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USGS2013

U.S. Geological Survey environmental health science strategy — Providing environmental health science for a changing world

Executive Summary America has an abundance of natural resources. We have bountiful clean water, fertile soil, and unrivaled national parks, wildlife refuges, and public lands. These resources enrich our lives and preserve our health and wellbeing. These resources have been maintained because of our history of respect for their value and an enduring commitment to their vigilant protection. Awareness of the social, economic, and personal value of the health of our environment is increasing. The emergence of environmentally driven diseases caused by exposure to contaminants and pathogens is a growing concern worldwide. New health threats and patterns of established threats are affected by both natural and anthropogenic changes to the environment. Human activities are key drivers of emerging (new and re-emerging) health threats. Societal demands for land and natural resources, quality of life, and economic prosperity lead to environmental change. Natural earth processes, climate trends, and related climatic events will compound the environmental impact of human activities. These environmental drivers will influence exposure to disease agents, including viral, bacterial, prion, and fungal pathogens, parasites, synthetic chemicals and substances, natural earth materials, toxins, and other biogenic compounds. The U.S. Geological Survey (USGS) defines environmental health science broadly as the interdisciplinary study of relations among the quality of the physical environment, the health of the living environment, and human health. The interactions among these three spheres are driven by human activities, ecological processes, and natural earth processes; the interactions affect exposure to contaminants and pathogens and the severity of environmentally driven diseases in animals and people. This definition provides USGS with a framework for synthesizing natural science information from across the Bureau and providing it to environmental, natural resource, agricultural, and public health managers. USGS specializes in science at the environment-health interface, by characterizing the processes that affect the interaction among the physical environment, the living environment, and people, and the resulting factors that affect ecological and human exposure to disease agents. The USGS is a Federal science agency with a broad range of natural science expertise relevant to environmental health. USGS provides scientific information and tools as a scientific basis for management and policy decisionmaking. This report describes a 10-year strategy that encompasses the portfolio of USGS environmental health science. It summarizes national environmental health priorities that USGS is best suited to address, and will serve as a strategic framework for USGS environmental health science goals, actions, and outcomes for the next decade. Implementation of this strategy is intended to aid coordination of USGS environmental health activities and to provide a focal point for disseminating information to stakeholders. The “One Health” paradigm advocated by the World Health Organization (WHO; World Health Organization, 2011), and the American Veterinary Medical Association (AVMA; American Veterinary Medical Association, 2008), among others, is based on a general recognition that the health of humans, animals, and the environment are inextricably linked. Thus, successful efforts to protect that health will require increased interdisciplinary research and increased communication and collaboration among the broader scientific and health community. This strategy is built upon that paradigm.

Circular↗

USGS2016

The Department of the Interior Southeast Climate Science Center synthesis report 2011–15—Projects, products, and science priorities

Introduction In 2009, the U.S. Department of the Interior (DOI) Secretary Ken Salazar established a network of eight regional Climate Science Centers (CSCs) that, along with the Landscape Conservation Cooperatives (LCCs), would help define and implement the Department's climate adaptation response. The Southeast Climate Science Center (SE CSC) was established at North Carolina State University (NCSU) in Raleigh, North Carolina, in 2010, under a 5-year cooperative agreement with the U.S. Geological Survey (USGS), to identify and address the regional challenges presented by climate change and variability in the Southeastern United States. All eight regional CSC hosts, including NCSU, were selected through a competitive process. Since its opening, the focus of the SE CSC has been on working with partners in the identification and development of research-based information that can assist managers, including cultural and natural resource managers, in adapting to global change processes, such as climate and land use change, that operate at local to global scales and affect resources important to the DOI mission. The SE CSC was organized to accomplish three goals: Provide co-produced, researched based, actionable science that supports transparent global change adaptation decisions . Convene conversations among decision makers, scientists, and managers to identify key ecosystem adaptation decisions driven by climate and land use change, the values and objectives that will be used to make decisions, and the research-based information needed to assess adaptation options . Build the capacity of natural resource professionals, university faculty, and students to understand and frame natural resource adaptation decisions and develop and use research-based information to make adaptation decisions . This report provides an overview of the SE CSC and the projects developed by the SE CSC since its inception. An important goal of this report is to provide a framework for understanding the evolution of the SE CSC science agenda, which has evolved over the first 5 years of the Center’s operation.

Open-File Report↗

USGS2002

Data on surface-water, streambed-interstitial water, and bed-sediment quality for selected locations in the small arms impact area of central Fort Gordon, Georgia, September 4-6, 2001

In September 2001, the U.S. Geological Survey, in cooperation with the Environmental and Natural Resources Management Office of the U.S. Army Signal Center and Fort Gordon (U.S. Department of the Army), conducted a chemical assessment of surface water, streambed-interstitial water, and bed sediments within the small arms impact area of Fort Gordon Military Installation. The study was conducted in support of the development of an Integrated Natural Resources Management Plan (INRMP) for Fort Gordon, Georgia. An effective INRMP ensures that natural resources conservation measures and U.S. Army activities on the military base are integrated and consistent with Federal requirements to manage military installations on an ecosystem basis. Filtered water samples were collected from five sites along South Prong Creek and three sites along Marcum Branch Creek for chemical analyses of major ions, nutrients, and selected trace elements. On-site measurements of pH, temperature, specific conductance, and dissolved oxygen were made at the eight sites. Filtered water collected showed varying concentrations in both surface- and streambed-interstitial water. Bed-sediment samples collected from South Prong Creek contain elevated levels of arsenic, barium, beryllium, cadmium, chromium, cobalt, copper, iron, lead, manganese, nickel, selenium, vanadium, and total organic carbon relative to previous concentrations (McConnell and others, 2000). Bed-sediment samples collected from Marcum Branch Creek contain elevated levels of beryllium, copper, lead, manganese, mercury, selenium, and total organic carbon relative to previous concentrations (McConnell and others, 2000).

Georgia↗

USGS2020

Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama

Barrier islands, such as Dauphin Island, Alabama, provide numerous invaluable ecosystem services including storm damage reduction and erosion control to the mainland, habitat for fish and wildlife, carbon sequestration in marshes, water catchment and purification, recreation, and tourism. These islands are dynamic environments that are gradually shaped by currents, waves, and tides under quiescent conditions yet can evolve in the time scale of hours to days during hurricanes and other extreme storms. The ecosystems associated with these islands also face numerous other hazards, including accelerated sea-level rise, oil spills, and anthropogenic stressors. Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Ala. The latter event prompted a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers to investigate viable, sustainable restoration measures that reduce degradation and enhance the natural resources of Dauphin Island, Ala. In collaboration with the State of Alabama and the National Fish and Wildlife Foundation, the overarching goal of the Alabama Barrier Island Restoration Feasibility Assessment project was to document baseline conditions and forecast potential conditions under varying sea-level change and storm scenarios for a no-action alternative along with a variety of restoration measures including beach and dune restoration, marsh and back-barrier restoration, and placement of sand in the littoral zone. The modeling component of this project used decadal hydrodynamic geomorphic, water quality, and habitat modeling to better understand how the various restoration measures may influence the habitat composition, sustainability, and resiliency of Dauphin Island under potential future conditions, benchmarked against the no-action case. The report covers the habitat modeling efforts associated with the Alabama Barrier Island Restoration Feasibility Assessment project. For various potential future island configurations for Dauphin Island, we predicted coverage of habitat types (for example, beach, dune, intertidal marsh, and woody vegetation) using a spatially explicit habitat model based on landscape-position information (for example, elevation and distance from shore) extracted from the hydrodynamic geomorphic outputs. Similarly, we forecasted habitat suitability for oysters and seagrass using habitat suitability index models. Another component of the Alabama Barrier Island Restoration Feasibility Assessment project, presented separately, integrates these habitat model results into a structured decision-making framework that accounts for competing objectives. Collectively, this information provides insights to natural resource managers and planners on how a restoration measure may maintain or impede natural coastal processes and provide information critical for making future-focused decisions regarding barrier island restoration.

Alabama↗

USGS2013

National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio

The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA. Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA. A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type. A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha. Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent. A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval. The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at <http://science.nature.nps.gov/im/inventory/veg> and <http://www.usgs.gov/core_science_systems/csas/vip/index.html>.

Natural Resource Technical Report↗

USGS2020

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.

Open-File Report↗

USGS2026

Evaluation of best management practices at an edge-of-field site in the Eagle Creek watershed, Ohio, 2012–20

In 2010, the U.S. Geological Survey worked in partnership with the Great Lakes Restoration Initiative and the Natural Resources Conservation Service to identify farm fields in priority watersheds—watersheds critically important to Great Lake health. Intensive best management practices were implemented in five States to test the efficacy of best management practices, also referred to as agricultural conservation practices, to reduce sediment and nutrient runoff on agricultural fields. These fields were chosen as representatives of the priority watersheds because their farming practices and geographical conditions were common among farms in those watersheds. A farm site located near Findlay, Ohio, in the Eagle Creek watershed used two conservation practices, cover crop (Natural Resources Conservation Service practice standard 340) and variable rate technology (VRT; Natural Resources Conservation Service practice standard 590), which represent common practices in the Maumee priority watershed. This study monitored surface runoff and subsurface tile runoff at the Eagle Creek watershed site. The effects of cover crop and VRT nutrient application on sediment and nutrient runoff were assessed from October 2012 to September 2020. Cover crops were applied in fall of 2016, 2017, and 2018, coinciding with VRT applications. The following parameters were analyzed as part of the study: runoff discharge; peak discharge; and concentrations and loads of total phosphorus, particulate phosphorus, dissolved reactive phosphorus, and suspended sediment. High peak runoff events disproportionally affected nutrient concentrations and loads in runoff. A threshold of the 85th percentile of the peak discharge was chosen to assess the effect of cover crop and VRT nutrient application on nutrient mitigation at each gage. Runoff events below the 85th percentile were considered small, and runoff events over the 85th percentile were considered large. Concentrations from collected water-quality samples were used for the analysis; estimated concentrations were excluded from the statistical evaluation. All surface runoff parameters during small runoff events, except surface runoff volume, were significantly lower in the period with cover crops and VRT implementation. Contrarily, subsurface runoff parameters during small events were not statistically different between the periods with and without cover crops and VRT implementation. Surface and subsurface parameters during large events were also not statistically different between the periods with and without cover crops and VRT implementation. These results indicate cover crops and VRT may improve water quality during small runoff events, but additional best management practices that mitigate large runoff events may lead to greater water-quality improvement given the contribution of large events to overall losses.

Ohio↗

USGS2010

Fort Collins Science Center- Policy Analysis and Science Assistance Branch : Integrating social, behavioral, economic and biological sciences

The Fort Collins Science Center's Policy Analysis and Science Assistance (PASA) Branch is a team of approximately 22 scientists, technicians, and graduate student researchers. PASA provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and biological analyses in the context of human-natural resource interactions. Resource planners, managers, and policymakers in the U.S. Departments of the Interior (DOI) and Agriculture (USDA), State and local agencies, as well as international agencies use information from PASA studies to make informed natural resource management and policy decisions. PASA scientists' primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to advance performance in policy relevant research areas. Management and research issues associated with human-resource interactions typically occur in a unique context, involve difficult to access populations, require knowledge of both natural/biological science in addition to social science, and require the skill to integrate multiple science disciplines. In response to these difficult contexts, PASA researchers apply traditional and state-of-the-art social science methods drawing from the fields of sociology, demography, economics, political science, communications, social-psychology, and applied industrial organization psychology. Social science methods work in concert with our rangeland/agricultural management, wildlife, ecology, and biology capabilities. The goal of PASA's research is to enhance natural resource management, agency functions, policies, and decision-making. Our research is organized into four broad areas of study.

Fact Sheet↗

USGS1996

Selected hydrologic data for the Beaver Dam Wash area, Washington County, Utah, Lincoln County, Nevada, and Mohave County, Arizona, 1991-95

The hydrologic data in this report were collected in Beaver Dam Wash and adjacent areas of Washington County, Utah, Lincoln County, Nevada, andMohave County, Arizona, from 1991 to 1995; some historical data from as far back as 1932 are included for comparative purposes. The data include records of about 100 wells, drillers' and geologic logs of selected wells, and results of chemical analyses of water from wells, springs, and surface-water sites. Discharge, water temperature, and specific-conductance measurements are reported for 33 surface-water and spring sites. Daily mean discharge data are reported for two U.S. Geological Survey streamflow-gaging stations on Beaver Dam Wash (1992-95). The data were collected as part of a study done by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Resources; the Nevada Department of Conservation and Natural Resources; and the Arizona Department of Water Resources.

Arizona, Nevada, Utah↗

USGS1985

ESTIMATE OF WORLD HEAVY CRUDE OIL AND NATURAL BITUMEN RESOURCES.

The quantity of heavy hydrocarbons - heavy crude oil and natural bitumens - known or surmised to be present in the earth is large. The total is estimated to fall in the range of 5,879,712-5,942,139 million barrels. The portion of this that may ultimately prove recoverable is small, perhaps on the order of 500,000 million barrels of heavy crude oil and 200,000 million barrels of bitumen.

Conference Paper↗

USGS1985

Ground water in Utah - A summary description of the resource and its related physical environment

Ground water is one of Utah’s most extensive and valuable natural resources. Because of its widespread occurrence in both wet and dry areas, ground water has been, and is a major factor affecting economic growth and development of the State. In some areas, ground water is used to supplement streamflow for irrigation, public supply, and other uses. In other areas, it is the only water available for use. Many communities obtain their entire water supply from ground-water sources (wells and springs) as do numerous rural and suburban households throughout the State. The ground-water reservoirs of Utah contain tremendous quantities of water – many times more than the quantity stored in all the lakes (including Great Salt Lake) and the surface-water reservoirs of the State combined. Water that discharges from those underground reservoirs in seeps and springs is vital in sustaining the flow of streams during dry summer months and in providing the water needed to maintain important wetland habitats. Those same underground reservoirs also provide large quantities of water in carryover storage for use during prolonged droughts. The U.S. Geological survey, under cooperative programs with the Utah department of Natural resources and other Federal, State, and local agencies has been studying Utah’s ground-water resources since 1897. Much information has been gained during those studies about the occurrence, availability, and quality of ground water; the withdrawal and use of the water; and the effects of withdrawal. This report summarizes that information in nontechnical language, which is designed for all readers. Readers interested in more detailed information about ground water in specific areas of Utah are referred to the reports listed by LaPray and Hamblin (1980).

Utah↗

USGS2024

Estimated reductions in phosphorus loads from removal of leaf litter in the Lake Champlain drainage area, Vermont

Excess nutrient loading and other factors are driving eutrophication and other negative effects on water-quality conditions in Lake Champlain and other receiving waters in Vermont. Two common best management practices were evaluated to determine how these practices can be optimized by targeting maintenance and operation to align better with seasonally driven needs, specifically to help municipalities remove a greater proportion of seasonal leaves and organic debris, reduce nutrient loading, and achieve water-quality goals. To characterize solid materials typically removed by the municipal BMPs of catch-basin (CB) cleaning and street cleaning (SC), subsamples of CB and SC materials were collected each month from nine participating municipalities in central and northwestern Vermont between September 2017 and November 2018. Monthly and seasonal composites of CB and SC samples were created from the subsamples of available materials from all municipalities. Samples were analyzed for concentrations of total organic carbon, total Kjeldahl nitrogen, and total phosphorus (P), and separated into three particle-size fractions. Distribution of particle-size fractions was similar between CB and SC as both practices generally collect the coarser fraction of solid materials (greater than 125 micrometers in diameter). In the fall, however, the range of the coarser fraction of materials increased. This is attributed to the ability of SC to collect leaves and other light organic materials that commonly pass through a CB system designed to trap heavier materials. Total organic carbon, total Kjeldahl nitrogen, and total P concentrations were highest in the catch-basin samples in the fall of 2017, and concentrations in the SC samples were highest in the fall of 2018. The collection of fewer samples in 2017 may account for some of the variability between fall 2017 and fall 2018 results. A subset of SC samples collected from piles representing specific street-cleaning routes in September and November 2018 were also analyzed. Materials collected in November were dominated by leaves, and the concentrations of the analyzed species of carbon, nitrogen, and phosphorus in some samples were more than double those in samples collected on the same street-cleaning routes in September. The Vermont Department of Environmental Conservation and the University of Vermont developed estimates of load-reduction credits for CB and SC practices based on a policy developed by the Wisconsin Department of Natural Resources that determined the potential for credits associated with leaf-removal activities. This process also considered BMPs that were initiated during the U.S. Environmental Protection Agency’s Lake Champlain Basin Total Maximum Daily Load monitoring period (2000 to 2009) and adapted the Wisconsin Department of Natural Resources policies to apply to existing SC routes in the cooperating Vermont municipalities that possessed at least 17 percent tree cover. This exercise demonstrated that applying the Wisconsin Department of Natural Resources policy to existing street-cleaning routes possessing 17 percent or more tree cover would result in reductions in total P loads up to 65 percent of mandated target reductions, and about a 25 percent reduction on average. Continuous simulations of stormwater runoff volume, and of loads of suspended sediments and total P, also were created for Englesby Brook Basin, an urbanized basin in Burlington and South Burlington that drains to Lake Champlain. Although the basin is more developed than the average of the nine cooperating municipalities, streamflow and P loading data collected by the U.S. Geological Survey were available to evaluate model performance. Simulations based on a year of average climatic conditions projected potential small reductions in total P of 0.08 to 0.10 percent as a result of CB cleaning and SC practices. Simulated weekly SC practices, however, reduced street-solid loads by as much as 7 percent. When the proportion of total P seen in fall SC materials collected in Vermont was applied to these simulated street-solid loads, estimated reductions of total P were about 29 percent. The combination of analytical results, estimated load-reduction credits, and simulated reductions indicate that targeted increases of SC activities to reduce leaf loading in the fall have the potential to reduce loading to receiving waters and could help regulated communities meet their water-quality goals.

Vermont↗

USGS2016

Groundwater contaminant plume maps and volumes, 100-K and 100-N Areas, Hanford Site, Washington

This study provides an independent estimate of the areal and volumetric extent of groundwater contaminant plumes which are affected by waste disposal in the 100-K and 100-N Areas (study area) along the Columbia River Corridor of the Hanford Site. The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past. All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER ® data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER ® , along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards. A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER ® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3). Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors. The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.

Washington↗

USGS2011

Adapting to climate change at Olympic National Forest and Olympic National Park

Climate change presents a major challenge to natural resource managers both because of the magnitude of potential effects of climate change on ecosystem structure, processes, and function, and because of the uncertainty associated with those potential ecological effects. Concrete ways to adapt to climate change are needed to help natural resource managers take the first steps to incorporate climate change into management and take advantage of opportunities to counteract the negative effects of climate change. We began a climate change adaptation case study at Olympic National Forest (ONF) in partnership with Olympic National Park (ONP) to determine how to adapt management of federal lands on the Olympic Peninsula, Washington, to climate change. The case study began in the summer of 2008 and continued for 1½ years. The case study process involved science-based sensitivity assessments, review of management activities and constraints, and adaptation workshops in each of four focus areas (hydrology and roads, fish, vegetation, and wildlife). The process produced adaptation options for ONF and ONP, and illustrated the utility of place-based vulnerability assessment and science-management workshops in adapting to climate change. The case study process provides an example for other national forests, national parks, and natural resource agencies of how federal land management units can collaborate in the initial stages of climate change adaptation. Many of the ideas generated through this process can potentially be applied in other locations and in other agencies

Washington↗

USGS2014

BatTool: an R package with GUI for assessing the effect of White-nose syndrome and other take events on Myotis spp. of bats

Background: Myotis species of bats such as the Indiana Bat and Little Brown Bat are facing population declines because of White-nose syndrome (WNS). These species also face threats from anthropogenic activities such as wind energy development. Population models may be used to provide insights into threats facing these species. We developed a population model, BatTool, as an R package to help decision makers and natural resource managers examine factors influencing the dynamics of these species. The R package includes two components: 1) a deterministic and stochastic model that are accessible from the command line and 2) a graphical user interface (GUI). Results: BatTool is an R package allowing natural resource managers and decision makers to understand Myotis spp. population dynamics. Through the use of a GUI, the model allows users to understand how WNS and other take events may affect the population. The results are saved both graphically and as data files. Additionally, R-savvy users may access the population functions through the command line and reuse the code as part of future research. This R package could also be used as part of a population dynamics or wildlife management course. Conclusions: BatTool provides access to a Myotis spp. population model. This tool can help natural resource managers and decision makers with the Endangered Species Act deliberations for these species and with issuing take permits as part of regulatory decision making. The tool is available online as part of this publication.

Source Code for Biology and Medicine↗

USGS2017

Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands

The Little Plover River is a groundwater-fed stream in the sand plains region of central Wisconsin. In this region, sandy sediment deposited during or soon after the last glaciation forms an important unconfined sand and gravel aquifer. This aquifer supplies water for numerous high-capacity irrigation, municipal, and industrial wells that support a thriving agricultural industry. In recent years the addition of many new wells, combined with observed diminished flows in the Little Plover and other nearby rivers, has raised concerns about the impacts of the wells on groundwater levels and on water levels and flows in nearby lakes, streams, and wetlands. Diverse stakeholder groups, including well operators, Growers, environmentalists, local land owners, and regulatory and government officials have sought a better understanding of the local groundwater-surface water system and have a shared desire to balance the water needs of the he liagricultural, industrial, and urban users with the maintenance and protection of groundwater-dependent natural resources. To help address these issues, the Wisconsin Department of Natural Resources requested that the Wisconsin Geological and Natural History Survey and U.S. Geological Survey cooperatively develop a groundwater flow model that could be used to demonstrate the relationships among groundwater, surface water, and well withdrawals and also be a tool for testing and evaluating alternative water management strategies for the central sands region. Because of an abundance of previous studies, data availability, local interest, and existing regulatory constraints the model focuses on the Little Plover River watershed, but the modeling methodology developed during this study can apply to much of the larger central sands of Wisconsin. The Little Plover River groundwater flow model simulates three-dimensional groundwater movement in and around the Little Plover River basin under steady-state and transient conditions. This model explicitly includes all high-capacity wells in the model domain and simulates seasonal variations in recharge and well pumping. The model represents the Little Plover River, and other significant streams and drainage ditches in the model domain, as fully connected to the groundwater system, computes stream base flow resulting from groundwater discharge, and routes the flow along the stream channel. A separate soil-water-balance (SWB) model was used to develop groundwater recharge arrays as input for the groundwater flow model. The SWB model uses topography, soils, land use, and climatic data to estimate recharge as deep drainage from the soil zone. The SWB model explicitly includes recharge originating as irrigation water, and computes irrigation using techniques similar to those used by local irrigation operators. The groundwater flow model uses the U.S. Geological Survey’s MODFLOW modeling code which is freely available, widely accepted, and commonly used by the groundwater community. The groundwater flow model and the SWB model use identical high-resolution numerical grids having model cells 100 feet on a side, with physical properties assigned to each grid cell. This grid allows accurate geographic placement of wells, streams, and other model features. The 3-dimensional grid has three layers; layers 1 and 2 represent the sand and gravel aquifer and layer 3 represents the underlying sandstone. The distribution of material properties in the model (hydraulic conductivity, aquifer thickness, etc.) comes from previous published geologic studies of the region, updated by calibration to recent streamflow and groundwater level data. The SWB model operates on a daily time step. The groundwater flow model was calibrated to monthly stress periods with time steps ranging from 1 to 16 days. More detailed time discretization is possible. The groundwater model was calibrated to water-level and streamflow data collected during 2013 and 2014 by adjusting model parameters (primarily hydraulic conductivity, storage, and recharge) until the model produced a conditionally optimal fit between field observations and model output, subject to consistency with previously published geologic studies. Calibration was performed under both steady and transient conditions, and used a sophisticated parameter-estimation procedure (PEST) for the calibration process and to identify important model parameters. For the Little Plover River, the two most important parameters are the global recharge multiplier and the hydraulic conductivity of the stream bed. The calibrated model produces water-level and mass-balance results that are consistent with field observations and previous studies of the area. The completed model is a powerful tool for testing and demonstrating alternative water-management scenarios. Example model applications described in this report include simulating how the cumulative impacts of pumping and land-use change have affected average baseflow in the Little Plover River. Depletion-potential mapping represents a method for predicting which wells and well locations have the greatest impact on nearby surface-water resources. The completed model is publicly available, along with a companion user’s guide to assist with its operation, at http://wgnhs.org/littleplover- river-groundwater-model.

Wisconsin↗

USGS2025

Workshop: Nature-based solutions to ecological and economic problems caused by extreme precipitation events in the Upper Mississippi River Basin

Future climate conditions in the Upper Mississippi River Basin are projected to include many more extreme precipitation events. These intense periods of rain can lead to flooding of the Mississippi River itself, as well the small streams and rivers that feed it. This flooding presents a challenge for local communities, farmers, small businesses, river users, and the ecosystems and wildlife in the area. To reduce the damage done by these extreme rainfall events, ‘natural solutions’ are often helpful. This might include preserving forests and grasslands to absorb rainwater before it arrives at streams or restoring wetlands to slow and clean runoff water. For river and natural resource managers to adapt to future climate by using these natural solutions, however, they require accurate information about the projected increase in extreme rainfall events and the effectiveness and costs of a variety of solutions. To provide this information, researchers must understand the decisions that managers are making and the challenges they face. In this project, researchers will host a workshop to facilitate knowledge sharing between natural resource managers, climate modelers, and scientists studying natural solutions. Participants will discuss climate projections related to extreme precipitation events in the region, as well as the management implications and decision-making challenges associated with these events. These conversations will cultivate collaborative relationships between managers and researchers to address critical knowledge gaps and improve future management efforts in the Upper Mississippi River Basin.

Upper Mississippi River basin↗

USGS1976

Water resources of the Rainy Lake watershed, northeastern Minnesota

The watershed includes 1,481 lakes that are 10 acres (4 square hectometers) or larger (Minnesota Division of Waters, Soils, and Minerals, 1968). The area of these lakes total about 435,000 acres (176,000 hm 2 ) or 15 percent of the watershed. Most of the lakes are smaller than 250 acres (101 hm 2 ) (graph); data pertaining to selected large lakes are given in the table below. More than 60 percent of the lakes larger than 10 acres (4 hm 2 ) are in the BWCA. The primitive character of the BWCA is maintained in accordance with the Wilderness Act of September 3, 1964. Most lakes not in the BWCA were assigned a Public Waters Classification by the Minnesota Department of Natural Resources, based upon the suitability of the lake for future shoreland development (unpublished data from the Minnesota Department of Natural Resources). “Natural environment” is most restrictive and “general development” least restrictive with respect to development standards. About 80 percent of lakes classified in the watershed have been designated “natural environment.”

Minnesota↗