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Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity

The composition, occurrence, distribution, and possible toxicity of chemical mixtures in the environment are research concerns of the U.S. Geological Survey and others. The presence of specific chemical mixtures may serve as indicators of natural phenomena or human-caused events. Chemical mixtures may also have ecological, industrial, geochemical, or toxicological effects. Chemical-mixture occurrences vary by analyte composition and concentration. Four related computer programs have been developed by the National Water-Quality Assessment Program of the U.S. Geological Survey for research of chemical-mixture compositions, occurrences, distributions, and possible toxicities. The compositions and occurrences are identified for the user-supplied data, and therefore the resultant counts are constrained by the user’s choices for the selection of chemicals, reporting limits for the analytical methods, spatial coverage, and time span for the data supplied. The distribution of chemical mixtures may be spatial, temporal, and (or) related to some other variable, such as chemical usage. Possible toxicities optionally are estimated from user-supplied benchmark data. The software for the analysis of chemical mixtures described in this report is designed to work with chemical-analysis data files retrieved from the U.S. Geological Survey National Water Information System but can also be used with appropriately formatted data from other sources. Installation and usage of the mixture software are documented. This mixture software was designed to function with minimal changes on a variety of computer-operating systems. To obtain the software described herein and other U.S. Geological Survey software, visit http://water.usgs.gov/software/.

Scientific Investigations Report↗

An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri

Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed. Distinct basin characteristics were evaluated and selected for use on the basis of their theoretical relation to flow, results from previous studies, and the ability to reliably measure the basin characteristic using digital datasets and geographic information system (GIS) technology. The key basin characteristics determined or computed for each of the 39 basins upstream from the streamflow-gaging stations were drainage area, percent impervious area, main-channel slope based on the 10- and 85-percent length method, percentage of the basin area in storage (lakes, ponds, reservoirs, wetlands), the composite Natural Resources Conservation Service curve number estimated from a combination of the soil type data and land-use characteristics, and the streamflow variability index developed for the recently completed study of low-flow regression in Missouri. Characteristics of spatial and temporal rainfall distribution came from the next generation weather radar (NEXRAD) network. Procedures were developed for this study to convert the variable radar sweep rate into a 5-minute total rainfall hyetograph using data from the radar bin at the centroid of a given basin. Additional characteristics determined for each storm on the basin included the 5-day and 14-day antecedent rainfall, estimated from the mean of daily rainfall values from various rain gages in the area. The database of observed rainfall and runoff events for the 39 basins upstream from the streamflow-gaging stations was analyzed to compute the optimal storm-specific initial abstraction and constant loss values, as well as the time to peak, peak streamflow, and shape factor values of the GUH. The optimal storm-specific values were used to develop a regional regression equation for initial abstraction; conversely, the constant loss was estimated not by regression but from either a generalized or specific regional mean value. The optimal storm-specific values of GUH time to peak, GUH peak streamflow, and GUH shape factor were used to develop regression equations for the GUH. The regression equations for the GUH initially were tested alone, and then were combined with the appropriate regional regression equation for initial abstraction and both the generalized regional and specific regional mean constant loss values. For the GUH regression equations, the interquartile range was substantially smaller than the range spanned by the minimum and maximum values, which indicates most of the errors have much smaller variation, and the minimum and maximum values may be extreme outliers. The central tendency of the regressed errors for peak streamflow and runoff hydrograph volume were both approximately zero, which implies a generally unbiased estimation of these values. The mean and median of the regressed errors for time to peak streamflow were both small but greater than zero, which implies the GUH regression equations create a hydrograph that has a peak that is later in time than observed. Specifically, the regressed times indicate an offset of about 10 minutes, on average, from observed. The mean and median of the regressed errors for widths of the runoff hydrograph at 50 and 75 percent were less than zero, which implies the GUH tends to slightly underestimate these widths compared to the observed. The appropriate regional initial abstraction regression equation was combined with both the generalized and the specific regional mean constant loss values and the GUH regression equations. Both the generalized regional mean constant loss and specific regional mean constant loss forms of the basin-loss model worked equally well to model the observed runoff hydrograph based on the error analysis, and neither model seems to make a consistently better approximation. Both initial abstraction and constant loss models combined with the GUH regression equations were further validated using several storms available after the start of the project in early 2011 with similar but consistently higher error results. If these methods are used in an urban area in Missouri other than those examined in this study, advice to the user is given to consider using the generalized regional mean values. If these methods are used in an urban area that is a subbasin of one of the basins in this study, advice to the user is given to consider using the specific regional mean values. The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.

Missouri↗

Role of stranded gas from Central Asia, Russia, Southeast Asia, and Australia in meeting Asia’s future demand for gas imports

Demand for natural gas is increasing more rapidly than anticipated in Far East markets because (1) China has modified its policies in order to increase reliance on gas, in part to mitigate the growth in its coal consumption (which now stand at almost half of world coal production), (2) Japan has announced its intention to eventually shutdown its nuclear power industry, and (3) India, which currently has more than 400 million people without electricity, desires to accelerate electrification. This analysis investigates the potential role of stranded gas from Central Asia, Russia, Southeast Asia, and Australia in meeting Asia's future demand for gas imports. It initially surveys the discovered or known gas in stranded gas accumulations in Central Asia, Russia, Australia, Indonesia, and Malaysia. It then examines the primary gas import markets of China, India, Japan, and South Korea by describing energy use, gas demand trends, and domestic gas supplies to establish boundaries that encompass the wide variation in gas import demands in these markets during the two decades following 2020. Then the cost of developing and delivering gas through overland pipelines from selected stranded gas fields in Central Asia and Russia to China is examined. Analysis shows that for the Shanghai market in China, the costs of developing and delivering Russia's stranded gas from the petroleum provinces of eastern Siberia are competitive with costs estimated for stranded gas from Central Asia. However, for the Western Siberian Basin, delivered gas costs are at least 3 US dollars per thousand cubic feet (USD/Mcf) higher than delivered gas from Central Asia. The extraction and transport costs to a liquefaction plant for gas from stranded gas fields located in Australia, Indonesia, Malaysia, and the basins of eastern Siberia are then evaluated. The resource cost functions presented show development and extraction costs as a function of the volume of stranded gas developed for each country. The analysis demonstrates that, although the Russian fields in areas of eastern Siberia are large with relatively low extraction costs, distances to a potential liquefaction plant at Vladivostok make them initially the high cost suppliers of the liquefied natural gas (LNG) market. For the LNG markets examined, Australia and Malaysia are initially the lowest cost suppliers. For the Shanghai market, a comparison of the cost of supplying gas by pipeline with the cost of supplying LNG shows that the pipeline costs from areas of eastern Siberia and Central Asia are generally lower than delivered cost of gas as LNG from the LNG supply sources considered.

Central Asia, Southeast Asia↗

Quantitative SWOT analysis: A structured and collaborative approach to reintroduction site selection for the endangered Pacific pocket mouse

Species extinction and loss of biodiversity are major crises in the Anthropocene. Translocations of threatened and endangered species, the movement of individuals to augment existing or establish new populations, are increasingly important conservation tools, but have historically had limited success. Selection of a suitable receiver site is essential to translocation success, with poor site suitability cited as one of the most common reasons for relocation failure. We utilized a quantitative SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to evaluate and prioritize potential receiver sites for the Pacific pocket mouse ( Perognathus longimembris pacificus ), an endangered subspecies of heteromyid rodent endemic to coastal southern California. With only three remaining extant populations, a conservation breeding and reintroduction program is underway with the goal of creating additional wild populations in new or historic locations throughout its indigenous range. Here we describe our use of SWOT analysis and discuss the strengths of this approach as well as improvements that could be made to the evaluation process for other species. Overall, we found that using a structured, transparent, and collaborative process was a valuable tool for prioritizing receiver sites. SWOT analysis is a flexible, repeatable, and proactive approach for identifying receiver sites and the preparations necessary to improve species-specific suitability. This approach has the potential to result in successful relocation compared to less structured site selection processes where poor site suitability is ultimately identified as a major factor in failure to establish wild populations.

California↗

Transcriptional profiling of MHC class I genes in rainbow trout infected with infectious hematopoietic necrosis virus

Major histocompatibility complex (MHC) molecules are important mediators of cell-mediated immunity in vertebrates. MHC class IA molecules are important for host anti-viral immunity as they present intracellular antigens and regulate natural killer cell (NK) activity. MHC class Ib molecules on the other hand are less understood and have demonstrated diverse immune and non-immune functions in mammals. Rainbow trout possess a single classical MHC IA locus ( Onmy -UBA) that is believed to function similar to that of mammalian MHC class Ia. Numerous MHC class Ib genes with undetermined functions have also been described in trout. Here we utilize quantitative reverse transcriptase PCR (qRT-PCR) techniques to survey the levels of basal and inducible transcription for selected trout MHC class Ib genes, sIgM and sentinels of IFN induction in response to viral infection. Basal transcription of all the class Ib genes examined in this study was lower than Onmy -UBA in naïve fish. UBA, along with all of the non-classical genes were induced in fish infected with virus but not in control fish. Our results support a non-classical designation for the majority of the class IB genes surveyed in this study based upon expression levels while also indicating that they may play an important role in anti-viral immunity in trout.

Molecular Immunology↗

Groundwater-quality data in the South Coast Range-Coastal study unit, 2008: Results from the California GAMA Program

Groundwater quality in the approximately 766-square-mile South Coast Range–Coastal (SCRC) study unit was investigated from May to December 2008, as part of the Priority Basins Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basins Project was developed in response to legislative mandates (Supplemental Report of the 1999 Budget Act 1999-00 Fiscal Year; and, the Groundwater Quality Monitoring Act of 2001 [Sections 10780-10782.3 of the California Water Code, Assembly Bill 599]) to assess and monitor the quality of groundwater in California, and is being conducted by the U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (SWRCB). The SCRC study unit was the 25th study unit to be sampled as part of the GAMA Priority Basins Project. The SCRC study unit was designed to provide a spatially unbiased assessment of untreated groundwater quality in the primary aquifer systems and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer systems (hereinafter referred to as primary aquifers) were defined as that part of the aquifer corresponding to the perforation interval of wells listed in the California Department of Public Health (CDPH) database for the SCRC study unit. The quality of groundwater in shallow or deep water-bearing zones may differ from the quality of groundwater in the primary aquifers; shallow groundwater may be more vulnerable to surficial contamination. In the SCRC study unit, groundwater samples were collected from 70 wells in two study areas (Basins and Uplands) in Santa Barbara and San Luis Obispo Counties. Fifty-five of the wells were selected using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and 15 wells were selected to aid in evaluation of specific water-quality issues (understanding wells). In addition to the 70 wells sampled, 3 surface-water samples were collected in streams near 2 of the sampled wells in order to better comprehend the interaction between groundwater and surface water in the area. The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOC], pesticides and pesticide degradates, polar pesticides and metabolites, and pharmaceutical compounds), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-TCP), naturally occurring inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], and alkalinity), and radioactive constituents (gross alpha and gross beta radioactivity). Naturally occurring isotopes (stable isotopes of hydrogen and oxygen in water, stable isotopes of nitrogen and oxygen in dissolved nitrate, stable isotopes of sulfur in dissolved sulfate, stable isotopes of carbon in dissolved inorganic carbon, activities of tritium, and carbon-14 abundance), and dissolved gases (including noble gases) also were measured to help identify the sources and ages of the sampled groundwater. In total, 298 constituents and field water-quality indicators were investigated. Three types of quality-control samples (blanks, replicates, and matrix-spikes) were collected at approximately 3 to 12 percent of the wells in the SCRC study unit, and the results for these samples were used to evaluate the quality of the data for the groundwater samples. Field blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Differences between replicate samples generally were less than 10 percent relative and/or standard deviation, indicating acceptable analytical reproducibility. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 84 percent of the compounds. This study did not attempt to evaluate the quality of drinking water delivered to consumers; after withdrawal from the ground, untreated groundwater typically is treated, disinfected, and/or blended with other waters to maintain water quality. Regulatory thresholds apply to water that is served to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-regulatory thresholds established for aesthetic concerns by CDPH. Comparisons between data collected for this study and thresholds for drinking water are for illustrative purposes only and are not indicative of compliance or noncompliance with those thresholds. Most organic and inorganic constituents that were detected in groundwater samples from the 55 grid wells in the SCRC study unit were detected at concentrations less than drinking-water thresholds. In addition, all detections of organic constituents in SCRC grid well samples were less than health-based thresholds. In total, VOCs were detected in 33 percent of the 55 grid wells sampled and pesticides and pesticide degradates were detected in 27 percent of grid wells sampled in the SCRC study unit. In the Basins study area, VOCs and pesticides and pesticide degradates were detected in approximately 33 percent of the 39 grid wells. In the Uplands study area, VOCs were detected in approximately 31 percent and pesticides and pesticide degradates were detected in approximately 13 percent of the 16 grid wells. Trace elements and minor ions were sampled for at 32 grid wells and nutrients at 33 grid wells in the SCRC study unit, and most detections were less than health-based thresholds. Exceptions in the Basins study area include one detection of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 µg/L and three detections of nitrite plus nitrate, as nitrogen (NO2-+NO3-) greater than the MCL-US of 10 mg/L. Exceptions in the Uplands study area include two detections of arsenic greater than the MCL-US and eight detections of molybdenum greater than the USEPA lifetime health advisory level (HAL-US) of 40 µg/L. All detections of major and minor ions and gross alpha and gross beta radioactivity from the SCRC grid wells were less than health-based thresholds. Results for trace elements, major ions, and TDS with non-enforceable thresholds set for aesthetic concerns from 16 Basins study area grid wells showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 µg/L were detected in grid wells. Manganese concentrations greater than the SMCL-CA of 50 µg/L were detected in six grid wells. Chloride concentrations greater than the recommended SMCL-CA threshold of 250 mg/L were detected in one grid well. Sulfate concentrations greater than the recommended SMCL-CA threshold of 250 mg/L were measured in 12 grid wells and 3 of these wells also were greater than the upper SMCL-CA threshold of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended threshold of 500 mg/L were measured in 14 of the 16 Basins study area grid wells and concentrations in 5 of these wells also were greater than the SMCL-CA upper threshold of 1,000 mg/L. In the Uplands study area, iron concentrations greater than the SMCL-CA were detected in 2 of 16 grid wells and manganese concentrations greater than the SMCL-CA were detected in 3 grid wells. TDS and sulfate concentrations greater than the recommended SMCL-CA thresholds were detected in 11 and 2 grid wells, respectively, but none of these concentrations were greater than the SMCL-CA upper thresholds.

California↗

Determination of total mercury in biological and geological samples

The analytical chemist is faced with several challenges when determining mercury in biological and geological materials. These challenges include widespread mercury contamination, both in the laboratory and the environment, possible losses of mercury during sample preparation and digestion, the wide range of mercury values commonly observed, ranging from the low nanogram per gram or per liter for background areas to hundreds of milligrams per kilogram in contaminated or ore-bearing areas, great matrix diversity, and sample heterogeneity1. These factors can be naturally occurring or anthropogenic, but must be addressed to provide a precise and accurate analysis. Although there are many instrumental methods available for the successful determination of mercury, no one technique will address all problems or all samples all of the time. The approach for the determination of mercury used at the U.S. Geological Survey, Crustal Imaging and Characterization Team, Denver Laboratories, utilizes a suite of complementary instrumental methods when approaching a study requiring mercury analyses. Typically, a study could require the analysis of waters, leachates or selective digestions of solids, vegetation, and biological materials such as tissue, bone, or shell, soils, rocks, sediments, coals, sludges, and(or) ashes. No one digestion or sample preparation method will be suitable for all of these matrices. The digestions typically employed at our laboratories include: (i) a closed-vessel microwave method using nitric acid and hydrogen peroxide, followed by digestion/dilution with a nitric acid/sodium dichromate solution, (ii) a robotic open test-tube digestion with nitric acid and sodium dichromate, (iii) a sealed Teflon? vessel with nitric acid and sodium dichromate, (iv) a sealed glass bottle with nitric acid and sodium dichromate, or (v) open test tube digestion with nitric and sulfuric acids and vanadium pentoxide. The common factor in all these digestions is that they are very oxidative to ensure the conversion of all mercury forms into Hg (II). Each method of digestion has its advantages and limitations. The method of detection used in our laboratories involves a combination of an in-house, custom, classic continuous-flow cold-vapor atomic absorption spectrometry (CVAAS), a commercially available, automated, flow-injection and a continuous flow cold-vapor atomic fluorescence spectrometry (CV-AFS) systems, and a relatively new, automated and integrated approach where solid or liquid samples are thermally decomposed under an oxygen atmosphere (a nitrogen atmosphere is used for coals) and the released mercury vapor trapped onto a gold gauze and then thermally released into an AAS system. Other less frequently used instrumental methods available for the determination of mercury include inductively coupled plasma ? optical emission spectrometry (ICP-OES), inductively couple plasma ? mass spectrometry (ICP-MS) (both solution nebulization and laser ablation), and instrumental neutron activation analysis (INAA). Results from two case studies involving the determination of mercury in the challenging matrices of biological materials will be presented. These will include fillet, liver and stomach-content samples from grayling for a baseline/background study in Alaska, and samples of meat tissue and shell material from Tanner crabs from Glacier Bay, Alaska. These studies show that the method of digestion is more important than a very sensitive detection limit for mercury.

Open-File Report↗

Fort Collins Science Center fiscal year 2010 science accomplishments

The scientists and technical professionals at the U.S. Geological Survey (USGS), Fort Collins Science Center (FORT), apply their diverse ecological, socioeconomic, and technological expertise to investigate complicated ecological problems confronting managers of the Nation's biological resources. FORT works closely with U.S. Department of the Interior (DOI) agency scientists, the academic community, other USGS science centers, and many other partners to provide critical information needed to help answer complex natural-resource management questions. In Fiscal Year 2010 (FY10), FORT's scientific and technical professionals conducted ongoing, expanded, and new research vital to the science needs and management goals of DOI, other Federal and State agencies, and nongovernmental organizations in the areas of aquatic systems and fisheries, climate change, data and information integration and management, invasive species, science support, security and technology, status and trends of biological resources (including the socioeconomic aspects), terrestrial and freshwater ecosystems, and wildlife resources, including threatened and endangered species. This report presents selected FORT science accomplishments for FY10 by the specific USGS mission area or science program with which each task is most closely associated, though there is considerable overlap. The report also includes all FORT publications and other products published in FY10, as well as staff accomplishments, appointments, committee assignments, and invited presentations.

Open-File Report↗

Streamflow and water-quality trends of the Rio Chama and Rio Grande, northern and central New Mexico, water years 1985 to 2002

The City of Albuquerque plans to divert San Juan-Chama Project water from the Rio Grande for potable water use. This report examines streamflow and water-quality trends in the Rio Chama and the Rio Grande for water years 1985 to 2002 following the implementation of reservoir storage agreements in northern and central New Mexico. Streamflow/water-quality stations used for this study include the Rio Grande stations of Taos, Otowi, San Felipe, and Albuquerque and the Rio Chama station of Chamita. Water years 1985 to 2002 were a period of larger than average precipitation and streamflow compared to the stations. historical averages. Annual precipitation and streamflow trended downward during the study period because of a drought during 1999 to 2002. Streamflow in the Rio Chama and Rio Grande was divided into three distinct seasonal periods that corresponded to natural and anthropogenic influences: fall/winter baseflow (November through February), snowmelt runoff (March through June), and the irrigation/monsoon (July through October) seasons. A calcium bicarbonate water type was evident at all study area stations on the Rio Chama and Rio Grande. Specific conductance increased downstream, but alkalinity and pH did not substantially change in the downstream direction. Nearly all nitrogen and phosphorous concentrations were less than 1 milligram per liter for all stations. Median trace-element concentrations and maximum radionuclide concentrations did not exceed drinking-water standards. Anthropogenic compounds were infrequently detected in the Rio Chama and Rio Grande, and concentrations did not exceed drinking-water standards. Water quality in the Rio Chama and Rio Grande varied spatially and temporally during water years 1985 to 2002. Specific conductance increased downstream in the Rio Grande during the fall/winter baseflow and snowmelt runoff seasons but was similar at the Taos, Otowi, and San Felipe stations during the irrigation/monsoon season. This similarity was a result of the release of stored water from Abiquiu Reservoir and Cochiti Lake, which masked the natural influences that increased specific conductance in the downstream direction during the other seasons. During all seasons, pH decreased and major ion concentrations remained stable at the Albuquerque station compared with the San Felipe station, but no single influence could be identified that caused these conditions. Manganese and uranium concentrations at the Otowi and San Felipe stations were largest during the fall/winter baseflow and smallest during the snowmelt runoff, indicating that ground-water inflows likely influenced these concentrations. Water-quality temporal trends were evaluated for selected constituents during the study period and during the individual seasons. Downward trends in major ion concentrations were similar in magnitude at the Taos and Otowi stations, indicating that an upstream influence and (or) the downward trend in annual precipitation was the main reason(s) for these trends. The stations most affected by reservoirs, Chamita and San Felipe, were the only stations at which downward trends in major ions were apparent for flow-adjusted concentrations but not for seasonally correlated low-adjusted concentrations, which indicates fewer seasonal differences at these stations due to reservoir operations.

Scientific Investigations Report↗

Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models

“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.

Ecography↗

Low-flow characteristics and regionalization of low-flow characteristics for selected streams in Arkansas

Water use in Arkansas has increased dramatically in recent years. Since 1990, the use of water for all purposes except power generation has increased 53 percent (4,004 cubic feet per second in 1990 to 6,113 cubic feet per second in 2005). The biggest users are agriculture (90 percent), municipal water supply (4 percent) and industrial supply (2 percent). As the population of the State continues to grow, so does the demand for the State’s water resources. The low-flow characteristics of a stream ultimately affect its utilization by humans. Specific information on the low-flow characteristics of streams is essential to State water-management agencies such as the Arkansas Department of Environmental Quality, the Arkansas Natural Resources Commission, and the Arkansas Game and Fish Commission when dealing with problems related to irrigation, municipal and industrial water supplies, fish and wildlife conservation, and dilution of waste. Low-flow frequency data are of particular value to management agencies responsible for the development and management of the State’s water resources. This report contains the low-flow characteristics for 70 active continuous-streamflow record gaging stations, 59 inactive continuous-streamflow record stations, and 101 partial-record gaging stations. These characteristics are the annual 7-day, 10-year low flow and the annual 7-day, 2-year low flow, and the seasonal, bimonthly, and monthly 7-day, 10-year low flow for the 129 active and inactive continuous-streamflow record and 101 partial-record gaging stations. Low-flow characteristics were computed on the basis of streamflow data for the period of record through September 2005 for the continuous-streamflow record and partial-record streamflow gaging stations. The low-flow characteristics of these continuous- and partial-record streamflow gaging stations were utilized in a regional regression analysis to produce equations for estimating the annual, seasonal, bimonthly, and monthly (November through April) 7-day, 10-year low flows and the annual 7-day, 2-year low flow for ungaged streams in the western two-thirds of Arkansas.

Arkansas↗

Guidelines for producing integrated 210Pb and 14C age-models

Accurate reconstructions of past environmental changes are crucial in paleoecological research and require reliable chronologies of sedimentary archives. Establishing robust age-models and obtaining the most appropriate proxies for analysis is a complex scientific endeavor, requiring extensive resources and collaboration among specialists, including radiochronologists. Radiometric dating methods, such as 210 Pb and radiocarbon ( 14 C), are frequently employed to establish chronologies in aquatic sedimentary deposits and peat bogs. In this study, we review key aspects of sampling, analysis, and the principles underlying 210 Pb and 14 C age-models, focusing on methods for developing robust joint chronologies for paleoenvironmental research. Drawing largely from the authors' experiences and group discussions during and after a scientific workshop in 2022, we discuss important considerations for site selection, sampling strategies, and radiometric dating to construct integrated 210 Pb and 14 C age-models. Using expert consensus, this group – called Paleostats – aims to provide a set of best practices for other geochronologists with this methods paper. Among our conclusions, we emphasize the importance of accounting for site-specific factors such as prior information on sedimentation rates to establish appropriate sampling and analytical strategies. The use of appropriate coring devices can minimize disturbance to sediments and ensure the core surface remains intact and preserved until sectioning. Where excess 210 Pb is expected, sectioning at intervals of ≤1 cm provides an adequate sampling resolution for 210 Pb dating. Exceptions are possible, allowing for ~2–3 cm sections in areas with confirmed high sedimentation rates (e.g., > 1 cm yr −1 ). Recovering deeper core sections for 14 C dating with sufficient overlap allows for accounting errors in depth estimates made in the field. Special attention is advised during time intervals where validation proxies, such as the human-made radionuclides 137 Cs or post-bomb 14 C, are expected, and to determine the depth of secular equilibrium between 210 Pb and 226 Ra. Radiocarbon analyses are commonly performed by accelerator mass spectrometry, and age models are constructed mainly using Bayesian statistics with Markov Chain Monte Carlo techniques (e.g., Bacon ). A Bayesian approach ( Plum ) is now available for producing 210 Pb age-models, which infers the 210 Pb ex flux, eliminates the need for selecting an equilibrium depth, and allows dating cores with incomplete 210 Pb ex inventory. Plum offers improved chronologies by integrating raw 210 Pb and 14 C data, and these age-models can be enriched with other dating methodologies, such as identifying tephras and other well-recorded historical events. Harmonized reporting would contribute to making radiometric age-models reproducible, which would benefit from an international effort. Using 210 Pb and 14 C to produce integrated age-models may yield better insights into the interplay between natural and recent anthropogenic forcings on ecosystems. This can enhance our understanding of environmental processes and their impacts on climate change, ultimately supporting science-based assessments and decisions.

Earth-Science Reviews↗

Beaver dam analogs did not improve beaver translocation outcomes in a desert river

Stream restoration programs employ beaver-related restoration techniques, including beaver translocations and installation of beaver dam analogs (BDA), to create complex in-stream habitat. We investigated whether BDA installations improved the probability of translocated beavers surviving and colonizing a section of a degraded desert river. We translocated beavers fitted with tracking devices to the Price River, Utah, United States, for 2 years before and after BDAs were installed. We monitored survival and site fidelity of beavers to estimate apparent survival ( φ ), using model selection to evaluate models with BDA, flow, and other factors hypothesized to relate to apparent survival. We found similar apparent survival 8 weeks post-release of pre-BDA ( φ = 0.50 ± 0.08 SE) and post-BDA beavers ( φ = 0.41 ± 0.06 SE). There were 15 predator-caused mortalities and 39 beavers emigrated out of the study site. Top models indicated apparent survival was negatively related to mean flow. Of the 70 BDAs constructed, beaver activity was detected on only two structures and the number of intact natural dams decreased due to monsoon floods. Our results suggest BDAs may not improve survival and site fidelity of translocated beavers in desert river systems. Instead, the dynamic flow of desert rivers and negative relationship between flow and apparent survival suggest the timing of release may be an important consideration for successful beaver translocation. Additional research is needed to understand how habitat, food availability, individual behavior, and resident conspecifics influence beaver translocation success.

Utah↗

A new process for organizing assessments of social, economic, and environmental outcomes: Case study of wildland fire management in the USA

Ecological risk assessments typically are organized using the processes of planning (a discussion among managers, stakeholders, and analysts to clarify ecosystem management goals and assessment scope) and problem formulation (evaluation of existing information to generate hypotheses about adverse ecological effects, select assessment endpoints, and develop an analysis plan). These processes require modification to be applicable for integrated assessments that evaluate ecosystem management alternatives in terms of their ecological, economic, and social consequences. We present 8 questions that define the steps of a new process we term integrated problem formulation (IPF), and we illustrate the use of IPF through a retrospective case study comparing 2 recent phases of development of the Fire Program Analysis (FPA) system, a planning and budgeting system for the management of wildland fire throughout publicly managed lands in the United States. IPF extends traditional planning and problem formulation by including the explicit comparison of management alternatives, the valuation of ecological, economic and social endpoints, and the combination or integration of those endpoints. The phase 1, limited-prototype FPA system used a set of assessment endpoints of common form (i.e., probabilities of given flame heights over acres of selected land-resource types), which were specified and assigned relative weights at the local level in relation to a uniform national standard. This approach was chosen to permit system-wide optimization of fire management budget allocations according to a cost-effectiveness criterion. Before full development, however, the agencies abandoned this approach in favor of a phase 2 system that examined locally specified (rather than system-optimized) allocation alternatives and was more permissive as to endpoint form. We demonstrate how the IPF process illuminates the nature, rationale, and consequences of these differences, and argue that its early use for the FPA system may have enabled a smoother development path.

Integrated Environmental Assessment and Management↗

Ground-water quality data in the Kern County Subbasin study unit, 2006— Results from the California GAMA Program

Ground-water quality in the approximately 3,000 square-mile Kern County Subbasin study unit (KERN) was investigated from January to March, 2006, as part of the Priority Basin Assessment Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Priority Basin Assessment project was developed in response to the Groundwater Quality Monitoring Act of 2001, and is being conducted by the California State Water Resources Control Board (SWRCB) in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory (LLNL). The Kern County Subbasin study was designed to provide a spatially unbiased assessment of raw (untreated) ground-water quality within KERN, as well as a statistically consistent basis for comparing water quality throughout California. Samples were collected from 50 wells within the San Joaquin Valley portion of Kern County. Forty-seven of the wells were selected using a randomized grid-based method to provide a statistical representation of the ground-water resources within the study unit. Three additional wells were sampled to aid in the evaluation of changes in water chemistry along regional ground-water flow paths. The ground-water samples were analyzed for a large number of man-made organic constituents (volatile organic compounds [VOCs], pesticides, and pesticide degradates), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), naturally occurring inorganic constituents (nutrients, major and minor ions, and trace elements), radioactive constituents, and microbial indicators. Naturally occurring isotopes (tritium, carbon-14, and stable isotopes of hydrogen, oxygen, nitrogen, and carbon) and dissolved noble gases also were measured to help identify the source and age of the sampled ground water. Quality-control samples (blanks, replicates, and laboratory matrix spikes) were collected and analyzed at approximately 10 percent of the wells, and the results for these samples were used to evaluate the quality of the data from the ground-water samples. Assessment of the quality-control information resulted in censoring of less than 0.4 percent of the data collected for ground-water samples. This study did not attempt to evaluate the quality of water delivered to consumers; after withdrawal from the ground, raw ground water typically is treated, disinfected, or blended with other waters to maintain acceptable water quality. Regulatory thresholds apply, not to the raw ground water, but to treated water that is served to the consumer. However, to provide some context for the results, concentrations of constituents measured in the raw ground water were compared with health-based thresholds established by the U.S. Environmental Protection Agency (USEPA) and the California Department of Public Health (CDPH), and as well as with thresholds established for aesthetic concerns (secondary maximum contaminant levels, SMCL-CA) by CDPH. VOCs and pesticides each were detected in approximately 60 percent of the grid wells, and detections of all compounds but one were below health-based thresholds. The fumigant, 1,2-dibromo-3-chloropropane (DBCP), was detected above the USEPA maximum contaminant level (MCL-US) in one sample. Detections of most inorganic constituents were also below health-based thresholds. Constituents detected above health-based thresholds include: nitrate, (MCL-US, 2 samples), arsenic (MCL-US, 2 samples), and vanadium (California notification level, NL-CA, 1 sample). All detections of radioactive constituents were below health-based thresholds, although nine samples had activities of radon-222 above the lower proposed MCL-US. Most of the samples from KERN wells had concentrations of major elements, total dissolved solids, and trace elements below the non-enforceable thresholds set for aesthetic concerns.

California↗

Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character

Fossil fuels from the Appalachian basin region have been major contributors to the Nation’s energy supplies over much of the last three centuries. Appalachian coal and petroleum resources are still available in sufficient quantities to contribute significantly to fulfilling the Nation’s energy needs. Although both conventional oil and gas continue to be produced in the Appalachian basin, most new wells in the region are drilled in shale reservoirs to produce natural gas. U.S. Geological Survey (USGS) Professional Paper 1708 is a modern, indepth collection of reports, cross sections, and maps that describe the geology of the Appalachian basin and its fossil fuel resources. This publication supplements and updates older USGS regional studies of Appalachian basin coal and petroleum resources. Some chapters are new, and several have been published in outside journals or as other USGS publications. Although this volume is not a comprehensive regional treatment of all notable geologic and fossil fuel localities in the Appalachian basin, the selected study areas and topics presented in the chapters pertain to large segments of the basin and a wide range of stratigraphic intervals. This volume discusses the locations of coal and petroleum accumulations, the stratigraphic and structural framework, and the geochemical characteristics of the coal beds and petroleum in the basin, as well as the results of recent USGS assessments of coal, oil, and gas resources in the basin. Many of the maps and accompanying data supporting the reports in this volume are available from chapter I.1 as downloadable geographic information system (GIS) data files about the characteristics of selected coal beds and oil and gas fields, locations of oil and gas wells, coal production, coal chemistry, total petroleum system (TPS) boundaries, and bedrock geology. Log ASCII Standard (LAS) files for geophysical (gamma ray) wireline well logs are included in other chapters. Professional Paper 1708 is intended primarily for geoscientists in academia, industry, and government who are interested in Appalachian basin geology and its coal and petroleum resources. Other users, however, may find the topics, papers, and digital images valuable for land-use and policy planning. Among the anticipated benefits of the report are improvements in (1) resource assessment estimates and methodology, (2) exploration strategies, (3) basin models, and (4) energy use policies.

Appalachian basin↗

Estimated dissolved-solids loads and trends at selected streams in and near the Uinta Basin, Utah, Water Years 1989–2013

The U.S. Geological Survey (USGS), in cooperation with the Colorado River Basin Salinity Control Forum, studied trends in dissolved-solids loads at selected sites in and near the Uinta Basin, Utah. The Uinta Basin study area includes the Duchesne River Basin and the Middle Green River Basin in Utah from below Flaming Gorge Reservoir to the town of Green River. Annual dissolved-solids loads for water years (WY) 1989 through 2013 were estimated for 16 gaging stations in the study area using streamflow and water-quality data from the USGS National Water Information System database. Eight gaging stations that monitored catchments with limited or no agricultural land use (natural subbasins) were used to assess loads from natural sources. Four gaging stations that monitored catchments with agricultural land in the Duchesne River Basin were used to assess loads from agricultural sources. Four other gaging stations were included in the dissolved-solids load and trend analysis to help assess the effects of agricultural areas that drain to the Green River in the Uinta Basin, but outside of the Duchesne River Basin. Estimated mean annual dissolved-solids loads for WY 1989–2013 ranged from 1,520 tons at Lake Fork River above Moon Lake, near Mountain Home, Utah (UT), to 1,760,000 tons at Green River near Green River, UT. The flow-normalized loads at gaging stations upstream of agricultural activities showed no trend or a relatively small change. The largest net change in modeled flow-normalized load was -352,000 tons (a 17.8-percent decrease) at Green River near Green River, UT. Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively. Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively. The flow-normalized dissolved-solids loads estimated at Duchesne River near Randlett, UT, and White River near Watson, UT, decreased by 68,000 and 55,300 tons, or 27.8 and 20.8 percent respectively, when comparing 1989 to 2013. The drainage basins for both rivers have undergone salinity-control projects since the early 1980s to reduce the dissolved-solids load entering the Colorado River. Approximately 19 percent of the net change in flow-normalized load at Green River at Green River, UT, is from changes in load modeled at Duchesne River near Randlett, UT, and 16 percent from changes in load modeled at White River near Watson, UT. The net change in flow-normalized load estimated at Green River near Greendale, UT, for WY 1989–2013 accounts for about 45 percent of the net change estimated at Green River at Green River, UT. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites in the Duchesne River Basin show that 75,400 tons or 44 percent of the load at the Duchesne River near Randlett, UT, gaging station was not accounted for at any of the upstream gages. Most of this unmonitored load is derived from tributary inflow, groundwater discharge, unconsumed irrigation water, and irrigation tail water. A mass balance of WY 1989–2013 flow-normalized loads estimated at sites in the Duchesne River Basin indicates that the flow-normalized load of unmonitored inflow to the Duchesne River between the Myton and Randlett gaging stations decreased by 38 percent. The total net decrease in flow-normalized load calculated for unmonitored inflow in the drainage basin accounts for 94 percent of the decrease in WY 1989–2013 flow-normalized load modeled at the Duchesne River near Randlett, UT, gaging station. Irrigation improvements in the drainage basin have likely contributed to the decrease in flow-normalized load. Reductions in dissolved-solids load estimated by the Natural Resources Conservation Service (NRCS) and the Bureau of Reclamation (Reclamation) from on- and off-farm improvements in the Uinta Basin totaled about 135,000 tons in 2013 (81,900 tons from on-farm improvements and 53,300 tons from off-farm improvements). The reduction in dissolved-solids load resulting from on- and off-farm improvements facilitated by the NRCS and Reclamation in the Price River Basin from 1989 to 2013 was estimated to be 64,800 tons. The amount of sprinkler-irrigated land mapped in the drainage area or subbasin area for a gaging station was used to estimate the reduction in load resulting from the conversion from flood to sprinkler irrigation. Sprinkler-irrigated land mapped in the Uinta Basin totaled 109,630 acres in 2012. Assuming conversion to wheel-line sprinklers, a reduction in dissolved-solids load in the Uinta Basin of 95,800 tons in 2012 was calculated using the sprinkler-irrigation acreage and a pre-salinity-control project dissolved-solids yield of 1.04 tons per acre. A reduction of 72,800 tons in dissolved-solids load from irrigation improvements was determined from sprinkler-irrigated lands in the Ashley Valley and Jensen, Pelican Lake, and Pleasant Valley areas (mapped in 2012); and in the Price River Basin (mapped in 2011). This decrease in dissolved-solids load is 8,800 tons more than the decrease in unmonitored flow-normalized dissolved-solids load (-64,000 tons) determined for the Green River between the Jensen and Green River gaging stations. The net WY 1989–2013 change in flow-normalized dissolved-solids load at the Duchesne River near Randlett, UT, and the Green River between the Jensen and Green River, UT, gaging stations determined from mass-balance calculations was compared to reported reductions in dissolved-solids load from on- and off-farm improvements and estimated reductions in load determined from mapped sprinkler-irrigated areas in the Duchesne River Basin and the area draining to the Green River between the Jensen and Green River gaging stations. The combined NRCS and Reclamation estimates of reduction in dissolved-solids load from on- and off-farm improvements in the study area (200,000 tons) is more than the reduction in load estimated using the acreage with sprinkler improvements (136,000 tons) or the mass-balance of flow-normalized load (132,000 tons).

Utah↗

Modeling habitat distribution from organism occurrences and environmental data: Case study using anemonefishes and their sea anemone hosts

We demonstrate the KGSMapper (Kansas Geological Survey Mapper), a straightforward, web-based biogeographic tool that uses environmental conditions of places where members of a taxon are known to occur to find other places containing suitable habitat for them. Using occurrence data for anemonefishes or their host sea anemones, and data for environmental parameters, we generated maps of suitable habitat for the organisms. The fact that the fishes are obligate symbionts of the anemones allowed us to validate the KGSMapper output: we were able to compare the inferred occurrence of the organism to that of the actual occurrence of its symbiont. Characterizing suitable habitat for these organisms in the Indo-West Pacific, the region where they naturally occur, can be used to guide conservation efforts, field work, etc.; defining suitable habitat for them in the Atlantic and eastern Pacific is relevant to identifying areas vulnerable to biological invasions. We advocate distinguishing between these 2 sorts of model output, terming the former maps of realized habitat and the latter maps of potential habitat. Creation of a niche model requires adding biotic data to the environmental data used for habitat maps: we included data on fish occurrences to infer anemone distribution and vice versa. Altering the selection of environmental variables allowed us to investigate which variables may exert the most influence on organism distribution. Adding variables does not necessarily improve precision of the model output. KGSMapper output distinguishes areas that fall within 1 standard deviation (SD) of the mean environmental variable values for places where members of the taxon occur, within 2 SD, and within the entire range of values; eliminating outliers or data known to be imprecise or inaccurate improved output precision mainly in the 2 SD range and beyond. Thus, KGSMapper is robust in the face of questionable data, offering the user a way to recognize and clean such data. It also functions well with sparse datasets. These features make it useful for biogeographic meta-analyses with the diverse, distributed datasets that are typical for marine organisms lacking direct commercial value. ?? Inter-Research 2006.

Marine Ecology Progress Series↗