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At least 577 records · Page 32Linked to original sources

USGS2007

Predicting the next storm surge flood

The Virginia Institute of Marine Science (VIMS), National Weather Services (NWS) Sterling and Wakefield, Weather Forecast Offices (WFO), and the Chesapeake Bay Observing System (CBOS) jointly developed a prototype system of a regional capability to address national problem. The system was developed to integrate high-resolution atmospheric and hydrodynamic and storm surge models, evaluate the ability of the prototype to predict land inundation in the Washington, D.C., and provide flooding results to Emergency Managers (EM) using portive. The system is a potential tool for NWS WFOs to provide support to the EMs, first in the Chesapeake Bay region and then in other coastal regions by applying similar approaches in other coastal and Great Lakes regions. The Chesapeake Inundation Prediction System (CIPS) also is building on the initial prototype to predict the combined effects of storm surge and tidal and river flow inundation in the Chesapeake Bay and its tributaries.

Sea Technology↗

USGS2001

A geostatistical approach to predicting sulfur content in the Pittsburgh coal bed

The US Geological Survey (USGS) is completing a national assessment of coal resources in the five top coal-producing regions in the US. Point-located data provide measurements on coal thickness and sulfur content. The sample data and their geologic interpretation represent the most regionally complete and up-to-date assessment of what is known about top-producing US coal beds. The sample data are analyzed using a combination of geologic and Geographic Information System (GIS) models to estimate tonnages and qualities of the coal beds. Traditionally, GIS practitioners use contouring to represent geographical patterns of "similar" data values. The tonnage and grade of coal resources are then assessed by using the contour lines as references for interpolation. An assessment taken to this point is only indicative of resource quantity and quality. Data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the sample data. To develop a quantitative approach, geostatistics were applied to the data on coal sulfur content from samples taken in the Pittsburgh coal bed (located in the eastern US, in the southwestern part of the state of Pennsylvania, and in adjoining areas in the states of Ohio and West Virginia). Geostatistical methods that account for regional and local trends were applied to blocks 2.7 mi (4.3 km) on a side. The data and geostatistics support conclusions concerning the average sulfur content and its degree of reliability at regional- and economic-block scale over the large, contiguous part of the Pittsburgh outcrop, but not to a mine scale. To validate the method, a comparison was made with the sulfur contents in sample data taken from 53 coal mines located in the study area. The comparison showed a high degree of similarity between the sulfur content in the mine samples and the sulfur content represented by the geostatistically derived contours. Published by Elsevier Science B.V.

International Journal of Coal Geology↗

USGS2012

MERGANSER: an empirical model to predict fish and loon mercury in New England lakes

MERGANSER (MERcury Geo-spatial AssessmeNtS for the New England Region) is an empirical least-squares multiple regression model using mercury (Hg) deposition and readily obtainable lake and watershed features to predict fish (fillet) and common loon (blood) Hg in New England lakes. We modeled lakes larger than 8 ha (4404 lakes), using 3470 fish (12 species) and 253 loon Hg concentrations from 420 lakes. MERGANSER predictor variables included Hg deposition, watershed alkalinity, percent wetlands, percent forest canopy, percent agriculture, drainage area, population density, mean annual air temperature, and watershed slope. The model returns fish or loon Hg for user-entered species and fish length. MERGANSER explained 63% of the variance in fish and loon Hg concentrations. MERGANSER predicted that 32-cm smallmouth bass had a median Hg concentration of 0.53 μg g -1 (root-mean-square error 0.27 μg g -1 ) and exceeded EPA's recommended fish Hg criterion of 0.3 μg g -1 in 90% of New England lakes. Common loon had a median Hg concentration of 1.07 μg g -1 and was in the moderate or higher risk category of >1 μg g -1 Hg in 58% of New England lakes. MERGANSER can be applied to target fish advisories to specific unmonitored lakes, and for scenario evaluation, such as the effect of changes in Hg deposition, land use, or warmer climate on fish and loon mercury.

New England↗

USGS2016

Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail

Stable hydrogen isotope (δD) methods for tracking animal movement are widely used yet often produce low resolution assignments. Incorporating prior knowledge of abundance, distribution or movement patterns can ameliorate this limitation, but data are lacking for most species. We demonstrate how observations reported by citizen scientists can be used to develop robust estimates of species distributions and to constrain δD assignments. We developed a Bayesian framework to refine isotopic estimates of migrant animal origins conditional on species distribution models constructed from citizen scientist observations. To illustrate this approach, we analysed the migratory connectivity of the Virginia rail Rallus limicola , a secretive and declining migratory game bird in North America. Citizen science observations enabled both estimation of sampling bias and construction of bias-corrected species distribution models. Conditioning δD assignments on these species distribution models yielded comparably high-resolution assignments. Most Virginia rails wintering across five Gulf Coast sites spent the previous summer near the Great Lakes, although a considerable minority originated from the Chesapeake Bay watershed or Prairie Pothole region of North Dakota. Conversely, the majority of migrating Virginia rails from a site in the Great Lakes most likely spent the previous winter on the Gulf Coast between Texas and Louisiana. Synthesis and applications . In this analysis, Virginia rail migratory connectivity does not fully correspond to the administrative flyways used to manage migratory birds. This example demonstrates that with the increasing availability of citizen science data to create species distribution models, our framework can produce high-resolution estimates of migratory connectivity for many animals, including cryptic species. Empirical evidence of links between seasonal habitats will help enable effective habitat management, hunting quotas and population monitoring and also highlight critical knowledge gaps.

Journal of Applied Ecology↗

USGS2024

Signatures of wave erosion in Titan’s coasts

The shorelines of Titan’s hydrocarbon seas trace flooded erosional landforms such as river valleys; however, it is unclear whether coastal erosion has subsequently altered these shorelines. Spacecraft observations and theoretical models suggest that wind may cause waves to form on Titan’s seas, potentially driving coastal erosion, but the observational evidence of waves is indirect, and the processes affecting shoreline evolution on Titan remain unknown. No widely accepted framework exists for using shoreline morphology to quantitatively discern coastal erosion mechanisms, even on Earth, where the dominant mechanisms are known. We combine landscape evolution models with measurements of shoreline shape on Earth to characterize how different coastal erosion mechanisms affect shoreline morphology. Applying this framework to Titan, we find that the shorelines of Titan’s seas are most consistent with flooded landscapes that subsequently have been eroded by waves, rather than a uniform erosional process or no coastal erosion, particularly if wave growth saturates at fetch lengths of tens of kilometers.

Science Advances↗

USGS2026

Correcting a systematic bias in an ocean drilling project site 882 alkenone sea surface temperature record

Reconstructions of sea surface temperature (SST) in the geologic record are fundamental to our understanding of Earth's climate history and the evaluation of Earth's climate sensitivity to greenhouse gas forcing. SSTs are reconstructed with a variety of methods, including alkenone biomarker lipids produced by certain coccolithophore algae. One such alkenone SST reconstruction from the subpolar northwest Pacific Ocean Drilling Program (ODP) Site 882 (50.21° N, 167.35° E, 3244 m water depth) has played a large role in shaping the paleoclimate science community's view of global climate warmth during the Late Pliocene (3.6–2.6 million years ago) and the subsequent cooling that characterized the intensification of Northern Hemisphere Glaciation (Haug, 1995; Haug et al., 2005; Martínez-Garcia et al., 2010). First, we have found that the values reported in the PANGAEA archive for this ODP Site 882 alkenone dataset were inaccurately reported as U K' 37 values when they are instead U K 37 ( https://doi.org/10.1594/PANGAEA.315092 , Haug and Sarnthein, 2005). This error in the archived data table resulted in the incorporation of inaccurate absolute SST estimates by several studies that applied U K' 37 calibrations to this ODP Site 882 dataset (e.g., Brennan et al., 2022; Clark et al., 2024, 2025; Tierney et al., 2019, 2025b). Second, using other published data from ODP Site 882 (Studer et al., 2012) and nearby Site 883 (51.11° N, 167.46° E, 2384 m water depth; Herbert et al., 2016; Novak et al., 2024), we show that the original Haug (1995) alkenone SST record at ODP Site 882 systematically reports an amplified range of absolute SST values compared to the more recently generated data. This observation is consistent with the known concentration-dependent biases of the gas chromatography chemical ionization mass spectrometry (GC-CI-MS) analytical method used by the original ODP Site 882 study (Chaler et al., 2000, 2003; Haug, 1995; Hefter, 2008; Rosell-Mele et al., 1995). These concentration-dependent analytical biases complicate applying a uniform correction to the entire Haug (1995) dataset. However, we are able to leverage the published datasets to propose a correction and quantification of uncertainty for a subset of the Haug (1995) dataset measured at similar on-column analyte abundance. For these samples, we find an average analytical uncertainty equivalent to ±2.05 °C , which is greater than and in addition to the typical ±1.4 °C 1 σ prediction uncertainty of the U K' 37 sea surface temperature proxy. We then discuss the implications of the corrected dataset for our understanding of late Neogene and Quaternary climate in the Kuroshio Extension region.

Climate of the Past↗

USGS1998

Bacterial methylmercury degradation in Florida Everglades peat sediment

Methylmercury (MeHg) degradation was investigated along an eutrophication gradient in the Florida Everglades by quantifying 14 CH 4 and 14 CO 2 production after incubation of anaerobic sediments with [ 14 C]MeHg. Degradation rate constants ( k ) were consistently ≤0.1 d - 1 and decreased with sediment depth. Higher k values were observed when shorter incubation times and lower MeHg amendment levels were used, and k increased 2-fold as in-situ MeHg concentrations were approached. The average floc layer k was 0.046 ± 0.023 d - 1 ( n = 17) for 1−2 day incubations. In-situ degradation rates were estimated to be 0.02−0.5 ng of MeHg (g of dry sediment) - 1 d - 1 , increasing from eutrophied to pristine areas. Nitrate-respiring bacteria did not demethylate MeHg, and NO 3 - addition partially inhibited degradation in some cases. MeHg degradation rates were not affected by PO 4 3 - addition. 14 CO 2 production in all samples indicated that oxidative demethylation (OD) was an important degradation mechanism. OD occurred over 5 orders of magnitude of applied MeHg concentration, with lowest limits [1−18 ng of MeHg (g of dry sediment) - 1 ] in the range of in-situ MeHg levels. Sulfate reducers and methanogens were the primary agents of anaerobic OD, although it is suggested that methanogens dominate degradation at in-situ MeHg concentrations. Specific pathways of OD by these two microbial groups are proposed.

Florida↗

USGS2011

New strategy needed in earthquake, volcano monitoring

Recent advances in space geodesy provide unprecedented opportunities for measuring and understanding processes related to earthquake occurrence and volcanic eruptions in the United States and elsewhere. The Global Positioning System (GPS) uses Earth-orbiting satellites to obtain relative movements of ground points accurate to a few millimeters, either through periodically repeated surveys or by continuous measurements at permanent sites [ Segall and Davis , 1997]. Satellite interferometric synthetic aperture radar (InSAR) uses repeat-pass radar backscatter images of Earth's surface to obtain complete spatial mappings of surface deformation over 100 km × 100 km scenes to centimeter precision [ Massonnet and Feigl , 1998]. During the past 5 years GPS and InSAR increasingly have been applied to local studies of active fault zones and volcanic systems, imaging the sources of deformation buried in Earth's crust and quantifying the hazards they pose to society. The potential now exists to deploy these tools to map and monitor all of the actively deforming western United States, and a new scientific initiative with these goals is under active discussion [ Silver et al , 1998].

Eos Science News↗

USGS2022

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

Colorado↗

USGS2025

Mitigation of human cognitive bias in volcanic eruption forecasting

Modern operational eruption forecasting methods rely heavily on human judgment in the face of uncertainty and are thus susceptible to myriad cognitive biases and errors by the scientist-forecasters. Recent developments in the behavioral sciences have elucidated cognitive biases across a wide spectrum of human behaviors and found ways to mitigate them. These insights have led to significant gains in human forecast accuracy across a range of disciplines. However, such gains have yet to widely penetrate volcanic eruption forecasting efforts. In this study, we review recent progress in these fields as relevant to improving current eruption forecasting methods as practiced by volcano observatories worldwide. We group cognitive biases into 1) information and selection biases, 2) group effects and social-emotional biases, and 3) framing and decision biases and highlight the numerous places in which these biases may permeate eruption forecasts. We present a framework for improving group discussion and forecasting processes at volcano observatories, considering recent gains from behavioral sciences along with a mitigation checklist to effectively reduce bias in operational eruption forecasts. Finally, we present an updated forecasting methodology for use in our own group, the US Geological Survey (USGS) Volcano Disaster Assistance Program, based on previous “multiple datasets” methods, that includes clear and deliberate efforts to minimize cognitive biases and thus improve eruption forecasting accuracy.

Journal of Applied Volcanology↗

USGS2007

Global Data Toolset (GDT)

According to the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) approximately 60 percent of the data contained in the World Database on Protected Areas (WDPA) has missing or incomplete boundary information. As a result, global analyses based on the WDPA can be inaccurate, and professionals responsible for natural resource planning and priority setting must rely on incomplete geospatial data sets. To begin to address this problem the World Data Center for Biodiversity and Ecology, in cooperation with the U. S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC), the National Biological Information Infrastructure (NBII), the Global Earth Observation System, and the Inter-American Biodiversity Information Network (IABIN) sponsored a Protected Area (PA) workshop in Asuncion, Paraguay, in November 2007. The primary goal of this workshop was to train representatives from eight South American countries on the use of the Global Data Toolset (GDT) for reviewing and editing PA data. Use of the GDT will allow PA experts to compare their national data to other data sets, including non-governmental organization (NGO) and WCMC data, in order to highlight inaccuracies or gaps in the data, and then to apply any needed edits, especially in the delineation of the PA boundaries. In addition, familiarizing the participants with the web-enabled GDT will allow them to maintain and improve their data after the workshop. Once data edits have been completed the GDT will also allow the country authorities to perform any required review and validation processing. Once validated, the data can be used to update the global WDPA and IABIN databases, which will enhance analysis on global and regional levels.

Fact Sheet↗

USGS2016

Predictive mapping of seabirds, pinnipeds and cetaceans off the Pacific Coast of Washington

About this report This report supports Washington-led marine spatial planning and responsible stewardship of natural and cultural resources by the Olympic Coast National Marine Sanctuary. Washington state agencies and the sanctuary continually seek the best available science to improve management of marine uses and stewardship of resources (Etheridge et al., 2010; Washington Department of Fish and Wildlife, 2015a). This report and associated data provide new, state- and sanctuary-requested information on seabird, pinniped, and cetacean distributions. Through spatial planning, information on species distributions can help to identify high-value conservation areas, minimize adverse effects of ocean uses and mitigate impacts of coastal hazards. Correspondingly, the Washington Department of Fish and Wildlife has already begun to use the maps of predicted relative density presented in this report to identify ecologically important areas off the Pacific Coast of Washington and apply this information to plan for offshore renewable energy development. This is the culmination of three years of work to compile information on seabirds, pinnipeds, and cetaceans, and advance a modeling framework that can integrate data sets and develop accurate predictions of relative density for important species off the Pacific Coast of Washington. Previous reports, which evaluated existing datasets of at-sea observations (Menza et al., 2014; Kracker and Menza, 2015) and presented superseded versions of seabird models (Menza et al., 2015), provided base information for this report. In addition to the maps in this published report, all new seabird, pinniped and cetacean predictions will be made publicly available as digital geospatial data through the National Centers for Environmental Information. This research supports the National Oceanic and Atmospheric Administration (NOAA) Coastal Zone Management Program, a voluntary partnership between the federal government and U.S. coastal and Great Lakes states and territories authorized by the Coastal Zone Management Act (CZMA) of 1972 to address national coastal issues. The act provides the basis for protecting, restoring, and responsibly developing our nation’s diverse coastal communities and resources. To meet the goals of the CZMA, the national program takes a comprehensive approach to coastal resource management – balancing the often competing and occasionally conflicting demands of coastal resource use, economic development, and conservation. A wide range of issues are addressed through the program, including coastal development, water quality, public access, habitat protection, energy facility siting, ocean governance and planning, coastal hazards, and climate change. Accurate maps of seabird and marine mammal distributions are an important tool for making informed management decisions that affect all of these issues.

Washington↗

USGS2014

Mining continuous activity patterns from animal trajectory data

The increasing availability of animal tracking data brings us opportunities and challenges to intuitively understand the mechanisms of animal activities. In this paper, we aim to discover animal movement patterns from animal trajectory data. In particular, we propose a notion of continuous activity pattern as the concise representation of underlying similar spatio-temporal movements, and develop an extension and refinement framework to discover the patterns. We first preprocess the trajectories into significant semantic locations with time property. Then, we apply a projection-based approach to generate candidate patterns and refine them to generate true patterns. A sequence graph structure and a simple and effective processing strategy is further developed to reduce the computational overhead. The proposed approaches are extensively validated on both real GPS datasets and large synthetic datasets.

Lecture Notes in Computer Science (including subse↗

USGS1970

The diffusion of ions in unconsolidated sediments

Diffusion in unconsolidated sediments generally proceeds at rates ranging from half to one twentieth of those applying to diffusion of ions and molecules in free solution. Diffusion rates are predictable with respect to porosity and path tortuosity in host sediments, and can be conveniently measured by determinations of electrical resistivity on bulk sediment samples. Net ion flux is further influenced by reactions of diffusing species with enclosing sediments, but such influences should not be confused with or lumped with diffusion processes.

Earth and Planetary Science Letters↗

USGS2017

NDVI, scale invariance and the modifiable areal unit problem: An assessment of vegetation in the Adelaide Parklands

This research addresses the question as to whether or not the Normalised Difference Vegetation Index (NDVI) is scale invariant (i.e. constant over spatial aggregation) for pure pixels of urban vegetation. It has been long recognized that there are issues related to the modifiable areal unit problem (MAUP) pertaining to indices such as NDVI and images at varying spatial resolutions. These issues are relevant to using NDVI values in spatial analyses. We compare two different methods of calculation of a mean NDVI: 1) using pixel values of NDVI within feature/object boundaries and 2) first calculating the mean red and mean near-infrared across all feature pixels and then calculating NDVI. We explore the nature and magnitude of these differences for images taken from two sensors, a 1.24 m resolution WorldView-3 and a 0.1 m resolution digital aerial image. We apply these methods over an urban park located in the Adelaide Parklands of South Australia. We demonstrate that the MAUP is not an issue for calculation of NDVI within a sensor for pure urban vegetation pixels. This may prove useful for future rule-based monitoring of the ecosystem functioning of green infrastructure.

Adelaide Parklands↗

USGS2005

Initial results of rover localization and topographic mapping for the 2003 mars exploration rover mission

This paper presents the initial results of lander and rover localization and topographic mapping of the MER 2003 mission (by Sol 225 for Spirit and Sol 206 for Opportunity). The Spirit rover has traversed a distance of 3.2 km (actual distance traveled instead of odometry) and Opportunity at 1.2 km. We localized the landers in the Gusev Crater and on the Meridiani Planum using two-way Doppler radio positioning technology and cartographic triangulations through landmarks visible in both orbital and ground images. Additional high-resolution orbital images were taken to verify the determined lander positions. Visual odometry and bundle-adjustment technologies were applied to overcome wheel slippages, azimuthal angle drift and other navigation errors (as large as 21 percent). We generated timely topographic products including 68 orthophoto maps and 3D Digital Terrain Models, eight horizontal rover traverse maps, vertical traverse profiles up to Sol 214 for Spirit and Sol 62 for Opportunity, and five 3D crater models. A web-based landing-site Geographic Information System (GIS) has been set up at The Ohio State University to update and disseminate the daily localization and topographic information to support tactical and strategic operations of the mission. Also described in this paper are applications of the data for science operations planning, geological traverse survey, survey of wind-related features, and other science applications. The majority of the instruments onboard both rovers are healthy at this moment, and they will continue to explore the two landing sites on the Martian surface. We expect to report further localization and topographic mapping results to be achieved in the rest of the mission period and in post-mission data processing.

Photogrammetric Engineering and Remote Sensing↗

USGS2018

Toward salt marsh harvest mouse recovery: A review

The salt marsh harvest mouse (SMHM, Reithrodontomys raviventris ) is an endangered species, endemic to the San Francisco Estuary. Despite being protected for almost half a century and being included in a large number of recovery, restoration, and management plans, significant data gaps hinder conservation and management of the species, a challenge further complicated by developing threats such as climate change. In this review, we present the current state of knowledge; highlight research gaps on habitat requirements and distribution, taxonomic status and genetic structure, physiology, reproduction and demographics, population dynamics, and behavior and community interactions; and present an overview of threats to the species. Our review indicates that substantial data gaps exist; although some aspects of SMHM ecology, such as habitat use, have been addressed extensively, others, such as the effects of environmental contamination, are largely unaddressed. We suggest that conservation and restoration-planning processes consider experimental approaches within restoration designs to address these deficiencies. Continued investment in basic and applied SMHM ecology to collect baseline and long-term data will also be beneficial. Additionally, further coordination among managers and researchers can facilitate more effective responses to uncertainties and emerging threats, especially climate change, which threatens the SMHM and its habitat throughout its range.

San Francisco Estuary and Watershed Science↗

USGS2010

Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA

Investigating the routing of streamflow through a large drainage basin requires the determination of discharge at numerous locations in the channel network. Establishing a dense network of stream gages using conventional methods is both cost-prohibitive and functionally impractical for many research projects. We employ herein a previously tested, fluid-mechanically based model for generating rating curves to establish a stream gaging network in the Whitewater River basin in south-central Kansas. The model was developed for the type of channels typically found in this watershed, meaning that it is designed to handle deep, narrow geomorphically stable channels with irregular planforms, and can model overbank flow over a vegetated floodplain. We applied the model to ten previously ungaged stream reaches in the basin, ranging from third- to sixth-order channels. At each site, detailed field measurements of the channel and floodplain morphology, bed and bank roughness, and vegetation characteristics were used to quantify the roughness for a range of flow stages, from low flow to overbank flooding. Rating curves that relate stage to discharge were developed for all ten sites. Both fieldwork and modeling were completed in less than 2 years during an anomalously dry period in the region, which underscores an advantage of using theoretically based (as opposed to empirically based) discharge estimation techniques. ?? 2010 Springer Science+Business Media B.V.

Water Resources Management↗