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USGS2000

Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue

The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere-biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997-1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources.

Conference Paper↗

USGS2013

Advancements in understanding the aeromagnetic expressions of basin-margin faults—An example from San Luis Basin, Colorado

Advancements in aeromagnetic acquisition technology over the past few decades have led to greater resolution of shallow geologic sources with low magnetization, such as intrasedimentary faults and paleochannels. Detection and mapping of intrasedimentary faults in particular can be important for understanding the overall structural setting of an area, even if exploration targets are much deeper. Aeromagnetic methods are especially useful for mapping structures in mountain-piedmont areas at the margins of structural basins, where mineral exploration and seismic-hazard studies may be focused, and where logistical or data-quality issues encumber seismic methods. Understanding if the sources of aeromagnetic anomalies in this context originate from sedimentary units or bedrock is important for evaluating basin structure and/or depth to shallow exploration targets. Advancements in aeromagnetic acquisition technology over the past few decades have led to greater resolution of shallow geologic sources with low magnetization, such as intrasedimentary faults and paleochannels. Detection and mapping of intrasedimentary faults in particular can be important for understanding the overall structural setting of an area, even if exploration targets are much deeper. Aeromagnetic methods are especially useful for mapping structures in mountain-piedmont areas at the margins of structural basins, where mineral exploration and seismic-hazard studies may be focused, and where logistical or data-quality issues encumber seismic methods. Understanding if the sources of aeromagnetic anomalies in this context originate from sedimentary units or bedrock is important for evaluating basin structure and/or depth to shallow exploration targets. Although explorationists have surmised that subtle, narrow, linear aeromagnetic anomalies or gradients are caused by intrasedimentary faults, the nature of the magnetic sources has been debated. A common and intuitive explanation for the linear anomalies considers that the magnetic properties of the fault zone have been altered by secondary chemical processes, either through the growth or destruction of magnetic minerals. However, comprehensive, multidisciplinary studies of partially exposed intrasedimentary faults in basins within the central Rio Grande Rift, New Mexico, have shown that the anomalies can be completely explained by the tectonic juxtaposition of strata of differing magnetic properties at the fault (summarized in Grauch and Hudson, 2007 , 2011 ). Whereas a reduction in magnetic susceptibility was detected at some fault zones in the laboratory, the slight reduction and small volume of material affected were insufficient to produce aeromagnetic anomalies ( Hudson et al., 2008 ). A key finding of the studies summarized by Grauch and Hudson (2007 , 2011 ) is that multiple magnetic contrasts (sources) can be vertically stacked at one fault. This situation requires rethinking of common assumptions when modeling faults as simple steps or when interpreting depth-estimation results. The multiple contrasts in these case studies arise from the tectonic juxtaposition of stratified sediments with differing magnetic properties. Multiple, vertically stacked magnetic sources also can occur where volcanic layers are interbedded with the sedimentary section or where faults offset both shallow bedrock and its overlying sedimentary cover. The latter situation is common at basin margins. Herein, we summarize and expand on an investigation of the sources of aeromagnetic anomalies related to faults along the eastern margin of the San Luis Basin, northern Rio Grande Rift, Colorado ( Grauch et al., 2010 ). Similar to the faults examined in the central Rio Grande Rift, magnetic sources can be completely explained by tectonic juxtaposition and produce multiple, vertically stacked magnetic contrasts at individual faults. However, the geologic sources are different. They arise from both the sedimentary cover and the underlying bedrock rather than from stratified sediments. In addition, geologic evidence for secondary growth or destruction of magnetic minerals at the fault zone is lacking.

Colorado↗

USGS2002

Lead isotopic analyses of selected soil samples from the USEPA Vasquez Blvd.-I-70 study area, Denver, CO

Large amounts of arsenic contamination, in excess of 2000 ppm, have been found in some residential surface soils in northern Denver, Colorado (USEPA, 1999). Associated with the arsenic are elevated levels of metals such as lead, cadmium and mercury. Potential sources of this contamination include waste from smelters in the area and commercial herbicide containing arsenic trioxide and lead arsenate (USEPA, 1999). As a part of the U.S. Environmental Protection Agency’s Vasquez Boulevard-I-70 Project (VBI70 project; USEPA, 1999), lead isotopic analyses of selected soil samples, smelter waste, and a commercial herbicide and a commercial lead arsenate pesticide have been performed in order to constrain the possible sources of elevated lead, and by proxy arsenic, found in these residential soils. The isotopes of lead can be used as a natural tracer in determining sources of contaminants in soils and stream sediments (e.g. Church and others, 1997; Fey and others, 1999; Unruh and others, 2000). The element lead (Pb) consists of four naturally occurring and stable isotopes, 204Pb, 206Pb, 207Pb, and 208Pb. Three of these, 206Pb, 207Pb, and 208Pb are radiogenic decay products of naturally occurring 238U, 235U, and 232Th, respectively. Owing to variations among the U/Pb and Th/Pb elemental abundance ratios among different types of geologic materials, variations in the relative abundances of the Pb isotopes are produced among different materials during geologic time. In order for the Pb isotope method to be useful for determining possible contaminant sources, two important criteria must be met (e.g. Church and others 1997): (1) It must be possible to obtain and measure the Pb isotopic compositions in all potential contaminant sources and in uncontaminated material and (2) the Pb isotopic compositions of the potential contaminant sources must be distinctly different from one another and from uncontaminated background. Variations among the Pb isotopic ratios in selected samples can be correlated with potential sources of Pb with known isotopic compositions in order to determine the relative contribution of Pb from a specific source to the sample. The purpose of this study is to use Pb isotopic data obtained from a selected subset of samples to determine the Pb isotopic signatures of uncontaminated soils as well as those of potential sources of contamination. The data will eventually be used in conjunction with other geochemical data to help determine which source or sources of contamination are most likely responsible for the elevated arsenic levels in the residential soils.

Colorado↗

USGS1998

Accounting for cyanide and its degradation products at three Nevada gold mines; constraints from stable C- and N-isotopes

An understanding of the fate of cyanide (CN-) in mine process waters is important for addressing environmental concerns and for taking steps to minimize reagent costs. The utility of stable isotope methods in identifying cyanide loss pathways has been investigated in case studies at three Nevada gold mines. Freshly prepared barren solutions at the mines have cyanide d15N and d13C values averaging -4 ? and -36 ?, respectively, reflecting the nitrogen and carbon sources used by commercial manufacturers, air and natural gas methane. Pregnant solutions returning from ore heaps display small isotopic shifts to lower d15N and d13C values. The shifts are similar to those observed in laboratory experiments where cyanide was progressively precipitated as a cyanometallic compound, and are opposite in sign and much smaller in magnitude than the shifts observed in experiments where HCN was offgassed. Offgassing is inferred to be a minor cyanide loss mechanism in the heap leach operations at the three mines, and precipitation as cyanometallic compounds, and possibly coprecipitation with ferric oxides, is inferred to be an important loss mechanism. Isotopic analysis of dissolved inorganic carbon (DIC) shows that uptake of high d13C air CO2 has been important in many barren and pregnant solutions. However, DIC in reclaim pond waters at all three mines has low d13C values of -28 to -34 ? indicating cyanide breakdown either by hydrolysis or by other chemical pathways that break the C-N bond. Isotope mass balance calculations indicate that about 40 % of the DIC load in the ponds, at a minimum, was derived from cyanide breakdown. This level of cyanide hydrolysis accounts for 14-100 % of the dissolved inorganic nitrogen species present in the ponds. Overall, isotope data provide quantitative evidence that only minor amounts of cyanide are lost via offgassing and that significant amounts are destroyed via hydrolysis and related pathways. The data also highlight the possibility that significant cyanide may be either retained in the ore heaps or destroyed via other chemical pathways.

Open-File Report↗

USGS2009

Fire rehabilitation effectiveness: a chronosequence approach for the Great Basin

Federal land management agencies have invested heavily in seeding vegetation for emergency stabilization and rehabilitation (ES&R) of non-forested lands. ES&R projects are implemented to reduce post-fire dominance of non-native annual grasses, minimize probability of recurrent fire, quickly recover lost habitat for sensitive species, and ultimately result in plant communities with desirable characteristics including resistance to invasive species and resilience or ability to recover following disturbance. Land managers lack scientific evidence to verify whether seeding non-forested lands achieves their desired long-term ES&R objectives. The overall objective of our investigation is to determine if ES&R projects increase perennial plant cover, improve community composition, decrease invasive annual plant cover and result in a more desirable fuel structure relative to no treatment following fires while potentially providing habitat for Greater Sage-Grouse, a species of management concern. In addition, we provide the locations and baseline vegetation data for further studies relating to ES&R project impacts. We examined effects of seeding treatments (drill and broadcast) vs. no seeding on biotic and abiotic (bare ground and litter) variables for the dominant climate regimes and ecological types within the Great Basin. We attempted to determine seeding effectiveness to provide desired plant species cover while restricting non-native annual grass cover relative to post-treatment precipitation, post-treatment grazing level and time-since-seeding. Seedings were randomly sampled from all known post-fire seedings that occurred in the four-state area of Idaho, Nevada, Oregon and Utah. Sampling locations were stratified by major land resource area, precipitation, and loam-dominated soils to ensure an adequate spread of locations to provide inference of our findings to similar lands throughout the Great Basin. Nearly 100 sites were located that contained an ES&R project. Of these sites, 61 were seeded by using a drill, 27 were broadcast aerially, and 12 had a combination of both. We randomly sampled three burned and seeded, burned and unseeded, and unburned and unseeded locations in the vicinity of the fire, each within the same ecological site. We measured foliar cover of all plant functional groups (perennial or annual, shrub, grass, forb, native or introduced), biological soil crusts, and abiotic (bare soil and litter) variables using the line-point intercept protocol. Fuel loads and horizontal fuel continuity were measured. We applied linear mixed models to response variables (cover and density of plant groups) relative to the dependent variables (seeding treatments and precipitation/temperature relationships. Post-fire strengths with native perennial grasses or shrubs in mixes did not increase density or cover of these groups significantly relative to unseeded, burned areas. Seeded non-native perennial grasses and the shrub Bassia prostrata were effective in providing more cover in aerial and drill seedings. Seeded non-native perennial grass cover increased with increased annual precipitation regardless of seeding type. Seeding native shrubs, particularly Artemisia tridentata, did not significantly increase shrub cover in burned areas. Cover of undesirable non-native annual grasses was lower in drill seedings relative to unseeded areas but only at higher elevations. Seeding effectiveness after wildfire is unpredictable in drier, low elevation environments, and our findings indicate management objectives are more likely met when focusing efforts on higher elevation or higher precipitation locations where establishment of perennial grasses is more likely. On sites where potential for invasion and dominance of non-native annuals is high, such as lower and drier sites, intensive methods of restoration that include invasive plant control before seeding may be required. Where establishment of native perennial plants is the goal, managers might consider using native-only seed mixtures, because we found that the non-native perennials typically used in Great Basin restoration efforts are selected for their competitive nature and may reduce establishment of less competitive native species. Although we attempted to include information on livestock grazing history after seedings, we were unable to extract sufficient data from files to address this topic that may play an additional role in understanding native plant abundance post-fire seeding. Evaluation of drill and aerial seeding effects on fuel characteristics focused on two metrics that are standard inputs for fire behavior models, fuel load and fuel continuity. Fuel loads were evaluated separately for total fuel load biomass, and the individual components that sum to total biomass, namely herbaceous, shrub, shrub:herbaceous ratio, litter, 10-hour, and 100-hour fuel biomasses. Fuel continuity was evaluated using the following cover categories, total, annual grass, annual forb, perennial forb perennial grass, shrub, litter, vegetative interspace, and perennial interspace. Drill seeding did not affect fuel loads, except to reduce 10-hour fuels, probably due to mechanical destruction of dead and down fuels by the drill seeding equipment. Drill seeding did affect fuel continuity, specifically decreasing total plant cover by increasing perennial grass cover which suppressed annual grass and litter production resulting in a net decrease in continuity, but only at the elevations above approximately 1500m. Aerial seeding had no effect on any fuel load or fuel continuity category. For the Greater Sage-Grouse habitat study, we developed multi-scale empirical models of sage-grouse occupancy in 211 randomly located plots within a 40 million ha portion of the species’ range. We then used these models to predict sage-grouse habitat quality at 101 ES&R seeding projects. We compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe, and negatively associated with non-native grass and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.07–0.09) and was not significantly different from burned areas that had not been treated. Restoration was more often successful at higher elevation sites with low annual temperatures, high spring precipitation, and high plant diversity. No plots seeded after fire (n=313) met all overstory guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This trend was similar for summer habitat. Ninety-eight percent of treated plots did not meet winter habitat guidelines. Restoration actions in burned areas did not increase the probability of meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, local climate, and topography. Post-fire seeding treatments in Great Basin sagebrush shrublands generally have not created high quality habitat for sage-grouse. Understory conditions are more likely to be adequate than those of overstory, but in unfavorable climates, establishing forbs and reducing cheatgrass dominance is unlikely. Reestablishing sagebrush cover will require more than 20 years using the restoration methods of the past two decades. Given current fire frequencies and restoration capabilities, protection of landscapes containing a mix of dwarf sagebrush and big sagebrush steppe, minimal human development, and low non-native plant cover may provide the best opportunity for conservation of sage-grouse habitats. Our database of ES&R locations has used the Land Treatment Digital Library to archive data and location information regarding our study (see Pilliod and Welty 2013). This has contributed to two additional studies. One examined the potential spread of Bassia prostrata (aka Kochia prostrata; forage kochia) from ES&R project locations (Gray and Muir 2013). The second used remote sensing to determine the phenology of vegetation green-up on post-fire seeded sites (Sankey et al. 2013).

California;Idaho;Oregon;Utah↗

USGS2014

Concentrations of selected constituents in surface-water and streambed-sediment samples collected from streams in and near an area of oil and natural-gas development, south-central Texas, 2011-13

During 2011–13, the U.S. Geological Survey, in cooperation with the San Antonio River Authority and the Guadalupe-Blanco River Authority, analyzed surface-water and streambed-sediment samples collected from 10 sites in the San Antonio River Basin to provide data for a broad range of constituents that might be associated with hydraulic fracturing and the produced waters that are a consequence of hydraulic fracturing. Among surface-water samples, all sulfide concentrations were less than the method detection limit of 0.79 milligrams per liter. Four glycols—diethylene glycol, ethylene glycol, propylene glycol, and triethylene glycol—were analyzed for in surface-water samples collected for this study, and none were detected. Of the 91 semivolatile organic compounds analyzed for this study, there were six detections, all but one of which were in storm-runoff samples. The base-flow sample collected at the San Antonio River at Goliad, Tex. (SAR Goliad), site contained bis(2-ethylhexyl) phthalate, a plasticizer in polyvinyl chloride and a constituent in hydraulic fracturing fluids. The storm-runoff samples collected at the San Antonio River near Elmendorf, Tex. (SAR Elmendorf), and Ecleto Creek at County Road 326 near Runge, Tex. (Ecleto 2), sites also contained bis(2-ethylhexyl) phthalate. The storm-runoff sample collected at the SAR Elmendorf site contained the plasticizer diethyl phthalate. Both storm-runoff samples collected at the Ecleto Creek near Runge, Tex. (Ecleto 1), and Ecleto 2 sites contained benzyl alcohol, a solvent commonly used in paints. Of the 67 volatile organic compounds analyzed in this study, there were a total of six detections, all of which were in base-flow samples. The surface-water sample collected at the SAR Elmendorf site contained bromodichloromethane, dibromochloromethane, and trichloromethane, all of which are disinfection byproducts associated with the chlorination of municipal water supplies and of treated municipal wastewater. The sample collected at the Cibolo Creek near Saint Hedwig, Tex. (Cibolo St. Hedwig), site contained toluene, a fuel additive, solvent, and industrial feedstock used to produce benzene and a constituent associated with produced waters. The Cibolo St. Hedwig site is upstream from current (2014) oil and natural-gas production areas. Dichloromethane, an industrial solvent with multiple uses, was detected in surface-water samples at both the San Antonio River at State Highway 72 near Runge, Tex. (SAR 72), and SAR Goliad sites. In streambed-sediment samples, concentrations of total saturated hydrocarbons (TSH) ranged from an estimated 260 micrograms per kilogram (μg/kg) in the less than (<) 2-millimeter (mm) size-fraction sample collected at the SAR Goliad site to 11,000 μg/kg in the <2-mm size-fraction sample collected at the Ecleto 1 site. TSH concentrations were greater in the <63-micrometer (μm) size-fraction samples than in the <2-mm size-fraction samples in streambed-sediment samples collected from 5 of the 9 sites. Total polycyclic aromatic hydrocarbons (PAHs) were calculated as the sum of the individual PAHs and alkylated PAHs. Total PAH concentrations ranged from less than the method detection limit in the <2-mm size-fraction samples collected from multiple sites to 1,600 μg/kg in the <2-mm size-fraction sample collected from the San Antonio River near McFaddin, Tex. (SAR McFaddin), site. Total PAH concentrations were greater in the <63-μm size-fraction samples than in the <2-mm size-fraction samples at 7 of the 9 sites. During collection of streambed-sediment samples, additional samples from a subset of three sites (the SAR Elmendorf, SAR 72, and SAR McFaddin sites) were processed by using a 63-µm sieve on one aliquot and a 2-mm sieve on a second aliquot for PAH and n -alkane analyses. The purpose of analyzing PAHs and n -alkanes on a sample containing sand, silt, and clay versus a sample containing only silt and clay was to provide data that could be used to determine if these organic constituents had a greater affinity for silt- and clay-sized particles relative to sand-sized particles. The greater concentrations of PAHs in the <63-μm size-fraction samples at all three of these sites are consistent with a greater percentage of binding sites associated with fine-grained (<63 μm) sediment versus coarse-grained (<2 mm) sediment. The larger difference in total PAHs between the <2-mm and <63-μm size-fraction samples at the SAR Elmendorf site might be related to the large percentage of sand in the <2-mm size-fraction sample which was absent in the <63-μm size-fraction sample. In contrast, the <2-mm size-fraction sample collected from the SAR McFaddin site contained very little sand and was similar in particle-size composition to the <63-μm size-fraction sample.

Texas↗

USGS2017

Prediction and visualization of redox conditions in the groundwater of Central Valley, California

Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of models of varying complexity, as a basis for selecting final models. Trained models were applied to cross-validation testing data and a separate hold-out dataset to evaluate model predictive performance by emphasizing three model metrics of fit: Kappa; accuracy; and the area under the receiver operator characteristic curve (ROC). The final trained models were used for mapping predictions at discrete depths to a depth of 304.8 m. Trained DO and Mn models had accuracies of 86–100%, Kappa values of 0.69–0.99, and ROC values of 0.92–1.0. Model accuracies for cross-validation testing datasets were 82–95% and ROC values were 0.87–0.91, indicating good predictive performance. Kappas for the cross-validation testing dataset were 0.30–0.69, indicating fair to substantial agreement between testing observations and model predictions. Hold-out data were available for the manganese model only and indicated accuracies of 89–97%, ROC values of 0.73–0.75, and Kappa values of 0.06–0.30. The predictive performance of both the DO and Mn models was reasonable, considering all three of these fit metrics and the low percentages of low-DO and high-Mn events in the data.

California↗

USGS2007

Hierarchical spatiotemporal matrix models for characterizing invasions

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.

Biometrics↗

USGS2022

Database of biodiversity, habitat, and aquatic-resource quantification tools used in market-based conservation — 2022 update

Market-based conservation makes use of economic incentives to promote actions that avoid, minimize, or compensate for detrimental effects on natural resources and the environment. Examples of market-based conservation mechanisms include aquatic-resource (such as, streams, wetlands, and estuaries) compensatory mitigation, conservation banking, habitat exchanges, and payments for ecosystem services. A critical component in the operation of these market-based conservation mechanisms is the methods (hereafter referred to as “quantification tools”) used to assess existing (sometimes referred to as “baseline”) or potential site conditions. Quantification tools are used to assign values to the benefits provided by preservation, restoration, or enhancement actions, as well as the negative effects of human activities (for example, infrastructure development, energy extraction, and anthropogenic disasters). In 2018, the U.S. Geological Survey (USGS) published a database describing the attributes of 69 quantification tools developed for United States conservation markets. The database focused on tools used for species-based mitigation, payments for ecosystem services, and ecolabel programs (Chiavacci and Pindilli, 2020). Recently, the USGS, in collaboration with the U.S. Environmental Protection Agency, revised the original database by updating the existing tool information, adding newly developed tools, and broadening the scope to include tools developed for compensatory mitigation under the Clean Water Act Section 404 Regulatory Program.

Fact Sheet↗

USGS2010

Strontium isotope detection of brine contamination in the East Poplar oil field, Montana

Brine contamination of groundwater in the East Poplar oil field was first documented in the mid-1980s by the U.S. Geological Survey by using hydrochemistry, with an emphasis on chloride (Cl) and total dissolved solids concentrations. Supply wells for the City of Poplar are located downgradient from the oil field, are completed in the same shallow aquifers that are documented as contaminated, and therefore are potentially at risk of being contaminated. In cooperation with the Office of Environmental Protection of the Fort Peck Tribes, groundwater samples were collected in 2009 and 2010 from supply wells, monitor wells, and the Poplar River for analyses of major and trace elements, including strontium (Sr) concentrations and isotopic compositions. The ratio of strontium-87 to strontium-86 ( 87 Sr/ 86 Sr) is used extensively as a natural tracer in groundwater to detect mixing among waters from different sources and to study the effects of water/rock interaction. On a plot of the reciprocal strontium concentration against the 87 Sr/ 86 Sr ratio, mixtures of two end members will produce a linear array. Using this plotting method, data for samples from most of the wells, including the City of Poplar wells, define an array with reciprocal strontium values ranging from 0.08 to 4.15 and 87 Sr/ 86 Sr ratios ranging from 0.70811 to 0.70828. This array is composed of a brine end member with an average 87 Sr/ 86 Sr of 0.70822, strontium concentrations in excess of 12.5 milligrams per liter (mg/L), and chloride concentrations exceeding 8,000 mg/L mixing with uncontaminated water similar to that in USGS06-08 with 18.0 mg/L chloride, 0.24 mg/L strontium, and a 87 Sr/ 86 Sr ratio of 0.70811. The position of samples from the City of Poplar public-water supply wells within this array indicates that brine contamination has reached all three wells. Outliers from this array are EPU-4G (groundwater from the Cretaceous Judith River Formation), brine samples from disposal wells (Huber 5-D and EPU 1-D), USGS92-11 (a well with water that was considerably contaminated in 1992 and becoming less saline with time), and PNR-27 (only slightly below the defined trend with an 87 Sr/ 86 Sr ratio of 0.70793). Water samples from the City of Poplar wells are also enriched in anions and cations that are abundant in oil-field brine.

Open-File Report↗

USGS2016

Abstract volume for the 2016 biennial meeting of the Yellowstone Volcano Observatory

Introduction Every two years, scientists, natural resource managers, outreach specialists, and a variety of other interested parties get together for the biennial meeting of the Yellowstone Volcano Observatory (YVO). Each time, the theme varies. In past years, we have focused the meeting around topics including monitoring plans, emergency response, geodesy, and outreach. This year, we spent the first half-day devoted to recent research results, plans for upcoming studies, and geothermal monitoring. On the second day, our focus switched to eruption precursors, particularly as they apply to large caldera systems. Very few large explosive eruptions from caldera systems have taken place in recorded history. Therefore, there are few empirical data with which to characterize the nature of volcanic unrest that might precede eruptions with volcano explosivity index (VEI) of six or greater. For this reason, we set up a series of talks that explore what we know and don’t know about large eruptions. We performed an informal expert elicitation (a frequently used method to characterize expert opinion) with a small number of our colleagues, which served as the basis for a productive discussion session. This short volume of abstracts and extended abstracts provides a summary of the presentations made at the YVO meeting held in Mammoth Hot Springs, Wyoming, on May 10–11, 2016.

Open-File Report↗

USGS2022

Risk assessment for bull trout introduction into Sullivan Lake and Harvey Creek, northeastern Washington

The Kalispel Tribe of Indians (KT), U. S. Fish and Wildlife Service, and Washington Department of Fish and Wildlife are engaged in conservation of bull trout ( Salvelinus confluentus ) in the Lake Pend Oreille (LPO) Core Area. The LPO is a complex habitat core area which falls within three states (Montana, Idaho, and Washington) and a tribal entity. As part of the conservation process, KT worked in cooperation with the U. S. Geological Survey (USGS) to complete a risk assessment for introduction of bull trout into Sullivan Lake/Harvey Creek, northeastern, Washington. The risk assessment was designed to evaluate potential risks to resident fish species, to bull trout introduced into Sullivan Lake, and to bull trout donor source populations. This risk assessment describes the potential risks associated with pathogens (introduction of pathogens and increased pathogen burden), genetics (such as risk to donor sources, straying and breeding with native bull trout, and introduction of bull-brook hybrids), and ecological interactions (such as predation and competition). Potential donor source populations were identified and evaluated using a qualitative approach based on expert opinion and a decision framework. Literature reviews were completed for fish species composition and abundance in Sullivan Lake basin to assess potential ecological interactions and risks to these populations and to the introduced bull trout. The USGS assessed pathogen risks through two major questions: (1) whether introduced bull trout might bring pathogens into the Sullivan Lake basin that were not previously present and (2) whether the health of introduced bull trout could be adversely affected by pathogens already present in the basin. Assessment of genetic risks included demographic risks to donor source populations, potential for hybridization with native bull trout, and the risk of introducing bull-brook hybrids. Literature reviews were used in conjunction with discussions among regional biologists to identify potential donor source populations and their population attributes. A decision framework was developed by USGS in collaboration with KT biologists that identified desirable population attributes (life history behavior, abundance, population viability, feasibility of collection, and environmental match) associated with donor source populations and established ranking criteria. The population attribute information was used with the (1) decision framework, (2) established ranking criteria, and (3) expert opinion of regional biologists, to assign scores for overall ranking of donor source populations. The LPO source population was the highest ranked and is considered a robust and stable population. The risk of introducing pathogens from LPO into Sullivan Lake via a bull trout introduction program seems low, and indirect pathogen burden risks to resident species can be mitigated using established pathogen surveillance methods. The likelihood that bull trout, introduced into Sullivan Lake, stray and spawn with native bull trout is low. Nearest-neighbor donor source populations, such as LPO, could minimize negative fitness impacts that might occur from straying and interbreeding of individuals that become entrained and help maintain natural patterns of genetic diversity in native populations. The ecological risk that a bull trout introduction presents to resident species seems to be low but with some uncertainty. Pygmy whitefish, a Washington State Sensitive species, is likely most vulnerable to extirpation with increased predation pressure with introduction of an additional piscivore into the ecosystem. The status of the pygmy whitefish in Sullivan Lake is unknown. The ecological risks most likely to reduce the viability of introduced bull trout are predation by burbot and an adequate forage base in Sullivan Lake. Prior fish surveys provided data on resident species abundance, provided an established baseline for effective monitoring, and identifying ecosystem changes post-bull trout introduction to inform future adaptive management decisions.

Washington↗

USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗

USGS2024

An evaluation of fin ray microchemistry to describe movement of White Sturgeon in the Kootenai River basin: Insights and limitations

Introduction: White Sturgeon Acipenser transmontanus in the Kootenai River basin is listed as endangered in the United States and Canada. Declines have been mainly attributed to poor recruitment exacerbated by the environmental effects of Libby Dam in Montana. Reduced primary production downstream of Libby Dam has been identified as one factor limiting growth of White Sturgeon, thereby limiting natural reproduction through delayed sexual maturity. However, estimating changes in growth over time without knowledge of fish location (i.e., Kootenai River vs. Kootenay Lake) is difficult. The objective of this project was to use microchemistry analysis to describe the movement of White Sturgeon within the Kootenai River basin. Methods: Water samples ( n = 27) and White Sturgeon fin rays ( n = 162) collected in the Kootenai River basin were measured for strontium isotope ( 87 Sr: 86 Sr) ratios using laser ablation multicollector inductively coupled plasma mass spectrometry. All water samples and a subset of fin rays ( n = 8) were also analyzed for trace elements (e.g., Sr, Ba, Mg). Fin ray annuli were measured and tested using knowledge of known age; known locations from physical capture events were assigned to age at capture. Results: Strontium isotope analysis was unable to detect differences in the Kootenai River and Kootenay Lake using water or fin ray samples. The Kootenai River and Kootenay Lake were distinguishable using trace element data from water samples, but not fin rays. The discrepancy with trace elements appears to be associated with the physiology of fin ray growth. Discussion: Although this study did not meet its original objective of describing the movement of White Sturgeon in the Kootenai River basin from fin ray microchemistry, our results provide insight into the potential influence of physiology on microchemistry analysis. In particular, fin ray microchemistry of slow-growing fishes may be possible in freshwater systems with further investigation into the physiological processes associated with growth and the incorporation of elements into calcified structures.

British Columbia, Idaho, Montana↗

USGS2013

Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, i.e. the Frontignano (Italy) and the Mukilteo (USA) areas, respectively. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the Message Passing Interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

Geoscientific Model Development and Discussions↗

USGS2009

Environmental effects of hydrothermal alteration and historical mining on water and sediment quality in Central Colorado

The U.S. Geological Survey conducted an environmental assessment of 198 catchments in a 54,000-km2 area of central Colorado, much of which is on Federal land. The Colorado Mineral Belt, a northeast-trending zone of historical base- and precious-metal mining, cuts diagonally across the study area. The investigation was intended to test the hypothesis that degraded water and sediment quality are restricted to catchments in which historical mining has occurred. Water, streambed sediment, and aquatic insects were collected from (1) catchments underlain by single lithogeochemical units, some of which were hydrothermally altered, that had not been prospected or mined; (2) catchments that contained evidence of prospecting, most of which contain hydrothermally altered rock, but no historical mining; and (3) catchments, all of which contain hydrothermally altered rock, where historical but now inactive mines occur. Geochemical data determined from catchments that did not contain hydrothermal alteration or historical mines met water quality criteria and sediment quality guidelines. Base-metal concentrations from these types of catchments showed small geochemical variations that reflect host lithology. Hydrothermal alteration and mineralization typically are associated with igneous rocks that have intruded older bedrock in a catchment. This alteration was regionally mapped and characterized primarily through the analysis of remote sensing data acquired by the ASTER satellite sensor. Base-metal concentrations among unaltered rock types showed small geochemical variations that reflect host lithology. Base-metal concentrations were elevated in sediment from catchments underlain by hydrothermally altered rock. Classification of catchments on the basis of mineral deposit types proved to be an efficient and accurate method for discriminating catchments that have degraded water and sediment quality. Only about 4.5 percent of the study area has been affected by historical mining, whereas a larger part of the study area is underlain by hydrothermally altered rock that has weathered to produce water and sediment with naturally elevated geochemical baselines.

Colorado↗

USGS2018

Methods used to estimate daily streamflow and water availability in the Massachusetts Sustainable-Yield Estimator version 2.0

The Massachusetts Sustainable-Yield Estimator is a decision support tool that provides estimates of daily unaltered streamflow, water-use-adjusted streamflow, and water availability for ungaged, user-defined basins in Massachusetts. Daily streamflow at the ungaged site is estimated for unaltered (no water use) and water-use scenarios. The procedure for estimating streamflow was developed previously and has been implemented with minor changes and updated water-use data in version 2.0 of the Massachusetts Sustainable-Yield Estimator. Unaltered streamflow at selected exceedance probabilities is estimated by previously published regression equations. Streamflow is interpolated between the regressed quantiles to produce a continuous flow duration curve. A daily streamflow time series is produced for the ungaged site by relating the estimated flow duration curve at the ungaged site to a flow duration curve at a gaged reference site and then transferring the dates from the reference site to the ungaged site. Minor refinements were made to the previously published methods to estimate unaltered and water-use-adjusted streamflow, including a procedure to enforce the monotonic structure of the regression-based unaltered flow quantiles, improvements to the interpolation method used for computing the estimated flow duration curve, and updates to the methods used to compute time-lagged stream alterations from groundwater pumping or discharges. Additionally, a procedure was developed to estimate prediction intervals for daily and monthly unregulated streamflow time series at an ungaged site. The Massachusetts Sustainable-Yield Estimator computes water-use-adjusted streamflow using water-use data provided by the Massachusetts Department of Environmental Protection. Available water-use data included monthly withdrawal and wastewater discharge volumes from 2010 to 2014 for surface-water and groundwater sources. Water-use-adjusted streamflow represents the potential effect of current water use on natural streamflow in the basin over the range of historical hydrologic conditions. Georeferenced water withdrawal and discharge volumes were incorporated into the Massachusetts StreamStats web application for use in version 2.0 of the Massachusetts Sustainable-Yield Estimator. To compute water-use-adjusted streamflow, mean daily withdrawals and discharges within a user-defined basin are subtracted and added to the unaltered time series, respectively. Surface-water volumes are applied directly to the equation. Time-lagged streamflow alterations from groundwater withdrawal or wastewater discharge sources are estimated by using a response-coefficient method developed from results of previously published, calibrated groundwater models in Massachusetts. The Massachusetts Sustainable-Yield Estimator was updated to version 2.0 to improve software stability and usability. The version 2.0 software application was developed in Microsoft Access with a graphical user interface. All geoprocessing steps, including basin delineation and compilation of basin characteristics and water use within the basin, were completed in the Massachusetts StreamStats web application and exported for use by the Massachusetts Sustainable-Yield Estimator version 2.0.

Massachusetts↗

USGS2018

Field evaluation of carbon dioxide as a fish deterrent at a water management structure along the Illinois River

Construction of a water management structure (WMS) in the levee surrounding The Nature Conservancy’s Emiquon Preserve (Havana, Illinois, USA) created a new hydrological connection and potential aquatic invasive species pathway between the Illinois River and a large conservation wetland complex. Site managers need a control tool that deters the upstream passage of non-native fishes into the wetland lakes, but does not interfere with normal gate operation and water discharge. This short field study evaluated carbon dioxide (CO 2 ) injected into water as a non-obstructive method to reduce fish abundance near the WMS culverts. We quantified relative fish abundance using underwater sonar with and without injection of CO 2 into culverts during three discharge events: no flow (0 m 3 /s), restricted flow (0.9 m 3 /s), and unrestricted flow (3.2 m 3 /s). Overall, CO 2 reached or exceeded our target concentration of 100 mg/L during no flow and restricted flow, and fish abundance was 70–95% lower at culvert entrances relative to untreated control days. The target CO 2 level was not reached during unrestricted flow and fish abundance was not reduced during CO 2 injection. Atmospheric CO 2 concentrations were inconsequential and unaffected by CO 2 treatments throughout testing. Results from this initial field study provide several considerations for CO 2 as a fish deterrent in natural environments.

Illinois↗