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At least 487 records · Page 27Linked to original sources
USGS2015

Acute and chronic toxicity of sodium sulfate to four freshwater organisms in water-only exposures

The acute and chronic toxicity of sulfate (tested as sodium sulfate) was determined in diluted well water (hardness of 100 mg/L and pH 8.2) with a cladoceran ( Ceriodaphnia dubia ; 2-d and 7-d exposures), a midge ( Chironomus dilutus ; 4-d and 41-d exposures), a unionid mussel (pink mucket, Lampsilis abrupta ; 4-d and 28-d exposures), and a fish (fathead minnow, Pimephales promelas ; 4-d and 34-d exposures). Among the 4 species, the cladoceran and mussel were acutely more sensitive to sulfate than the midge and fathead minnow, whereas the fathead minnow was chronically more sensitive than the other 3 species. Acute-to-chronic ratios ranged from 2.34 to 5.68 for the 3 invertebrates but were as high as 12.69 for the fish. The fathead minnow was highly sensitive to sulfate during the transitional period from embryo development to hatching in the diluted well water, and thus, additional short-term (7- to 14-d) sulfate toxicity tests were conducted starting with embryonic fathead minnow in test waters with different ionic compositions at a water hardness of 100 mg/L. Increasing chloride in test water from 10 mg Cl/L to 25 mg Cl/L did not influence sulfate toxicity to the fish, whereas increasing potassium in test water from 1mg K/L to 3mg K/L substantially reduced the toxicity of sulfate. The results indicate that both acute and chronic sulfate toxicity data, and the influence of potassium on sulfate toxicity to fish embryos, need to be considered when environmental guidance values for sulfate are developed or refined.

Environmental Toxicology and Chemistry↗
USGS2005

Ground-water vulnerability to nitrate contamination at multiple thresholds in the mid-Atlantic region using spatial probability models

The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency?s Regional Vulnerability Assessment Program, has developed a set of statistical tools to support regional-scale, ground-water quality and vulnerability assessments. The Regional Vulnerability Assessment Program?s goals are to develop and demonstrate approaches to comprehensive, regional-scale assessments that effectively inform managers and decision-makers as to the magnitude, extent, distribution, and uncertainty of current and anticipated environmental risks. The U.S. Geological Survey is developing and exploring the use of statistical probability models to characterize the relation between ground-water quality and geographic factors in the Mid-Atlantic Region. Available water-quality data obtained from U.S. Geological Survey National Water-Quality Assessment Program studies conducted in the Mid-Atlantic Region were used in association with geographic data (land cover, geology, soils, and others) to develop logistic-regression equations that use explanatory variables to predict the presence of a selected water-quality parameter exceeding a specified management concentration threshold. The resulting logistic-regression equations were transformed to determine the probability, P(X), of a water-quality parameter exceeding a specified management threshold. Additional statistical procedures modified by the U.S. Geological Survey were used to compare the observed values to model-predicted values at each sample point. In addition, procedures to evaluate the confidence of the model predictions and estimate the uncertainty of the probability value were developed and applied. The resulting logistic-regression models were applied to the Mid-Atlantic Region to predict the spatial probability of nitrate concentrations exceeding specified management thresholds. These thresholds are usually set or established by regulators or managers at National or local levels. At management thresholds of 1 milligram per liter and 3 milligrams per liter as nitrogen, the probability of nitrate concentrations exceeding these levels is greater than 50 percent (0.50) throughout much of the Mid-Atlantic Region. This includes extensive areas throughout central Maryland, southeastern Pennsylvania, northwestern Pennsylvania, and the Delmarva Peninsula. In addition, extensive areas in North Carolina and Virginia also have high probabilities of nitrate concentrations in ground water exceeding management thresholds of 1 milligram per liter and 3 milligrams per liter. The mapped areas showing a high predicted probability of nitrate concentrations in ground water exceeding 1 milligram per liter and 3 milligrams per liter correspond to areas that are mapped as cultivated land cover and/or overlying carbonate rocks. At a management threshold of 10 milligrams per liter (corresponding to the U.S. Environmental Protection Agency standard for nitrate in drinking water of 10 milligrams per liter), the predicted probability of nitrate concentrations in ground water exceeding this level is low for most of the Mid-Atlantic Region, except for the Delmarva Peninsula, southeastern Pennsylvania, and areas mapped as carbonate rocks in Virginia, Maryland, and Pennsylvania.

Scientific Investigations Report↗
USGS2021

Freshwater cyanotoxin mixtures in recurring cyanobacterial blooms in Voyageurs National Park

Algal and cyanobacterial blooms can foul water systems, inhibit recreation, and produce cyanotoxins, which can be toxic to humans, domestic animals, and wildlife. Blooms that recur yearly present a special challenge, in that chronic effects of most cyanotoxins are unknown. To better understand cyanotoxin timing, possible environmental triggers, and inter-relations among taxa and toxins in bloom communities, recurring cyanobacterial blooms were investigated at three recreational sites in Kabetogama Lake in Voyageurs National Park from 2016-2019. Results indicated that peak neurotoxin concentrations occurred before peak microcystin concentrations and that toxin-forming cyanobacteria were present before visible blooms, which is a serious human health concern. Two cyanotoxin mixture models (MIX) and two microcystin (MC) models were developed using near-real-time environmental variables and additional comprehensive variables based on laboratory analyses. Comprehensive models explained more variability than the environmental models and neither MIX model was a better fit than the MC models. However, the MIX models produced no false negatives, indicating that all observations above human-health regulatory guidelines were simulated by the MIX models. The results show that a model based on a cyanotoxin mixture is more protective of human health than a model based on microcystin alone. In 2019, 7 of 19 toxins were detected in various mixtures. The potential toxin producing cyanobacteria, Microcystis , was significantly correlated with microcystin-YR, while Pseudanabaena sp. and Synechococcus sp. were negatively correlated to several toxins. Jaccard and Sorenson indices indicated strong same-day similarities among the three bloom communities. Nitrogen-fixing cyanobacteria were present at every site, and when combined with internal loading of phosphorus, might explain similarities among sites, and why seasonal differences, even in samples from the same site, were stronger. Information from this dissertation adds to the body of work on recurring blooms and under-studied toxins and toxin mixtures, providing a better understanding of future research options for freshwater cyanotoxins in and outside of Voyageurs National Park.

Minnesota↗
USGS2019

Toward sustainable environmental quality: Priority research questions for North America

Anticipating, identifying, and prioritizing strategic needs represent essential activities by research organizations. Decided benefits emerge when these pursuits engage globally important environment and health goals, including the United Nations Sustainable Development Goals. To this end, horizon scanning efforts can facilitate identification of specific research needs to address grand challenges. We report and discuss 40 priority research questions following engagement of scientists and engineers in North America. These timely questions identify the importance of stimulating innovation and developing new methods, tools, and concepts in environmental chemistry and toxicology to improve assessment and management of chemical contaminants and other diverse environmental stressors. Grand challenges to achieving sustainable management of the environment are becoming increasingly complex and structured by global megatrends, which collectively challenge existing sustainable environmental quality efforts. Transdisciplinary, systems‐based approaches will be required to define and avoid adverse biological effects across temporal and spatial gradients. Similarly, coordinated research activities among organizations within and among countries are necessary to address the priority research needs reported here. Acquiring answers to these 40 research questions will not be trivial, but doing so promises to advance sustainable environmental quality in the 21st century.

Environmental Toxicology and Chemistry↗
USGS2007

Evaluation of Approaches for Managing Nitrate Loading from On-Site Wastewater Systems near La Pine, Oregon

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the Oregon Department of Environmental Quality and Deschutes County, to develop a better understanding of the effects of nitrogen from on-site wastewater disposal systems on the quality of ground water near La Pine in southern Deschutes County and northern Klamath County, Oregon. Simulation models were used to test the conceptual understanding of the system and were coupled with optimization methods to develop the Nitrate Loading Management Model, a decision-support tool that can be used to efficiently evaluate alternative approaches for managing nitrate loading from on-site wastewater systems. The conceptual model of the system is based on geologic, hydrologic, and geochemical data collected for this study, as well as previous hydrogeologic and water quality studies and field testing of on-site wastewater systems in the area by other agencies. On-site wastewater systems are the only significant source of anthropogenic nitrogen to shallow ground water in the study area. Between 1960 and 2005 estimated nitrate loading from on-site wastewater systems increased from 3,900 to 91,000 pounds of nitrogen per year. When all remaining lots are developed (in 2019 at current building rates), nitrate loading is projected to reach nearly 150,000 pounds of nitrogen per year. Low recharge rates (2-3 inches per year) and ground-water flow velocities generally have limited the extent of nitrate occurrence to discrete plumes within 20-30 feet of the water table; however, hydraulic-gradient and age data indicate that, given sufficient time and additional loading, nitrate will migrate to depths where many domestic wells currently obtain water. In 2000, nitrate concentrations greater than 4 milligrams nitrogen per liter (mg N/L) were detected in 10 percent of domestic wells sampled by Oregon Department of Environmental Quality. Numerical simulation models were constructed at transect (2.4 square miles) and study-area (247 square miles) scales to test the conceptual model and evaluate processes controlling nitrate concentrations in ground water and potential ground-water discharge of nitrate to streams. Simulation of water-quality conditions for a projected future build-out (base) scenario in which all existing lots are developed using conventional on-site wastewater systems indicates that, at equilibrium, average nitrate concentrations near the water table will exceed 10 mg N/L over areas totaling 9,400 acres. Other scenarios were simulated where future nitrate loading was reduced using advanced treatment on-site systems and a development transfer program. Seven other scenarios were simulated with total nitrate loading reductions ranging from 15 to 94 percent; simulated reductions in the area where average nitrate concentrations near the water table exceed 10 mg N/L range from 22 to 99 percent at equilibrium. Simulations also show that the ground-water system responds slowly to changes in nitrate loading due to low recharge rates and ground-water flow velocity. Consequently, reductions in nitrate loading will not immediately reduce average nitrate concentrations and the average concentration in the aquifer will continue to increase for 25-50 years depending on the level and timing of loading reduction. The capacity of the ground-water system to receive on-site wastewater system effluent, which is related to the density of homes, presence of upgradient residential development, ground-water recharge rate, ground-water flow velocity, and thickness of the oxic part of the aquifer, varies within the study area. Optimization capability was added to the study-area simulation model and the combined simulation-optimization model was used to evaluate alternative approaches to management of nitrate loading from on-site wastewater systems to the shallow alluvial aquifer. The Nitrate Loading Management Model (NLMM) was formulated to find the minimum red

Scientific Investigations Report↗
USGS2014

Spatially explicit habitat models for 28 fishes from the Upper Mississippi River System (AHAG 2.0)

Environmental management actions in the Upper Mississippi River System (UMRS) typically require pre-project assessments of predicted benefits under a range of project scenarios. The U.S. Army Corps of Engineers (USACE) now requires certified and peer-reviewed models to conduct these assessments. Previously, habitat benefits were estimated for fish communities in the UMRS using the Aquatic Habitat Appraisal Guide (AHAG v.1.0; AHAG from hereon). This spreadsheet-based model used a habitat suitability index (HSI) approach that drew heavily upon Habitat Evaluation Procedures (HEP; U.S. Fish and Wildlife Service, 1980) by the U.S. Fish and Wildlife Service (USFWS). The HSI approach requires developing species response curves for different environmental variables that seek to broadly represent habitat. The AHAG model uses species-specific response curves assembled from literature values, data from other ecosystems, or best professional judgment. A recent scientific review of the AHAG indicated that the model’s effectiveness is reduced by its dated approach to large river ecosystems, uncertainty regarding its data inputs and rationale for habitat-species response relationships, and lack of field validation (Abt Associates Inc., 2011). The reviewers made two major recommendations: (1) incorporate empirical data from the UMRS into defining the empirical response curves, and (2) conduct post-project biological evaluations to test pre-project benefits estimated by AHAG. Our objective was to address the first recommendation and generate updated response curves for AHAG using data from the Upper Mississippi River Restoration-Environmental Management Program (UMRR-EMP) Long Term Resource Monitoring Program (LTRMP) element. Fish community data have been collected by LTRMP (Gutreuter and others, 1995; Ratcliff and others, in press) for 20 years from 6 study reaches representing 1,930 kilometers of river and >140 species of fish. We modeled a subset of these data (28 different species; occurrences at sampling sites as observed in day electrofishing samples) using multiple logistic regression with presence/absence responses. Each species’ probability of occurrence, at each sample site, was modeled as a function of 17 environmental variables observed at each sample site by LTRMP standardized protocols. The modeling methods used (1) a forward-selection process to identify the most important predictors and their relative contributions to predictions; (2) partial methods on the predictor set to control variance inflation; and (3) diagnostics for LTRMP design elements that may influence model fits. Models were fit for 28 species, representing 3 habitat guilds (Lentic, Lotic, and Generalist). We intended to develop “systemic models” using data from all six LTRMP study reaches simultaneously; however, this proved impossible. Thus, we “regionalized” the models, creating two models for each species: “Upper Reach” models, using data from Pools 4, 8, and 13; and “Lower Reach” models, using data from Pool 26, the Open River Reach of the Mississippi River, and the La Grange reach of the Illinois River. A total of 56 models were attempted. For any given site-scale prediction, each model used data from the three LTRMP study reaches comprising the regional model to make predictions. For example, a site-scale prediction in Pool 8 was made using data from Pools 4, 8, and 13. This is the fundamental nature and trade-off of regionalizing these models for broad management application. Model fits were deemed “certifiably good” using the Hosmer and Lemeshow Goodness-of-Fit statistic (Hosmer and Lemeshow, 2000). This test post-partitions model predictions into 10 groups and conducts inferential tests on correspondences between observed and expected probability of occurrence across all partitions, under Chi-square distributional assumptions. This permits an inferential test of how well the models fit and a tool for reporting when they did not (and perhaps why). Our goal was to develop regionalized models, and to assess and describe circumstances when a good fit was not possible. Seven fish species composed the Lentic guild. Good fits were achieved for six Upper Reach models. In the Lower Reach, no model produced good fits for the Lentic guild. This was due to (1) lentic species being much less prominent in the Lower Reach study areas, and (2) those that do express greater prominence principally do so only in the La Grange reach of the Illinois River. Thus, developing Lower Reach models for Lentic species will require parsing La Grange from the other two Lower Reach study areas and fitting separate models. We did not do that as part of this study, but it could be done at a later time. Nine species comprised the Lotic guild. Good fits were achieved for seven Upper Reach models and six Lower Reach models. Four species had good fits for both regions (flathead catfish, blue sucker, sauger, and shorthead redhorse). Three species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (blue catfish, rock bass, and skipjack herring). Twelve species comprised the Generalist guild. Good fits were achieved for five Upper Reach models and eight Lower Reach models. Six species had good fits for both regions (brook silverside, emerald shiner, freshwater drum, logperch, longnose gar, and white bass). Two species showed zoogeographic zonation, with a good model fit in one of the regions, but not in the region in which they were absent or rarely occurred (red shiner and blackstripe topminnow). Poorly fit models were almost always due to the diagnostic variable “field station,” a surrogate for river mile. In these circumstances, the residuals for “field station” were non-randomly distributed and often strongly ordered. This indicates either fitting “pool scale” models for these species and regions, or explicitly model covariances between “field station” and the other predictors within the existing modeling framework. Further efforts on these models should seek to resolve these issues using one of these two approaches. In total, nine species, representing two of the three guilds (Lotic and Generalist), produced well-fit models for both regions. These nine species should comprise the basis for AHAG 2.0. Additional work, likely requiring downscaling of the regional models to pool-scale models, will be needed to incorporate additional species. Alternately, a regionalized AHAG could be comprised of those species, per region, that achieved well-fit models. The number of species and the composition of the regional species pools will differ among regions as a consequence. Each of these alternatives has both pros and cons, and managers are encouraged to consider them fully before further advancing this approach to modeling multi-species habitat suitability.

Upper Mississippi River System↗
USGS1979

A methodology for post-EIS (environmental impact statement) monitoring

A methodology for monitoring the impacts predicted in environmental impact statements (EIS's) was developed using the EIS on phosphate development in southeastern Idaho as a case study. A monitoring system based on this methodology: (1) coordinates a comprehensive, intergovernmental monitoring effort; (2) documents the major impacts that result, thereby improving the accuracy of impact predictions in future EIS's; (3) helps agencies control impacts by warning them when critical impact levels are reached and by providing feedback on the success of mitigating measures; and (4) limits monitoring data to the essential information that agencies need to carry out their regulatory and environmental protection responsibilities. The methodology is presented as flow charts accompanied by tables that describe the objectives, tasks, and products for each work element in the flow chart.

Circular↗
USGS2013

Mobile Bay

Mobile Bay is the largest bay found in Alabama’s coastal area (Handley et al., 2007). It was named an Estuary of National Significance in 1995 under the U.S. Environmental Protection Agency’s (EPA) National Estuary Program (NEP), and its Comprehensive Conservation Management Plan was completed in 2002. Mobile Bay is 1,070 km 2 (413 miles 2 ) in area and 51 km (32 miles) long, making it the sixth largest estuary in the continental United States (Mobile Bay NEP, 2008). Its ecosystem provides habitat for more than 300 species of birds, 310 species of fish, 68 species of reptiles, 57 species of mammals, 40 species of amphibians, and 15 species of shrimp (Mobile Bay NEP, 1997). Mobile Bay lies between the Mississippi and Atlantic Flyways (Mobile Bay NEP, 2003). Commercial and residential development and industrial use is heavy in the Mobile Bay area. Although local growth and industrial markets support the Mobile Bay area economy, the resulting environmental damage to the very ecosystem upon which they depend remains a threat to the environment, economy, and population. The Mobile Bay ecosystem boasts high biological diversity and productivity and supports many freshwater and saltwater species of recreational and commercial importance. The great diversity of Mobile Bay reflects the diversity of Alabama, which is home to the largest number of different plant and animal species of all states east of the Mississippi River (Stein, 2002), and is bolstered by the unique climate and geographic conditions surrounding the bay. Freshwater inflow from the Mobile-Tensaw River Delta, ranging from 60,000 to 3,700,000 gallons per second (Wallace, 1996), mixes with saltwater from the Gulf of Mexico, which enters Mobile Bay via wind and tides (Burgan and Engle, 2006). Because of the unique conditions surrounding Mobile Bay, including shallow waters, a dynamic climate, and artificial hydrologic modifications—such as the construction of the Mobile Bay Causeway in the 1920s, which serves as an unintentional barrier between Delta waters north of the Causeway and saline waters south of the Causeway, the salinity of Mobile Bay is highly variable. Mobile Bay receives an average of 165 cm (65 inches) of rain per year from tropical storms, summer thunderstorms, and winter cold fronts (Stout et al., 1998). The climate and geography that have made Mobile Bay so rich in resources have also contributed to the threats surrounding its ecosystem. The extensive amount of rain in Mobile Bay creates large amounts of runoff, polluting the waters with fertilizers, chemicals, sediment, oil, trash, and sewage (Mobile Bay NEP, 1997). Tourism, ecotourism, recreational and commercial fishing, recreational boating, shipping, and chemical, pulp, and paper production are significant industries in Mobile Bay and the surrounding areas. Despite the approximate \$3 billion and 55,000 jobs these industries bring into the community (Alabama Tourism Department, 2010), the growth, development, and environmental stress they create are major threats to the Mobile Bay ecosystem. Among the nation’s states, Alabama ranks fifth in number of different species (144 endemic species), second in number of extinctions that have already occurred (90 extinct species) and fourth in number of species at risk for extinction (14.8% at risk out of 4,533 total species; Stein, 2002). Twenty-one of these threatened and endangered species are found in Mobile Bay, whose brackish waters provide a nursery area for many species of vertebrates and invertebrates. Some of these species include the Alabama sturgeon, Gulf sturgeon, heavy pigtoe mussel, inflated heel-splitter mussel, West Indian manatee, Alabama beach mouse, Perdido beach mouse, Alabama red-bellied turtle, gopher tortoise, Kemp’s ridley sea turtle, green sea turtle, loggerhead sea turtle, eastern indigo snake, flatwoods salamander, piping plover, red-cockaded woodpecker, and wood stork. Habitat loss underlies the decline of some bird species in Mobile Bay, and large mammals such as the red wolf, Florida panther, and Florida black bear are no longer found in the area. However, some rare species, such as the swallow-tailed kite, sandhill crane, and gopher tortoise can still be found (Duke and Kruczynski, 1992). The value of wetlands in Mobile Bay and the rest of the Gulf of Mexico is still being investigated. Although various monetary valuations of wetlands exist, critics remark that undervaluation of wetlands is inevitable (Mobile Bay NEP, 2008) and that estimates often do not place appropriate value on ecological services (Mitsch and Gosselink, 2000). Additionally, many estimates account only for anthropogenic values. One estimate concludes that one acre of wetlands performs \$3,000 worth of water purification each year (Mobile Bay NEP, 1997). With more than 76,890 hectares (190,000 acres) of wetlands in the Mobile Bay area, that equates to a value exceeding one-half billion dollars every year. Tourism, fishing, boating, production, and shipping are significant industries in the Mobile Bay area. More than 90% of fish landed in recreational and commercial fishing in the bay depend on bay habitat, including wetlands, for life requirements (Mobile Bay NEP, 1997). The Port of Mobile is Alabama’s only ocean-ship port (Mobile Bay NEP, 2008). Baldwin County, on the eastern side of the bay, experienced a population increase of 75% from 1990 to 2007, with an 89% increase in housing units (Mobile Bay NEP, 2008). Development and industry support the Mobile Bay economy, but they depend on the continued health, sustainability, and production of the water and living resources of the Mobile Bay ecosystem. Wetland loss, along with other forms of environmental degradation, remains a threat to the Mobile Bay ecosystem and Mobile Bay’s socioeconomic foundation.

Alabama↗
USGS2020

Economic, land use, and ecosystem services impacts of Rwanda's Green Growth Strategy: An application of the IEEM+ESM platform

We develop and link the Integrated Economic-Environmental Modeling (IEEM) Platform to ecosystem services modeling (ESM). The IEEM+ESM Platform is an innovative decision-making framework for exploring complex public policy goals and elucidating synergies and trade-offs between alternative policy portfolios. The IEEM+ESM approach is powerful in its ability to shed light on (i) change in land use and ecosystem services driven by public policy and the supply and demand responses of businesses and households; and (ii) impacts on standard economic indicators of concern to Ministries of Finance such as gross domestic product and employment, as well as changes in wealth and ecosystem services. The IEEM+ESM approach is being adopted rapidly and by the end of 2020, IEEM+ESM Platforms will be implemented for about 25 countries. To demonstrate the insights generated by the IEEM+ESM approach, we apply it to the analysis of alternative green growth strategies in Rwanda, a country that has made strong progress in reducing poverty and enhancing economic growth in the last 15 years. The case of Rwanda is particularly compelling as it faces intense pressure on its natural capital base and ecosystem services, already with the highest population density in Africa, which is projected to double by 2050. In applying IEEM+ESM and comparing the outcomes of Rwanda’s green growth policies, increasing fertilization of agricultural crops shows the largest economic gains but also trade-offs in environmental quality reflected through higher nutrient export and reduced water quality. Combining crop fertilization with forest plantations better balances critical ecosystem services and their role in underpinning economic development as Rwanda progresses toward its target of middle-income status by 2035. This application to Rwanda’s green growth strategy demonstrates the value-added of the IEEM+ESM approach in generating results that speak to both economic outcomes and impacts on market and non-market ecosystem services.

Science of the Total Environment↗
USGS2004

The value of long-term monitoring in the development of ground-water-flow models

As environmental issues have come to the forefront of public concern, so has the awareness of the importance of ground water in the overall water cycle and as a source of the Nation’s drinking water. Heightened interest has spawned a host of scientific enterprises (Taylor and Alley, 2001). Some activities are directed toward collection of water-level data and related information to monitor the physical and chemical state of the resource. Other activities are directed at interpretive studies undertaken, for example, to optimize the location of new water-supply wells or to protect rivers and lakes fed by ground water. An important type of interpretive study is the computer ground-water-flow model that inte- grates field data in a mathematical framework. Long-term, systematic collection of hydro- logic data is crucial to the construction and testing of ground-water models so that they can reproduce the evolution of flow systems and forecast future conditions.

Wisconsin↗
USGS2005

Development of an approach for integrating components of the U.S. Geological Survey Biomonitoring of Environmental Status and Trends (BEST) and National Stream Quantity Accounting Network (NASQAN) programs for large U.S. rivers

A national-scale framework for monitoring environmental contaminants in fish and effects of contaminant exposure on fish in large U.S. rivers has been proposed by the Biomonitoring of Environmental Status and Trends (BEST) Program of the U.S. Geological Survey (USGS). The framework shares many features and objectives with the USGS National Stream Quantity Accounting Network (NASQAN) Program, which monitors water quality in large U.S. river basins–those with drainage areas of 250,000 to 1,200,000 square miles at their most downstream stations. Because the two programs appear to be complementary, this study was initiated in 2001 to investigate alternative techniques for summarizing and integrating the water-quality data with the fish-contaminant and fish-health data, and to provide recommendations to the BEST program for future integrated studies.

Scientific Investigations Report↗
USGS1969

Environmental impact of the Big Cypress Swamp jetport

Development of the proposed jetport and its attendant facilities will lead to land drainage and development for agriculture, industry, housing, transportation, and services in the Big Cypress Swamp which will inexorably destroy the south Florida ecosystem and this the Everglades National Park.

Florida↗
USGS2004

Metadata for ReVA logistic regression dataset

The U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency's Regional Vulnerability Assessment Program, has developed a set of statistical tools to support regional-scale, ground-water quality and vulnerability assessments. The Regional Vulnerability Assessment Program goals are to develop and demonstrate approaches to comprehensive, regional-scale assessments that effectively inform water-resources managers and decision-makers as to the magnitude, extent, distribution, and uncertainty of current and anticipated environmental risks. The U.S. Geological Survey is developing and exploring the use of statistical probability models to characterize the relation between ground-water quality and geographic factors in the Mid-Atlantic Region. Available water-quality data obtained from U.S. Geological Survey National Water-Quality Assessment Program studies conducted in the Mid-Atlantic Region were used in association with geographic data (land cover, geology, soils, and others) to develop logistic-regression equations that use explanatory variables to predict the presence of a selected water-quality parameter exceeding specified management concentration thresholds. The resulting logistic-regression equations were transformed to determine the probability, P(X), of a water-quality parameter exceeding a specified management threshold. Additional statistical procedures modified by the U.S. Geological Survey were used to compare the observed values to model-predicted values at each sample point. In addition, procedures to evaluate the confidence of the model predictions and estimate the uncertainty of the probability value were developed and applied. The resulting logistic-regression models were applied to the Mid-Atlantic Region to predict the spatial probability of nitrate concentrations exceeding specified management thresholds. These thresholds are usually set or established by regulators or managers at national or local levels. At management thresholds of 1 milligram per liter, and 3 milligrams per liter, the probability of nitrate concentrations exceeding these levels is greater than 50 percent (.50) throughout much of the Mid-Atlantic Region. This includes extensive areas throughout central Maryland, southeastern Pennsylvania, northwestern Pennsylvania and the Delmarva Peninsula. In addition, extensive areas in North Carolina and Virginia also have high probabilities of nitrate concentrations in ground water exceeding management thresholds of 1 milligram per liter and 3 milligrams per liter. The mapped areas showing a high predicted probability of nitrate concentrations in ground water exceeding 1 milligram per liter and 3 milligrams per liter correspond to areas that are mapped as cultivated land cover overlying carbonate rocks. At a management threshold of 10 milligrams per liter (corresponding to the U.S. Environmental Protection Agency standard for nitrate in drinking water of 10 milligrams per liter), the predicted probability of nitrate concentrations in ground water exceeding this level are low for most of the Mid-Atlantic Region except for the Delmarva Peninsula, southeastern Pennsylvania, and areas mapped as carbonate rocks in Virginia, Maryland, and Pennsylvania.

Open-File Report↗
USGS2024

Evaluating the reliability of environmental concentration data to characterize exposure in environmental risk assessments

Environmental risk assessments often rely on measured concentrations in environmental matrices to characterize exposure of the population of interest—typically, humans, aquatic biota, or other wildlife. Yet, there is limited guidance available on how to report and evaluate exposure datasets for reliability and relevance, despite their importance to regulatory decision-making. This paper is the second of a four-paper series detailing the outcomes of a Society of Environmental Toxicology and Chemistry Technical Workshop that has developed Criteria for Reporting and Evaluating Exposure Datasets (CREED). It presents specific criteria to systematically evaluate the reliability of environmental exposure datasets. These criteria can help risk assessors understand and characterize uncertainties when existing data are used in various types of assessments and can serve as guidance on best practice for the reporting of data for data generators (to maximize utility of their datasets). Although most reliability criteria are universal, some practices may need to be evaluated considering the purpose of the assessment. Reliability refers to the inherent quality of the dataset and evaluation criteria address the identification of analytes, study sites, environmental matrices, sampling dates, sample collection methods, analytical method performance, data handling or aggregation, treatment of censored data, and generation of summary statistics. Each criterion is evaluated as “fully met,” “partly met,” “not met or inappropriate,” “not reported,” or “not applicable” for the dataset being reviewed. The evaluation concludes with a scheme for scoring the dataset as reliable with or without restrictions, not reliable, or not assignable, and is demonstrated with three case studies representing both organic and inorganic constituents, and different study designs and assessment purposes. Reliability evaluation can be used in conjunction with relevance evaluation (assessed separately) to determine the extent to which environmental monitoring datasets are “fit for purpose,” that is, suitable for use in various types of assessments. Integr Environ Assess Manag 2024;00:1–23. © 2024 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Integrated Environmental Assessment and Management↗
USGS1988

Eutrophication of lakes and reservoirs: A framework for making management decisions

The development of management strategies for the protection of environmental quality usually involves consideration both of technical and nontechnical issues. A logical, step-by-step framework for development of such strategies is provided. Its application to the control of cultured eutrophication of lakes and reservoirs illustrates its potential usefulness. From the perspective of the policymaker, the main consideration is that the eutrophication-related water quality of a lake or reservoir can be managed for given water uses. The approach presented here allows the rational assessment of relevant water-quality parameters and establishment of water-quality goals, consideration of social and other nontechnical issues, the possibilities of public involvement in the decision-making process, and a reasonable economic analysis within a management framework.

Ambio↗
USGS2014

SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

Future Generation Computer Systems↗
USGS2007

U.S. Geological Survey Field Leach Test for Assessing Water Reactivity and Leaching Potential of Mine Wastes, Soils, and Other Geologic and Environmental Materials

The U. S. Geological Survey (USGS) has developed a fast (5-minute), effective, simple, and cost-effective leach test that can be used to simulate the reactions that occur when materials are leached by water. The USGS Field Leach Test has been used to predict, assess, and characterize the geochemical interactions between water and a broad variety of geologic and environmental matrices. Examples of some of the samples leached include metal mine wastes, various types of dusts, biosolids (processed sewage sludge), flood and wetland sediments, volcanic ash, forest-fire burned soils, and many other diverse matrices. The Field Leach Test has been an integral part of these investigations and has demonstrated its value as a geochemical characterization tool. It has enabled investigators to identify which constituents are water reactive, soluble, mobilized, and made bioaccessible because of leaching by water, and to understand potential impacts of these interactions on the surrounding environment.

Techniques and Methods↗