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USGS1969

The determination of the acoustic parameters of volcanic rocks from compressional velocity measurements

A statistical analysis was made of the relationship of various acoustic parameters of volcanic rocks to compressional wave velocities for data obtained in a volcanic region in Nevada. Some additional samples, chiefly granitic rocks, were also included in the study to extend the range of parameters and the variety of siliceous rock types sampled. Laboratory acoustic measurements obtained on 62 dry core samples were grouped with similar measurements obtained from geophysical logging devices at several depth intervals in a hole from which 15 of the core samples had been obtained. The effects of lithostatic and hydrostatic load on changing the rock acoustic parameters measured in the hole were noticeable when compared with the laboratory measurements on the same core. The results of the analyses determined by grouping all of the data, however, indicate that dynamic Young's, shear and bulk modulus, shear velocity, shear and compressional characteristic impedance, as well as amplitude and energy reflection coefficients may be reliably estimated on the basis of the compressional wave velocities of the rocks investigated. Less precise estimates can be made of density based on the rock compressional velocity. The possible extension of these relationships to include many siliceous rocks is suggested.

International Journal of Rock Mechanics and Mining↗

USGS2021

The response of streams in the Adirondack region of New York to projected changes in sulfur and nitrogen deposition under changing climate

Modeling studies project that in the future surface waters in the northeast US will continue to recover from acidification over decades following reductions in atmospheric sulfur dioxide and nitrogen oxides emissions. However, these studies generally assume stationary climatic conditions over the simulation period and ignore the linkages between soil and surface water recovery from acid deposition and changing climate, despite fundamental impacts to watershed processes and comparable time scales for both phenomena. In this study, the integrated biogeochemical model PnET-BGC was applied to two montane forest watersheds in the Adirondack region of New York, USA to evaluate the recovery of surface waters from historical acidification in response to possible future changes in climate and atmospheric sulfur and nitrogen deposition. Statistically downscaled climate scenarios on average project warmer temperatures and greater precipitation for the Adirondack by the end of the century. Model simulations suggest under constant climate, acid-sensitive Buck Creek would gain 12.8 μeq L −1 of acid neutralizing capacity (ANC) by 2100 from large reductions in deposition, whereas acid insensitive Archer Creek is projected to gain 7.9 μeq L −1 of ANC. However, climate change could limit those improvements in acid-base status. Under climate change, a negative offset relative to the ANC increases with no climate change are projected for both streams by 2100. In acid-insensitive Archer Creek the negative offset (−8.5 μeq L −1 ) was large enough that ANC is projected to decrease by −0.6 μeq L −1 , whereas in acid-sensitive Buck Creek, the negative offset (−0.4 μeq L −1 ) resulted in a slight decline of the projected future ANC increase to 12.4 μeq L −1 . Calculated target loads for 2150 for both sites decreased when future climate change was considered in model simulations, which suggests further reductions in acid deposition may be necessary to restore ecosystem structure and function under a changing climate.

New York↗

USGS2017

3D Pressure‐limited approach to model and estimate CO2 injection and storage capacity: saline Mount Simon Formation

To estimate the carbon dioxide (CO 2 ) injection and storage capacity of saline formations, we used Tough2‐ECO2N simulation software to develop a pressure‐limited (dynamic) simulation approach based on applying three‐dimensional (3D) numerical simulation only on the effective injection area (A eff ) surrounding each injection well. A statistical analysis was performed to account for existing reservoir heterogeneity and property variations. The accuracy of the model simulation results (such as CO 2 plume extension and induced injection well bottomhole pressure values) were tested and verified against the data obtained from the Decatur CO 2 injection study of the Mount Simon Formation. Next, we designed a full‐field CO 2 injection pattern by populating the core sections of this formation with a series of the simulated effective injection areas such that each simulated A eff acts as a closed domain. The results of this analysis were used to estimate the optimum number and location of the required CO 2 injection wells, along with the dynamic annual CO 2 injection rate and overall pressure‐limited storage capacity of this formation. This approach enabled us to model separate CO 2 injection activities independently at different sections of the same saline formation and to model and simulate faults and natural barriers by considering them as boundary conditions for each simulated A eff without constructing full‐field models. Using this approach, a series of modeled A eff with relevant properties may be redesigned to model any other saline formation with a similar structure.

Mount Simon Formation↗

USGS2024

Multiple lines of evidence point to pesticides as stressors affecting invertebrate communities in small streams in five United States regions

Multistressor studies were performed in five regions of the United States to assess the role of pesticides as stressors affecting invertebrate communities in wadable streams. Pesticides and other chemical and physical stressors were measured in 75 to 99 streams per region for 4 weeks, after which invertebrate communities were surveyed (435 total sites). Pesticides were sampled weekly in filtered water, and once in bed sediment. The role of pesticides as a stressor to invertebrate communities was assessed by evaluating multiple lines of evidence: toxicity predictions based on measured pesticide concentrations, multivariate models and other statistical analyses, and previously published mesocosm experiments. Toxicity predictions using benchmarks and species sensitivity distributions and statistical correlations suggested that pesticides were present at high enough concentrations to adversely affect invertebrate communities at the regional scale. Two undirected techniques—boosted regression tree models and distance-based linear models—identified which pesticides were predictors of (respectively) invertebrate metrics and community composition. To put insecticides in context with known, influential covariates of invertebrate response, generalized additive models were used to identify which individual pesticide(s) were important predictors of invertebrate community condition in each region, after accounting for natural covariates. Four insecticides were identified as stressors to invertebrate communities at the regional scale: bifenthrin, chlordane, fipronil and its degradates, and imidacloprid. Fipronil was particularly important in the Southeast region, and imidacloprid, bifenthrin, and chlordane were important in multiple regions. For imidacloprid, bifenthrin, and fipronil, toxicity predictions were supported by mesocosm experiments that demonstrated adverse effects on naïve aquatic communities when dosed under controlled conditions. These multiple lines of evidence do not prove causality—which is challenging in the field under multistressor conditions—but they make a strong case for the role of insecticides as stressors adversely affecting invertebrate communities in streams within the five sampled regions.

Science of the Total Environment↗

USGS2017

PeRL: A circum-Arctic Permafrost Region Pond and Lake database

Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1. 0 × 10 4 m 2 , have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1. 4 × 10 6 km 2 across the Arctic, about 17 % of the Arctic lowland ( < 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1. 0 × 10 6 m 2 down to 1. 0 × 10 2 m 2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1. 0 × 10 to 9. 4 × 10 1 km −2 . Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. The implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands. Waterbody maps, study area boundaries, and maps of regional permafrost landscapes including detailed metadata are available at https://doi.pangaea.de/10.1594/PANGAEA.868349 .

Earth System Science Data↗

USGS2019

Machine learning classifiers for attributing tephra to source volcanoes: An evaluation of methods for Alaska tephras

Glass composition-based correlations of volcanic ash (tephra) traditionally rely on extensive manual plotting. Many previous statistical methods for testing correlations are limited by using geochemical means, masking diagnostic variability. We suggest that machine learning classifiers can expedite correlation, quickly narrowing the list of likely candidates using well-trained models. Eruptives from Alaska's Aleutian Arc-Alaska Peninsula and Wrangell volcanic field were used as a test environment for 11 supervised classification algorithms, trained on nearly 2000 electron probe microanalysis measurements of glass major oxides, representing 10 volcanic sources. Artificial neural networks and random forests were consistently among the top-performing learners (accuracy and kappa > 0.96). Their combination as an average ensemble effectively improves their performance. Using this combined model on tephras from Eklutna Lake, south-central Alaska, showed that predictions match traditional methods and can speed correlation. Although classifiers are useful tools, they should aid expert analysis, not replace it. The Eklutna Lake tephras are mostly from Redoubt Volcano. Besides tephras from known Holocene-active sources, Holocene tephra geochemically consistent with Pleistocene Emmons Lake Volcanic Center (Dawson tephra), but from a yet unknown source, is evident. These tephras are mostly anchored by a highly resolved varved chronology and represent new important regional stratigraphic markers.

Journal of Quaternary Science↗

USGS2017

Is “morphodynamic equilibrium” an oxymoron?

Morphodynamic equilibrium is a widely adopted yet elusive concept in the field of geomorphology of coasts, rivers and estuaries. Based on the Exner equation, an expression of mass conservation of sediment, we distinguish three types of equilibrium defined as static and dynamic, of which two different types exist. Other expressions such as statistical and quasi-equilibrium which do not strictly satisfy the Exner conditions are also acknowledged for their practical use. The choice of a temporal scale is imperative to analyse the type of equilibrium. We discuss the difference between morphodynamic equilibrium in the “real world” (nature) and the “virtual world” (model). Modelling studies rely on simplifications of the real world and lead to understanding of process interactions. A variety of factors affect the use of virtual-world predictions in the real world (e.g., variability in environmental drivers and variability in the setting) so that the concept of morphodynamic equilibrium should be mathematically unequivocal in the virtual world and interpreted over the appropriate spatial and temporal scale in the real world. We draw examples from estuarine settings which are subject to various governing factors which broadly include hydrodynamics, sedimentology and landscape setting. Following the traditional “tide-wave-river” ternary diagram, we summarize studies to date that explore the “virtual world”, discuss the type of equilibrium reached and how it relates to the real world.

Earth-Science Reviews↗

USGS2014

Great Lakes prey fish populations: a cross-basin overview of status and trends based on bottom trawl surveys, 1978-2013

The assessment of Great Lakes prey fish stocks have been conducted annually with bottom trawls since the 1970s by the Great Lakes Science Center, sometimes assisted by partner agencies. These stock assessments provide data on the status and trends of prey fish that are consumed by important commercial and recreational fishes. Although all these annual surveys are conducted using bottom trawls, they differ among the lakes in the proportion of the lake covered, seasonal timing, trawl gear used, and the manner in which the trawl is towed (across or along bottom contours). Because each assessment is unique, population indices were standardized to the highest value for a time series within each lake for the following prey species: Cisco (Coregonus artedi), Bloater (C. hoyi), Rainbow Smelt (Osmerus mordax), Alewife (Alosa pseudoharengus), and Round Goby (Neogobius melanostomus). In this report, standardized indices are presented in graphical form along with synopses to provide a short, informal cross-basin summary of the status and trends of principal prey fishes. There was basin-wide agreement in the trends of age-1 and older biomass for all prey species, with the highest concordance occurring for coregonids and Rainbow Smelt, and weaker concordance for Alewife. For coregonids, the highest biomass occurred from the mid-1980s to the mid-1990s. Rainbow Smelt biomass declined slowly and erratically during the last quarter century. Alewife biomass was generally higher from the early 1980s through 1990s across the Great Lakes, but since the early 1990s, trends have been divergent across the lakes, though there has been a downward trend in all lakes since 2005. Recently, Lake Huron has shown resurgence in biomass of Bloater, achieving 75% of its maximum record in 2012 due to recruitment of a succession of strong and moderate year classes that appeared in 2005-2011. Also, strong recruitment of the 2010 year class of Alewife has led to a sharp increase in biomass of Alewife in Lake Michigan. In general, trends in year-class strengths were less concordant across the basin and only coregonids showed statistical agreement across the upper Great Lakes. The appearance of strong and moderate year-classes of Bloater in Lake Huron in 2005- 2011 countered the trend of continuing weak year-classes of coregonids in Lakes Michigan and Superior. Not shown in our analysis is the appearance of the 2013 year-class of Bloater in Huron, the largest to date. There was no agreement in cross-basin trends in year-class strengths for Rainbow Smelt and Alewife, although there was agreement between pairs of lakes. Although there was statistical agreement in trends of age-0 and older Round Goby biomass among lakes where this species has successfully invaded (Michigan, Huron, Erie and Ontario), temporal patterns of biomass in each lake were different. Round Goby may be approaching equilibrium in Lake Erie, peaking in Lake Huron, and expanding in Lake Michigan. The trend in Lake Ontario remains unclear. Declining abundance in Lake Erie has corresponded with evidence that Round Goby have become increasingly incorporated into piscivore diets, e.g., Lake Trout, Walleye, Smallmouth Bass, Yellow Perch, and Burbot in Lakes Michigan, Huron, Erie, and Ontario. Round Goby continue to be absent from spring bottom trawl assessments in Lake Superior, but their presence in the harbors and embayments of Duluth and Thunder Bay (U.S. Geological Survey and Ontario Ministry of Natural Resources, unpublished data), suggests that there is potential for future colonization.

Great Lakes↗

USGS2004

Incorporating uncertainty into mercury-offset decisions with a probabilistic network for National Pollutant Discharge Elimination System permit holders: An interim report

This interim report describes an alternative approach for evaluating the efficacy of using mercury (Hg) offsets to improve water quality. Hg-offset programs may allow dischargers facing higher-pollution control costs to meet their regulatory obligations by making more cost effective pollutant-reduction decisions. Efficient Hg management requires methods to translate that science and economics into a regulatory decision framework. This report documents the work in progress by the U.S. Geological Survey’s Western Geographic Science Center in collaboration with Stanford University toward developing this decision framework to help managers, regulators, and other stakeholders decide whether offsets can cost effectively meet the Hg total maximum daily load (TMDL) requirements in the Sacramento River watershed. Two key approaches being considered are: (1) a probabilistic approach that explicitly incorporates scientific uncertainty, cost information, and value judgments; and (2) a quantitative approach that captures uncertainty in testing the feasibility of Hg offsets. Current fate and transport-process models commonly attempt to predict chemical transformations and transport pathways deterministically. However, the physical, chemical, and biologic processes controlling the fate and transport of Hg in aquatic environments are complex and poorly understood. Deterministic models of Hg environmental behavior contain large uncertainties, reflecting this lack of understanding. The uncertainty in these underlying physical processes may produce similarly large uncertainties in the decisionmaking process. However, decisions about control strategies are still being made despite the large uncertainties in current Hg loadings, the relations between total Hg (HgT) loading and methylmercury (MeHg) formation, and the relations between control efforts and Hg content in fish. The research presented here focuses on an alternative analytical approach to the current use of safety factors and deterministic methods for Hg TMDL decision support, one that is fully compatible with an adaptive management approach. This alternative approach uses empirical data and informed judgment to provide a scientific and technical basis for helping National Pollutant Discharge Elimination System (NPDES) permit holders make management decisions. An Hg-offset system would be an option if a wastewater-treatment plant could not achieve NPDES permit requirements for HgT reduction. We develop a probabilistic decision-analytical model consisting of three submodels for HgT loading, MeHg, and cost mitigation within a Bayesian network that integrates information of varying rigor and detail into a simple model of a complex system. Hg processes are identified and quantified by using a combination of historical data, statistical models, and expert judgment. Such an integrated approach to uncertainty analysis allows easy updating of prediction and inference when observations of model variables are made. We demonstrate our approach with data from the Cache Creek watershed (a subbasin of the Sacramento River watershed). The empirical models used to generate the needed probability distributions are based on the same empirical models currently being used by the Central Valley Regional Water Quality Control Cache Creek Hg TMDL working group. The significant difference is that input uncertainty and error are explicitly included in the model and propagated throughout its algorithms. This work demonstrates how to integrate uncertainty into the complex and highly uncertain Hg TMDL decisionmaking process. The various sources of uncertainty are propagated as decision risk that allows decisionmakers to simultaneously consider uncertainties in remediation/implementation costs while attempting to meet environmental/ecologic targets. We must note that this research is on going. As more data are collected, the HgT and cost-mitigation submodels are updated and the uncertainties may be reduced. Subsequently, the value of using a probabilistic framework for estimating and explicitly stating these uncertainties within a decisionmaking process can be estimated when new data are collected. Future work includes the design and implementation of a Bayesian network decision support system (BN-DSS) to produce mitigation scenarios for offset-project evaluation in the Cache Creek watershed. The decisionmaker, a wastewater-treatment plant, is expected to evaluate potential Hg-offset programs in terms of changes in HgT load changes, MeHg-production potential, project cost, and other suitability criteria. Subsequently, scenarios can be analyzed by performing sensitivity analyses and ranking environmental and economic uncertainties in terms of the decisionmaker’s preferences and risk choices. Such an analysis allows decisionmakers and stakeholders to explore various scenarios and predict the consequences of different stated preferences over outcomes.

Open-File Report↗

USGS2011

Flow regime, temperature, and biotic interactions drive differential declines of trout species under climate change

Broad-scale studies of climate change effects on freshwater species have focused mainly on temperature, ignoring critical drivers such as flow regime and biotic interactions. We use downscaled outputs from general circulation models coupled with a hydrologic model to forecast the effects of altered flows and increased temperatures on four interacting species of trout across the interior western United States (1.01 million km 2 ), based on empirical statistical models built from fish surveys at 9,890 sites. Projections under the 2080s A1B emissions scenario forecast a mean 47% decline in total suitable habitat for all trout, a group of fishes of major socioeconomic and ecological significance. We project that native cutthroat trout Oncorhynchus clarkii , already excluded from much of its potential range by nonnative species, will lose a further 58% of habitat due to an increase in temperatures beyond the species' physiological optima and continued negative biotic interactions. Habitat for nonnative brook trout Salvelinus fontinalis and brown trout Salmo trutta is predicted to decline by 77% and 48%, respectively, driven by increases in temperature and winter flood frequency caused by warmer, rainier winters. Habitat for rainbow trout, Oncorhynchus mykiss , is projected to decline the least (35%) because negative temperature effects are partly offset by flow regime shifts that benefit the species. These results illustrate how drivers other than temperature influence species response to climate change. Despite some uncertainty, large declines in trout habitat are likely, but our findings point to opportunities for strategic targeting of mitigation efforts to appropriate stressors and locations.

Proceedings of the National Academy of Sciences of↗

USGS2021

Assessing the impact of drought on arsenic exposure from private domestic wells in the conterminous United States

This study assesses the potential impact of drought on arsenic exposure from private domestic wells by using a previously developed statistical model that predicts the probability of elevated arsenic concentrations (>10 μg per liter) in water from domestic wells located in the conterminous United States (CONUS). The application of the model to simulate drought conditions used systematically reduced precipitation and recharge values. The drought conditions resulted in higher probabilities of elevated arsenic throughout most of the CONUS. While the increase in the probability of elevated arsenic was generally less than 10% at any one location, when considered over the entire CONUS, the increase has considerable public health implications. The population exposed to elevated arsenic from domestic wells was estimated to increase from approximately 2.7 million to 4.1 million people during drought. The model was also run using total annual precipitation and groundwater recharge values from the year 2012 when drought existed over a large extent of the CONUS. This simulation provided a method for comparing the duration of drought to changes in the predicted probability of high arsenic in domestic wells. These results suggest that the probability of exposure to arsenic concentrations greater than 10 μg per liter increases with increasing duration of drought. These findings indicate that drought has a potentially adverse impact on the arsenic hazard from domestic wells throughout the CONUS.

Conterminous United States↗

USGS2022

HydroBench: Jupyter supported reproducible hydrological model benchmarking and diagnostic tool

Evaluating whether hydrological models are right for the right reasons demands reproducible model benchmarking and diagnostics that evaluate not just statistical predictive model performance but also internal processes. Such model benchmarking and diagnostic efforts will benefit from standardized methods and ready-to-use toolkits. Using the Jupyter platform, this work presents HydroBench, a model-agnostic benchmarking tool consisting of three sets of metrics: 1) common statistical predictive measures, 2) hydrological signature-based process metrics, including a new time-linked flow duration curve and 3) information-theoretic diagnostics that measure the flow of information among model variables. As a test case, HydroBench was applied to compare two model products (calibrated and uncalibrated) of the National Hydrologic Model - Precipitation Runoff Modeling System (NHM-PRMS) at the Cedar River watershed, WA, United States. Although the uncalibrated model has the highest predictive performance, particularly for high flows, the signature-based diagnostics showed that the model overestimates low flows and poorly represents the recession processes. Elucidating why low flows may have been overestimated, the information-theoretic diagnostics indicated a higher flow of information from precipitation to snowmelt to streamflow in the uncalibrated model compared to the calibrated model, where information flowed more directly from precipitation to streamflow. This test case demonstrated the capability of HydroBench in process diagnostics and model predictive and functional performance evaluations, along with their tradeoffs. Having such a model benchmarking tool not only provides modelers with a comprehensive model evaluation system but also provides an open-source tool that can further be developed by the hydrological community.

Frontiers in Earth Sciences↗

USGS2012

The population structure of Escherichia coli isolated from subtropical and temperate soils

While genotypically-distinct naturalized Escherichia coli strains have been shown to occur in riparian soils of Lake Michigan and Lake Superior watersheds, comparative analyses of E. coli populations in diverse soils across a range of geographic and climatic conditions have not been investigated. The main objectives of this study were to: (a) examine the population structure and genetic relatedness of E. coli isolates collected from different soil types on a tropical island (Hawaii), and (b) determine if E. coli populations from Hawaii and temperate soils (Indiana, Minnesota) shared similar genotypes that may be reflective of biome-related soil conditions. DNA fingerprint and multivariate statistical analyses were used to examine the population structure and genotypic characteristics of the E. coli isolates. About 33% (98 of 293) of the E. coli from different soil types and locations on the island of Oahu, Hawaii, had unique DNA fingerprints, indicating that these bacteria were relatively diverse; the Shannon diversity index for the population was 4.03. Nearly 60% (171 of 293) of the E. coli isolates from Hawaii clustered into two major groups and the rest, with two or more isolates, fell into one of 22 smaller groups, or individual lineages. Multivariate analysis of variance of 89, 21, and 106 unique E. coli DNA fingerprints for Hawaii, Indiana, and Minnesota soils, respectively, showed that isolates formed tight cohesive groups, clustering mainly by location. However, there were several instances of clonal isolates being shared between geographically different locations. Thus, while nearly identical E. coli strains were shared between disparate climatologically- and geographically-distinct locations, a vast majority of the soil E. coli strains were genotypically diverse and were likely derived from separate lineages. This supports the hypothesis that these bacteria are not unique and multiple genotypes can readily adapt to become part of the soil autochthonous microflora.

Hawai'i, Indiana, Minnesota↗

USGS2019

Differentiating anthropogenic and natural sources of uranium by geochemical fingerprinting of groundwater at the Homestake Uranium Mill, Milan, New Mexico, USA

A multiparameter geochemical-isotopic fingerprinting approach was used to differentiate natural and anthropogenic signatures of uranium contamination near the Homestake uranium mill site (Site), near Milan, New Mexico, USA. The Site consists of two tailings piles from milling operations and groundwater contamination from these tailings have been noted. The Site lies within the lower San Mateo Creek Basin with multiple regional sources of U contamination from mining and mill operations and is underlain by a heterogeneous alluvial aquifer, which is underlain by basement rock of the Chinle Group and the lowermost San Andres-Glorieta aquifer. To help decipher signatures, several statistical approaches were used including PCA, NMDS, and cluster analysis. Trilinear piper diagrams indicate two end member water types at the Site, sulfate-Na-K and sulfate-Ca. Natural alluvial aquifer groundwater in this area, relatively unaffected by mining or milling, appears to be more dominated by bicarbonate than sulfate and the deeper San Andres-Glorieta aquifer that has a mixture of sulfate and bicarbonate. Uranium concentrations from the Site fall into three broad categories, less than the drinking water standard of 30 µg/L (n=3), from 30 to 100 µg/L (n=9) and greater than 100 µg/L (n=8). Component loadings in a principal component analysis are highest for uranium isotopes, 228Ra, gross alpha-beta, molybdenum, chloride, uranium, and sodium, which affect the similarities or differences among wells sampled. Results suggest that several alluvial wells upgradient from the Site have anthropogenic fingerprints from regional sources related to upgradient mining. Wells with higher uranium concentrations have uranium activity ratios close to 1, which is indicative of mining or milling signatures. These same wells have elevated radon activities. This information can be used to inform Site managers on the source of water related to uranium at the Site and provide an approach for geochemical fingerprinting.

New Mexico↗

USGS2020

Understanding the relationship between stream metabolism and biological assemblages

Biological assemblages are commonly used for assessing stream health, but there is increased interest among the freshwater research community in incorporating measures of stream function, such as metabolism, to strengthen stream-health assessments. Presently, there is limited information about the relationships between stream metabolism and biological assemblages, along with the measurement period required to relate metabolism with stream biota. Our study assessed which environmental factors explained stream metabolism and to what degree stream metabolism and minimum dissolved oxygen (DOmin) were related to invertebrate and fish metrics in streams distributed across several regions of the United States. Furthermore, we evaluated the number of metabolism monitoring days required for maximizing the ability to detect relationships between stream metabolism and biological assemblage metrics. We sampled 17 sites distributed among reference, agricultural, and urban areas for stream metabolism, nutrients, habitat, and biological assemblages (invertebrates and fishes). Overall, sites were heterotrophic with gross primary production (GPP) and ecosystem respiration (ER) related primarily to days since last high flow, canopy cover, maximum water temperature, and total phosphorus. DOmin was related to days since last high flow, canopy cover, and maximum water temperature. We were unable to determine a clear statistical relationship between invertebrate metrics (invertebrate richness; Ephemeroptera, Plecoptera, and Trichoptera richness; and scraper-taxa richness) and GPP, ER, or DOmin. In contrast, we found that 2 fish-assemblage metrics were associated with stream metabolism and DOmin. A fish multimetric index (FMMI) was negatively correlated with GPP ( r = −0.5, p = 0.048) and positively correlated with DOmin ( r = 0.47, p = 0.06). Percentage of omnivorous fish taxa was positively correlated with GPP ( r = 0.72, p = 0.001) and ER ( r = 0.55, p = 0.02) and negatively correlated with DOmin ( r = −0.67, p = 0.003). The lack of detected relationships for most of the biological-assemblage metrics with stream metabolism may be partially due to 1 or more factors, including high variability, low sample size, limited range in metabolism values, assemblage metrics used, and geographic distribution of sites. Comparing stream-metabolism measurement periods (in days) to biological-assemblage metrics indicated that optimum correlations occurred at 2 d for DOmin, 3 d for GPP, and 14 d for ER. Although our study found limited relationships of stream metabolism and DOmin with biological assemblages, future studies should consider a larger sample size (≥30), 14-d or longer metabolism measurement period, and assessment of other taxa-specific or assemblage metrics.

Freshwater Science↗

USGS2016

Combined effects of projected sea level rise, storm surge, and peak river flows on water levels in the Skagit Floodplain

Current understanding of the combined effects of sea level rise (SLR), storm surge, and changes in river flooding on near-coastal environments is very limited. This project uses a suite of numerical models to examine the combined effects of projected future climate change on flooding in the Skagit floodplain and estuary. Statistically and dynamically downscaled global climate model scenarios from the ECHAM-5 GCM were used as the climate forcings. Unregulated daily river flows were simulated using the VIC hydrology model, and regulated river flows were simulated using the SkagitSim reservoir operations model. Daily tidal anomalies (TA) were calculated using a regression approach based on ENSO and atmospheric pressure forcing simulated by the WRF regional climate model. A 2-D hydrodynamic model was used to estimate water surface elevations in the Skagit floodplain using resampled hourly hydrographs keyed to regulated daily flood flows produced by the reservoir simulation model, and tide predictions adjusted for SLR and TA. Combining peak annual TA with projected sea level rise, the historical (1970–1999) 100-yr peak high water level is exceeded essentially every year by the 2050s. The combination of projected sea level rise and larger floods by the 2080s yields both increased flood inundation area (+ 74%), and increased average water depth (+ 25 cm) in the Skagit floodplain during a 100-year flood. Adding sea level rise to the historical FEMA 100-year flood resulted in a 35% increase in inundation area by the 2040's, compared to a 57% increase when both SLR and projected changes in river flow were combined.

Washington↗

USGS2017

Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

Tennessee↗

USGS2020

Post-fire vegetation response in a repeatedly burned low-elevation sagebrush steppe protected area provides insights about resilience and invasion resistance

Sagebrush steppe ecosystems are threatened by human land-use legacies, biological invasions, and altered fire and climate dynamics. Steppe protected areas are therefore of heightened conservation importance but are few and vulnerable to the same impacts broadly affecting sagebrush steppe. To address this problem, sagebrush steppe conservation science is increasingly emphasizing a focus on resilience to fire and resistance to non-native annual grass invasion as a decision framework. It is well-established that the positive feedback loop between fire and annual grass invasion is the driving process of most contemporary steppe degradation. We use a newly developed ordinal zero-augmented beta regression model fit to large-sample vegetation monitoring data from John Day Fossil Beds National Monument, USA, spanning 7 years to evaluate fire responses of two native perennial foundation bunchgrasses and two non-native invasive annual grasses in a repeatedly burned, historically grazed, and inherently low-resilient protected area. We structured our model hierarchically to support inferences about variation among ecological site types and over time after also accounting for growing-season water deficit, fine-scale topographic variation, and burn severity. We use a state-and-transition conceptual diagram and abundances of plants listed in ecological site reference conditions to formalize our hypothesis of fire-accelerated transition to ecologically novel annual grassland. Notably, big sagebrush ( Artemisia tridentata ) and other woody species were entirely removed by fire. The two perennial grasses, bluebunch wheatgrass ( Pseudoroegneria spicata ) and Thurber's needlegrass ( Achnatherum thurberianum ) exhibited fire resiliency, with no apparent trend after fire. The two annual grasses, cheatgrass ( Bromus tectorum ) and medusahead ( Taeniatherum caput-medusae ), increased in response to burn severity, most notably medusahead. Surprisingly, we found no variation in grass cover among ecological sites, suggesting fire-driven homogenization as shrubs were removed and annual grasses became dominant. We found contrasting responses among all four grass species along gradients of topography and water deficit, informative to protected-area conservation strategies. The fine-grained influence of topography was particularly important to variation in cover among species and provides a foothold for conservation in low-resilient, aridic steppe. Broadly, our study demonstrates how to operationalize resilience and resistance concepts for protected areas by integrating empirical data with conceptual and statistical models.

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