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USGS2021

U.S. Geological Survey 21st-Century science strategy 2020–2030

Today’s Earth system challenges are far more complex and urgent than those that existed in 1879 when the USGS was established. Society’s greatest challenges are directly or indirectly linked to major areas of USGS science. Increased pressures on natural resources continue with consequences for national security, food and water availability, natural disasters, human health, and biodiversity loss. As we look forward 10, 20, and 30 years, our mission will be more important than ever before. A broad but coherent view is required for stewardship of the Nation’s land, water, mineral, energy, and ecosystem resources, which involves complex tradeoffs among multiple, often competing objectives. Increasingly, resource managers and decision makers need “the whole USGS”: integrated multidisciplinary Earth and biological science data, geospatial tools, predictive models, decision-support tools, and the expertise to interpret them. This Science Strategy defines a vision and mission for how we will continue to evolve USGS Science to address these Earth system challenges.

Circular↗

USGS2022

Global groundwater solute composition and concentrations

Informed analysis of policies related to food security, global climate change, wetland ecology, environmental nutrient flux, element cycling, groundwater weathering, continental denudation, human health, etc. depends to a large extent on quantitative estimates of solute mass fluxes into and out of all global element pools including the enigmatic global aquifer systems. Herein for the first time, we proffer the mean global solute concentration of all major and selected minor and trace solutes in the active groundwater that represents 99% of liquid fresh water on Earth. Concentrations in this significant element pool have yielded to a geospatial machine learning kNN-nearest neighbors’ algorithm with numerous geospatial predictors utilizing a large new lithology/climate/aquifer age/elevation based solute database. The predicted concentrations are consistent with traditional solute ratios, concentrations, and thermodynamic saturation indices.

Groundwater↗

USGS2020

Statewide assessment of karst aquifers in New York with an inventory of closed-depression and focused-recharge features

Karst is a landscape formed from the dissolution of soluble rock or rock containing minerals that are easily dissolved from within the rock. The landscape is characterized by sinkholes, caves, losing streams, springs, and underground drainage systems, which rapidly move water through the karst. The two forms of karst in New York State include carbonate karst, which forms in carbonate rock (limestone, marble, and dolostone), and evaporite karst, which forms in rock that contains the evaporite minerals gypsum and halite. Past and recent studies of karst across the State have shown that areas of focused recharge in karstic carbonate rock allow contaminants to enter aquifer systems with little attenuation. Focused areas of recharge need to be identified to help prevent such contamination from sources on or adjacent to the karst. The New York State Departments of Environmental Conservation and Health are collaborating with the agricultural community to make farmers and farm-planning advisors more aware of karst and how to manage daily farming activities to reduce their impact on surface water and groundwater resources, especially in karst areas. There is also a need to make regulators, planners, and the general public aware of New York’s karst resources and to properly protect and manage these resources to protect the quality of groundwater and surface water that can flow into, through, and from karst bedrock. Using publicly available geospatial data, karst bedrock and closed depressions over or near karst rock were identified across New York. Carbonate, evaporite, and marble geologic units were selected from a statewide 1:250,000-scale bedrock geology dataset. The selected geologic units were intersected with 7.5-minute quadrangle maps to define the study area. The U.S. Geological Survey has compiled an inventory of closed depressions from statewide digital contour data, scanned 7.5-minute topographic maps known as a digital raster graphics, and light detection and ranging (lidar) digital elevation models. Analysis of the data resulted in the identification of 5,023 closed depressions statewide. The inventory was conducted to eliminate duplication of results from analysis of the three data sources. A series of overlay analyses was conducted using the closed depressions and thematic data known to be key factors in determining the probability of a closed depression contributing to focused groundwater recharge; the thematic data include bedrock geology, soil type, soil infiltration rate, and land cover. Though the extent of karst development is important in understanding the interaction between surface water and groundwater in karst terrains, some of the worst cases of groundwater contamination in karst can occur where only minor karst features might be present. The presence of karst—be it a short section of a solutioned fracture or an extensive cave system—requires careful consideration, forward-looking environmental planning, and consistent water-quality protection to preserve New York State’s water resources.

New York↗

USGS2002

Preliminary United States-Mexico border watershed analysis, twin cities area of Nogales, Arizona and Nogales, Sonora

The United States - Mexico border area faces the challenge of integrating aspects of its binational physical boundaries to form a unified or, at least, compatible natural resource management plan. Specified geospatial components such as stream drainages, mineral occurrences, vegetation, wildlife, and land-use can be analyzed in terms of their overlapping impacts upon one another. Watersheds have been utilized as a basic unit in resource analysis because they contain components that are interrelated and can be viewed as a single interactive ecological system. In developing and analyzing critical regional natural resource databases, the Environmental Protection Agency (EPA) and other federal and non-governmental agencies have adopted a ?watershed by watershed? approach to dealing with such complicated issues as ecosystem health, natural resource use, urban growth, and pollutant transport within hydrologic systems. These watersheds can facilitate the delineation of both large scale and locally important hydrologic systems and urban management parameters necessary for sustainable, diversified land-use. The twin border cities area of Nogales, Sonora and Nogales, Arizona, provide the ideal setting to demonstrate the utility and application of a complete, cross-border, geographic information systems (GIS) based, watershed analysis in the characterization of a wide range of natural resource as well as urban features and their interactions. In addition to the delineation of a unified, cross-border watershed, the database contains sewer/water line locations and status, well locations, geology, hydrology, topography, soils, geomorphology, and vegetation data, as well as remotely sensed imagery. This report is preliminary and part of an ongoing project to develop a GIS database that will be widely accessible to the general public, researchers, and the local land management community with a broad range of application and utility.

Arizona, Sonora↗

USGS2014

Use of satellite imagery to identify vegetation cover changes following the Waldo Canyon Fire event, Colorado, 2012-2013

The Waldo Canyon Fire of 2012 was one of the most destructive wildfire events in Colorado history. The fire burned a total of 18,247 acres, claimed 2 lives, and destroyed 347 homes. The Waldo Canyon Fire continues to pose challenges to nearby communities. In a preliminary emergency assessment conducted in 2012, the U.S. Geological Survey (USGS) concluded that drainage basins within and near the area affected by the Waldo Canyon Fire pose a risk for future debris flow events. Rainfall over burned, formerly vegetated surfaces resulted in multiple flood and debris flow events that affected the cities of Colorado Springs and Manitou Springs in 2013. One fatality resulted from a mudslide near Manitou Springs in August 2013. Federal, State, and local governments continue to monitor these hazards and other post-fire effects, along with the region’s ecological recovery. At the request of the Colorado Springs Office of Emergency Management, the USGS Special Applications Science Center developed a geospatial product to identify vegetation cover changes following the 2012 Waldo Canyon Fire event. Vegetation cover was derived from July 2012 WorldView-2 and September 2013 QuickBird multispectral imagery at a spatial resolution of two meters. The 2012 image was collected after the fire had reached its maximum extent. Per-pixel increases and decreases in vegetation cover were identified by measuring spectral changes that occurred between the 2012 and 2013 image dates. A Normalized Difference Vegetation Index (NDVI), and Green-Near Infrared Index (GRNIR) were computed from each image. These spectral indices are commonly used to characterize vegetation cover and health condition, due to their sensitivity to detect foliar chlorophyll content. Vector polygons identifying surface-cover feature boundaries were derived from the 2013 imagery using image segmentation software. This geographic software groups similar image pixels into vector objects based upon their spatial and spectral characteristics. The vector dataset was then populated with the per-pixel spectral change information to provide an estimated percentage of vegetation increase or decrease of pixels within each polygon. Information collected during a field visit to the Waldo Canyon burn scar in September 2013 was used to help validate this assessment (see photographs 1-3). The numbers on the satellite images correspond to the location of the photographs. For display purposes, the polygons shown on the map represent areas where significant decrease or increase in vegetation cover occurred. Only polygons that held a 70 percent or greater cover change are shown on this map (a GIS dataset with complete information is available upon request). A significant increase in vegetation cover was found in the burned area. This increase is likely due to the growth of grasses and other herbaceous vegetation. Minimal vegetation cover decrease was detected at this threshold. This product is meant to provide a broad survey of post-fire vegetation trends within the Waldo Canyon burned area to Federal, State, and local officials. It is not designed to quantify species-level vegetation change at this time.

Colorado↗

USGS2009

USGS Science: Addressing Our Nation's Challenges

With 6.6 billion people already living on Earth, and that number increasing every day, human influence on our planet is ever more apparent. Changes to the natural world combined with increasing human demands threaten our health and safety, our national security, our economy, and our quality of life. As a planet and a Nation, we face unprecedented challenges: loss of critical and unique ecosystems, the effects of climate change, increasing demand for limited energy and mineral resources, increasing vulnerability to natural hazards, the effects of emerging diseases on wildlife and human health, and growing needs for clean water. The time to respond to these challenges is now, but policymakers and decisionmakers face difficult choices. With competing priorities to balance, and potentially serious - perhaps irreversible - consequences at stake, our leaders need reliable scientific information to guide their decisions. As the Nation's earth and natural science agency, the USGS monitors and conducts scientific research on natural hazards and resources and how these elements and human activities influence our environment. Because the challenges we face are complex, the science needed to better understand and deal with these challenges must reflect the complex interplay among natural and human systems. With world-class expertise in biology, geology, geography, hydrology, geospatial information, and remote sensing, the USGS is uniquely capable of conducting the comprehensive scientific research needed to better understand the interdependent interactions of Earth's systems. Every day, the USGS helps decisionmakers to minimize loss of life and property, manage our natural resources, and protect and enhance our quality of life. This brochure provides examples of the challenges we face and how USGS science helps decisionmakers to address these challenges.

General Information Product↗

USGS2025

Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models

The report focuses on the screening of previously published concentration data associated with 12 elements of concern (aluminum, arsenic, cadmium, chromium, copper, iron, mercury, manganese, lead, selenium, uranium, and zinc) measured in stream surface waters of three hydrologic basins (Delaware River Basin, Illinois River Basin, and the Upper Colorado River Basin). The purpose of this analysis is to determine what subsets of the original dataset (containing more than 1,500,000 observations) may be most suitable for each of two types of modeling efforts. The first type of modeling envisions a machine learning approach to determine which geospatial attributes are most significant in describing the spatial distribution of elemental concentrations within a basin. The second type of modeling envisions a stepwise regression approach to develop multivariable models that can be used to determine high resolution time-series estimates of elemental concentrations or loads at discrete U.S. Geological Survey real-time stream surface water sites. These site-specific temporal models are based on continuous measurements of available discharge and (or) in situ sensor data (temperature, pH, turbidity, dissolved oxygen, specific conductance, and (or) fluorescent dissolved organic matter) as the explanatory variables. The data screening for both model types considered historical trends in analytical methods and detection quantitation limits, the extent of censored data, data density, and environmental relevance with respect to three U.S. Environmental Protection Agency water quality thresholds (drinking water guidelines, human health criteria, and aquatic life criteria). The result of this analysis was the production of a final list of potential models deemed suitable for further development based upon the data exclusion (or inclusion) scheme developed herein for each model type. In both cases, the final models included mostly the three crustal elements (iron, manganese, and aluminum) that are found at comparatively high concentrations in surface water, whereas most of the more pernicious elements were excluded from the final model lists owing to various data limitations. The one exception to this was arsenic, for which the existing data were sufficient at three U.S. Geological Survey real-time sites for potential further development of time-series models.

Colorado, Delaware, Illinois, Indiana, Maryland, N↗

USGS2011

Onshore and offshore geologic map of the Coal Oil Point area, southern California

Geologic maps that span the shoreline and include both onshore and offshore areas are potentially valuable tools that can lead to a more in depth understanding of coastal environments. Such maps can contribute to the understanding of shoreline change, geologic hazards, both offshore and along-shore sediment and pollutant transport. They are also useful in assessing geologic and biologic resources. Several intermediate-scale (1:100,000) geologic maps that include both onshore and offshore areas (herein called onshore-offshore geologic maps) have been produced of areas along the California coast (see Saucedo and others, 2003; Kennedy and others, 2007; Kennedy and Tan, 2008), but few large-scale (1:24,000) maps have been produced that can address local coastal issues. A cooperative project between Federal and State agencies and universities has produced an onshore-offshore geologic map at 1:24,000 scale of the Coal Oil Point area and part of the Santa Barbara Channel, southern California (fig. 1). As part of the project, the U.S. Geological Survey (USGS) and the California Geological Survey (CGS) hosted a workshop (May 2nd and 3rd, 2007) for producers and users of coastal map products (see list of participants) to develop a consensus on the content and format of onshore-offshore geologic maps (and accompanying GIS files) so that they have relevance for coastal-zone management. The USGS and CGS are working to develop coastal maps that combine geospatial information from offshore and onshore and serve as an important tool for addressing a broad range of coastal-zone management issues. The workshop was divided into sessions for presentations and discussion of bathymetry and topography, geology, and habitat products and needs of end users. During the workshop, participants reviewed existing maps and discussed their merits and shortcomings. This report addresses a number of items discussed in the workshop and details the onshore and offshore geologic map of the Coal Oil Point area. Results from this report directly address issues raised in the California Ocean Protection Act (COPA) Five Year Strategic Plan. For example, one of the guiding principles of the COPA five-year strategic plan is to 'Recognize the interconnectedness of the land and the sea, supporting sustainable uses of the coast and ensuring the health of ecosystems.' Results from this USGS report directly connect the land and sea with the creation of both a seamless onshore and offshore digital terrain model (DTM) and geologic map. One of the priority goals (and objectives) of the COPA plan is to 'monitor and map the ocean environment to provide data about conditions and trends.' Maps within this report provide land and sea geologic information for mapping and monitoring nearshore sediment processes, pollution transport, and sea-level rise and fall.

California↗

USGS2018

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↗

USGS2018

Necropsy-based wild fish health assessment

Anthropogenic influences from increased nutrients and chemical contaminants, to habitat alterations and climate change, can have significant effects on fish populations. Adverse effects monitoring, utilizing biomarkers from the organismal to the molecular level, can be used to assess the cumulative effects on fishes and other organisms. Fish health has been used worldwide as an indicator of aquatic ecosystem health. The necropsy-based fish health assessment provides data on visible abnormalities and lesions, parasites, condition and organosomatic indices. These can be compared by site, season and sex, as well as temporally, to document change over time. Severity ratings can be assigned to various observations to calculate a fish health index for more quantitative assessment. A drawback of the necropsy-based assessment is that it is based on visual observations and condition factors, which are not as sensitive as tissue and subcellular biomarkers for sublethal effects. Additionally, it is rarely possible to identify causes or risk factors associated with observed abnormalities. So, for instance a raised lesion or "tumor" on the fins, lips or body surface may be a neoplasm. However, it could also be a response to a parasite, chronic inflammation or hyperplasia of normal cells in response to an irritant. Conversely, neoplasms, certain parasites, other infectious agents and many tissue changes are not visible and so may be underestimated. However, during the necropsy-based assessment, blood (plasma), tissues for histopathology (microscopic pathology), genomics and other molecular analyses, and otoliths for aging can be collected. These downstream analyses, together with geospatial analyses, habitat assessments, water quality and contaminant analyses can all be important in comprehensive ecosystem evaluations.

Journal of Visualized Experiments↗

USGS2023

Per- and polyfluorinated alkyl substances (PFAS) in Pennsylvania surface waters: A statewide assessment, associated sources, and land-use relations

The objectives of this study are to identify per- and polyfluoroalkyl substances (PFAS) in Pennsylvania surface waters, corresponding associations with potential sources of PFAS contamination (PSOC) and other parameters, and compare raw surface water concentrations to human and ecological benchmarks. Surface water samples from 161 streams were collected in September 2019 and were analyzed for 33 target PFAS and water chemistry. Land use and physical attributes in upstream catchments and geospatial counts of PSOC in local catchments are summarized. The hydrologic yield of the sum of 33 PFAS (∑PFAS) for each stream was computed by normalizing each site's load by the drainage area of the upstream catchment. Utilizing conditional inference tree analysis, the percentage of development (>7.58 %) was identified as a primary driver of the ∑PFAS hydrologic yields. When percentage of development was removed from analysis, ∑PFAS yields were closely related to surface water chemistry associated with landscape alteration (e.g., development or agricultural cropland), such as concentrations of total nitrogen, chloride, and ammonia, but also to count of water pollution control facilities (agricultural, industrial, stormwater, and/or municipal waste pollution abatement facilities). In oil and gas development regions, ∑PFAS yields were associated with combined sewage outfalls. Sites surrounded by ≥2 electronic manufacturing facilities had elevated ∑PFAS yields (median = 241 ng/s/km 2 ). Study results are critical to guide future research, regulatory policy, best practices that will mitigate PFAS contamination, and the communication of human health and ecological risks associated with PFAS exposure from surface waters.

Pennsylvania↗

USGS2019

Demonstrating the value of Earth observations—methods, practical applications, and solutions—group on Earth observations side event proceedings

Executive Summary The U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the European Association for Remote Sensing Companies, and the European Space Agency in coordination with the GEOValue Community hosted a side event to the Group on Earth Observations Plenary on October 23–24, 2017, in Washington, D.C. The workshop, entitled “Demonstrating the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together more than 60 international experts including economists, scientists, and engineers to consider the state of the science and applications of valuing Earth observations (EO). This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure the value of information generated from the use of satellite and in-situ data. The mix of government agencies, international financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, approaches, and outcomes. During the first part of the workshop, the focus was on the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal benefits of specific actions (for example, investments in EO). Some methods focus on broad measures of economic activity (for example, gross domestic product) or methods to assess total economic value such as contingent valuation surveys. Alternatively, use-case approaches (a use case is defined as an evaluation in which one or more decisions, applications, or other uses of data, information, and information products are specifically considered) start with the specific actions and how information is used to support decision making and affect outcomes. The second part of the meeting was focused on the use and development of value chains and decision trees. A value chain can be defined as the set of value-adding activities that one or more organizations perform in creating and distributing goods and services. In terms of EO, the value chain approach can be applied to consider societal benefits of the data and assess the value of data and data features. The EO value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision makers’ actions. To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. Extending the value chain concept and incorporating tenets of Bayesian decision making, a decision tree would include one or more use cases. The value provided by the marginal increase in information could flow from one or several parts of the supply side of the value chain. The decision tree is based on the premise that information has no value if it is not used in at least one decision. By connecting the value chain and the decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with information versus one without. A third part of the meeting applied the value chain and decision-tree frameworks to five specific thematic areas, each with the focus of using information for a decision point: Effect of increasing temperatures on human health; Flooding—Mitigating, managing, and avoiding impacts to safety and property damage; Harmful algal blooms—Effects on human health, recreation, and tourism; Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the economy; and Effects of natural hazards on transportation systems—Effects on mobility, safety, and the economy. During the working session, five separate groups worked to define and delineate the value chains and decision trees associated with each topic, discussing the related challenges and data needs. The outcomes were reported back to the full group. Because of the complexity of the topics, most groups first identified a network of value chains and then narrowed the scope to develop a single value chain to address their group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring that the value chain and decision-tree frameworks are very effective for informing quantitative impact assessments and developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Open-File Report↗

USGS2016

Estimating natural monthly streamflows in California and the likelihood of anthropogenic modification

Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.

California↗

USGS2017

Oregon OCS seafloor mapping: Selected lease blocks relevant to renewable energy

In 2014 the U.S. Geological Survey (USGS) and the Bureau of Ocean Energy Management (BOEM) entered into Intra-agency agreement M13PG00037 to map an area of the Oregon Outer Continental Shelf (OCS) off of Coos Bay, Oregon, under consideration for development of a floating wind energy farm. The BOEM requires seafloor mapping and site characterization studies in order to evaluate the impact of seafloor and sub-seafloor conditions on the installation, operation, and structural integrity of proposed renewable energy projects, as well as to assess the potential effects of construction and operations on archaeological resources. The mission of the USGS is to provide geologic, topographic, and hydrologic information that contributes to the wise management of the Nation's natural resources and that promotes the health, safety, and well being of the people. This information consists of maps, databases, and descriptions and analyses of the water, energy, and mineral resources, land surface, underlying geologic structure, and dynamic processes of the earth. For the Oregon OCS study, the USGS acquired multibeam echo sounder and seafloor video data surrounding the proposed development site, which is 95 km2 in area and 15 miles offshore from Coos Bay. The development site had been surveyed by Solmar Hydro Inc. in 2013 under a contract with WindFloat Pacific. The USGS subsequently produced a bathymetry digital elevation model and a backscatter intensity grid that were merged with existing data collected by the contractor. The merged grids were published along with visual observations of benthic geo-habitat from the video data in an associated USGS data release (Cochrane and others, 2015). This report includes the results of analysis of the video data conducted by Oregon State University and the geo-habitat interpretation of the multibeam echo sounder (MBES) data conducted by the USGS. MBES data was published in Cochrane and others (2015). Interpretive data associated with this publication is published in Cochrane (2017). All the data is provided as geographic information system (GIS) files that contain both Esri ArcGIS geotiffs or shapefiles. For those who do not own the full suite of Esri GIS and mapping software, the data can be read using Esri ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed August 29, 2016). Web services, which consist of standard implementations of ArcGIS representational state transfer (REST) Service and Open Geospatial Consortium (OGC) GIS web map service (WMS), also are available for all published GIS data. Web services were created using an ArcGIS service definition file, resulting in data layers that are symbolized as shown on the associated report figures. Both the ArcGIS REST Service and OGC WMS Service include all the individual GIS layers. Data layers are bundled together in a map-area web service; however, each layer can be symbolized and accessed individually after the web service is ingested into a desktop application or web map. Web services enable users to download and view data, as well as to easily add data to their own workflows, using any browser-enabled, standalone or mobile device. Though the surficial substrate is dominated by combinations of mud and sand substrate, a diverse assortment of geomorphologic features are related to geologic processes—one anticlinal ridge where bedrock is exposed, a slump and associated scarps, and pockmarks. Pockmarks are seen in the form of fields of small pockmarks, a lineation of large pockmarks with methanogenic carbonates, and areas of large pockmarks that have merged into larger variously shaped depressions. The slump appears to have originated at the pockmark lineation. Video-supervised numerical analysis of the MBES backscatter intensity data and vector ruggedness derived from the MBES bathymetry data was used to produce a substrate model called a seafloor character raster for the study area. The seafloor character raster consists of three substrate classes: soft-flat areas, hard-flat areas, and hard-rugged areas. A Coastal and Marine Ecological Classification Standard (CMECS) geoform and substrate map was also produced using depth, slope, and benthic position index classes to delineate geoform boundaries. Seven geoforms were identified in this process, including ridges, slump scars, slump deposits, basins, and pockmarks. Statistical analysis of the video data for correlations between substrate, depth, and invertebrate assemblages resulted in the identification of seven biomes: three hard-bottom biomes and four softbottom biomes. A similar analysis of vertebrate observations produces a similar set of biomes. The biome between-group dissimilarity was very high or high. Invertebrates alone represent most of the structure of the whole benthic community into different assemblages. A biotope map was generated using the seafloor character raster and the substrate and depth values of the biomes. Hard substrate biotopes were small in size and were located primarily on the ridge and in pockmarks along the pockmark lineation. The soft-bottom bitopes consisted of large contiguous areas delimited by isobaths.

Open-File Report↗

USGS2023

Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America

ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable. The ShakeAlert system uses, among other public alerting platforms like a mobile phone operating system, smartphone apps, and the Federal Emergency Management Agency Integrated Public Alert & Warning System (IPAWS). IPAWS sends Wireless Emergency Alerts (WEAs) informing people via their smartphones and other mobile devices about various events, such as natural hazards, child abductions, or public health information about COVID-19. However, little is known about the IPAWS delivery latencies. Given that people may have only a few seconds of notice after they receive an alert to take a protective action before they feel earthquake shaking, quantifying latencies is critical to understanding whether the IPAWS system is useful for EEW. In this study, we developed new methods to test the IPAWS distribution system's performance, both with devices in a controlled environment and as well as with a 2019 community-based feedback form, in Oakland and San Diego County, California, respectively. The controlled environment test used mobile phones (including smart and non-smart phones) and associated devices to determine alert receipt times; the community research form had participants self-report their receipt times. By triangulating the data between the controlled test environment and the community research, we determined the latency statistics as well as whether the geofence (the geographic area where the alert was intended to be sent) held broadly. We found that the latencies were similar between the two tests despite the large differences in population sizes. WEA messages were received within a median time frame of 6–12 s, and the geofence held with only a few exceptions. We use this latency to assess how the system would have performed in two large earthquakes, the 1989 M6.9 Loma Prieta and 2019 M7.1 Ridgecrest earthquakes, which both occurred near our WEA test locations. Our analysis revealed that had IPAWS been available during those earthquakes, particularly Loma Prieta, it would have provided crucial seconds of notice that damaging shaking was imminent in some locations relatively far from the epicenter. Further, we find affordable non-smart phones can receive WEAs as fast as smartphones. Finally, our new method can be used for latency and geospatial testing going forward for IPAWS and other similar alerting systems.

California↗

USGS2014

Geospatial association between adverse birth outcomes and arsenic in groundwater in New Hampshire, USA

There is increasing evidence of the role of arsenic in the etiology of adverse human reproductive outcomes. Because drinking water can be a major source of arsenic to pregnant women, the effect of arsenic exposure through drinking water on human birth may be revealed by a geospatial association between arsenic concentration in groundwater and birth problems, particularly in a region where private wells substantially account for water supply, like New Hampshire, USA. We calculated town-level rates of preterm birth and term low birth weight (term LBW) for New Hampshire, by using data for 1997–2009 stratified by maternal age. We smoothed the rates by using a locally weighted averaging method to increase the statistical stability. The town-level groundwater arsenic probability values are from three GIS data layers generated by the US Geological Survey: probability of local groundwater arsenic concentration >1 µg/L, probability >5 µg/L, and probability >10 µg/L. We calculated Pearson’s correlation coefficients ( r ) between the reproductive outcomes (preterm birth and term LBW) and the arsenic probability values, at both state and county levels. For preterm birth, younger mothers (maternal age <20) have a statewide r = 0.70 between the rates smoothed with a threshold = 2,000 births and the town mean arsenic level based on the data of probability >10 µg/L; for older mothers, r = 0.19 when the smoothing threshold = 3,500; a majority of county level r values are positive based on the arsenic data of probability >10 µg/L. For term LBW, younger mothers (maternal age <25) have a statewide r = 0.44 between the rates smoothed with a threshold = 3,500 and town minimum arsenic concentration based on the data of probability >1 µg/L; for older mothers, r = 0.14 when the rates are smoothed with a threshold = 1,000 births and also adjusted by town median household income in 1999, and the arsenic values are the town minimum based on probability >10 µg/L. At the county level for younger mothers, positive r values prevail, but for older mothers, it is a mix. For both birth problems, the several most populous counties—with 60–80% of the state’s population and clustering at the southwest corner of the state—are largely consistent in having a positive r across different smoothing thresholds. We found evident spatial associations between the two adverse human reproductive outcomes and groundwater arsenic in New Hampshire, USA. However, the degree of associations and their sensitivity to different representations of arsenic level are variable. Generally, preterm birth has a stronger spatial association with groundwater arsenic than term LBW, suggesting an inconsistency in the impact of arsenic on the two reproductive outcomes. For both outcomes, younger maternal age has stronger spatial associations with groundwater arsenic.

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