Science support for salt pond restoration and management in south San Francisco Bay
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Fact Sheet↗
SEARCH · USGS Science
Results for “Science Report”
Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.
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Tampa Bay Integrated Science Pilot Study: data information management system (DIMS)
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Open-File Report↗
State of California sea level rise guidance: 2024 Science and policy update
No abstract available.
California↗
The surface of crystalline basement, Great Valley and Sierra Nevada, California: A digital map database
Crystalline basement in central California extends westward from the exposed Sierra Nevada beneath the sedimentary fill of the Great Valley and under the eastern edge of the Coast Ranges at mid-crustal depth. The surface of this basement is defined from three types of control: in the Sierra Nevada from the topography itself, beneath the eastern two thirds of the Great Valley in considerable detail from numerous wells drilled for oil and gas, and beneath the western San Joaquin Valley in less detail from seismic reflection and refraction profiles. Together, these data demonstrate that the surface of crystalline rock is continuous from the exposed rock in the mountains to the top of high-velocity rock buried deep beneath the eastern front of the southern Coast Ranges. This report presents a compilation of data through 1985 that define the surface of this crystalline basement, a contour map of the surface, and the lithology of the basement rock sampled by many of the wells. The compilation was begun as part of the investigation of the 1983 Coalinga earthquake, and was subsequently converted to digital form and extended to the whole of the Great Valley and Sierra Nevada. The main purpose was to explore and document the shape and continuity of the basement surface and to determine the relation of the surface to the tectonic wedge hypothesis (Wentworth and others, 1984; Wentworth and Zoback, 1989). Available basement samples from wells - principally the thin-section collection of May and Hewitt (1948) preserved by the California Academy of Sciences - were also reexamined by cooperating petrologists in an effort to distinguish wells that bottomed in ophiolitic rocks.
California↗
Measuring and attributing sedimentary and geomorphic responses to modern climate change: Challenges and opportunities
Today, climate change is affecting virtually all terrestrial and nearshore settings. This commentary discusses the challenges of measuring climate-driven physical landscape responses to modern global warming: short and incomplete data records, land use and seismicity masking climatic effects, biases in data availability and resolution, and signal attenuation in sedimentary systems. We identify opportunities to learn from historical and paleo data, select especially sensitive study sites, and report null results to better characterize the extent and nuances of climate-change effects. We then discuss efforts to improve attribution practices, which will lead to better predictive capabilities. We encourage the earth-science community to prioritize scientific research on climate-driven physical landscape changes so that societies will be better prepared to manage the effects on health and safety, infrastructure, water–food–energy security, economics, and ecosystems that follow from climate-driven physical landscape change.
Earth's Future↗
Host Fish Identification and Early Life Thermal Requirements for the Federal Endangered Winged Mapleleaf Mussel
The winged mapleleaf mussel (Quadrula fragosa, WML) is a Federal endangered species historically inhabiting at least 34 river systems in 12 Midwestern states. Only four populations are currently known to exist, including one confirmed reproducing population in the St. Croix National Scenic Riverway (NSR) bordering Minnesota and Wisconsin. Recovery efforts are limited by a lack of life history information, particularly which species of fish serve as host to the mussel's parasitic larvae (glochidia). Since 1997, biologists at the University of Minnesota have tried to identify host fish for the WML. Department of the Interior colleagues working in western Wisconsin at the U.S. Fish and Wildlife Service's La Crosse Fishery Resources Office and Genoa National Fish Hatchery, the National Park Service's St. Croix NSR, and the U.S. Geological Survey's Upper Midwest Environmental Sciences Center (UMESC) in La Crosse joined the team in 2001 to expand and accelerate the laboratory host fish identification program by making use of the well-equipped aquatic research facilities at UMESC. We report on several WML early life history investigations conducted at UMESC since autumn 2003 to identify suitable host fish species and evaluate thermal requisites for the development of glochidia into free-living juvenile mussels.
Fact Sheet↗
Water-Quality and Lake-Stage Data for Wisconsin Lakes, Water Year 2007
The U.S. Geological Survey (USGS), in cooperation with local and other agencies, collects data at selected lakes throughout Wisconsin. These data, accumulated over many years, provide a data base for developing an improved understanding of the water quality of lakes. To make these data available to interested parties outside the USGS, the data are published annually in this report series. The locations of water-quality and lake-stage stations in Wisconsin for water year 2007 are shown in figure 1. A water year is the 12-month period from October 1 through September 30. It is designated by the calendar year in which it ends. Thus, the period October 1, 2005 through September 30, 2007 is called 'water year 2007.' The purpose of this report is to provide information about the chemical and physical characteristics of Wisconsin lakes. Data that have been collected at specific lakes, and information to aid in the interpretation of those data, are included in this report. Data collected include measurements of in-lake water quality and lake stage. Time series of Secchi depths, surface total phosphorus and chlorophyll a concentrations collected during non-frozen periods are included for all lakes. Graphs of vertical profiles of temperature, dissolved oxygen, pH, and specific conductance are included for sites where these parameters were measured. Descriptive information for each lake includes: location of the lake, area of the lake?s watershed, period for which data are available, revisions to previously published records, and pertinent remarks. Additional data, such as streamflow and water quality in tributary and outlet streams of some of the lakes, are published in another volume: 'Water Resources Data-Wisconsin, 2007.'
Open-File Report↗
Strategic plan for the U.S. Geological Survey status and trends of Biological Resources Program: 2004-2009
The mission of the USGS Status and Trends of Biological Resources Program is to measure, predict, assess, and report the status and trends of the Nation's biological resources to facilitate research, enable resource management and stewardship, and promote public understanding and appreciation of our living resources. Determining the status (abundance, distribution, productivity, and health) and trends (how these variables change over time) of our living natural resources is critical for their Trumpeter swan with numbered wing tags. This tech- protection or restoration. The Progg ran nique allows birds to he monitored remotely without the provides the USGS, other agencies of need for recapture to identify individuals. Photo by the Department of the Interior (DOI), Wayne Miller. other federal and state agencies, and the public with science-based monitoring data and information for local, regional, and national assessment of biological resources and the ecosystems that support them.
Circular↗
Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images
Reliable detection and characterization of water ice on the Martian surface is pivotal to not only understand its present and past climate, but to also provide valuable information on in-situ resource availability and distribution for future human exploration missions. Ice-rich features are currently identified with visible/near-IR (VNIR), thermal IR and radar data. However, their coarse spatial scale sometimes limits confident characterization of small (i.e., meter-scale) icy exposures resulting from recent activity like new impacts. Water ice bearing materials possess weaker spectral characteristics at wavelengths shorter than ∼1030 nm that may be resolved by VNIR imaging instruments like the High Resolution Imaging Science Experiment (HiRISE) and the Colour and Stereo Surface Imaging System (CaSSIS). Our study assesses the spectral capability of HiRISE colour observations to help distinguish high purity water ice exposures from ice-poor materials. We report detailed methodologies for reliable colour characterization of icy surface using unfiltered HiRISE images. We present the first quantitative approach to uniquely characterize high-purity ice-rich materials through spectral shape and spectral parameterization methods at high spatial resolution (∼50 cm/pixel). We also present three spectral parameters to aid detection of pure water ice features, while also providing statistical constraints to enable a quantitative interpretation scheme. Our methods are observed to work well in characterizing and separating ice-rich features uniquely from ice-poor and ferrous materials. However, we do observe that these methods have a lower grain size detection limit of ∼250–300 μm, and may not be able to uniquely separate frosts from ground ice exposures. We also apply these methods to better constrain the composition of bright materials exposed by recent impacts identified in previous surveys, where substantial evidence for ice-bearing materials was previously unavailable. Overall, our work proposes HiRISE colour-based methods as a novel approach for high-resolution multispectral characterization of ice-rich features on the Martian surface, which is of particular value since the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has ceased operations.
Icarus↗
Response to comment on “Persistence of pharmaceutical compounds and other organic wastewater contaminants in a conventional drinking-water-treatment plant”
The U.S. Geological Survey (USGS) and the Centers for Disease Control thank Dr. Till for her comments concerning our research ( Till, 2005 ) and welcome the opportunity to respond. The primary objective of our study was to evaluate the potential for organic wastewater-related contaminants (OWCs), including pharmaceuticals, to survive a conventional drinking-water-treatment process and persist in potable-water supplies ( Stackelberg et al., 2004 ). Our study was supported by two USGS laboratories: the National Water Quality Laboratory (NWQL), which provided the HPLC/ESI-MS and CLLE GC/MS data and the Ocala Water Quality and Research Laboratory (OWQRL), which provided the LC/MS data ( Stackelberg et al., 2004 ). Although discussed as distinct techniques by Dr. Till and indicated by differing acronyms to distinguish the laboratories producing the data, as described in our paper, the two LC/MS methods are very similar; they consist of a solid-phase extraction method with analysis of the extract produced using high-performance liquid chromatography coupled to an electrospray ionization mass spectrometer operated in the positive mode. The NWQL and OWQRL report ‘trace’ and ‘ultratrace’ determinations of analytes that provide significant benefit for describing the presence and fate of low-level contaminants. For mass spectral methods, an analyte is qualitatively identified by its retention time on the chromatographic column as well as the presence of two or more confirming ions with area ratios that match that of the reference standard compounds. Because of a recognized increased risk of false positives, these qualitative identification criteria are used in conjunction with abundant quality-control samples (detailed below) to confirm detection prior to making an estimate of the concentration. These qualitative identification criteria must be met before a compound is considered present (or detected) in a sample ( Oblinger Childress et al., 1999 ). When a compound has been qualitatively identified in an environmental sample (whether above or below its reporting level [RL]), it is assessed in context with associated field and laboratory blanks, field and laboratory replicates, and other data, such as appropriate laboratory reagent spikes. An environmental concentration is calculated only after determining that field and laboratory procedures did not contaminate the samples. The concentrations are then calculated from 5- to 8-point calibration curves using internal standard quantitation. Our lowest calibration standard is intentionally much lower than the RL, typically 10 times lower. The most abundant molecular or fragment ion is used for quantitation, and, for the two LC/MS methods, at least one, and where possible two, qualifier ions are used for confirmation. For the GC/MS method, with its greater degree of fragmentation, one quantitation and two qualifier ions are used. When any of the abovementioned qualitative identification criteria are not met, the analyte is considered not present and is reported as “less than” the RL.
Science of the Total Environment↗
Sampling trace organic compounds in water: a comparison of a continuous active sampler to continuous passive and discrete sampling methods
A continuous active sampling method was compared to continuous passive and discrete sampling methods for the sampling of trace organic compounds (TOCs) in water. Results from each method are compared and contrasted in order to provide information for future investigators to use while selecting appropriate sampling methods for their research. The continuous low-level aquatic monitoring (CLAM) sampler (C.I.Agent® Storm-Water Solutions) is a submersible, low flow-rate sampler, that continuously draws water through solid-phase extraction media. CLAM samplers were deployed at two wastewater-dominated stream field sites in conjunction with the deployment of polar organic chemical integrative samplers (POCIS) and the collection of discrete (grab) water samples. All samples were analyzed for a suite of 69 TOCs. The CLAM and POCIS samples represent time-integrated samples that accumulate the TOCs present in the water over the deployment period (19–23 h for CLAM and 29 days for POCIS); the discrete samples represent only the TOCs present in the water at the time and place of sampling. Non-metric multi-dimensional scaling and cluster analysis were used to examine patterns in both TOC detections and relative concentrations between the three sampling methods. A greater number of TOCs were detected in the CLAM samples than in corresponding discrete and POCIS samples, but TOC concentrations in the CLAM samples were significantly lower than in the discrete and (or) POCIS samples. Thirteen TOCs of varying polarity were detected by all of the three methods. TOC detections and concentrations obtained by the three sampling methods, however, are dependent on multiple factors. This study found that stream discharge, constituent loading, and compound type all affected TOC concentrations detected by each method. In addition, TOC detections and concentrations were affected by the reporting limits, bias, recovery, and performance of each method.
Science of the Total Environment↗
Predicting biological conditions for small headwater streams in the Chesapeake Bay watershed
A primary goal for Chesapeake Bay watershed restoration is to improve stream health and function in 10% of stream miles by 2025. Predictive spatial modeling of stream conditions, when accurate, is one method to fill gaps in monitoring coverage and estimate baseline conditions for restoration goals. Predictive modeling can also monitor progress as additional data become available. We developed a random forests model to predict biological condition of small streams (<200 km 2 in drainage) in the Chesapeake Bay watershed. Biological condition was measured with the Chesapeake Bay Basin-wide Index of Biotic Integrity (Chessie BIBI), a stream macroinvertebrate index. Our goal was to predict biological condition in all unsurveyed small streams present in a 1:24,000 scale catchment layer as a 2004–2008 baseline. We reclassified the 5-category Chessie BIBI ratings into two categories, poor and fair/good, to align with management goals of the Chesapeake Bay Program. The model included 12 geospatial predictor variables including measures on spatial location, bioregion, land cover, soil, precipitation, and number of dams in local catchments. We trained the model with a random 75% subset of Chessie BIBI data ( n = 1449), and used the remaining 25% of Chessie BIBI data ( n = 484) as test data. The model performed well, correctly predicting 72% of samples in training data and 73% of samples in test data, but model accuracy varied among bioregions. We performed uncertainty analyses by adding bands of either ±0.05 or ±0.10 BIBI units to the cutoff between poor and fair/good. These uncertainty analyses resulted in 14.5% (±0.05 band) and 24.8% (±0.10 band) of samples in test data being classified as in uncertain condition. For 95,877 small stream reaches in the Chesapeake Bay watershed, the model predicted 64% in fair/good condition, the ±0.05 uncertainty analyses predicted 57% in fair/good condition, and the ±0.10 uncertainty analysis predicted 50% in fair/good condition. These reported values have different implications for the number of improved stream miles required to meet the goal of improving 10%. Incorporating uncertainty provides an assessment of model strength as well as confidence in predictions. We, therefore, suggest increased reporting of uncertainty in studies that spatially predict stream conditions.
Chesapeake Bay watershed↗
An introduction to current climate projections and their use in climate impacts research
Using climate projections to evaluate future climate impacts and their associated risks requires a background knowledge of the nature of climate change, use of climate models to develop future projections, and knowledge of how to address climate scenario uncertainty. This chapter provides an overview of climate and climate change, some of the foundational climate science that underlies current climate change assessments, and a brief introduction to climate models and climate scenario uncertainty. Global projections of temperature and precipitation changes from the recent Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) and a brief comparison to the prior assessment (AR5) are provided. The main sources of uncertainty in these projections include climate variability, climate model differences and treatment of scientific knowledge gaps, and greenhouse gas (GHG) emissions. When projections are downscaled to local resolution, downscaling is an additional source of uncertainty. These uncertainties can be incorporated in assessments of climate impacts by choosing a range of scenarios that directly address the sources of uncertainty. Evaluating the likelihood of a given climate impact on animal health or management strategies requires consideration of the main sources of climate projection uncertainties. Adaptation requires consideration of global-to-regional contexts of climate changes and impacts, but also adaptive capacity.
Book chapter↗
Resources to inform the 2026 Colorado Climate Preparedness Roadmap: Compound hazards and associated public health implications
Changing environmental conditions are increasing the frequency and severity of extreme weather and environmental hazards, including heat waves, wildfires, drought, reduced water quality, and degraded air quality from ozone (O3) and fine particulate matter pollution (AghaKouchak et al., 2020; Bolinger et al., 2024; Colorado Health Institute, 2023a; Fann et al., 2015; IPCC, 2023a; Nagamoto et al., 2024; Nolte et al., 2018, 2021; Zscheischler et al., 2020). Strong scientific evidence indicates that climate change will increase risks to public health and safety throughout the 21st century, particularly through compound climate events (AghaKouchak et al., 2020; Cascio, 2018; Childs et al., 2022; Ebi, 2025; IPCC, 2023a, 2023b; Ma et al., 2024; Marlier et al., 2026; National Academy of Medicine, 2025; Reid et al., 2016; Reid & Maestas, 2019; Simpson et al., 2023; van den Hurk et al., 2023; Volckens, 2024; Zscheischler et al., 2018, 2020). Compound hazards, which are co-occurring or sequential hazards such as heat waves occurring alongside drought, wildfire, and poor air quality from smoke, can amplify public health risks beyond the effects of individual hazards alone (Marlier et al., 2026; Zscheischler et al., 2020). In Colorado, compound climate events with clear implications for public health are already evident (see “Core definitions” section for additional context on compound climate events). Recent statewide assessments have documented increasing heat waves, drought, and wildfires linked to rising temperatures, while emerging data show that climate change is reversing decades of air quality improvements through increased O3 and fine particulate matter pollution due to wildfire, and increased aerosolized topsoil (i.e., dust) due to drought (Bolinger et al., 2024; Childs et al., 2022; Fann et al., 2015; Ghanbari et al., 2023; Larsen et al., 2022; Nolte et al., 2018, 2021; Volckens, 2024). These environmental shifts are associated with increases in eye and kidney-health related concerns, heat-related illness, exacerbations of asthma and other respiratory conditions, increased risk of infectious disease, cardiovascular stress, and mental health impacts, with disparities in risk for children, older adults, outdoor workers, and communities with existing health and economic vulnerabilities (Baraghoshi et al., 2023; Butler-Dawson et al., 2026; Cascio, 2018; Cleland et al., 2022; Colorado Health Institute, 2023a; Grover et al., 2024; Lee et al., 2023; Ma et al., 2024; Macaluso et al., 2024; Marlier et al., 2026; National Academy of Medicine, 2025; Patnaik et al., 2024; Peters et al., 2019; Reid et al., 2016; Reid & Maestas, 2019). The state is actively pursuing strategies to mitigate the risks of these compound climate events on the public, including expanding climate and health surveillance, strengthening early-warning systems and public communication around smoke and air quality, and developing integrated policy agendas that link climate mitigation, adaptation, and health equity (CDPHE, 2025; Colorado Health Institute, 2023b; Zemaitis & Bailey, 2024). For example, state and partner organizations have articulated cross-sector goals to prepare for health impacts related to extreme heat, wildfires, flooding, drought, declines in water quality, and poor air quality, including updating workplace safety protocols, enhancing community-based resilience, adapting clinical care assessments to include climate-related stressors, and improving access to mental and behavioral health services following climate-related disasters (Colorado Health Institute, 2023b; CDPHE, 2025; Zemaitis & Bailey, 2024). To better prepare for current risks and make informed decisions, more information is needed, including methods to analyze historical and projected conditions in near real time, characterize interactions among compound hazards, and translate climate and air quality science into actionable guidance for public health agencies, health care systems, and communities across Colorado (Ebi, 2025; Marlier et al., 2026; National Academy of Medicine, 2025; Simpson et al., 2023; Zscheischler et al., 2018). For this report, we focus on extreme heat and outdoor air quality (ozone [O3] and fine particulate matter [PM2.5]) as the main compound hazards causing compound climate events, given that 1) the state of Colorado has experienced poor air quality for some time, 2) these climate events are affecting large population numbers, and 3) there is capacity to consider and respond to these climate-driven events.
Colorado↗
Global Land Information System (GLIS)
The Global Land Information System (GLIS) is an interactive computer system developed by the U.S. Geological Survey (USGS) for scientists seeking sources of information about the Earth's land surfaces. GLIS contains "metadata," that is, descriptive information about data sets. Through GLIS, scientists can evaluate data sets, determine their availability, and place online requests for products. GLIS is more, however, than a mere list of products. It offers online samples of earth science data that may be ordered through the system.
General Information Product↗
U.S. Geological Survey activities related to American Indians and Alaska Natives: Fiscal year 2006
In the late 1800s, John Wesley Powell, the second director of the U.S. Geological Survey (USGS), followed his interest in the tribes of the Great Basin and Colorado Plateau and studied their cultures, languages, and surroundings. From that early time, the USGS has recognized the importance of Native knowledge and living in harmony with nature as complements to the USGS mission to better understand the Earth. Combining traditional ecological knowledge with empirical studies allows the USGS and Native American governments, organizations, and people to increase their mutual understanding and respect for this land. The USGS is the earth and natural science bureau within the U.S. Department of the Interior (DOI). The USGS does not have regulatory or land management responsibilities.
Circular↗
EAARL coastal topography-Cape Hatteras National Seashore, North Carolina, post-Nor'Ida, 2009: first surface
These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.
Data Series↗
Selected applications of hydrologic science and research in Maryland, Delaware, and Washington, D.C., 2001-2003
One of the roles of the U.S. Geological Survey (USGS) is to provide reliable water data and unbiased water science needed to describe and understand the Nation?s water resources. This fact sheet describes selected techniques that were used by the USGS to collect, transmit, evaluate, or interpret data, in support of investigations that describe the quantity and quality of water resources in Maryland (MD), Delaware (DE), and the District of Columbia (D.C.). These hydrologic investigations generally were performed in cooperation with universities, research centers, and other Federal, State, and local Government agencies. The applications of hydrologic science and research that were selected for this fact sheet were used or tested in the MD-DE-DC District from 2001 through 2003, and include established methods, new approaches, and preliminary research. The USGS usually relies on standard methods or protocols when conducting water-resources research. Occasionally, traditional methods must be modified to address difficult environmental questions or challenging sampling conditions. Technologies developed for other purposes can sometimes be successfully applied to the collection or dissemination of water-resources data. The USGS is continually exploring new ways to collect, transmit, evaluate, and interpret data. The following applications of hydrologic science and research illustrate a few of the recent advances made by scientists working for and with the USGS.
Fact Sheet↗