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USGS2015

The U.S. Geological Survey Geologic Collections Management System (GCMS)—A master catalog and collections management plan for U.S. Geological Survey geologic samples and sample collections

**Updated guidance is available in USGS Instructional Memorandum CSS 2019-01 .** Abstract The U.S. Geological Survey (USGS) is widely recognized in the earth science community as possessing extensive collections of earth materials collected by research personnel over the course of its history. In 2006, a Geologic Collections Inventory was conducted within the USGS Geology Discipline to determine the extent and nature of its sample collections, and in 2008, a working group was convened by the USGS National Geologic and Geophysical Data Preservation Program to examine ways in which these collections could be coordinated, cataloged, and made available to researchers both inside and outside the USGS. The charge to this working group was to evaluate the proposition of creating a Geologic Collections Management System (GCMS), a centralized database that would (1) identify all existing USGS geologic collections, regardless of size, (2) create a virtual link among the collections, and (3) provide a way for scientists and other researchers to obtain access to the samples and data in which they are interested. Additionally, the group was instructed to develop criteria for evaluating current collections and to establish an operating plan and set of standard practices for handling, identifying, and managing future sample collections. Policies and procedures promoted by the GCMS would be based on extant best practices established by the National Science Foundation and the Smithsonian Institution. The resulting report—USGS Circular 1410, “The U.S. Geological Survey Geologic Collections Management System (GCMS): A Master Catalog and Collections Management Plan for U.S. Geological Survey Geologic Samples and Sample Collections”—has been developed for sample repositories to be a guide to establishing common practices in the collection, retention, and disposal of geologic research materials throughout the USGS. While constructing this report, the GCMS’s potential customers and their needs were considered. Two critical definitions have been clarified: a repository is a facility for the long-term management of geologic collections, and a collection is a set of specimens that have been brought together on the basis of some common characteristic. Required sample metadata for newly collected samples, as well as for older collections, were also stipulated and are listed and explained in this report. Several basic policies are also recommended by the GCMS in order to standardize operations among the physical repositories where collections are currently housed. The GCMS Collection Management Plan provides a set of protocols and templates for the management of scientific collections, including access, storage, transfer, and disposal of physical geologic samples and data. This plan is flexible to allow each repository to adapt the practices best suited to its collections. The general consideration for implementation of the GCMS is that all active USGS geologic sample repositories will form the core of GCMS and that participating science centers will develop procedures based on proposed GCMS methodologies. The GCMS is a collective resource for the entire USGS community and the users who discover the geologic materials kept in these repositories and seek to access them.

Circular↗

USGS2000

Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.

Conference Paper↗

USGS2009

NBII-SAIN Data Management Toolkit

The Strategic Plan for the U.S. Geological Survey Biological Informatics Program (2005-2009) recognizes the need for effective data management: Though the Federal government invests more than $600 million per year in biological data collection, it is difficult to address these issues because of limited accessibility and lack of standards for data and information...variable quality, sources, methods, and formats (for example observations in the field, museum specimens, and satellite images) present additional challenges. This is further complicated by the fast-moving target of emerging and changing technologies such as GPS and GIS. Even though these technologies offer new solutions, they also create new informatics challenges (Ruggiero and others, 2005). The USGS National Biological Information Infrastructure program, hereafter referred to as NBII, is charged with the mission to improve the way data and information are gathered, documented, stored, and accessed. The central objective of this project is a direct reflection of the purpose of NBII as described by John Mosesso, Program Manager of the U.S. Geological Survey-Biological Informatics Program-GAP Analysis: At the outset, the reason for bringing about NBII was that there were significant amounts of data and information scattered all over the U.S., not accessible, in incompatible formats, and that NBII was tasked with addressing this problem...NBII's focus is to pull data together that truly matters to someone or communities. Essentially, the core questions are: 1) what are the issues, 2) where is the data, and 3) how can we make it usable and accessible (John Mosesso, U.S. Geological Survey, oral commun., 2006). Redundancy in data collection can be a major issue when multiple stakeholders are involved with a common effort. In 2001 the U.S. General Accounting Office (USGAO) estimated that about 50 percent of the Federal government's geospatial data at the time was redundant. In addition, approximately 80 percent of the cost of a spatial information system is associated with spatial data collection and management (U.S. General Accounting Office, 2003). These figures indicate that the resources (time, personnel, money) of many agencies and organizations could be used more efficiently and effectively. Dedicated and conscientious data management coordination and documentation is critical for reducing such redundancy. Substantial cost savings and increased efficiency are direct results of a pro-active data management approach. In addition, details of projects as well as data and information are frequently lost as a result of real-world occurrences such as the passing of time, job turnover, and equipment changes and failure. A standardized, well documented database allows resource managers to identify issues, analyze options, and ultimately make better decisions in the context of adaptive management (National Land and Water Resources Audit and the Australia New Zealand Land Information Council on behalf of the Australian National Government, 2003). Many environmentally focused, scientific, or natural resource management organizations collect and create both spatial and non-spatial data in some form. Data management appropriate for those data will be contingent upon the project goal(s) and objectives and thus will vary on a case-by-case basis. This project and the resulting Data Management Toolkit, hereafter referred to as the Toolkit, is therefore not intended to be comprehensive in terms of addressing all of the data management needs of all projects that contain biological, geospatial, and other types of data. The Toolkit emphasizes the idea of connecting a project's data and the related management needs to the defined project goals and objectives from the outset. In that context, the Toolkit presents and describes the fundamental components of sound data and information management that are common to projects involving biological, geospatial, and other related data

Open-File Report↗

USGS1995

Fluid-inclusion evidence for past temperature fluctuations in the Kilauea East Rift Zone geothermal area, Hawaii

Heating and freezing data were obtained for fluid inclusions in hydrothermal quartz, calcite, and anhydrite from several depths in three scientific observation holes drilled along the lower East Rift Zone of Kilauea volcano, Hawaii. Compositions of the inclusion fluids range from dilute meteoric water to highly modified sea water concentrated by boiling. Comparison of measured drill-hole temperatures with fluid-inclusion homogenization-temperature ( T h ) data indicates that only about 15% of the fluid inclusions could have formed under the present thermal conditions. The majority of fluid inclusions studied must have formed during one or more times in the past when temperatures fluctuated in response to the emplacement of nearby dikes and their subsequent cooling. The fluid-inclusion data indicate that past temperatures in SOH-4 well were as much as 64°C hotter than present temperatures between 1000 and 1500 m depth and they were a maximum of 68°C cooler than present temperatures below 1500 m depth. Similarly, the data show that past temperatures near the bottoms of SOH-1 and SOH-2 wells were up to 45 and 59°C, respectively, cooler than the present thermal conditions; however, the remainder of fluid-inclusion T h values for these two drill holes suggest that the temperatures of the trapped waters were nearly the same as the present temperatures at these slightly shallower depths. Several hydrothermal minerals (erionite, mordenite, truscottite, smectite, chlorite-smectite, chalcedony, anhydrite, and hematite), occurring in the drill holes at higher temperatures than they are found in geothermal drill holes of Iceland or other geothermal areas, provide additional evidence for a recent heating trend.

Geothermics↗

USGS2017

Research article: Watershed management councils and scientific models: Using diffusion literature to explain adoption

Recent literature on the diffusion of innovations concentrates either specifically on public adoption of policy, where social or environmental conditions are the dependent variables for adoption, or on private adoption of an innovation, where emphasis is placed on the characteristics of the innovation itself. This article uses both the policy diffusion literature and the diffusion of innovation literature to assess watershed management councils' decisions to adopt, or not adopt, scientific models. Watershed management councils are a relevant case study because they possess both public and private attributes. We report on a survey of councils in the United States that was conducted to determine the criteria used when selecting scientific models for studying watershed conditions. We found that specific variables from each body of literature play a role in explaining the choice to adopt scientific models by these quasi-public organizations. The diffusion of innovation literature contributes to an understanding of how organizations select models by confirming the importance of a model's ability to provide better data. Variables from the policy diffusion literature showed that watershed management councils that employ consultants are more likely to use scientific models. We found a gap between those who create scientific models and those who use these models. We recommend shrinking this gap through more communication between these actors and advancing the need for developers to provide more technical assistance.

Environmental Practice↗

USGS2014

A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

Inland Waters↗

USGS2015

Hydrologic record extension of water-level data in the Everglades Depth Estimation Network (EDEN), 1991-99

The real-time Everglades Depth Estimation Network (EDEN) has been established to support a variety of scientific and water management purposes. The expansiveness of the Everglades, limited number of gaging stations, and extreme sensitivity of the ecosystem to small changes in water depth have created a need for accurate water-level and water-depth maps. The EDEN water-surface elevation model uses data from approximately 240 gages in the Everglades to create daily continuous interpolations of the water-surface elevation and water depth for the freshwater portion of the Everglades from 2000 to the present (2014). These maps provide hydrologic data previously unavailable for assessing biological and ecological studies. Ecologists working in the Everglades expressed a need to the EDEN project team for daily EDEN water-level surfaces from 1990 to 1999. The additional 10 years of surfaces will provide ecologists and resource managers with two decades (1991–2011) of surfaces to analyze hydrologic dynamics. Before 2000, many of the EDEN gages used to generate water surfaces were not in operation. These datasets were extended to provide estimations of hydrologic time-series histories. The general approach to the record extension (hindcasts) was to (1) create a database of available data from 1990 to the present; (2) use dynamic cluster analysis to group stations with similar hydrologic behaviors for subareas of the Everglades with a large number of stations; (3) use results from the cluster analysis to select candidate explanatory variables; (4) develop linear regression or artificial neural network models to extend water-level records; and (5) evaluate record extensions by using model performance statistics and comparison of water-surface maps for similar hydrologic conditions for the hindcasted period (1991–99) and measured period (2000–11). To hindcast and fill data records, 214 empirical models were developed—189 are linear regression models and 25 are artificial neural network models. The coefficient of determination (R 2 ) for 163 of the models is greater than 0.80 and the median percent model error (root mean square error divided by the range of the measured data) is 5 percent. To evaluate the performance of the hindcast models as a group, contour maps of modeled water-level surfaces at 2-centimeter (cm) intervals were generated using the hindcasted data. The 2-cm contour maps were examined for selected days to verify that water surfaces from the EDEN model are consistent with the input data. The biweekly 2-cm contour maps did show a higher number of issues during days in 1990 as compared to days after 1990. May 1990 had the lowest water levels in the Everglades of the 21-year dataset used for the hindcasting study. To hindcast these record low conditions in 1990, many of the hindcast models would require large extrapolations beyond the range of the predictive quality of the models. For these reasons, it was decided to limit the hindcasted data to the period January 1, 1991, to December 31, 1999. Overall, the hindcasted and gap-filled data are assumed to provide reasonable estimates of station-specific water-level data for an extended historical period to inform research and natural resource management in the Everglades.

Florida↗

USGS2001

TES premapping data: Slab ice and snow flurries in the Martian north polar night

In the 1970s, Mariner and Viking spacecraft observations of the north polar region of Mars revealed polar brightness temperatures that were significantly below the expected kinetic temperatures for CO 2 sublimation. For the past few decades, the scientific community has speculated as to the nature of these Martian polar cold spots. Thermal Emission Spectrometer (TES) thermal spectral data have shown these cold spots to result largely from fine‐grained CO 2 and have constrained most of these cold spots to the surface (or near‐surface). Cold spot formation is strongly dependent on topography, forming preferentially near craters and on polar slopes. TES data, combined with Mars Orbiter Laser Altimeter (MOLA) cloud data, suggest atmospheric condensates form a small fraction of the observed cold spots. TES observations of spectra close to a blackbody indicate that another major component of the polar cap is slab CO 2 ice; these spectrally bland regions commonly have a low albedo. The cause is uncertain but may result from most of the light being reflected toward the specular direction, from the slab ice being intrinsically dark, or from it being transparent. Regions of the cap where the difference between the brightness temperatures at 18 μm ( T 18 ) and 25 μm ( T 25 ) is less than 5° are taken to indicate deposits of slab ice. Slab ice is the dominant component of the polar cap at latitudes outside of the polar night.

Journal of Geophysical Research E: Planets↗

USGS2014

Reflections on a vision for integrated research and monitoring after 15 years

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

Aquatic Geochemistry↗

USGS1994

Bibliography of The World Energy Resources Program

The following publications were prepared in the course of World Energy Studies by program scientists. Most are open-file reports because we consider it our prime responsibility to get the program supporting data into the public record. Various of the authors have also seen fit to publish their work in refereed scientific journals and those publication outlets are also listed. The summation of the program work is reported in the proceedings volumes of the World Petroleum Congresses-see Global section of the bibliography. In those reports, petroleum resource data were aggregated by major petroleum resource countries. It is our intention to ultimately report resource data by petroleum basin in order to provide a closer tie of resource understanding and petroleum geology.

Open-File Report↗

USGS2019

A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats

This scientific investigations report describes an effort by the U.S. Geological Survey (USGS) that used research, monitoring data, and modeling to develop a methodology to assess both the current and future population-level consequences of wind energy development on species of birds and bats that are present in the United States during any part of their life cycle. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions with turbines, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology assesses species at the national and regional scales and identifies those species potentially in need of more detailed study, as well as those species that are likely at low risk from wind energy development. This approach is fundamentally different from existing methods focusing on impacts at individual facilities. This report supersedes USGS Scientific Investigations Report 2015–5066 by the same authors, which described a preliminary version of the methodology. Following reviews of the preliminary methodology by a panel of external experts, public comments, and additional internal review, the methodology was revised and finalized. The three components of the refined methodology described in this new report rely on publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics of species, and population models. First, three metrics are combined to determine direct and indirect relative effects from wind energy facilities to generate a list of species scores. Second, a generic population model estimates the expected change in population trend caused by the additive mortality from collisions with wind turbines. Third, the methodology combines an estimate of observed fatalities and an estimate of potential biological removal to assess the possibility of a decrease in population size. The latter two components are quantitative. In a test case, the methodology was used to analyze data for six bird species and three bat species. Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable or may require further study. These assumptions should be carefully considered when using outputs from the methodology. Increases in the quality of data for fatalities from collisions with wind turbines, species distributions, abundance, and demography will likely improve results for uses of the methodology. The methodology’s design identifies and prioritizes a subset of the bird and bat species that may experience population-level impacts from collisions with wind turbines, both currently and from future wind energy development in the United States. Results of an assessment using this methodology could focus future research to improve our understanding of those impacts and to guide avoidance and minimization strategies. In addition, this methodology can be used to identify species for more intensive demographic modeling or to highlight those species that may not require any additional research because effects of wind energy development on their populations are projected to be small. The effects of wind energy facilities on nine unidentified species used in the test case described in this report have not been assessed. Their data were simply used to show the application of the methodology to real-world data and the types of outputs it would produce.

Scientific Investigations Report↗

USGS2025

Estimated average annualized tsunami losses for the United States

Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels. Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below. ■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events. ■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin. ■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest. ■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats. ■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin. ■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea. Several historical events stand out because of their catastrophic impacts. ■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005). ■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982). ■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023). ■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024). ■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011). More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis. This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.

Alaska, California, Hawaii Oregon, Washington↗

USGS2010

Development of a channel classification to evaluate potential for cottonwood restoration, lower segments of the Middle Missouri River, South Dakota and Nebraska

This report documents development of a spatially explicit river and flood-plain classification to evaluate potential for cottonwood restoration along the Sharpe and Fort Randall segments of the Middle Missouri River. This project involved evaluating existing topographic, water-surface elevation, and soils data to determine if they were sufficient to create a classification similar to the Land Capability Potential Index (LCPI) developed by Jacobson and others (U.S. Geological Survey Scientific Investigations Report 2007–5256) and developing a geomorphically based classification to apply to evaluating restoration potential. Existing topographic, water-surface elevation, and soils data for the Middle Missouri River were not sufficient to replicate the LCPI. The 1/3-arc-second National Elevation Dataset delineated most of the topographic complexity and produced cumulative frequency distributions similar to a high-resolution 5-meter topographic dataset developed for the Lower Missouri River. However, lack of bathymetry in the National Elevation Dataset produces a potentially critical bias in evaluation of frequently flooded surfaces close to the river. High-resolution soils data alone were insufficient to replace the information content of the LCPI. In test reaches in the Lower Missouri River, soil drainage classes from the Soil Survey Geographic Database database correctly classified 0.8–98.9 percent of the flood-plain area at or below the 5-year return interval flood stage depending on state of channel incision; on average for river miles 423–811, soil drainage class correctly classified only 30.2 percent of the flood-plain area at or below the 5-year return interval flood stage. Lack of congruence between soil characteristics and present-day hydrology results from relatively rapid incision and aggradation of segments of the Missouri River resulting from impoundments and engineering. The most sparsely available data in the Middle Missouri River were water-surface elevations. Whereas hydraulically modeled water-surface elevations were available at 1.6-kilometer intervals in the Lower Missouri River, water-surface elevations in the Middle Missouri River had to be interpolated between streamflow-gaging stations spaced 3–116 kilometers. Lack of high-resolution water-surface elevation data precludes development of LCPI-like classification maps. An hierarchical river classification framework is proposed to provide structure for a multiscale river classification. The segment-scale classification presented in this report is deductive and based on presumed effects of dams, significant tributaries, and geological (and engineered) channel constraints. An inductive reach-scale classification, nested within the segment scale, is based on multivariate statistical clustering of geomorphic data collected at 500-meter intervals along the river. Cluster-based classifications delineate reaches of the river with similar channel and flood-plain geomorphology, and presumably, similar geomorphic and hydrologic processes. The dominant variables in the clustering process were channel width (Fort Randall) and valley width (Sharpe), followed by braiding index (both segments). Clusters with multithread and highly sinuous channels are likely to be associated with dynamic channel migration and deposition of fresh, bare sediment conducive to natural cottonwood germination. However, restoration potential within these reaches is likely to be mitigated by interaction of cottonwood life stages with the highly altered flow regime.

Scientific Investigations Report↗

USGS2014

The National Map hydrography data stewardship: what is it and why is it important?

The National Hydrography Dataset (NHD) and Watershed Boundary Dataset (WBD) were designed and populated by a large consortium of agencies involved in hydrography across the United States. The effort was led by the U.S. Geological Survey (USGS), the U.S. Environmental Protection Agency (EPA), and the Natural Resources Conservation Service (NRCS). The high-resolution NHD dataset, completed in 2007, is based on the USGS 7.5-minute series topographic maps at a scale of 1:24,000. There are now 26 million features in the NHD representing a 7.5 million mile stream network with over 6.5 million waterbodies. The six-level WBD, completed in 2010, is based on 1:24,000 scale data and contains over 23,000 watershed polygons. The NHD’s flow network, attribution, and linear referencing are used to conduct extensive scientific analyses. The NHD is ideal for cartographic applications such as the US Topo topographic map series, and also is available on the Geospatial Platform, which provides shared and trusted geospatial data, services, and applications for use by government agencies, their partners, and the public. The WBD watersheds are used by scientists and managers to identify discrete drainage areas. The ongoing maintenance of the NHD and WBD is essential for improving these datasets to meet the ever increasing demand for currency, additional detail, and more significant attribution. The best source of information about changes in local hydrography are users closest to the data, such as State and local governments, as well as Federal land management agencies, and other users of the data. The need for local knowledge has led to the creation of a collaborative data stewardship process to revise and maintain the NHD.

Fact Sheet↗

USGS2021

An attention U-Net model for detection of fine-scale hydrologic streamlines

Surface water is an irreplaceable resource for human survival and environmental sustainability. Accurate, finely detailed cartographic representations of hydrologic streamlines are critically important in various scientific domains, such as assessing the quantity and quality of present and future water resources, modeling climate changes, evaluating agricultural suitability, mapping flood inundation, and monitoring environmental changes. Conventional approaches to detecting such streamlines cannot adequately incorporate information from the complex three-dimensional (3D) environment of streams and land surface features. Such information is vital to accurately delineate streamlines. In recent years, high accuracy lidar data has become increasingly available for deriving both 3D information and terrestrial surface reflectance. This study develops an attention U-net model to take advantage of high-accuracy lidar data for finely detailed streamline detection and evaluates model results against a baseline of multiple traditional machine learning methods. The evaluation shows that the attention U-net model outperforms the best baseline machine learning method by an average F1 score of 11.25% and achieves significantly better smoothness and connectivity between classified streamline channels. These findings suggest that our deep learning approach can harness high-accuracy lidar data for fine-scale hydrologic streamline detection, and in turn produce desirable benefits for many scientific domains.

North Carolina↗

USGS2013

California State Waters Map series data catalog

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California's State Waters. The CSMP approach is to create highly detailed seafloor maps and associated data layers through the collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. CSMP has divided coastal California into 110 map blocks (fig. 1), each to be published individually as USGS Scientific Investigations Maps (SIMs) at a scale of 1:24,000. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the seafloor geology and shallow (to about 100 m) subsurface geology. This CSMP data catalog contains much of the data used to prepare the SIMs in the California State Waters Map Series. Other data that were used to prepare the maps were compiled from previously published sources (for example, onshore geology) and, thus, are not included herein.

California↗

USGS2023

Automated construction of Streamflow-Routing networks for MODFLOW—Application in the Mississippi Embayment region

In humid regions with dense stream networks, surface water exerts a fundamental control on the water levels and flow directions of shallow groundwater. Understanding interactions between groundwater and surface water is critical for managing groundwater resources and groundwater-dependent ecosystems. Representing streams in groundwater models has historically been arduous and error prone. In recent years, however, all the information needed to numerically describe stream boundary conditions for a model area has become readily available online, as have robust open-source software tools for translating that information to a model grid. The SFRmaker Python package leverages geospatial capabilities in the scientific Python ecosystem to robustly automate the production of input to the Streamflow-Routing (SFR) Package of MODFLOW from the National Hydrography Dataset Plus or other hydrography data. This report documents an application of SFRmaker to automate production of SFR Package input for groundwater models within the Mississippi Embayment Regional Aquifer Study area. SFR Package input was developed in three steps: (1) preprocessing to develop a single set of grid-independent flowlines from National Hydrography Dataset Plus version 2 data; (2) setting up the SFR package from the preprocessed flowlines, and (3) correcting streambed top elevations after an initial model run. Separating the hydrography preprocessing from the construction of SFR Package input was advantageous in that it minimized the need to repeat computationally expensive geoprocessing (thereby speeding model construction) and also allowed for the curation of a single set of grid-independent SFR input data that can be used for any MODFLOW model within the study area.

Mississippi Embayment Region↗

USGS2007

Geoinformatics 2007: data to knowledge

Geoinformatics is the term used to describe a variety of efforts to promote collaboration between the computer sciences and the geosciences to solve complex scientific questions. It refers to the distributed, integrated digital information system and working environment that provides innovative means for the study of the Earth systems, as well as other planets, through use of advanced information technologies. Geoinformatics activities range from major research and development efforts creating new technologies to provide high-quality, sustained production-level services for data discovery, integration and analysis, to small, discipline-specific efforts that develop earth science data collections and data analysis tools serving the needs of individual communities. The ultimate vision of Geoinformatics is a highly interconnected data system populated with high quality, freely available data, as well as, a robust set of software for analysis, visualization, and modeling.

Scientific Investigations Report↗