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USGS2018

Grizzly bear depredation on grazing allotments in the Yellowstone ecosystem

Grizzly bear (Ursus arctos) conflicts with humans, including livestock depredation on public land grazing allotments, have increased during the last several decades within the Greater Yellowstone Ecosystem (GYE) in the western United States as the grizzly bear population has grown in number and occupied range. Minimizing conflicts and improving conservation efficacy requires information on the relationships between livestock depredations, allotment management, grizzly bear habitat conditions, and their interactions. We used generalized linear mixed models to evaluate spatio-temporal relationships between grizzly bear depredation of livestock and the characteristics of 316 United States Department of Agriculture Forest Service and National Park Service grazing allotments in the GYE during 1992–2014. We evaluated relationships at 2 spatial extents, representing daily and annual grizzly bear activity areas. During the study period, more grazing allotments became occupied by grizzly bears and most livestock depredations were associated with these areas of population expansion. Number of livestock (beta = 1.15 +/- 0.19 [SE]) and grizzly bear density index (beta = 1.13 +/- 0.10) had the greatest effects on the number of livestock depredation events relative to other allotment attributes. Estimated number of depredation events increased by approximately 20% when cow-calf pairs increased by 100 pairs and grizzly bear density index increased by 1 bear/196 km2 (the average annual home-range size of a female grizzly bear in the GYE). Additionally, grazing allotment size was positively related to the number of depredation events (beta = 0.56 +/- 0.16), whereas the presence of bull cattle or horses was associated with an approximately 50% reduction in depredations (beta = -0.71 +/- 0.37). Livestock depredation events were greater for allotments with lower road density (beta = -0.89 +/- 0.28), less rugged terrain (beta = -0.57 +/- 0.25), higher vegetative primary productivity (beta = 0.33 +/- 0.16), and more whitebark pine coverage (beta = 0.30 +/- 0.15). Relationships between depredations and grizzly bear habitat conditions varied across spatial extents. As the grizzly bear population continues to expand, natural resource managers and livestock producers could focus efforts on allotments with a higher density of grizzly bears, fewer roads, and quality grizzly bear habitat, including higher vegetative productivity, when developing cooperative management plans and preventative measures to reduce the likelihood of depredation. The perspectives gained from our analysis provide context for long-term, landscape-level planning to accommodate livestock production on public lands while meeting conservation goals for grizzly bears.

Idaho, Montana, Wyoming↗

USGS2012

National assessment of shoreline change: Historical shoreline change in the Hawaiian Islands

Sandy beaches of the United States are some of the most popular tourist and recreational destinations. Coastal property constitutes some of the most valuable real estate in the country. Beaches are an ephemeral environment between water and land with unique and fragile natural ecosystems that have evolved in equilibrium with the ever-changing winds, waves, and water levels. Beachfront lands are the site of intense residential and commercial development even though they are highly vulnerable to several natural hazards, including marine inundation, flooding and drainage problems, effects of storms, sea-level rise, and coastal erosion. Because the U.S. population continues to shift toward the coast where valuable coastal property is vulnerable to erosion, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change. One aspect of this effort, the National Assessment of Shoreline Change, uses shoreline position as a proxy for coastal change because shoreline position is one of the most commonly monitored indicators of environmental change (for example, Fletcher, 1992; Dolan and others, 1991; Douglas and others, 1998; Galgano and others, 1998). Additionally, the National Research Council (1990) recommended the use of historical shoreline analysis in the absence of a widely accepted model of shoreline change. A principal purpose of the USGS shoreline change research is to develop a common methodology so that shoreline change analyses for the continental U.S., portions of Hawaii, and Alaska can be updated periodically in a consistent and systematic manner. The primary objectives of this study were to (1) develop and implement improved methods of assessing and monitoring shoreline movement, and (2) improve current understanding of the processes controlling shoreline movement. Achieving these ongoing long-term objectives requires research that (1) examines the original sources of shoreline data (for example, maps, air photos, global positioning system (GPS), Light Detection and Ranging (lidar)); (2) evaluates the utility of different shoreline proxies (for example, geomorphic feature, water mark, tidal datum, elevation), including the errors associated with each; (3) investigates bias and potential errors associated with integrating different shoreline proxies from different sources; (4) develops standard, uniform methods of shoreline change analysis; (5) examines the effects of human activities on shoreline movement and rates of change; and (6) investigates alternative mathematical methods for calculating historical rates of change and uncertainties associated with them. This report summarizes historical shoreline changes on the three most densely populated islands of the eight main Hawaiian Islands: Kauai, Oahu, and Maui. The report emphasizes the hazard from “chronic” (decades to centuries) erosion at regional scales and strives to relate this hazard to the body of knowledge regarding coastal geology of Hawaii because of its potential impact on natural resources, the economy, and society. Results are organized by coastal regions (island side) and sub-regions (common littoral characteristics). This report of Hawaii coasts is part of a series of reports that include text summarizing methods, results, and implications of the results. In addition, geographic information system (GIS) data used in the analyses are made available for download (Romine and others, 2012). The rates of shoreline change and products presented in this report are not intended for site-specific analysis of shoreline movement, nor are they intended to replace any official source of shoreline change information identified by local or State government agencies, or other Federal entities that are used for regulatory purposes. Rates of shoreline change presented herein may differ from other published rates, and differences do not necessarily indicate that the other rates are inaccurate. Some discrepancies are to be expected, considering the many possible ways of determining shoreline positions and rates of change, and the inherent uncertainty in calculating these rates. Rates of shoreline change presented in this report represent shoreline movement under past conditions and are not intended for use in predicting future shoreline positions or future rates of shoreline change.

Hawai'i↗

USGS1980

Research on interactive genetic-geological models to evaluate favourability for undiscovered uranium resources

Current methods of evaluating favourability for undiscovered uranium resources are unduly subjective, quite possibly inconsistent and, as a consequence, of questionable reliability. This research is aimed at reducing the subjectivity and increasing the reliability by designing an improved method that depends largely on geological data and their statistical frequency of occurrence. This progress report outlines a genetic approach to modelling the geological factors that controlled uranium mineralization in order to evaluate the favourability for the occurrence of undiscovered uranium deposits of the type modeled. A genetic model is constructed from all the factors that describe the processes, in chronological sequence, that formed uranium deposits thought to have a common origin. The field and laboratory evidence for the processes constitute a geologic occurrence base that parallels the chronological sequence of events. The genetic model and the geologic-occurrence base are portrayed as two columns of an interactive matrix called the "genetic-geologic model". For each column, eight chronological stages are used to describe the overall formation of the uranium deposits. These stages consist of (1) precursor processes; (2) host-rock formation; (3) preparation of host-rock; (4) uranium-source development; (5) transport of uranium; (6) primary uranium deposition; (7) post-deposition modification; and (8) preservation. To apply the genetic-geological model to evaluate favourability, a question is posed that determines the presence or absence of each attribute listed under the geologic-occurrence base. By building a logic circuit of the attributes according to either their essential or non-essential nature, the resultant match between a well-documented control area and the test area may be determined. The degree of match is a measure of favourability for uranium occurrence as hypothesized in the genetic model. This process of geological decision analysis results in a series of favourability maps that can be combined into a final composite favourability map.

Conference Paper↗

USGS2014

Hydrology and numerical simulation of groundwater movement and heat transport in Snake Valley and surrounding areas, Juab, Miller, and Beaver Counties, Utah, and White Pine and Lincoln Counties, Nevada

Snake Valley and surrounding areas, along the Utah-Nevada state border, are part of the Great Basin carbonate and alluvial aquifer system. The groundwater system in the study area consists of water in unconsolidated deposits in basins and water in consolidated rock underlying the basins and in the adjacent mountain blocks. Most recharge occurs from precipitation on the mountain blocks and most discharge occurs from the lower altitude basin-fill deposits mainly as evapotranspiration, springflow, and well withdrawals. The Snake Valley area regional groundwater system was simulated using a three-dimensional model incorporating both groundwater flow and heat transport. The model was constructed with MODFLOW-2000, a version of the U.S. Geological Survey’s groundwater flow model, and MT3DMS, a transport model that simulates advection, dispersion, and chemical reactions of solutes or heat in groundwater systems. Observations of groundwater discharge by evapotranspiration, springflow, mountain stream base flow, and well withdrawals; groundwater-level altitudes; and groundwater temperatures were used to calibrate the model. Parameter values estimated by regression analyses were reasonable and within the range of expected values. This study represents one of the first regional modeling efforts to include calibration to groundwater temperature data. The inclusion of temperature observations reduced parameter uncertainty, in some cases quite significantly, over using just water-level altitude and discharge observations. Of the 39 parameters used to simulate horizontal hydraulic conductivity, uncertainty on 11 of these parameters was reduced to one order of magnitude or less. Other significant reductions in parameter uncertainty occurred in parameters representing the vertical anisotropy ratio, drain and river conductance, recharge rates, and well withdrawal rates. The model provides a good representation of the groundwater system. Simulated water-level altitudes range over almost 2,000 meters (m); 98 percent of the simulated values of water-level altitudes in wells are within 30 m of observed water-level altitudes, and 58 percent of them are within 12 m. Nineteen of 20 simulated discharges are within 30 percent of observed discharge. Eighty-one percent of the simulated values of groundwater temperatures in wells are within 2 degrees Celsius (°C) of the observed values, and 55 percent of them are within 0.75 °C. The numerical model represents a more robust quantification of groundwater budget components than previous studies because the model integrates all components of the groundwater budget. The model also incorporates new data including (1) a detailed hydrogeologic framework, and (2) more observations, including several new water-level altitudes throughout the study area, several new measurements of spring discharge within Snake Valley which had not previously been monitored, and groundwater temperature data. Uncertainty in the estimates of subsurface flow are less than those of previous studies because the model balanced recharge and discharge across the entire simulated area, not just in each hydrographic area, and because of the large dataset of observations (water-level altitudes, discharge, and temperatures) used to calibrate the model and the resulting transmissivity distribution. Groundwater recharge from precipitation and unconsumed irrigation in Snake Valley is 160,000 acre-feet per year (acre-ft/yr), which is within the range of previous estimates. Subsurface inflow from southern Spring Valley to southern Snake Valley is 13,000 acre-ft/yr and is within the range of previous estimates; subsurface inflow from Spring Valley to Snake Valley north of the Snake Range, however, is only 2,200 acre-ft/yr, which is much less than has been previously estimated. Groundwater discharge from groundwater evapotranspiration and springs is 100,000 acre-ft/yr, and discharge to mountain streams is 3,300 acre-ft/yr; these are within the range of previous estimates. Current well withdrawals are 28,000 acre-ft/yr. Subsurface outflow from Snake Valley moves into Pine Valley (2,000 acre-ft/yr), Wah Wah Valley (23 acre-ft/yr), Tule Valley (33,000 acre-ft/yr), Fish Springs Flat (790 acre-ft/yr), and outside of the study area towards Great Salt Lake Desert (8,400 acre-ft/yr); these outflows, totaling about 44,000 acre-ft/yr, are within the range of previous estimates. The subsurface flow amounts indicate the degree of connectivity between hydrographic areas within the study area. The simulated transmissivity and locations of natural discharge, however, provide a better estimate of the effect of groundwater withdrawals on groundwater resources than does the amount and direction of subsurface flow between hydrographic areas. The distribution of simulated transmissivity throughout the study area includes many areas of high transmissivity within and between hydrographic areas. Increased well withdrawals within these high transmissivity areas will likely affect a large part of the study area, resulting in declining groundwater levels, as well as leading to a decrease in natural discharge to springs and evapotranspiration.

Nevada, Utah↗

USGS2003

Quantile regression models of animal habitat relationships

Typically, all factors that limit an organism are not measured and included in statistical models used to investigate relationships with their environment. If important unmeasured variables interact multiplicatively with the measured variables, the statistical models often will have heterogeneous response distributions with unequal variances. Quantile regression is an approach for estimating the conditional quantiles of a response variable distribution in the linear model, providing a more complete view of possible causal relationships between variables in ecological processes. Chapter 1 introduces quantile regression and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of estimates for homogeneous and heterogeneous regression models. Chapter 2 evaluates performance of quantile rankscore tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). A permutation F test maintained better Type I errors than the Chi-square T test for models with smaller n , greater number of parameters p , and more extreme quantiles τ. Both versions of the test required weighting to maintain correct Type I errors when there was heterogeneity under the alternative model. An example application related trout densities to stream channel width:depth. Chapter 3 evaluates a drop in dispersion, F -ratio like permutation test for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). Chapter 4 simulates from a large ( N = 10,000) finite population representing grid areas on a landscape to demonstrate various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable (spatially and not spatially structured). Depending on whether interactions of the measured habitat and unmeasured variable were negative (interference interactions) or positive (facilitation interactions), either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Sampling ( n = 20 - 300) simulations demonstrated that confidence intervals constructed by inverting rankscore tests provided valid coverage of these biased parameters. Quantile regression was used to estimate effects of physical habitat resources on a bivalve mussel ( Macomona liliana ) in a New Zealand harbor by modeling the spatial trend surface as a cubic polynomial of location coordinates.

Thesis↗

USGS2013

Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in Global mineral resource assessment

The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of Southeast Asia and Melanesia as part of a global mineral resource assessment. The region hosts world-class porphyry copper deposits and underexplored areas that are likely to contain undiscovered deposits. Examples of known porphyry copper deposits include Batu Hijau and Grasberg in Indonesia; Panguna, Frieda River, and Ok Tedi in Papua New Guinea; and Namosi in Fiji. This assessment covers the countries of Cambodia, Indonesia, Lao People’s Democratic Republic, Malaysia, Myanmar, Papua New Guinea, Singapore, Thailand, and parts of southeastern China, India, the Solomon Islands, Vanuatu, and Fiji. Twenty-two geographic areas were delineated as tracts that are permissive for porphyry copper deposits in Southeast Asia. Permissive tracts are grouped into four broadly defined geographic/geologic areas, as follows: (1) the Indochina Peninsula area, (2) Indonesian and Malaysian Islands, (3) New Guinea Island and Papuan New Guinea islands, and (4) Melanesia. Individual tracts range from less than 1,000 to more than 350,000 square kilometers in area. Permissive tracts are based on mapped and inferred subsurface (<1 kilometer depth) distributions of igneous rocks of specific age ranges that define magmatic arcs and magmatic belts that are likely to contain porphyry copper deposits. Most of these magmatic arcs are subduction-related, although some have porphyry-style deposits occurring in postcollisional and (or) poorly understood tectonic settings. Although maps at a variety of different scales were used in the compilation, the final tract boundaries are intended for use at a scale of 1:1,000,000. Global grade and tonnage models for porphyry copper deposits were evaluated. Most of the known deposits are best described as fitting the copper-gold (Cu-Au) subtype of porphyry copper deposit. For some permissive tracts, a general porphyry copper-gold-molybdenum (Cu-Au-Mo) model was used. Assessment participants estimated numbers of undiscovered deposits at different levels of confidence for most of the permissive tracts. These estimates were combined with grade and tonnage models using a Monte Carlo simulation to estimate undiscovered resources. Additional resources in extensions of deposits with identified resources were not evaluated. Assessment results, presented in tables and graphs, show mean amounts of metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract. This assessment estimated a mean of 89 undiscovered porphyry copper deposits for the assessed permissive tracts in Southeast Asia and Melanesia. About 288 million metric tons (Mt) of copper and 18,000 metric tons (t) of gold, as well as byproduct molybdenum and silver, could be associated with undiscovered deposits. This represents about four times the number of deposits with identified resources (23) already discovered in Southeast Asia; reliable reported identified resources for those 23 deposits total 84 Mt of copper and 6,000 t of gold. Eleven permissive tracts have no known porphyry copper deposits with reported resources. Three of those 11 tracts lacked sufficient information for a probabilistic assessment and are discussed in qualitative terms. On a regional basis, both the Indochina Peninsula area and the Indonesian-Malaysian Islands area are estimated to contain about 10 times as much in place copper in undiscovered porphyry copper deposits as has been identified to date. For the New Guinea Island areas, the ratio of undiscovered to identified copper resources is about 2. Some parts of the region have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in Southeast Asia and Melanesia. However, predicted undiscovered deposits may not be found, and if found, may not be developed. This assessment includes an overview of the assessment results with summary tables. Detailed descriptions of each tract are included in appendixes, with estimates of numbers of undiscovered deposits, and probabilistic estimates of amounts of copper, molybdenum, gold, and silver that could be contained in undiscovered deposits for each permissive tract. A geographic information system (GIS) that accompanies the report includes tract boundaries and a database of known porphyry copper deposits and significant prospects.

Scientific Investigations Report↗

USGS2023

Prediction of the probability of elevated nitrate concentrations at groundwater depths used for drinking-water supply in the Puget Sound basin, Washington, 2004–19

The Puget Sound basin encompasses the 13,700-square-mile area that drains to the Puget Sound and the adjacent marine waters of Washington State. Well more than 4 million people live within the basin, with numbers continuing to increase, who rely on the basin’s natural resources including groundwater. The Puget Sound Partnership was created by a Washington State statute to implement a science-based recovery of the Puget Sound to help address impacts to these resources. As part of the recovery, the partnership developed the Puget Sound Vital Signs as measures of ecosystem health that guide the assessment of progress toward Puget Sound recovery goals. The Puget Sound Partnership Leadership Council adopted a Drinking Water Vital Sign associated with human health and quality of life, recognizing certain indicators as integral to the sustainability of Puget Sound recovery efforts. One such Vital Sign indicator was the vulnerability of groundwater throughout the aquifers of the Puget Sound basin to elevated nitrate concentrations as defined by the probability of exceeding 2 milligrams/liter (mg/L) at a specific location and well depth. The U.S. Geological Survey (USGS) led the effort to characterize groundwater vulnerability. For this study, groundwater vulnerability refers to a probability with which a contaminant applied at or near the land surface can migrate to the aquifer of interest for a given set of land-use practices. Nitrate concentration data were selected for evaluation because elevated nitrate concentrations are typically caused by anthropogenic activities and have been associated with deleterious impacts on human health. To identify groundwater vulnerability to elevated nitrate concentrations, logistic regression was used to relate anthropogenic (human associated) and natural variables to the occurrence of elevated nitrate concentrations in untreated groundwater from large public water supply system wells found within the Washington State Department of Health Sentry database. Variables that were analyzed included well depth, soil hydraulic conductivity, precipitation, population density, fertilizer application amounts, and land-use types. Statistically significant models that predicted the probabilities of groundwater nitrate concentrations greater than 2 mg/L based on the predictor variables were created for the time periods 2000–04, 2005–09, 2010–14, and 2015–19. For all time periods, well depth and a measure of the abundance of urban and agricultural land over or near the well consistently helped explain the vulnerability of the well to elevated nitrate concentrations defined as a probability of exceeding 2 mg/L of nitrate. Precipitation and (or) soil hydraulic conductivity were also important predictor variables in the models. The models for each time period were used to create maps of groundwater vulnerability at 150- and 300-foot depths throughout the Puget Sound basin. As expected, the most vulnerable locations were associated with shallower well depths and increased agriculture and urban land cover. Across all four time periods, groundwater vulnerability throughout the Puget Sound was low, with probabilities of exceeding 2 mg/L concentrations of nitrate at depths at 150 and 300 feet typically less than 50 percent. Results also found a slight decrease in probabilities of elevated nitrate concentrations throughout the basin over time. More specifically, additional statistical tests found that groundwater with probabilities of less than about 60 percent declined from 2000 to 2019 and represented more than 75 percent of the modeled Puget Sound basin aquifer. Wells with greater than 60 percent probability increased over the same time period but represented only about 25 percent of the aquifer. The maps and statistical analysis presented in the study provide valuable and informative evaluation of the vulnerability of groundwater in the Puget Sound basin to elevated nitrate concentrations. The probability maps do not represent measured nitrate concentrations in groundwater, but rather they present the probability that nitrate concentrations exceed 2 mg/L. The models and predictions from this study are a viable indicator for the Puget Sound Partnership’s Healthy Human Population—Drinking Water Vital Sign. The logistic regression modeling approach presented here benefits water managers by allowing them to assess temporal trends in a range of probabilities, explore vulnerability changes as new regional land cover and anthropogenic data are generated, and distinguish vulnerabilities at different depths within the aquifer.

Washington↗

USGS1996

Synthesis of natural flows at selected sites in the upper Missouri River basin, Montana, 1928-89

Natural monthly streamflows were synthesized for the years 1928-89 for 43 sites in the upper Missouri River Basin upstream from Fort Peck Lake in Montana. The sites are represented as nodes in a streamflow accounting model being developed by the Bureau of Reclamation. Recorded and historical flows at most sites have been affected by human activities including reservoir storage, diversions for irrigation, and municipal use. Natural flows at the sites were synthesized by eliminating the effects of these activities. Recorded data at some sites do not include the entire study period. The missing flows at these sites were estimated using a statistical procedure. The methods of synthesis varied, depending on upstream activities and information available. Recorded flows were transferred to nodes that did not have streamflow-gaging stations from the nearest station with a sufficient length of record. The flows at one node were computed as the sum of flows from three upstream tributaries. Monthly changes in reservoir storage were computed from monthend contents. The changes in storage were corrected for the effects of evaporation and precipitation using pan-evaporation and precipitation data from climate stations. Irrigation depletions and consumptive use by the three largest municipalities were computed. Synthesized natural flow at most nodes was computed by adding algebraically the upstream depletions and changes in reservoir storage to recorded or historical flow at the nodes.

Water-Resources Investigations Report↗

USGS2002

Simulated pond-aquifer interactions under natural and stressed conditions near Snake Pond, Cape Cod, Massachusetts

A numerical model was used to simulate pond-aquifer interactions under natural and stressed conditions near Snake Pond, Cape Cod, Massachusetts. Simulation results show that pond-bottom hydraulic conductivity, which represents the degree of hydraulic connection between the pond and the aquifer, is an important control on these interactions. As this parameter was incrementally increased from 10 to 350 feet per day, the rate of ground-water inflow into the pond under natural conditions increased by about 250 percent, the associated residence times of water in the pond decreased by about 50 percent, and ground-water inflow to the pond shifted closer to the pond shore. Most ground-water inflow (90 to 98 percent) was in the upper model layer, which corresponded to shallow, near-shore areas of the pond, over the entire range of pond-bottom hydraulic conductivity. Ground-water flow paths into the pond became more vertical, the contributing area to the pond became larger, and the pond captured water from greater depths in the aquifer as the hydraulic conductivity of the pond bottom was increased. The pond level, however, remained nearly constant, and regional ground-water levels and gradients differed little over the range of pond-bottom hydraulic conductivity, indicating that calibrated models with similar head solutions can have different pond-aquifer interaction characteristics. Hydrologic stresses caused by a simulated plume-containment system that specifies the extraction and injection of large volumes of ground water near the pond increased the pond level by about 0.4 foot and ground-water inflow rates into the pond by about 25 percent. Several factors related to the operation of the simulated containment system are affected by the hydraulic conductivity of the pond bottom. With increasing pond-bottom hydraulic conductivity, the amount of injected water that flows into Snake Pond increased and the amount of water recirculated between extraction and injection wells decreased. Comparison of simulations in which pond-bottom hydraulic conductivity was varied throughout the pond and simulations in which hydraulic conductivity was varied only in areas corresponding to shallow, near-shore areas of the pond indicate that the simulated hydraulic conductivity of the pond bottom in deeper parts of the pond had little effect on pond-aquifer interactions under both natural and stressed conditions.

Massachusetts↗

USGS2011

Assessment of coal geology, resources, and reserves in the Southwestern Powder River Basin, Wyoming

The availability of abundant new borehole data from recent coal bed natural gas development was utilized by the U.S. Geological Survey for a comprehensive evaluation of coal resources and reserves in the southwestern part of the Powder River Basin in Wyoming. This report on the Southwestern Powder River Basin assessment area represents the third area within the basin to be assessed, the first being for coal resources and reserves in the Gillette coal field in 2008, and the second for coal resources and reserves in the northern Wyoming area of the basin in 2010. There are no active coal mines in the Southwestern Powder River Basin assessment area. The only significant production is attributed to the Dave Johnston Mine, in the extreme southern part of the area, which accounted for some 104 million short tons of coal from 1959 to 2000. Several small mines were developed in the 1950s near the Lake DeSmet area in the northwestern part of the area; however, less than 25,000 short tons of coal were produced. Eight coal beds are present at depths between 1,000 and 2,000 ft in the Southwestern Powder River Basin assessment area. Portions of these coal beds might be recovered by underground mining methods in the future; however, the lack of sufficient drill data precluded an economic study to assess the potential of surface mineable coal resources. Consequently, none of the coal resources in the Southwestern Powder River Basin assessment area were designated as reserves or recoverable coal. A total of 37 coal beds were identified during this assessment, 23 of which were modeled and evaluated to determine in-place coal resources. The total original coal resource in the Southwestern Powder River Basin assessment area for these 23 coal beds, with no restrictions applied was calculated to be 369 billion short tons. Available coal resources, which are part of the original resource that is accessible for potential mine development after subtracting all restrictions, are about 341 billion short tons (92.4 percent of the total original resource). Approximately 61 percent are at depths between 1,000 and 2,000 ft, with a modeled price of about $30 per short ton. Therefore, the majority of coal resources in the South-western Powder River Basin assessment area are considered sub-economic.

Open-File Report↗

USGS2022

Over a third of groundwater in USA public-supply aquifers is Anthropocene-age and susceptible to surface contamination

The distribution of groundwater age is useful for evaluating the susceptibility and sustainability of groundwater resources. Here, we compute the aquifer-scale cumulative distribution function to characterize the age distribution for 21 Principal Aquifers that account for ~80% of public-supply pumping in the United States. The aquifer-scale cumulative distribution function for each Principal Aquifer was derived from an ensemble of modeled age distributions (~60 samples per aquifer) based on multiple tracers: tritium, tritiogenic helium-3, sulfur hexafluoride, chlorofluorocarbons, carbon-14, and radiogenic helium-4. Nationally, the groundwater is 38% Anthropocene (since 1953), 34% Holocene (75 – 11,800 years ago), and 28% Pleistocene (>11,800 years ago). The Anthropocene fraction ranges from <5 to 100%, indicating a wide range in susceptibility to land-surface contamination. The Pleistocene fraction of groundwater exceeds 50% in 7 eastern aquifers that are predominately confined. The Holocene fraction of groundwater exceeds 50% in 5 western aquifers that are predominately unconfined. The sustainability of pumping from these Principal Aquifers depends on rates of recharge and release of groundwater stored in fine-grained layers.

Nature Communications Earth & Environment↗

USGS2014

The 3D Elevation Program: summary for Illinois

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Illinois, elevation data are critical for flood risk management, water supply and quality, infrastructure and construction management, agriculture and precision farming, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Illinois↗

USGS2019

Predicting hydrologic disturbance of streams using species occurrence data

Aquatic organisms have adapted over evolutionary time-scales to hydrologic variability represented by the natural flow regime of rivers and streams in their unimpaired state. Rapid landscape change coupled with growing human demand for water have altered natural flow regimes of many rivers and streams on a global scale. Climate non-stationarity is expected to further intensify hydrologic variability, placing increased pressure on aquatic communities. Using a machine learning approach and georeferenced species occurrence data, we modeled and mapped spatial patterns of hydrologic disturbance for streams in Arkansas, Missouri, and eastern Oklahoma. Random forest (RF) models trained on fish community data, hydrologic, and landscape metrics for gaged streams in the National Hydrography (NHDPlusV2) database were used to predict a hydrologic disturbance index (HDI) for ungaged streams. The HDI is part of the USGS Geospatial Attributes of Gages for Evaluating Streamflow (GAGESII) database and is a composite index of watershed-scale disturbance from anthropogenic stressors. Fish presence/absence data had similar overall model prediction accuracy (77%; 95% CI: 0.74, 0.80) as flow variables (76%; CI: 0.73, 0.80). Including topographic variables increased the RF prediction accuracy of both the fish (90%; CI: 0.88, 0.92) and flow models (86%; CI: 0.84, 0.89). Spatial patterns of hydrologic disturbance suggest distinct ecohydrological regions exist where conservation actions may be focused. Streams with low HDI were predominately located in the Ozark Highlands, Boston Mountains, and Ouachita Mountains. Correlation analysis of HDI by flow regime showed groundwater stable streams had the lowest disturbance frequency, with over 50% of stream reaches with low HDI located in forested land cover. HDI was highest for big rivers, intermittent runoff streams and streams in areas of agricultural land use. Our results show long-term georeferenced biological data can provide a valuable resource for predictive modeling of hydrologic disturbance for ungaged rivers and streams.

Arkansas, Missouri, Oklahoma↗

USGS1996

Small watershed studies: Analytical approaches for understanding ecosystem response to environmental change

Biogeochemical studies in small watersheds provide an analytical approach to understand how ecosystems respond to natural climatic variations and human-induced environmental change. Small watersheds, usually less than 5 km2, are small enough to permit characterization and understanding of ecosystem processes within relatively simple, homogeneous biological and physical settings; yet they are large enough to incorporate more complex processes and element cycles than can be studied at plot scales. Watersheds comprise discrete hydrochemical environments allowing quantification of hydrologic, element, and energy budgets. Element budgets, or mass balances, can be quantified as the difference between the mass of a solute that enters a watershed in wet and dry deposition and leaves a watershed in streamflow. Element budgets are primary tools used to investigate biogeochemical processes. Monitoring various aspects of element budgets to assess ecosystem health and stability is analogous to measuring the pulse or blood chemistry of a patient. Monitoring streamwater chemistry, basic climate, soil, and biotic variables provide a means to integrate complex biogeochemical processes and evaluate trends in water quality. Small watershed studies provide a scientific basis to develop predictive models of watershed function. Major emphases of small watershed studies include investigation of hydrologic and chemical responses to natural climate variation, anthropogenic stressors, and alternate forest-management practices. The nature and significance of biogeochemical research in small watersheds is reviewed by Moldan and Cerny (1994). The U.S. Geological Survey, U.S. Department of Agriculture Forest Service, and other federal agencies support several long-term small watershed studies to provide insight into a variety of ecosystem processes. Long-term records are essential to distinguish trends resulting from natural climatic variations or other stressors. The following sites, with noted periods of records, are examples of intensively studied forested watersheds in eastern USA supported by federal agencies: ■ Coweeta Hydrologic Laboratory, North Carolina, (1939-present), Swank and Crossley (1988). ■ Hubbard Brook Experimental Forest, New Hampshire, (1956-present), Bormann and Likens (1979). ■ Sleepers River Research Watershed, Vermont, (1958-present), Shanley et al. (1995). ■ Walker Branch Watershed, Tennessee, (1967-present), Johnson and Van Hook (1989). ■ Catoctin Mountains Research Site, Maryland, (1982-present), Rice and Bricker (1995). ■ Catskill Stream Network, New York, (1983- present), Murdoch and Stoddard (1992). ■ Panola Mountain Research Watershed, Georgia, (1985-present), Huntington et al. (1993). Small watershed studies also provide essential baseline information for understanding variations in water quality and element cycling in "pristine" ecosystems that can be used as benchmarks to evaluate anthropogenic impacts and alternate watershed management practices. This paper provides examples of how analytical tools developed through watershed research provide insight into ecosystem processes and can contribute to the management of watershed resources.

Conference Paper↗

USGS2012

Spatial ecology of refuge selection by an herbivore under risk of predation

Prey species use structures such as burrows to minimize predation risk. The spatial arrangement of these resources can have important implications for individual and population fitness. For example, there is evidence that clustered resources can benefit individuals by reducing predation risk and increasing foraging opportunity concurrently, which leads to higher population density. However, the scale of clustering that is important in these processes has been ignored during theoretical and empirical development of resource models. Ecological understanding of refuge exploitation by prey can be improved by spatial analysis of refuge use and availability that incorporates the effect of scale. We measured the spatial distribution of pygmy rabbit (Brachylagus idahoensis) refugia (burrows) through censuses in four 6-ha sites. Point pattern analyses were used to evaluate burrow selection by comparing the spatial distribution of used and available burrows. The presence of food resources and additional overstory cover resources was further examined using logistic regression. Burrows were spatially clustered at scales up to approximately 25 m, and then regularly spaced at distances beyond ~40 m. Pygmy rabbit exploitation of burrows did not match availability. Burrows used by pygmy rabbits were likely to be located in areas with high overall burrow density (resource clusters) and high overstory cover, which together minimized predation risk. However, in some cases we observed an interaction between either overstory cover (safety) or understory cover (forage) and burrow density. The interactions show that pygmy rabbits will use burrows in areas with low relative burrow density (high relative predation risk) if understory food resources are high. This points to a potential trade-off whereby rabbits must sacrifice some safety afforded by additional nearby burrows to obtain ample forage resources. Observed patterns of clustered burrows and non-random burrow use improve understanding of the importance of spatial distribution of refugia for burrowing herbivores. The analyses used allowed for the estimation of the spatial scale where subtle trade-offs between predation avoidance and foraging opportunity are likely to occur in a natural system.

Ecosphere↗

USGS2006

Pesticide toxicity index for freshwater aquatic organisms, 2nd edition

The U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program is designed to assess current water-quality conditions, changes in water quality over time, and the effects of natural and human factors on water quality for the Nation's streams and ground-water resources. For streams, one of the most difficult parts of the assessment is to link chemical conditions to effects on aquatic biota, particularly for pesticides, which tend to occur in streams as complex mixtures with strong seasonal patterns. A Pesticide Toxicity Index (PTI) was developed that combines pesticide exposure of aquatic biota (measured concentrations of pesticides in stream water) with acute toxicity estimates (standard endpoints from laboratory bioassays) to produce a single index value for a sample or site. The development of the PTI was limited to pesticide compounds routinely measured in NAWQA studies and to toxicity data readily available from existing databases. Qualifying toxicity data were found for one or more types of test organisms for 124 of the 185 pesticide compounds measured in NAWQA samples, but with a wide range of available bioassays per compound (1 to 232). In the databases examined, there were a total of 3,669 bioassays for the 124 compounds, including 398 48-hour EC50 values (concentration at which 50 percent of test organisms exhibit a sublethal response) for freshwater cladocerans, 699 96-hour LC50 values (concentration lethal to 50 percent of test organisms) for freshwater benthic invertebrates, and 2,572 96-hour LC50 values for freshwater fish. The PTI for a particular sample is the sum of toxicity quotients (measured concentration divided by the median toxicity concentration from bioassays) for each detected pesticide, and thus, is based on the concentration addition model of pesticide toxicity. The PTI can be calculated for specific groups of pesticides and for specific taxonomic groups. Although the PTI does not determine whether water in a sample is toxic to aquatic organisms, its values can be used to rank or compare the toxicity of samples or sites on a relative basis for use in further analysis or additional assessments. The PTI approach may be useful as a basis for comparing the potential significance of pesticides in different streams on a common basis, for evaluating relations between pesticide exposure and observed biological conditions, and for prioritizing where further studies are most needed.

Scientific Investigations Report↗

USGS2023

Predicting large hydrothermal systems

We train five models using two machine learning (ML) regression algorithms (i.e., linear regression and XGBoost) to predict hydrothermal upflow in the Great Basin. Feature data are extracted from datasets supporting the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems project (INGENIOUS). The label data (the reported convective signals) are extracted from measured thermal gradients in wells by comparing the total estimated heat flow at the wells to the modeled background conductive heat flow. That is, the reported convective signal is the difference between the background conductive heat flow and the well heat flow. The reported convective signals contain outliers that may affect upflow prediction, so the influence of outliers is tested by constructing models for two cases: 1) using all the data (i.e., -91 to 11,105 mW/m2), and 2) truncating the range of labels to include only reported convective signals between -25 and 200 mW/m2. Because hydrothermal systems are sparse, models that predict high convective signal in smaller areas better match the natural frequency of hydrothermal systems. Early results demonstrate that XGBoost outperforms linear regression. For XGBoost using the truncated range of labels, half of the high reported signals are within < 3 % of the highest predictions. For XGBoost using the entire range of labels, half of the high reported signals are in < 13 % of the highest predictions. While this implies that the truncated regression is superior, the all-data model better predicts the locations of power-producing systems (i.e., the operating power plants are in a smaller fraction of the study area given by the highest predictions). Even though the models generally predict greater hydrothermal upflow for higher reported convective signals than for lower reported convective signals, both XGBoost models consistently underpredict the magnitude of higher signals. This behavior is attributed to low resolution/granularity of input features compared with the scale of a hydrothermal upflow zone (a few km or less across). Trouble estimating exact values while still reliably predicting high versus low convective signals suggests that a future strategy such as ranked ordinal regression (e.g., classifying into ordered bins for low, medium, high, and very high convective signal) might fit better models, since doing so reduces problems introduced by outliers while preserving the property of larger versus smaller signals.

Geothermal Resources Council Transactions↗

USGS2012

How well do the rosgen classification and associated "natural channel design" methods integrate and quantify fluvial processes and channel response?

Over the past 10 years the Rosgen classification system and its associated methods of "natural channel design" have become synonymous (to many without prior knowledge of the field) with the term "stream restoration" and the science of fluvial geomorphology. Since the mid 1990s, this classification approach has become widely, and perhaps dominantly adopted by governmental agencies, particularly those funding restoration projects. For example, in a request for proposals for the restoration of Trout Creek in Montana, the Natural Resources Conservation Service required "experience in the use and application of a stream classification system and its implementation." Similarly, classification systems have been used in evaluation guides for riparian areas and U.S. Forest Service management plans. Most notably, many highly trained geomorphologists and hydraulic engineers are often held suspect, or even thought incorrect, if their approach does not include reference to or application of a classification system. This, combined with the para-professional training provided by some involved in "natural channel design" empower individuals and groups with limited backgrounds in stream and watershed sciences to engineer wholesale re-patterning of stream reaches using 50-year old technology that was never intended for engineering design. At Level I, the Rosgen classification system consists of eight or nine major stream types, based on hydraulic-geometry relations and four other measures of channel shape to distinguish the dimensions of alluvial stream channels as a function of the bankfull stage. Six classes of the particle size of the boundary sediments are used to further sub-divide each of the major stream types, resulting in 48 or 54 stream types. Aside from the difficulty in identifying bankfull stage, particularly in incising channels, and the issue of sampling from two distinct populations (beds and banks) to classify the boundary sediments, the classification provides a consistent and reproducible means for practitioners to describe channel morphology although difficulties have been encountered in lower-gradient stream systems. Use of the scheme to communicate between users or as a conceptual model, however, has not justified its use for engineering design or for predicting river behavior; its use for designing mitigation projects, therefore, seems beyond its technical scope. Copyright ASCE 2005.

Conference Paper↗