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At least 109 records · Page 6Linked to original sources
USGS2026

Anthropogenic and geogenic factors affecting groundwater arsenic and potential drinking water exposure in the San Luis Valley, Colorado

Groundwater arsenic is a serious health threat in many regions with limited surface water drinking supplies. In the San Luis Valley, Colorado, USA, where most residents rely on groundwater for drinking water, elevated groundwater arsenic concentrations (≥5 μg/L) were observed in 19.8% of private wells. Many recent studies have leveraged data science methods to estimate the spatial variability of arsenic at local, regional, and global scales. These studies typically predict depth-independent arsenic concentrations due to limited well depth information. However, arsenic concentrations may vary greatly with depth due to heterogeneous aquifer geochemistry, including redox potential, pH, and biogeochemical conditions. In this study, we apply random forest modeling to predict elevated groundwater arsenic concentrations (≥5 μg/L) over space and depth continuously across the San Luis Valley using a community-driven data set of 435 groundwater measurements of major ions and trace metals. Our model reveals the influence of several known or hypothesized drivers or proxy drivers of arsenic in groundwater, including surface elevation, fraction of fine-grained aquifer sediments, well depth, soil pH, long-term subsidence, and geothermal influences. Elevation, percentage of fine-grained sediments, and elemental indicators of geothermal fluid influence are some of the most important predictors of arsenic, while long-term subsidence is found to have a weak but positive relationship with arsenic. The model has a specificity of 0.82 and a sensitivity of 0.81 on held-out test data sets. In addition to improving understanding of drivers of arsenic in the region, this model produces pseudo-3D estimates of groundwater arsenic. The model can also be used to assess the time-dependent exposure to arsenic as the depth of domestic wells changes over time.

Colorado↗
USGS2012

Assessment of regional change in nitrate concentrations in groundwater in the Central Valley, California, USA, 1950s-2000s

A regional assessment of multi-decadal changes in nitrate concentrations was done using historical data and a spatially stratified non-biased approach. Data were stratified into physiographic subregions on the basis of geomorphology and soils data to represent zones of historical recharge and discharge patterns in the basin. Data were also stratified by depth to represent a shallow zone generally representing domestic drinking-water supplies and a deep zone generally representing public drinking-water supplies. These stratifications were designed to characterize the regional extent of groundwater with common redox and age characteristics, two factors expected to influence changes in nitrate concentrations over time. Overall, increasing trends in nitrate concentrations and the proportion of nitrate concentrations above 5 mg/L were observed in the east fans subregion of the Central Valley. Whereas the west fans subregion has elevated nitrate concentrations, temporal trends were not detected, likely due to the heterogeneous nature of the water quality in this area and geologic sources of nitrate, combined with sparse and uneven data coverage. Generally low nitrate concentrations in the basin subregion are consistent with reduced geochemical conditions resulting from low permeability soils and higher organic content, reflecting the distal portions of alluvial fans and historical groundwater discharge areas. Very small increases in the shallow aquifer in the basin subregion may reflect downgradient movement of high nitrate groundwater from adjacent areas or overlying intensive agricultural inputs. Because of the general lack of regionally extensive long-term monitoring networks, the results from this study highlight the importance of placing studies of trends in water quality into regional context. Earlier work concluded that nitrate concentrations were steadily increasing over time in the eastern San Joaquin Valley, but clearly those trends do not apply to other physiographic subregions within the Central Valley, even where land use and climate are similar.

California↗
USGS2021

Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Water Resources Research↗
USGS2004

Validation of two dilution models to predict chloramine-T concentrations in aquaculture facility effluent

Accurate estimates of drug concentrations in hatchery effluent are critical to assess the environmental risk of hatchery drug discharge resulting from disease treatment. This study validated two dilution simple n models to estimate chloramine-T environmental introduction concentrations by comparing measured and predicted chloramine-T concentrations using the US Geological Survey's Upper Midwest Environmental Sciences Center aquaculture facility effluent as an example. The hydraulic characteristics of our treated raceway and effluent and the accuracy of our water flow rate measurements were confirmed with the marker dye rhodamine WT. We also used the rhodamine WT data to develop dilution models that would (1) estimate the chloramine-T concentration at a given time and location in the effluent system and (2) estimate the average chloramine-T concentration at a given location over the entire discharge period. To test our models, we predicted the chloramine-T concentration at two sample points based on effluent flow and the maintenance of chloramine-T at 20 mg/l for 60 min in the same raceway used with rhodamine WT. The effluent sample points selected (sample points A and B) represented 47 and 100% of the total effluent flow, respectively. Sample point B is-analogous to the discharge of a hatchery that does not have a detention lagoon, i.e. The sample site was downstream of the last dilution water addition following treatment. We then applied four chloramine-T flow-through treatments at 20mg/l for 60 min and measured the chloramine-T concentration in water samples collected every 15 min for about 180 min from the treated raceway and sample points A and B during and after application. The predicted chloramine-T concentration at each sampling interval was similar to the measured chloramine-T concentration at sample points A and B and was generally bounded by the measured 90% confidence intervals. The predicted aver,age chloramine-T concentrations at sample points A or B (2.8 and 1.3 mg/l, respectively) were not significantly different (P > 0.05) from the average measured chloramine-T concentrations (2.7 and 1.3 mg/l, respectively). The close agreement between our predicted and measured chloramine-T concentrations indicate either of the dilution models could be used to adequately predict the chloramine-T environmental introduction concentration in Upper Midwest Environmental Sciences Center effluent.

Aquacultural Engineering↗
USGS2023

Application of the technology readiness levels framework to natural resource management tools

Technology advancements in fisheries science can provide useful tools to support natural resource management and conservation. However, new technologies may also present challenges for decision makers due to the lack of a standardized process to assess technologies for consideration within management plans. Future technology development in fishery and water resources could benefit from a framework that assigns an appropriate technology development stage and defines the readiness for implementation. Technology Readiness Levels (TRL) are one established research and development scale used throughout engineering and related disciplines that could be applied to natural resource management tools. The TRL assess the maturity of a technology from nascent idea through a fully developed technology. Steps within this scale could provide a general framework for researchers to follow when planning and conducting studies, while similarly providing a standard scale for resource managers to assess readiness for technology transfer and implementation. The goal of this paper is to describe TRL in the context of natural resource management tools and offer this existing framework as one option to facilitate communication between researchers and managers.

Fisheries↗
USGS2024

Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems

Inland fisheries often receive little to no attention in global discussions about sustainable development. The consequences of overlooking inland fisheries in sustainability dialogues are increasingly problematic as fisheries stressors (e.g., overharvest, species invasion, climate change, habitat modification) intensify. Elevating the global profile of inland fisheries requires an approach for quantifying and clearly conveying the ecological, economic, and societal values of these systems. One such approach involves the Blue Economy, a multifaceted concept initially used to describe the intersection of marine conservation and sustainable use of marine resources for economic growth. Although conceptually powerful, the Blue Economy has rarely been applied to inland waters and fisheries. To address this knowledge gap, we conceptualized Laurentian Great Lakes fisheries from a Blue Economy perspective. In particular, we evaluated the utility of the coupled human and natural systems (CHANS) framework for characterizing the ecological, economic, and societal values of Laurentian Great Lakes fisheries and associated contributions to the Blue Economy (e.g., human livelihoods, food security, recreation, conservation, economic prosperity). There are numerous opportunities to leverage CHANS methods (e.g., metacoupling, telecoupling) and associated mathematical models to advance fisheries science, inform fisheries management, and ultimately move toward a Blue Economy in the Laurentian Great Lakes. To that end, we demonstrated applications of CHANS methods, discussed strategies for communicating with stakeholders, and provided insights for navigating challenges to developing a Blue Economy in the Laurentian Great Lakes—a model that could be used in the African Great Lakes and other large ecosystems in the world.

Laurentian Great Lakes↗
USGS2018

Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal

The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.

Open Water Journal↗
USGS2020

Snow processes in mountain forests: Interception modeling for coarse-scale applications

Snow interception by the forest canopy controls the spatial heterogeneity of subcanopy snow accumulation leading to significant differences between forested and nonforested areas at a variety of scales. Snow intercepted by the forest canopy can also drastically change the surface albedo. As such, accurately modeling snow interception is of importance for various model applications such as hydrological, weather, and climate predictions. Due to difficulties in the direct measurements of snow interception, previous empirical snow interception models were developed at just the point scale. The lack of spatially extensive data sets has hindered the validation of snow interception models in different snow climates, forest types, and at various spatial scales and has reduced the accurate representation of snow interception in coarse-scale models. We present two novel empirical models for the spatial mean and one for the standard deviation of snow interception derived from an extensive snow interception data set collected in an evergreen coniferous forest in the Swiss Alps. Besides open-site snowfall, subgrid model input parameters include the standard deviation of the DSM (digital surface model) and/or the sky view factor, both of which can be easily precomputed. Validation of both models was performed with snow interception data sets acquired in geographically different locations under disparate weather conditions. Snow interception data sets from the Rocky Mountains, US, and the French Alps compared well to the modeled snow interception with a normalized root mean square error (NRMSE) for the spatial mean of ≤10 % for both models and NRMSE of the standard deviation of ≤13 %. Compared to a previous model for the spatial mean interception of snow water equivalent, the presented models show improved model performances. Our results indicate that the proposed snow interception models can be applied in coarse land surface model grid cells provided that a sufficiently fine-scale DSM is available to derive subgrid forest parameters.

Utah↗
USGS1996

Overview of the limnology of crater lake

Crater Lake occupies the collapsed caldera of volcanic Mount Mazama in Crater Lake National Park, Oregon. It is the deepest lake (589 m) in the United States and the 7th deepest lake in the world. The water column mixes to a depth of about 200 m in winter and spring from wind energy and cooling. The deep lake is mixed in winter and early spring each year when relatively cold water near the surface sinks and exchanges positions with water in the deep basins of the lake. The lake becomes thermally stratified in summer and early fall. The metalimnion extends to a depth of about 100 m; thus most of the water column is a cold hypolimnion. Secchi disk clarity measurements typically are in the upper-20-m range to the low-30-m range in summer and early fall. Concentrations of nutrients are low, although conductivity is relatively high owing to the inflow of hydrothermal fluids. Total chlorophyll is low in concentration, but typically maximal at a depth of 120 m during periods of thermal stratification. Primary production also is low, with the maximum levels occurring between the depth of 40 and 80 m. Phytoplankton taxa are spatially segregated from each other within the water column to a depth of 200 m in summer and early fall. The same generalization applies to the Zooplankton taxa. Water level, clarity, concentrations of total chlorophyll, primary production, and abundances of zooplankton and introduced kokanee salmon exhibit long-term fluctuations. Based primarily on a recent 10-year study of the lake, the lake is considered to be pristine, except for the consequences of fish introductions. ?? 1996 by the Northwest Scientific Association. All rights reserved.

Northwest Science↗
USGS2013

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary 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 policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking 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 wellbeing 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 decisionmakers 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 U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau 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 Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. 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 for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: 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 decisionmaking 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 decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS 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 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 in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗
USGS2014

Landscape and climate science and scenarios for Florida

The Peninsular Florida Landscape Conservation Cooperative (PFLCC) is part of a network of 22 Landscape Conservation Cooperatives (LCCs) that extend from Alaska to the Caribbean. LCCs are regional-applied conservation-science partnerships among Federal agencies, regional organizations, States, tribes, nongovernmental organizations (NGOs), private stakeholders, universities, and other entities within a geographic area. The goal of these conservation-science partnerships is to help inform managers and decision makers at a landscape scale to further the principles of adaptive management and strategic habitat conservation. A major focus for LCCs is to help conservation managers and decision makers respond to large-scale ecosystem and habitat stressors, such as climate change, habitat fragmentation, invasive species, and water scarcity. The purpose of the PFLCC is to facilitate planning, design, and implementation of conservation strategies for fish and wildlife species at the landscape level using the adaptive management framework of strategic habitat conservation—integrating planning, design, delivery, and evaluation. Florida faces a set of unique challenges when responding to regional and global stressors because of its unique ecosystems and assemblages of species, its geographic location at the crossroads of temperate and tropical climates, and its exposure to both rapid urbanization and rising sea levels as the climate warms. In response to these challenges, several landscape-scale science projects were initiated with the goal of informing decision makers about how potential changes in climate and the built environment could impact habitats and ecosystems of concern in Florida and the Southeast United States. In June 2012, the PFLCC, North Carolina State University, convened a workshop at the U.S. Geological Survey (USGS) Coastal and Marine Science Center in St. Petersburg to assess the results of these integrated assessments and to foster an open dialogue about science gaps and future research needs.

Florida↗
USGS2025

Discovery of an intact Quaternary paleosol, Georgia Bight, USA

A previously buried paleosol was found on the continental shelf during a study of sea floor scour, nucleated by large artificial reef structures such as vessel hulks, barges, train cars, military vehicles, etc., called “scour nuclei”. It is a relic paleo-land surface of sapling-sized tree stumps, root systems, and fossil animal bone exhumed by scour processes active adjacent to the artificial reef structure. Over the span of five research cruises to the site in 2022–2024, soil samples were taken using hand excavation, PONAR grab samplers, split spoon, hollow tube auger, and a modified Shelby-style push box. High-definition (HD) video was taken using a Remotely Operated Vehicle (ROV) and diver-held cameras. Radiocarbon dating of wood samples returned ages of 42,015–43,417 calibrated years before present (cal yrBP). Pollen studies, together with the recovered macrobotanical remains, support our interpretation of the site as a freshwater forested wetland whose keystone tree species was Taxodium distichum —bald cypress. The paleosol was identified as an Aquult, a sub-order of Ultisols where water tables are at or near the surface year-round. A deep (0.25 m+) argillic horizon comprised the bulk of the preserved soil. Comparable Ultisols found in Georgia wetlands include Typic Paleaquult (Grady and Bayboro series) soils.

Georgia↗
USGS2019

A novel method to characterise levels of pharmaceutical pollution in large scale aquatic monitoring campaigns

Much of the current understanding of pharmaceutical pollution in the aquatic environment is based on research conducted in Europe, North America and other select high-income nations. One reason for this geographic disparity of data globally is the high cost and analytical intensity of the research, limiting accessibility to necessary equipment. To reduce the impact of such disparities, we present a novel method to support large-scale monitoring campaigns of pharmaceuticals at different geographical scales. The approach employs the use of a miniaturised sampling and shipping approach with a high throughput and fully validated direct-injection High-Performance Liquid Chromatography-Tandem Mass Spectrometry method for the quantification of 61 active pharmaceutical ingredients (APIs) and their metabolites in tap, surface, wastewater treatment plant (WWTP) influent and WWTP effluent water collected globally. A 7-day simulated shipping and sample stability assessment was undertaken demonstrating no significant degradation over the 1–3 days which is typical for global express shipping. Linearity (r 2 ) was consistently ≥0.93 (median = 0.99 ± 0.02), relative standard deviation of intra- and inter-day repeatability and precision was <20% for 75% and 68% of the determinations made at three concentrations, respectively, and recovery from Liquid Chromatography Mass Spectrometry grade water, tap water, surface water and WWTP effluent were within an acceptable range of 60–130% for 87%, 76%, 77% and 63% of determination made at three concentrations respectively. Limits of detection and quantification were determined in all validated matrices and were consistently in the ng/L level needed for environmentally relevant API research. Independent validation of method results was obtained via an interlaboratory comparison of three surface-water samples and one WWTP effluent sample collected in North Liberty, Iowa (USA). Samples used for the interlaboratory validation were analysed at the University of York Centre of Excellence in Mass Spectrometry (York, UK) and the U.S. Geological Survey National Water Quality Laboratory in Denver (Colorado, USA). These results document the robustness of using this method on a global scale. Such application of this method would essentially eliminate the interlaboratory analytical variability typical of such large-scale datasets where multiple methods were used.

Applied Sciences↗
USGS2021

Cyprosulfamide: Analysis of the herbicide safener and two of its degradates in surface water and groundwater from the Midwestern United States

Herbicide safeners are commonly included in herbicide formulations to selectively protect crops from herbicide toxicity but are poorly understood in terms of their environmental occurrence and fate. This study established an analytical method for a newer safener, cyprosulfamide, and two of its degradates, cyprosulfamide desmethyl and N -cyclopropyl-4-sulfamoylbenzamide, in water via solid-phase extraction and liquid chromatography with tandem mass spectroscopy. To evaluate the potential for off-field transport and transformation of cyprosulfamide, the method was used to analyze groundwater and surface water samples collected near cornfields in the midwestern United States where cyprosulfamide had been applied. All three compounds were detected in surface water samples ( N = 34); N -cyclopropyl-4-sulfamoylbenzamide was most frequently detected (56%), followed by cyprosulfamide (25%) and cyprosulfamide desmethyl (19%). Maximum concentrations ranged from 22.0 to 5185.9 ng/L, with the highest concentrations and detection rates during the growing season. None of our target analytes were detected in groundwater.

ACS Agricultural Science and Technology↗
USGS1992

A model for the assessment of aquifer contamination potential based on regional geologic framework

The texture and three-dimensional framework of geologic materials should be considered in assessments of groundwater's vulnerability to contamination because geology controls the movement of contaminants and groundwater and influences groundwater quality. Contaminants are introduced into, transmitted through, and stored by geologic materials. We present a model that identifies aquifers and ranks sequences of geologic materials by their relative potential for transmitting water and contaminants from land surface. With this basis, the model can be used to assess the potential for contamination of aquifers by surface activities such as landfitling of wastes or application of agricultural chemicals. A regional map of aquifer contamination potential can be generated from the model; it retains the geologic map information intact and available for reinterpretation or other uses. The model was developed using broad, regional map information and is intended to be a general tool for assessing the regional vulnerability of aquifers to contamination. It is not intended for local, site-specific use, but for prioritizing local areas where contamination potential and/or land-use history warrant more detailed assessment or monitoring. Because it provides a regional view of contamination potential, regional patterns or trends of map units should be evaluated, rather than using the map information literally to assess local areas. Methods of applying this model and contamination potential map to groundwater protection and management are currently being studied; research includes an attempt to statistically validate the model with water-quality data, and to identify natural groupings of the ranked contamination potential map units. ?? 1992 Springer-Verlag New York Inc.

Environmental Geology and Water Sciences↗
USGS2002

Impacts of swine manure pits on groundwater quality

Manure deep-pits are commonly used to store manure at confined animal feeding operations. However, previous to this study little information had been collected on the impacts of deep-pits on groundwater quality to provide science-based guidance in formulating regulations and waste management strategies that address risks to human health and the environment. Groundwater quality has been monitored since January 1999 at two hog finishing facilities in Illinois that use deep-pit systems for manure storage. Groundwater samples were collected on a monthly basis and analyzed for inorganic and bacteriological constituent concentrations. The two sites are located in areas with geologic environments representing different vulnerabilities for local groundwater contamination. One site is underlain by more than 6 m of clayey silt, and 7-36 m of shale. Concentrations of chloride, ammonium, phosphate, and potassium indicated that local groundwater quality had not been significantly impacted by pit leakage from this facility. Nitrate concentrations were elevated near the pit, often exceeding the 10 mg N/l drinking water standard. Isotopic nitrate signatures suggested that the nitrate was likely derived from soil organic matter and fertilizer applied to adjacent crop fields. At the other site, sandstone is located 4.6-6.1 m below land surface. Chloride concentrations and ??15N and ??18O values of dissolved nitrate indicated that this facility may have limited and localized impacts on groundwater. Other constituents, including ammonia, potassium, phosphate, and sodium were generally at or less than background concentrations. Trace- and heavy-metal concentrations in groundwater samples collected from both facilities were at concentrations less than drinking water standards. The concentration of inorganic constituents in the groundwater would not likely impact human health. Fecal streptococcus bacteria were detected at least once in groundwater from all monitoring wells at both sites. Fecal streptococcus was more common and at greater concentrations than fecal coliform. The microbiological data suggest that filtration of bacteria by soils may not be as effective as commonly assumed. The presence of fecal bacteria in the shallow groundwater may pose a significant threat to human health if the ground water is used for drinking. Both facilities are less than 4 years old and the short-term impacts of these manure storage facilities on groundwater quality have been limited. Continued monitoring of these facilities will determine if they have a long-term impact on groundwater resources. ?? 2002 Elsevier Science Ltd. All rights reserved.

Environmental Pollution↗
USGS1992

Ground-water models cannot be validated

Ground-water models are embodiments of scientific hypotheses. As such, the models cannot be proven or validated, but only tested and invalidated. However, model testing and the evaluation of predictive errors lead to improved models and a better understanding of the problem at hand. In applying ground-water models to field problems, errors arise from conceptual deficiencies, numerical errors, and inadequate parameter estimation. Case histories of model applications to the Dakota Aquifer, South Dakota, to bedded salts in New Mexico, and to the upper Coachella Valley, California, illustrate that calibration produces a nonunique solution and that validation, per se , is a futile objective. Although models are definitely valuable tools for analyzing ground-water systems, their predictive accuracy is limited. The terms validation and verification are misleading and their use in ground-water science should be abandoned in favor of more meaningful model-assessment descriptors.

Advances in Water Resources↗
USGS1990

A quantitative micropaleontologic method for shallow marine peleoclimatology: Application to Pliocene deposits of the western North Atlantic Ocean

A transfer function was developed to estimate summer and winter paleotemperatures for arctic to tropical regions of the western North Atlantic Ocean using fossil ostracode assemblages. Q-mode factor analysis was run on ostracode assemblages from 100 modern bottom sediment samples from continental shelves of North America, Greenland and the Caribbean using 59 ostracode taxa. Seven factors accounting for 80% of the variance define assemblages that correspond to frigid, subfrigid, cold temperate, mild temperate, warm temperate, subtropical and tropical climatic zones. Multiple regression of the factor matrix against observed February and August bottom temperatures yielded an astracode transfer function with an accuracy of about ??2??C. The transfer function was used to reconstruct middle Pliocene (3.5-3.0 Ma) shallow marine climates of the western North Atlantic during the marine transgression that deposited the Yorktown Formation (Virginia and North Carolina), the Duplin Formation (South and North Carolina) and the Pinecrest beds (Florida). Middle Pliocene paleowater temperatures in Virginia averaged 19??C in August and 13.5??C in February, about 5??C to 8??C warmer than at comparable depths off Virginia today. August and February water temperatures in North Carolina were 23??C and 13.4??C, in South Carolina about 23??C and 13.5??C and in southern Florida about 24.6??C and 15.4??C. Marine climates north of 35??N were warmer than today; south of 35??N, they were about the same or slightly cooler. Thermal gradients along the coast were generally not as steep as they are today. The North Atlantic transfer function can be applied to other shallow marine Pliocene and Pleistocene deposits of eastern North America. ?? 1990 Elsevier Science Publishers B.V.

Marine Micropaleontology↗