses provide a useful means for greater understanding of water and land resources, which can lead to better resource management and planning.

California↗
USGS2012

Using geochemistry to identify the source of groundwater to Montezuma Well, a natural spring in Central Arizona, USA: Part 2

Montezuma Well is a unique natural spring located in a sinkhole surrounded by travertine. Montezuma Well is managed by the National Park Service, and groundwater development in the area is a potential threat to the water source for Montezuma Well. This research was undertaken to better understand the sources of groundwater to Montezuma Well. Strontium isotopes ( 87 Sr/ 86 Sr) indicate that groundwater in the recharge area has flowed through surficial basalts with subsequent contact with the underlying Permian aged sandstones and the deeper, karstic, Mississippian Redwall Limestone. The distinctive geochemistry in Montezuma Well and nearby Soda Springs (higher concentrations of alkalinity, As, B, Cl, and Li) is coincident with added carbon dioxide and mantle-sourced He. The geochemistry and isotopic data from Montezuma Well and Soda Springs allow for the separation of groundwater samples into four categories: (1) upgradient, (2) deep groundwater with carbon dioxide, (3) shallow Verde Formation, and (4) mixing zone. δ 18 O and δD values, along with noble gas recharge elevation data, indicate that the higher elevation areas to the north and east of Montezuma Well are the groundwater recharge zones for Montezuma Well and most of the groundwater in this portion of the Verde Valley. Adjusted groundwater age dating using likely 14 C and δ 13 C sources indicate an age for Montezuma Well and Soda Springs groundwaters at 5,400–13,300 years, while shallow groundwater in the Verde Formation appears to be older (18,900). Based on water chemistry and isotopic evidence, groundwater flow to Montezuma Well is consistent with a hydrogeologic framework that indicates groundwater flow by (1) recharge in higher elevation basalts to the north and east of Montezuma Well, (2) movement through the upgradient Permian and Mississippian units, especially the Redwall Limestone, and (3) contact with a basalt dike/fracture system that provides a mechanism for groundwater to flow to the surface. While the exact nature of the groundwater flow connections is still uncertain, the available data indicate that flow to Montezuma Well may be more susceptible to future groundwater development in the Redwall Limestone than from any other geologic unit. Overall, the shallow groundwater in the surrounding Verde Formation appears to be largely disconnected from deeper groundwater flowing to Montezuma Well.

Arizona↗
USGS1999

Assessing the influence of reacting pyrite and carbonate minerals on the geochemistry of drainage in the Coeur d'Alene mining district

The relative abundance of minerals that react to generate or consume acid in mineralized areas is critical in determining the quality of water draining from such areas. This work examines the fundamental reactions that influence the pH and composition of drainage from mine adits and tailings piles. We construct triangle diagrams that predict stoichiometric relationships between concentrations of dissolved SO4 dissolved Ca and Mg, and either alkalinity or acidity by considering reactions involving the oxidation of pyrite, dissolution of carbonate minerals, and precipitation of iron oxide and iron hydroxysulfate minerals. Drainage data from the Coeur d'Alene mining district are used to test our stoichiometric approach. Comparisons between theoretical predictions and drainage data indicate that the range of pH values in the mining district is due to reacting pyrite to carbonate mineral ratios that range from near 0/1 to 1/1. Calcite and ankerite are the dominant carbonate minerals that buffer the acid produced during pyrite oxidation and ferrihydrite or schwertmannite precipitation.The relative abundance of minerals that react to generate or consume acid in mineralized areas is critical in determining the quality of water draining from such areas. This work examines the fundamental reactions that influence the pH and composition of drainage from mine adits and tailings piles. We construct triangle diagrams that predict stoichiometric relationships between concentrations of dissolved SO4, dissolved Ca and Mg, and either alkalinity or acidity by considering reactions involving the oxidation of pyrite, dissolution of carbonate minerals, and precipitation of iron oxide and iron hydroxysulfate minerals. Drainage data from the Coeur d'Alene mining district are used to test our stoichiometric approach. Comparisons between theoretical predictions and drainage data indicate that the range of pH values in the mining district is due to reacting pyrite to carbonate mineral ratios that range from near 0/1 to 1/1. Calcite and ankerite are the dominant carbonate minerals that buffer the acid produced during pyrite oxidation and ferrihydrite or schwertmannite precipitation.

Idaho↗
USGS2008

Decadal-scale changes of nitrate in ground water of the United States, 1988-2004

This study evaluated decadal-scale changes of nitrate concentrations in groundwater samples collected by the USGS National Water-Quality Assessment Program from 495 wells in 24 well networks across the USA in predominantly agricultural areas. Each well network was sampled once during 1988-1995 and resampled once during 2000-2004. Statistical tests of decadal-scale changes of nitrate concentrations in water from all 495 wells combined indicate there is a significant increase in nitrate concentrations in the data set as a whole. Eight out of the 24 well networks, or about 33%, had significant changes of nitrate concentrations. Of the eight well networks with significant decadal-scale changes of nitrate, all except one, the Willamette Valley of Oregon, had increasing nitrate concentrations. Median nitrate concentrations of three of those eight well networks increased above the USEPA maximum contaminant level of 10 mg L-1. Nitrate in water from wells with reduced conditions had significantly smaller decadal-scale changes in nitrate concentrations than oxidized and mixed waters. A subset of wells had data on ground water recharge date; nitrate concentrations increased in response to the increase of N fertilizer use since about 1950. Determining ground water recharge dates is an important component of a ground water trends investigation because recharge dates provide a link between changes in ground water quality and changes in land-use practices. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗
USGS2006

Interdisciplinary science in support of environmental health along the United States-Mexico border

The diverse, fragile ecosystems of the borderlands have been pushed beyond sustainable levels due to rapid population growth and land-use changes. Water shortages and pollution, poor air quality, increased soil salinities, residual pesticides and heavy metal contaminants are some of the many stressors that are degrading the quality of life in the borderlands. The relationship between human health and environmental quality challenges public officials, medical professionals, and resource managers on both sides of the border in their efforts to provide for and maintain healthy communities. To help understand the relationship between environmental and human health, the U.S. Geological Survey's (USGS) Border Environmental Health Initiative (BEHI) created an Internet Map Service (IMS) with binational georeferenced data. The goal is to have seamless integration of borderwide datasets at regional and local scales that can lend understanding of the linkages between the condition of the physical environment and public health issues.

Fact Sheet↗
USGS2016

Dragonfly Mercury Project—A citizen science driven approach to linking surface-water chemistry and landscape characteristics to biosentinels on a national scale

Mercury is a globally distributed pollutant that threatens human and ecosystem health. Even protected areas, such as national parks, are subjected to mercury contamination because it is delivered through atmospheric deposition, often after long-range transport. In aquatic ecosystems, certain environmental conditions can promote microbial processes that convert inorganic mercury to an organic form (methylmercury). Methylmercury biomagnifies through food webs and is a potent neurotoxicant and endocrine disruptor. The U.S. Geological Survey (USGS), the University of Maine, and the National Park Service (NPS) Air Resources Division are working in partnership at more than 50 national parks across the United States, and with citizen scientists as key participants in data collection, to develop dragonfly nymphs as biosentinels for mercury in aquatic food webs. To validate the use of these biosentinels, and gain a better understanding of the connection between biotic and abiotic pools of mercury, this project also includes collection of landscape data and surface-water chemistry including mercury, methylmercury, pH, sulfate, and dissolved organic carbon and sediment mercury concentration. Because of the wide geographic scope of the research, the project also provides a nationwide “snapshot” of mercury in primarily undeveloped watersheds.

Fact Sheet↗