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At least 253 records · Page 14Linked to original sources
USGS2022

San Francisco Estuary chlorophyll sensor and sample analysis intercomparison

This report presents an assessment of chlorophyll collection methods and anonymous results of field and laboratory comparisons in 2018 - 2019 by agencies in the San Francisco Estuary (SFE). The methods assessment and comparison exercises, with funding provided by the Delta Regional Monitoring Program and Bay Nutrient Management Strategy and in-kind contributions from participating agencies, are a first step to facilitate future comparisons and syntheses of data and inform best science practices in the region. In situ sonde comparison exercises found general agreement between two models of Yellow Springs Instrument (YSI) sensors, but the newer sensor (EXO v2 - total algae) measured higher chlorophyll fluorescence (fCHL) relative to the older YSI sensor (6-series 6025). Results may be attributed to the use of a two-point calibration and the fluorescence response of algal cultures in sensor development by the manufacturer. The laboratory comparison included participation by 12 distinct field - laboratory pairs (or groups), with one group analyzing filters using two analytical methods. Filters were collected in triplicate across three sampling events in 2018, and all sample results were pooled together. Results of statistical analyses indicated that nominal filter pore size, the grinding method associated with pigment extraction, and analytical methods do not introduce variability to the chlorophyll-a measurement (Chl-a). When Chl-a results were assessed by sample event, however, significant differences between nominal pore size and analytical methods existed; these differences could be attributed to the small sample size per event. Consistent reporting units and high-concentration calibration standards for field sensors among data collection agencies would improve the consistency and comparability of data collected in the SFE. More routine split sampling events, longer term sensor comparison exercises, and further processing and analytical comparisons that control for individual filterers may also enhance comparability in the region.

California↗
USGS2000

Sampling for mercury at subnanogram per litre concentrations for load estimation in rivers

Estimation of constituent loads in streams requires collection of stream samples that are representative of constituent concentrations, that is, composites of isokinetic multiple verticals collected along a stream transect. An all-Teflon isokinetic sampler (DH-81) cleaned in 75??C, 4 N HCl was tested using blank, split, and replicate samples to assess systematic and random sample contamination by mercury species. Mean mercury concentrations in field-equipment blanks were low: 0.135 ng??L-1 for total mercury (??Hg) and 0.0086 ng??L-1 for monomethyl mercury (MeHg). Mean square errors (MSE) for ??Hg and MeHg duplicate samples collected at eight sampling stations were not statistically different from MSE of samples split in the laboratory, which represent the analytical and splitting error. Low fieldblank concentrations and statistically equal duplicate- and split-sample MSE values indicate that no measurable contamination was occurring during sampling. Standard deviations associated with example mercury load estimations were four to five times larger, on a relative basis, than standard deviations calculated from duplicate samples, indicating that error of the load determination was primarily a function of the loading model used, not of sampling or analytical methods.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2023

Wide-area debris field and seabed characterization of a deep ocean dump site surveyed by autonomous underwater vehicles

Disposal of industrial and hazardous waste in the deep ocean was a pervasive global practice near coastlines in the 20th century. Uncertainty in the quantity, location, and contents of dumped materials at historical disposal sites underscores ongoing risks to marine ecosystems and human health. This study presents analysis of a 150-km2 wide-area sidescan sonar survey conducted in March 2021 with two autonomous underwater vehicles (AUVs) at an offshore dumpsite in San Pedro Basin, California. Previous camera surveys located 60 barrels and other debris; sediment analysis in the region showed varying concentrations of the insecticidal chemical Dichlorodiphenyl-trichloroethane (DDT), for which an estimated 350-700 metric tons was discarded in the San Pedro Basin between 1947 and 1961. A lack of primary historical documents from Montrose Chemical or California Salvage Company that specify the DDT acid waste disposal method has contributed to the ambiguity surrounding whether the dumping method was via bulk discharge or containerized units. Barrels and debris visually detected during previous surveys by Remotely Operated Vehicles (ROVs) Jason and SuBastian and AUV Sentry served as the basis for ground truth testing and object classification using size and acoustic intensity characteristics. Target detection and classification algorithms were developed using image and signal processing techniques that resulted in the identification of over 74,000 debris targets within the survey region. Statistical, spectral, and machine learning techniques are used to characterize seabed variability and for bottom-type classification. These analytical techniques combined with the survey capabilities of AUVs provide a framework for efficient mapping and characterization of uncharted deep-water disposal sites.

California↗
USGS2026

Bottom-up characterization of geologic methane emissions in the San Juan Basin in the southwestern USA

Methane is a potent greenhouse gas that plays an important role in atmospheric chemistry and global warming. The current global methane budget has large uncertainties, and a better understanding of the budget would help to guide strategies for reducing anthropogenic emissions to fight climate change. Natural geologic methane emissions are a particularly poorly constrained source, with top-down estimates from 14 C in ice cores suggesting much lower geologic emissions than bottom-up scaling of direct flux measurements. Our study aims to contribute to resolving this discrepancy through improved bottom-up characterization of geologic methane seepage in the San Juan Basin in southwestern Colorado and northwestern New Mexico, USA. We performed 983 new flux chamber measurements in this basin during summer 2022 and winter 2023 field campaigns. Our results, in combination with prior measurements, suggest that natural seepage in the San Juan Basin only occurs on or near the Fruitland coal outcrop. Specifically, our new measurements confirm previous measurements of seepage along the northwestern exposure of the Fruitland outcrop in Colorado (a known hydrodynamic overpressure region) and for the first time, identified seepage locations along the southernmost Fruitland outcrop exposure in New Mexico, in association with a coal cleat and a fault. Overall, seepage along the Fruitland coal outcrop is heterogeneously distributed, with both positive and negative (interpreted as microbial soil sink) methane fluxes. Features that are hypothesized to be predictive of seepage (e.g., faults) were not associated with positive methane fluxes in areas outside of the Fruitland outcrop. Our best estimate for total geologic methane seepage in the San Juan Basin from spatial interpolation and statistical upscaling is approximately 0.14 Tg CH 4 /yr, with a range from 0.029 to 0.48 Tg CH 4 /yr. This best-estimate value is lower than a previous bottom-up estimate from a gridded seepage inventory, but higher than a previous top-down estimate.

Colorado, New Mexico↗
USGS1999

Characterization of branch complexity by fractal analyses and detect plant functional adaptations

The comparison between complexity in the sense of space occupancy (box-counting fractal dimension Dc and information dimension DI ) and heterogeneity in the sense of space distribution (average evenness index and evenness variation coefficient JCV) were investigated in mathematical fractal objects and natural branch ¯ J structures. In general, increased fractal dimension was paired with low heterogeneity. Comparisons between branch architecture in Anthyllis cytisoides under different slope exposure and grazing impact revealed that branches were more complex and more homogeneously distributed for plants on northern exposures than southern, while grazing had no impact during a wet year. Developmental instability was also investigated by the statistical noise of the allometric relation between internode length and node order. In conclusion, our study demonstrated that fractal dimension of branch structure can be used to analyze the structural organization of plants, especially if we consider not only fractal dimension but also shoot distribution within the canopy (lacunarity). These indexes together with developmental instability analyses are good indicators of growth responses to the environment.

International Journal of Plant Sciences↗
USGS2016

Towards simplification of hydrologic modeling: Identification of dominant processes

The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

Hydrology and Earth System Sciences↗
USGS2013

Thermal tolerance of meltwater stonefly Lednia tumana nymphs from an alpine stream in Waterton–Glacier International Peace Park, Montana, USA

Global climate change threatens to affect negatively the structure, function, and diversity of aquatic ecosystems worldwide. In alpine systems, the thermal tolerances of stream invertebrates can be assessed to understand better the potential effects of rising ambient temperatures and continued loss of glaciers and snowpack on alpine stream ecosystems. We measured the critical thermal maximum (CTM) and lethal temperature maximum (LTM) of the meltwater stonefly ( Lednia tumana ), a species limited to glacial and snowmelt-driven alpine streams in the Waterton–Glacier International Peace Park area and a candidate for listing under the US Endangered Species Act. We collected L. tumana nymphs from Lunch Creek in Glacier National Park, Montana (USA) and transported them to a laboratory at the University of Montana Flathead Lake Biological Station, Polson, Montana. We placed nymphs in a controlled water bath at 1 of 2 acclimation temperatures, 8.5 and 15°C. We increased water temperature at a constant rate of 0.3°C/min. We calculated the average CTM and LTM (± SD) for each acclimation temperature and compared them with Student’s t-tests. Predicted chronic temperature maxima were determined using the ⅓ rule. Mean LTMs were 32.3 ± 0.28°C and 31.05 ± 0.78°C in the 8.5 and 15°C acclimation treatments, respectively. CTM and LTM metrics were lower in the 15 than in the 8.5°C acclimation treatment, but these differences were not statistically significant (p > 0.05). The predicted chronic temperature maxima were 20.6 and 20.2°C for the 8.5 and 15°C acclimation treatments, respectively. More research is needed on the effects of chronic exposures to rising stream temperatures, but our results can be used to assess the potential effects of warming water temperatures on L. tumana and other aquatic macroinvertebrates in alpine ecosystems.

Montana↗
USGS2014

Annual flood sensitivities to El Niño-Southern Oscillation at the global scale

Floods are amongst the most dangerous natural hazards in terms of economic damage. Whilst a growing number of studies have examined how river floods are influenced by climate change, the role of natural modes of interannual climate variability remains poorly understood. We present the first global assessment of the influence of El Niño–Southern Oscillation (ENSO) on annual river floods, defined here as the peak daily discharge in a given year. The analysis was carried out by simulating daily gridded discharges using the WaterGAP model (Water – a Global Assessment and Prognosis), and examining statistical relationships between these discharges and ENSO indices. We found that, over the period 1958–2000, ENSO exerted a significant influence on annual floods in river basins covering over a third of the world's land surface, and that its influence on annual floods has been much greater than its influence on average flows. We show that there are more areas in which annual floods intensify with La Niña and decline with El Niño than vice versa. However, we also found that in many regions the strength of the relationships between ENSO and annual floods have been non-stationary, with either strengthening or weakening trends during the study period. We discuss the implications of these findings for science and management. Given the strong relationships between ENSO and annual floods, we suggest that more research is needed to assess relationships between ENSO and flood impacts (e.g. loss of lives or economic damage). Moreover, we suggest that in those regions where useful relationships exist, this information could be combined with ongoing advances in ENSO prediction research, in order to provide year-to-year probabilistic flood risk forecasts.

Hydrology and Earth System Sciences↗
USGS2024

Aftershock forecasting

Aftershocks can compound the impacts of a major earthquake, disrupting recovery efforts and potentially further damaging weakened buildings and infrastructure. Forecasts of the probability of aftershocks can therefore aid decision-making during earthquake response and recovery. Several countries issue authoritative aftershock forecasts. Most aftershock forecasts are based on simple statistical models that were first developed in the 1980s and remain the best available models. We review these statistical models, and the wide-ranging research to advance aftershock forecasting through better statistical, physical, and machine learning methods. Physics-based forecasts based on mainshock stress changes can sometimes match the statistical models in testing, but don’t yet outperform them. Physical models are also hampered by unsolved problems such as the mechanics of dynamic triggering and the influence of background conditions. Initial work on machine learning forecasts shows promise, and new machine learning earthquake catalogs provide an opportunity to advance all types of aftershock forecasts.

Annual Review of Earth and Planetary Sciences↗
USGS2010

Land-cover change in the Ozark Highlands, 1973-2000

Led by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land-Cover Trends Project was initiated in 1999 and aims to document the types, geographic distributions, and rates of land-cover change on a region by region basis for the conterminous United States, and to determine some of the key drivers and consequences of the change (Loveland and others, 2002). For 1973, 1980, 1986, 1992, and 2000 land-cover maps derived from the Landsat series are classified by visual interpretation, inspection of historical aerial photography and ground survey, into 11 land-cover classes. The classes are defined to capture land cover that is discernable in Landsat data. A stratified probability-based sampling methodology undertaken within the 84 Omernik Level III Ecoregions (Omernik, 1987) was used to locate the blocks, with 9 to 48 blocks per ecoregion. The sampling was designed to enable a statistically robust 'scaling up' of the sample-classification data to estimate areal land-cover change within each ecoregion (Loveland and others, 2002; Stehman and others, 2005). At the time of writing, approximately 90 percent of the 84 conterminous United States ecoregions have been processed by the Land-Cover Trends Project. Results from these completed ecoregions illustrate that across the conterminous United States there is no single profile of land-cover/land-use change, rather, there are varying pulses affected by clusters of change agents (Loveland and others, 2002). Land-Cover Trends Project results for the conterminous United States to-date are being used for collaborative environmental change research with partners such as; the National Science Foundation, the National Oceanic and Atmospheric Administration, and the U.S. Fish and Wildlife Service. The strategy has also been adapted for use in a NASA global deforestation initiative, and elements of the project design are being used in the North American Carbon Program's assessment of forest disturbance.

Open-File Report↗
USGS2008

Multi-proxy evidence for Late Pleistocene-Holocene climatic and environmental changes in Lop-Nur, Xinjiang, Northwest China

A 10.35-m-long sediment core from the Luobei depression in Lop-Nur, Xinjiang, Northwest China, provides detailed information about environmental changes during the Late Pleistocene. The samples taken every 5 cm of the core were analyzed for 10 environmental proxies, including magnetic susceptibility, granularity, chroma, carbonate and loss on ignition (LOI), and pH value. The chronology data are provided by the uranium/thorium disequilibrium dates. The sediments of the section were deposited during the last 32000 years. The results of analysis of 10 proxies were examined using multivariate statistical analysis, and the principal components were calculated. According to the results, the Late Pleistocene sequence contains four climatic and environmental stages appearing in the cycles of cold-wet and warm-dry changes. During 10-9 ka BP, it was the earliest warm episode in the Holocene. Environmental changes in this district were restricted by global change, as suggested by the analysis of glacial-interglacial cycles. But it was different from the mutative trend of a monsoon region in East China because of its own characteristics, which was the situation of cold-wet and warm-dry climate-environment change. The candidate reason may be the uplift of the Tibet Plateau and the westerly wind circulation. ?? Science Press, Institute of Geochemistry, CAS and Springer-Verlag GmbH 2008.

Chinese Journal of Geochemistry↗
USGS2026

Microplastics undergo fragmentation during pressurized membrane filtration

Low-micrometer microplastics (<10 μm) have been detected in drinking water, driving growing interest in using pressure-driven membrane filtration to remove these particles and ensure drinking water safety. However, little attention is paid to the fate of microplastics concentrated in the filtration byproduct. In this study, using well-defined polystyrene (PS) and poly(methyl methacrylate) microspheres as model particles, we observed microplastic fragmentation during nanofiltration and the subsequent release of smaller fragments. After operating for 3 h at 20 bar, 67.9 ± 8.0% of the PS spheres in the concentrate, based on particles counted in selected fields of view, were transformed into fractured particles. The characteristic Raman band signals of microplastics were significantly weakened after fragmentation, leading to detection challenges. To address this, a data processing algorithm was developed to identify PS fragments as small as 1 μm. Preliminary statistical analysis reveals that within the tested pressure range, operation time has a stronger influence on fragmentation than pressure magnitude alone and that fragmentation is further governed by the intrinsic mechanical properties of the tested model polymers. This work provides direct evidence that pressure-driven membrane processes induce microplastic fragmentation and highlights the environmental risks associated with the discharge of fragmented microplastics into the concentrate.

Environmental Science & Technology Letters↗
USGS2013

Sediment transport measurements

Sediment erosion, transport, and deposition in fluvial systems are complex processes that are treated in detail in other sections of this book. Development of methods suitable for the collection of data that contribute to understanding these processes is a still-evolving science. Sediment and ancillary data are fundamental requirements for the proper management of river systems, including the design of structures, the determination of aspects of stream behavior, ascertaining the probable effect of removing an existing structure, estimation of bulk erosion, transport, and sediment delivery to the oceans, ascertaining the long-term usefulness of reservoirs and other public works, tracking movement of solid-phase contaminants, restoration of degraded or otherwise modified streams, and assistance in the calibration and validation of numerical models. This chapter presents techniques for measuring bed-material properties and suspended and bed-load discharges. Well-established and relatively recent, yet adequately tested, sampling equipment and methodologies, with designs that are guided by sound physical and statistical principles, are described. Where appropriate, the theory behind the development of the equipment and guidelines for its use are presented.

Book chapter↗
USGS2018

Performance metrics for the assessment of satellite data products: An ocean color case study

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r 2 ), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multi-metric and user-dependent approach that can be applied within science, modeling, and resource management communities.

Optics Express↗
USGS2017

Translating statistical species-habitat models to interactive decision support tools

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

PLoS ONE↗
USGS2022

Targeted and non-targeted analysis of young-of-year smallmouth bass using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry

Smallmouth bass in the Susquehanna River Basin, Chesapeake Bay Watershed, USA, have been exhibiting clinical signs of disease and reproductive endocrine disruption (e.g., intersex, male plasma vitellogenin) for over fifteen years. Previous histological and targeted chemical analyses have identified infectious agents and pollutants in fish tissues including organic contaminants, mercury, and perfluorinated compounds, but a common causative link for the observed signs of disease across this widespread area has not been determined. This study examines 146 young-of-year smallmouth bass collected from 14 sampling sites in the Susquehanna River Basin, Pennsylvania, USA with varying levels of disease prevalence. Whole fish were extracted by a recently developed modification to the quick, easy, cheap, effective, rugged, and safe extraction method and analyzed by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry. A targeted analysis was conducted to identify the presence and quantity of 127 known contaminants, including polychlorinated biphenyls, brominated diphenyl ethers, organochlorinated pesticides, and pharmaceutical and personal care products. A non-targeted analysis was conducted on the same data set to identify analytes of interest not included on routine target compound lists. Chromatographic alignment through Statistical Compare (ChromaTOF GC) was followed by Fisher ratio and principal component analysis to reduce the data set from thousands of peaks per sample to a final data set of 65 analytes of interest. Comparisons of these 65 compounds between Normal (no observed health anomalies) and Lesioned (observed health anomaly at time of collection) fish revealed increased levels of three chemical families in Lesioned fish including esters, ketones, and nitrogen containing compounds.

Chesapeake Bay watershed, Susquehanna River basin↗
USGS2012

Applications of fluorescence spectroscopy for predicting percent wastewater in an urban stream

Dissolved organic carbon (DOC) is a significant organic carbon reservoir in many ecosystems, and its characteristics and sources determine many aspects of ecosystem health and water quality. Fluorescence spectroscopy methods can quantify and characterize the subset of the DOC pool that can absorb and re-emit electromagnetic energy as fluorescence and thus provide a rapid technique for environmental monitoring of DOC in lakes and rivers. Using high resolution fluorescence techniques, we characterized DOC in the Tualatin River watershed near Portland, Oregon, and identified fluorescence parameters associated with effluent from two wastewater treatment plants and samples from sites within and outside the urban region. Using a variety of statistical approaches, we developed and validated a multivariate linear regression model to predict the amount of wastewater in the river as a function of the relative abundance of specific fluorescence excitation/emission pairs. The model was tested with independent data and predicts the percentage of wastewater in a sample within 80% confidence. Model results can be used to develop in situ instrumentation, inform monitoring programs, and develop additional water quality indicators for aquatic systems.

Oregon↗
USGS2001

A comparative assessment of contaminants in fish from four resacas of the Texas, USA-Tamaulipas, Mexico border region

A recent survey of contaminant information for the Lower Rio Grande Valley (LRGV), Texas, has shown that little is known about contaminants and their impacts on biota of resacas (oxbows) along the US-Mexico border. In 1996, fish were collected from four resacas in the Texas- Tamaulipas border region to assess contaminant loadings and their impacts on fish and birds. Tissue residue concentrations in fish were analyzed and also compared to two histopathological bioindicators of unhealthy environmental conditions. Of the organochlorine insecticides measured, DDE was the most common and was present at relatively high concentrations (10 ??g/g w/w) at some sites. DDE concentrations were nearly 20 times greater in fish from resacas in Texas than from resacas in Tamaulipas, although the limited sample sizes obtained precluded statistical comparisons. DDE concentrations in fish from the two Texas resacas were also greater than those reported in fish from nearby areas during the 1980s and 1990s. Most trace element concentrations were similar among resacas from Texas and Tamaulipas. Arsenic, however, was two to six times greater in fish from a downtown resaca in Matamoros than in fish from other resacas in Tamaulipas and Texas. The bioindicators, pigment accumulation, and macrophage aggregates (MAs), in general, reflected the contamination indicated by the tissue residues for each site. Overall, it appears that some resacas of the US-Mexico border region are contaminant sinks and could pose potential health or reproductive problems for fish and wildlife, and humans that consume fish from those sites. Published by Elsevier Science Ltd.

Environment International↗