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USGS1994

Biomonitoring our streams

Testing for chemical pollution in our nation's streams has traditionally meant using analytical chemistry. In recent years, environmental agencies have endorsed biological monitoring to enhance or replace chemical monitoring. The theory behind biological monitoring (biomonitoring) is to use the organisms living in the aquatic system as a measure of water quality. This concept was applied to air quality and used by miners who took canaries into deep mines with them. If the canary died, the miners knew the air was bad, and they had to leave the mine. Biomonitoring an aquatic system uses the same theoretical approach . Aquatic organisms are subject to pollutants in the stream as it flows by, day or night. Consequently, the health of the organisms reflects the quality of the water they live in. If the pollution levels reach a critical concentration, certain organisms will die, migrate away, or fail to reproduce, eventually leading to the disappearance of those species at the polluted site. Normally, these organisms will return if conditions improve in the system. The three general components of an aquatic ecosystem that influence the biological community are: water chemistry, geomorphology, and hydrology. Each component influences the health of the biological community individually and together . Toxic chemicals are only a single factor within the water-chemistry component. The relation of these three components to each other can be shown on a triangle (figure 1). The relative importance of one component may change with time and location . At certain times of the year or in different geographical settings, a single factor may exert primary control on the well-being of the biological community. For example, straightening a stream and removing all woody debris drastically alters a stream's geomorphology. This results in loss of natural habitat and shelter for certain organisms. The organisms that require this shelter will disappear from the modified system. Separating the influence of one component from the others is difficult. Consideration of all three components and their interactions is critical when interpreting biomonitormg data.

Open-File Report↗

USGS2021

Approaches for assessing long-term annual yields of highway and urban runoff in selected areas of California with the Stochastic Empirical Loading and Dilution Model (SELDM)

The California Department of Transportation, commonly known as CalTrans, and other municipal separate storm sewer system permittees in California as well as other State departments of transportation nationwide need information about potential loads and yields (loads per unit area) of constituents of concern in stormwater runoff and discharges from stormwater best management practices (BMPs). Although its National Pollution Discharge Elimination System stormwater permit is focused on areas subject to total maximum daily load (TMDL) regulations, CalTrans builds and maintains BMPs to minimize the adverse effects of roadway runoff on receiving waters throughout the State. This report describes approaches used by the U.S. Geological Survey in cooperation with CalTrans for using the Stochastic Empirical Loading and Dilution Model (SELDM) to assess long-term annual yields of highway and urban runoff in selected areas of California. In this study, a series of regional and local yields were simulated to provide statewide planning-level estimates and more refined TMDL-specific yield values. SELDM was used to analyze 368 State roadway and urban runoff yields for 53 runoff quality constituents. The analyses included 222 random-seed analyses, 60 regional State roadway-runoff analyses, 24 regional urban roadway-runoff analyses, and 62 focused TMDL-area analyses. This report describes approaches and statistics used to analyze available hydrologic and runoff quality data in all analyses. Results for all analyses are provided in the model archive, but only a selected subset of results are presented as examples in this report. State roadway runoff, urban runoff, and BMP discharge yields for total suspended solids, total nitrogen, total phosphorus, and total zinc were selected as examples because they are widespread constituents of concern with substantial amounts of State roadway and urban runoff monitoring data. In this report, a hypothetical basin was specified by using available geographic information to demonstrate use of the State roadway and urban runoff yields to estimate long-term annual stormwater loads from developed areas. Application of these yields to the hypothetical basin indicates that although State-roadway yields may be higher than urban-runoff yields for some constituents, State-roadway loads may be a small proportion of total stormwater loads because State roadways themselves are a small fraction of the total impervious area in such basins. Although application of results from this study may have considerable uncertainty for any particular stormwater outfall, the study does provide robust estimates to support basin-scale runoff-load analyses in California. These analyses also provide estimates for the 12 U.S. Environmental Protection Agency level III ecoregions that are completely or partially within the boundaries of the State of California.

California↗

USGS2007

The National Assessment of Shoreline Change: A GIS compilation of vector cliff edges and associated cliff erosion data for the California coast

The U.S. Geological Survey has generated a comprehensive data clearinghouse of digital vector cliff edges and associated rates of cliff retreat along the open-ocean California coast. These data, which are presented herein, were compiled as part of the U.S. Geological Survey's National Assessment of Shoreline Change Project. Cliff erosion is a chronic problem along many coastlines of the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information including rates and trends of coastal cliff retreat. There is also a critical need for these data to be consistent from one region to another. One objective of this work is to a develop standard, repeatable methodology for mapping and analyzing cliff edge retreat so that periodic, systematic, and internally consistent updates of cliff edge position and associated rates of erosion can be made at a national scale. This data compilation for open-ocean cliff edges for the California coast is a separate, yet related study to Hapke and others, 2006 documenting shoreline change along sandy shorelines of the California coast, which is itself one in a series that includes the Gulf of Mexico and the Southeast Atlantic coast (Morton and others, 2004; Morton and Miller, 2005). Future reports and data compilations will include coverage of the Northeast U.S., the Great Lakes, Hawaii and Alaska. Cliff edge change is determined by comparing the positions of one historical cliff edge digitized from maps with a modern cliff edge derived from topographic LIDAR (light detection and ranging) surveys. Historical cliff edges for the California coast represent the 1920s-1930s time-period; the most recent cliff edge was delineated using data collected between 1998 and 2002. End-point rate calculations were used to evaluate rates of erosion between the two cliff edges. Please refer to our full report on cliff edge erosion along the California coastline at http://pubs.usgs.gov/of/2007/1133/ for additional information regarding methods and results (Hapke and others, 2007). Data in this report are organized into downloadable layers by region (Northern, Central and Southern California) and are provided as vector datasets with accompanying metadata. Vector cliff edges may represent a compilation of data from one or more sources and the sources used are included in the dataset metadata. This project employs the Environmental Systems Research Institute's (ESRI) ArcGIS as it's Geographic Information System (GIS) mapping tool and contains several data layers (shapefiles) that are used to create a geographic view of the California coast. The vector data form a basemap comprising polygon and line themes that include a U.S. coastline (1:80,000), U.S. cities, and state boundaries.

California↗

USGS2004

Economic analysis of alternative bison and elk management practices on the National Elk Refuge and Grand Teton National Park: A comparison of visitor and household responses

The U.S. Fish and Wildlife Service (FWS) and the National Park Service (NPS) are preparing a management plan for bison and elk inhabiting the National Elk Refuge (NER) and Grand Teton National Park (GTNP). These animals are part of the bison and elk herds in Jackson Hole, one of the largest concentrations of freeranging bison and elk in the world. A range of alternatives for managing the bison and elk herds in the project area will be developed in an Environmental Impact Statement. The EIS will likely include such issues as habitat management, disease management, winter-feeding and hunting programs related to the NER and GTNP. The purposes of this study are to determine how the current management and EIS alternatives for bison and elk inhabiting the NER and GTNP would change: Visitor use Total visitor expenditures in the local and regional economy Local area employment and income in the local and regional economy Visitor net economic benefits Acceptability of individual elk and bison management practices to visitors and household living in Teton County, rest of Wyoming, and rest of the United States. Assessing public attitudes and economic effects for different EIS alternatives can provide managers with valuable information regarding the advantages and disadvantages of these alternatives. Economic issues such as local job and income effects are often raised by interest groups opposed to changes in current agency management actions. Having objective data on what the job and income impacts are can help to defuse that issue. Survey data on visitor and public preferences is also useful to supplement the traditional public involvement process conducted as part of the EIS process. This is because the survey reaches visitors and a broad geographic array of residents who may not typically participate in the traditional EIS public involvement process. That is, the survey reflects the effort of the EIS planning team reaching out to the public, rather than requiring the public to come to the EIS meeting locations. Attendance at public meetings is often inconvenient for occasional visitors to the NER and GTNP who frequently live long distances from the relevant FWS and NPS offices. It is also inconvenient for residents of states outside the state where the resource is located.

Wyoming↗

USGS2006

The National Assessment of Shoreline Change: A GIS compilation of vector shorelines and associated shoreline change data for the sandy shorelines of the California coast

Introduction The Coastal and Marine Geology Program of the U.S. Geological Survey has generated a comprehensive data clearinghouse of digital vector shorelines and shoreline change rates for the sandy shoreline along the California open coast. These data, which are presented herein, were compiled as part of the U.S. Geological Survey's National Assessment of Shoreline Change Project. Beach erosion is a chronic problem along many open-ocean shores of the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information including rates and trends of shoreline migration. There is also a critical need for shoreline change data that is consistent from one coastal region to another. One purpose of this work is to develop standard, repeatable methods for mapping and analyzing shoreline movement so that periodic, systematic, and internally consistent updates of shorelines and shoreline change rates can be made at a National Scale. This data compilation for open-ocean, sandy shorelines of the California coast is one in a series that already includes the Gulf of Mexico and the Southeast Atlantic Coast (Morton et al., 2004; Morton et al., 2005) and will eventually cover Washington, Oregon, and parts of Hawaii and Alaska. Short- and long-term shoreline change evaluations are determined by comparing the positions of three historical shorelines digitized from maps, with a modern shoreline derived from LIDAR (light detection and ranging) topographic surveys. Historical shorelines generally represent the following time-periods: 1850s-1880s, 1920s-1930s, and late 1940s-1970s. The most recent shoreline is from data collected between 1997 and 2002. Long-term rates of change are calculated by linear regression using all four shorelines. Short-term rates of change are end-point rate calculations using the two most recent shorelines. Please refer to our full report on shoreline change of the California coastline at http://pubs.usgs.gov/of/2006/1219/ for additional information regarding methods and results (Hapke et al., 2006). Data in this report are organized into downloadable layers by region (Northern, Central and Southern California) and are provided as vector datasets with metadata. Vector shorelines may represent a compilation of data from one or more sources and these sources are included in the dataset metadata. This project employs the Environmental Systems Research Institute's (ESRI) ArcGIS as it's GIS mapping tool and contains several data layers (shapefiles) that are used to create a geographic view of the California Coast. These vector data form a basemap comprised of polygon and line themes that include a U.S. coastline (1:80,000), U.S. cities, and state boundaries.

California↗

USGS2005

Submersed Aquatic Vegetation Modeling Output Online

Introduction The ability to predict the distribution of submersed aquatic vegetation in the Upper Mississippi River on the basis of physical or chemical variables is useful to resource managers. Wildlife managers have a keen interest in advanced estimates of food quantity such as American wildcelery (Vallisneria americana) population status to give out more informed advisories to hunters before the fall hunting season. Predictions for distribution of submerged aquatic vegetation beds can potentially increase hunter observance of voluntary avoidance zones where foraging birds are left alone to feed undisturbed. In years when submersed aquatic vegetation is predicted to be scarce in important wildlife habitats, managers can get the message out to hunters well before the hunting season (Jim Nissen, Upper Mississippi River National Wildlife and Fish Refuge, La Crosse District Manager, La Crosse, Wisconsin, personal communication). We developed a statistical model to predict the probability of occurrence of submersed aquatic vegetation in Pool 8 of the Upper Mississippi River on the basis of a few hydrological, physical, and geomorphic variables. Our model takes into consideration flow velocity, wind fetch, bathymetry, growing-season daily water level, and light extinction coefficient in the river (fig. 1) and calculates the probability of submersed aquatic vegetation existence in Pool 8 in individual 5- x 5-m grid cells. The model was calibrated using the data collected in 1998 (516 sites), 1999 (595 sites), and 2000 (649 sites) using a stratified random sampling protocol (Yin and others, 2000b). To validate the model, we chose the data from the Long Term Resource Monitoring Program (LTRMP) transect sampling in backwater areas (Rogers and Owens 1995; Yin and others, 2000a) and ran the model for each 5- x 5-m grid cell in every growing season from 1991 to 2001. We tallied all the cells and came up with an annual average percent frequency of submersed aquatic vegetation occurrence and compared the results with actual LTRMP survey data (fig. 2). Both a paired Student's test (P = 0.4620) and a Wilcoxon's two-sample test (P = 0.4738) did not contradict our null hypothesis that the model prediction and the sampling data are statistically the same. We have not found an effective statistical test to compare model-predicted spatial pattern with aerial photography geographic information, but we are satisfied with the model's outcome on the basis of visual inspection (fig. 3). A unique feature about this model is that a prediction can be made by the end of June each year; therefore, providing wildlife managers an assessment of current year vegetation growth condition 3 to 4 months ahead of the arrival of migrating waterfowl that feed on submersed aquatic vegetation. We are working with the LTRMP partnership to create a mechanism so that model predictions (fig. 4) can be updated annually and the results posted on the LTRMP Web site. Our model underestimated the prevalence of vegetation from 2001 to 2004. We speculate that the summer water level reduction conducted in 2001 and 2002 triggered vegetation responses that are outside the model's domain. Future enhancement of the model will incorporate the summer water level drawdown effects as well as the effects of growth conditions in previous years.

Open-File Report↗

USGS2007

Eogenetic karst hydrology: Insights from the 2004 hurricanes, peninsular Florida

Eogenetic karst lies geographically and temporally close to the depositional environment of limestone in warm marine water at low latitude, in areas marked by midafternoon thunderstorms during a summer rainy season. Spring hydrographs from such an environment in north-central Florida are characterized by smooth, months-long, seasonal maxima. The passage of Hurricanes Frances and Jeanne in September 2004 over three field locations shows how the eogenetic karst of the Upper Floridan Aquifer responds to unequivocal recharge events. Hydrographs at wells in the High Springs area, Rainbow Springs, and at Morris, Briar, and Bat Caves all responded promptly with a similar drawn-out rise to a maximum that extended long into the winter dry season. The timing indicates that the typical hydrograph of eogenetic karst is not the short-term fluctuations of springs in epigenic, telogenetic karst, or the smoothed response to all the summer thunderstorms, but rather the protracted response of the system to rainfall that exceeds a threshold. The similarity of cave and noncave hydrographs indicates distributed autogenic recharge and a free communication between secondary porosity and permeable matrix - both of which differ from the hydrology of epigenic, telogenetic karst. At Briar Cave, drip rates lagged behind the water table rise, suggesting that recharge was delivered by fractures, which control the cave's morphology. At High Springs, hydrographs at the Santa Fe River and a submerged conduit apparently connected to it show sharp maxima after the storms, unlike the other cave hydrographs. Our interpretation is that the caves, in general, are discontinuous. ?? 2007 National Ground Water Association.

Ground Water↗

USGS2024

Identifying transportation data and system needs for a Federal lands transportation data platform

Executive Summary Modern transportation and land-use planning efforts include information from many sources to address topics such as safety, efficiency, commercial, and social needs. This wide breadth of topics provides opportunities for collaboration and development of common tools for diverse users. In many cases, different information systems provide the spatial data and geographic content necessary for transportation and land-use planners to consider multiple lines of evidence. The Federal Highway Administration Office of Federal Lands Highway (FLH) and Federal Land Management Agency partners use detailed spatial and quantitative data to inform transportation decisions. However, logistic challenges to data sharing exist because data are often managed by separate agencies; data-exchange frameworks and interagency data agreements are insufficient; and consistency from aggregated data requires maintenance, coordination, and supporting infrastructure. The FLH and U.S. Geological Survey collaboratively examined (1) use and availability of spatial data for transportation planning and (2) a possible mechanism to use more shared and consistent data in a common planning environment. The goals of this collaborative effort were to describe data needs from the perspective of planners and to identify opportunities for shared data resources. Results presented here focus on two workshops and a subsequent investigation of data and tools available from partner agencies. The objectives of this report are to (1) describe information used in transportation planning with geographic data; (2) identify spatially explicit data that inform transportation plans and could be shared among all partners; and (3) describe current platforms, planning and administrative opportunities, and potential barriers to developing an integrated planning tool. Key information and data needs were identified in three major classes: system, user, and influential factors. System data are parts of the transportation network and information about the condition of individual segments and the network. User data provide details about the function of the system and insights into potential needs; for example, user trips between source and destinations inform road and network demands that can lead to congestion and safety issues (in the future, user data might also include scenarios and projections based on land-use plans). Influential data represent social and environmental factors that influence transit demands and network conditions. These factors could be popular locations or seasonal events that influence demand and congestion; wildlife habitat or migration intersections that affect safety and management priorities; or geologic features that influence hazards, maintenance, and safety. Responses described here provide specific information for web-tool design and give a framework for interagency communication and cooperation to address specific information needs for integrated planning. Existing web-mapping and web-services, and the data that inform them, are also described. Commonly, these data are created and published by one agency, and the core users are outside of that agency; for example, threatened species distributions are published by the U.S. Fish and Wildlife Service for consideration by planners in advance of National Environmental Policy Act (42 U.S.C. 4321 et seq.) evaluation. This report is provided to inform FLH leaders and Federal Land Management Agency partners by articulating user needs and requirements for integrated planning tool(s). Programmers creating a secure web-based data-sharing platform (with data-viewing, -analysis and -download functions) can use the information presented here to organize data and user interfaces. This integrated perspective can help FLH and Federal Land Management Agency partners develop transportation networks that better serve the needs of people in local communities and across States and the Nation.

Open-File Report↗

USGS2013

Archive of U.S. Geological Survey selected single-beam bathymetry datasets, 1969-2000

New national programs, as well as natural and man-made disasters, have raised awareness about the need to find new and improved ways to share information about the coastal and marine environment with a wide-ranging public audience. The U.S. Geological Survey (USGS) Coastal and Marine Geology Program (CMGP) has begun a large-scale effort to incorporate the program's published, digital geophysical data into a single point of access known as the Coastal and Marine Geoscience Data System (CMGDS) (http://cmgds.marine.usgs.gov/). To aid in data discovery, work is also being done to import CMGP data into highly visible data and information resources, such as the National Oceanic and Atmospheric Administration's (NOAA) National Geophysical Data Center (NGDC) and two widely used Earth-science tools, GeoMapApp (GMA) (http://www.geomapapp.org) and Virtual Ocean (VO) (http://www.virtualocean.org/). This task of the CMGP Integrated Data Management System project will help support information exchange with partners, regional planning groups, and the public, as well as facilitate integrated spatial-data analysis. Sharing USGS-CMGP geophysical data via CMGDS, NGDC, GMA, and VO will aid data discovery and enable the data to support new purposes beyond those for which the data were originally intended. In order to make data available to NGDC, and from there into GMA and VO, the data must be reformatted into a standard exchange format and published. In 1977, a group of geophysical data managers from the public and private sectors developed the MGD77 format as the standard exchange format for geophysical data. In 2010, a tab-delimited version of the format was added as MGD77T (Hittelman and others, 1977). The MGD77T geophysical data format can include bathymetry, magnetics, gravity, and seismic navigation data. It is used for the transmission of data between marine institutions, data centers, and can be used by various software programs as an exchange format. A header (documentation) file and data file are created for each survey (Hittelman and others, 1977). More details about the MGD77T format are available at http://www.ngdc.noaa.gov/mgg/dat/geodas/docs/mgd77.pdf (74MB PDF). This archive describes the detailed steps used to convert single-beam bathymetry and navigation files into the MGD77T format (Hittelman and others, 1977) for submission to NGDC and formal Federal Geographic Data Committee (FGDC) (http://www.fgdc.gov/metadata) metadata as a publication of these single-beam bathymetry datasets.

Data Series↗

USGS2007

Scale-dependent approaches to modeling spatial epidemiology of chronic wasting disease.

This e-book is the product of a second workshop that was funded and promoted by the United States Geological Survey to enhance cooperation between states for the management of chronic wasting disease (CWD). The first workshop addressed issues surrounding the statistical design and collection of surveillance data for CWD. The second workshop, from which this document arose, followed logically from the first workshop and focused on appropriate methods for analysis, interpretation, and use of CWD surveillance and related epidemiology data. Consequently, the emphasis of this e-book is on modeling approaches to describe and gain insight of the spatial epidemiology of CWD. We designed this e-book for wildlife managers and biologists who are responsible for the surveillance of CWD in their state or agency. We chose spatial methods that are popular or common in the spatial epidemiology literature and evaluated them for their relevance to modeling CWD. Our opinion of the usefulness and relevance of each method was based on the type of field data commonly collected as part of CWD surveillance programs and what we know about CWD biology, ecology, and epidemiology. Specifically, we expected the field data to consist primarily of the infection status of a harvested or culled sample along with its date of collection (not date of infection), location, and demographic status. We evaluated methods in light of the fact that CWD does not appear to spread rapidly through wild populations, relative to more highly contagious viruses, and can be spread directly from animal to animal or indirectly through environmental contamination. We discovered that many of the wellpublished methods were developed for fast-spreading human diseases, such as influenza and measles. While these methods are applicable to fast spreading wildlife diseases, such as foot-and-mouth disease or West Nile virus, many are not likely to work well for CWD. Only limited data exist to evaluate geographic and spatial spread because many locations where we find CWD tend to be locations where samples have just been taken or sample sizes have just become large enough to have a high probability of detecting a low prevalence. Consequently, methods that work well to describe or predict the spread of foot-and-mouth disease throughout England, which occurred within a year, do not work well for describing or predicting CWD spread. We did not exclude methods that we regarded as inappropriate; rather, we included methods that are commonly used for disease epidemiology and then discussed their applicability for modeling the spatial epidemiology of CWD. We hope including inappropriate methods with an explanation of why they are ill-suited for CWD will make it easier to drop them from consideration and explain to others why they were not recommended for spatial modeling of CWD. We organized the three chapters by scale and extent for which each method was developed or best suited. The first chapter covers methods appropriate to multi-jurisdictional or multi-state modeling, which we call “regional” scale. The second chapter covers methods appropriate for within state areas such as wildlife management units or metapopulations, which we call “landscape” scale. The third chapter covers methods appropriate for population or individual-based modeling, which we call “fine” scale. We know this rubric is somewhat artificial because many methods work at multiple scales. We hope, however, that this structure addresses some of the challenges faced by managers that work at local, regional, state, and national scales. Further, the resolution of empirical data often changes with spatial scale, which affects the utility of different modeling approaches. For example, individual-based models work best at modeling spread within populations, while risk analysis is most useful for summarizing data over larger scales such as a region. Because some methods are applicable at several scales, however, we included a graphic at the beginning of each method that indicates the range of scales for which it applies. For example, the graphic to the right indicates that the method is most applicable for regional-scale modeling. There is also a question of resolution as well as scale and extent for each method. CWD surveillance data have been collected over large areas, such as a wildlife management unit or state, but the resolution of the data may be fine scale with GPS locations for many samples. For each method, we described the required resolution of the data and describe the type of data required, as well as what questions the method could answer and how useful the method is, given typical CWD data. For each scale, we presented a focal approach that would be useful for understanding the spatial pattern and epidemiology of CWD, as well as being a useful tool for CWD management. The focal approaches include risk analysis and micromaps for the regional scale, cluster analysis for the landscape scale, and individual based modeling for the fine scale of within population. For each of these methods, we used simulated data and walked through the method step by step to fully illustrate the “how to”, with specifics about what is input and output, as well as what questions the method addresses. We also provided a summary table to, at a glance, describe the scale, questions that can be addressed, and general data required for each method described in this e-book. We hope that this review will be helpful to biologists and managers by increasing the utility of their surveillance data, and ultimately be useful for increasing our understanding of CWD and allowing wildlife biologists and managers to move beyond retroactive fire-fighting to proactive preventative action.

Book↗

USGS2007

Integration of seafloor point data in usSEABED

Sediments of the beach, nearshore, and continental shelves record a complex interplay of processes including wave energy and direction , currents, beach erosion or accretion, bluff or cliff retreat, fluvial input, sediment longshore and cross-shelf transport processes, contaminant content and transport, sediment sources and sinks, and others. In turn, sediments and rocks modify wave patterns, affect recreation and tourism, and provide habitat for fish, epifauna, and infauna. Character of the surficial seafloor also influences navigation, commercial and recreational fishing and gathering of other food sources, communication, piplines, national defense, and provides geologic resources including sand and gravel aggregates, minerals, and real or potential energy sources. The beaches, nearshore, and continental margins fall under overlapping levels of managerial responsibility between Federal, State, regional, and local government agencies and consortia. In addition, universities and other academic institutions investigate these places for pure or applied scientific reasons. Mapping is usually the first step in understanding any issue and is often comprised of remotely gathered geophysical data such as bathymetry and backscatter imagery, and groundtruthing; that is, the collection of physical and virtual samples to tie the remotely gathered data to reality. The physical samples are described and (or) carefully analyzed for grain-size information -- which records both the site's physical conditions and geologic past -- and commonly, for constituent components such as mineral and rock types (to determine onland sources and in situ chemical processes), carbonate and organic content and microfossils (for biological and oceanographic influences), and structure such as layering and bioturbation (for physical influences). The samples may also be subjected to physical tests such as comp[action analyses, liquefaction or plasticity limits, ans other parameters important when considering construction of offshore structures. In recent years, virtual sampling of the seafloor has become popular, through the use of towed video or photographic equipment and the addition of camera to oceanographic equipment such as corers and tripods. Before about ten years ago, most maps were made by hand. Recently, with the advent of desktop GIS packages, map making and resource analysis can be done nearly "on-the-fly" if geographically located data exist. While the problems of projection, scale, and resolution of digitized paper maps are commonly known amongst GIS-users, access to the original underlying point data allows for maps to be regenerated for digital use using statistically proven methods, provides increasing data density by including multiple studies, as well as allows the point data to be used in other ways than just mapping. These point data may be available in raw or refined or in worded descriptions. Raw data such as granulometric analyses can be manipulated through the use of known equations or empirical relationships to provide information about other parameters of the sediment, such as mean grainsize, sorting, erodability, or rugosity. If refined data are presented such as gravel, sand, and mud percentages, the parameter noted earlier may be estimated. In the case of worded descriptions, values for geologic terms can be assigned, for example, "fine sand" equate to 0.2 mm sized particles, to provide numeric terms for GIS or modeling purposes.

Conference Paper↗

USGS2012

Flood-inundation maps for Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, Atlanta, Georgia

Digital flood-inundation maps for a 5.5-mile reach of the Peachtree Creek from the Norfolk Southern Railway bridge to the Moores Mill Road NW bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with the City of Atlanta, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Peachtree Creek at Atlanta, Georgia (02336300) and the USGS streamgage at Chattahoochee River at Georgia 280, near Atlanta, Georgia (02336490). Current water level (stage) at these USGS streamgages may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Peachtree Creek, which is available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC–RAS software for a 6.5-mile reach of Peachtree Creek and was used to compute flood profiles for a 5.5-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Peachtree Creek at Atlanta, Georgia, streamgage (02336300), and the Chattahoochee River at Georgia 280, near Atlanta, Georgia, streamgage (02336490) as well as high water marks collected during the 2010 annual peak flow event. The hydraulic model was then used to determine 50 water-surface profiles. The profiles are for 10 flood stages at the Peachtree Creek streamgage at 1-foot intervals referenced to the streamgage datum and ranging from just above bankfull stage (15.0 feet) to approximately the highest recorded water level at the streamgage (24.0 feet). At each stage on Peachtree Creek, five stages at the Chattahoochee River streamgage, from 26.4 feet to 38.4 feet in 3-foot intervals, were used to determine backwater effects. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from Light Detection and Ranging (LiDAR) data having a 0.3-foot vertical and 16.4-foot horizontal resolution—to delineate the area flooded for each 1-foot increment of stream stage. The availability of these maps, when combined with real-time information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with critical information during flood response activities, such as evacuations and road closures as well as for postflood-recovery efforts.

Georgia↗

USGS2000

Nutrient, suspended-sediment, and total suspended-solids data for surface water in the Great Salt Lake basins study unit, Utah, Idaho, and Wyoming, 1980-95

Selected nitrogen and phosphorus (nutrient), suspended-sediment and total suspended-solids surface-water data were compiled from January 1980 through December 1995 within the Great Salt Lake Basins National Water-Quality Assessment study unit, which extends from southeastern Idaho to west-central Utah and from Great Salt Lake to the Wasatch and western Uinta Mountains. The data were retrieved from the U.S. Geological Survey National Water Information System and the State of Utah, Department of Environmental Quality, Division of Water Quality database. The Division of Water Quality database includes data that are submitted to the U.S. Environmental Protection Agency STOrage and RETrieval system. Water-quality data included in this report were selected for surface-water sites (rivers, streams, and canals) that had three or more nutrient, suspended-sediment, or total suspended-solids analyses. Also, 33 percent or more of the measurements at a site had to include discharge, and, for non-U.S. Geological Survey sites, there had to be 2 or more years of data. Ancillary data for parameters such as water temperature, pH, specific conductance, streamflow (discharge), dissolved oxygen, biochemical oxygen demand, alkalinity, and turbidity also were compiled, as available. The compiled nutrient database contains 13,511 samples from 191 selected sites. The compiled suspended-sediment and total suspended-solids database contains 11,642 samples from 142 selected sites. For the nutrient database, the median (50th percentile) sample period for individual sites is 6 years, and the 75th percentile is 14 years. The median number of samples per site is 52 and the 75th percentile is 110 samples. For the suspended-sediment and total suspended-solids database, the median sample period for individual sites is 9 years, and the 75th percentile is 14 years. The median number of samples per site is 76 and the 75th percentile is 120 samples. The compiled historical data are being used in the basinwide sampling strategy to characterize the broad-scale geographic and seasonal water-quality conditions in relation to major contaminant sources and background conditions. Data for this report are stored on a compact disc.

Idaho, Utah, Wyoming↗

USGS2008

Methods and Indicators for Assessment of Regional Ground-Water Conditions in the Southwestern United States

Monitoring the status and trends in the availability of the Nation's ground-water supplies is important to scientists, planners, water managers, and the general public. This is especially true in the semiarid to arid southwestern United States where rapid population growth and limited surface-water resources have led to increased use of ground-water supplies and water-level declines of several hundred feet in many aquifers. Individual well observations may only represent aquifer conditions in a limited area, and wells may be screened over single or multiple aquifers, further complicating single-well interpretations. Additionally, changes in ground-water conditions may involve time scales ranging from days to many decades, depending on the timing of recharge, soil and aquifer properties, and depth to the water table. The lack of an easily identifiable ground-water property indicative of current conditions, combined with differing time scales of water-level changes, makes the presentation of ground-water conditions a difficult task, particularly on a regional basis. One approach is to spatially present several indicators of ground-water conditions that address different time scales and attributes of the aquifer systems. This report describes several methods and indicators for presenting differing aspects of ground-water conditions using water-level observations in existing data-sets. The indicators of ground-water conditions developed in this study include areas experiencing water-level decline and water-level rise, recent trends in ground-water levels, and current depth to ground water. The computer programs written to create these indicators of ground-water conditions and display them in an interactive geographic information systems (GIS) format are explained and results illustrated through analyses of ground-water conditions for selected alluvial basins in the Lower Colorado River Basin in Arizona.

Scientific Investigations Report↗

USGS2015

A rapid approach for automated comparison of independently derived stream networks

This paper presents an improved coefficient of line correspondence (CLC) metric for automatically assessing the similarity of two different sets of linear features. Elevation-derived channels at 1:24,000 scale (24K) are generated from a weighted flow-accumulation model and compared to 24K National Hydrography Dataset (NHD) flowlines. The CLC process conflates two vector datasets through a raster line-density differencing approach that is faster and more reliable than earlier methods. Methods are tested on 30 subbasins distributed across different terrain and climate conditions of the conterminous United States. CLC values for the 30 subbasins indicate 44–83% of the features match between the two datasets, with the majority of the mismatching features comprised of first-order features. Relatively lower CLC values result from subbasins with less than about 1.5 degrees of slope. The primary difference between the two datasets may be explained by different data capture criteria. First-order, headwater tributaries derived from the flow-accumulation model are captured more comprehensively through drainage area and terrain conditions, whereas capture of headwater features in the NHD is cartographically constrained by tributary length. The addition of missing headwaters to the NHD, as guided by the elevation-derived channels, can substantially improve the scientific value of the NHD.

Cartography and Geographic Information Science↗

USGS2015

Special considerations for specimen collections that may be involved in law enforcement cases

Causes of mortality in wildlife include natural conditions—such as the viral, bacterial, and fungal diseases discussed in other chapters of this manual—and human intervention. Direct human intervention in wildlife deaths may be associated with individual human actions, such as gunshot or poisonings, or with institutions, such as wind farms or mining operations. Mortality that can be directly attributed to humans may be considered a crime based on the animal(s) affected and (or) the agent used. Wildlife laws were established to protect our nation’s wildlife resources and assist in conserving healthy populations of native wildlife. A variety of laws pertain to wildlife, such as the Migratory Bird Treaty Act, which makes it illegal, except as permitted, to capture, kill, or possess a portion or all of any migratory bird, a member of the group that includes the vast majority of wild birds present in the United States. Similar to pathogens that can spread unchecked through a wild population, a person or an institution that illegally kills wildlife may continue this practice indefinitely or until the illegal activities are detected and addressed. Convicting the perpetrator of a crime, however, requires that certain practices and procedures be followed so that a solid legal case can be constructed. As with any crime, investigation of the event is led by law enforcement personnel who are well-versed in the applicable laws, oversee the collection of evidence, and pursue persons or entities of interest. These individuals are uniquely qualified and trained to maintain the integrity of evidence, evaluate suspects to effectively prosecute the case, and effect the penalties of the law. The investigation of direct crimes against humans may involve teams of 5–10 law enforcement agents and specialists—each with a certain focus such as blood spatter, fingerprints, or ballistics—in processing a crime scene. In contrast, investigations of crimes against wildlife generally involve markedly fewer wildlife law enforcement agents, and in many instances of unlawful wildlife death, only one law enforcement agent is available to process an entire crime scene and work on a case. Thus, the assistance of individuals familiar with the geographical area, the endemic animal populations, and the local ecology can be very important for building an effective case. The aims of this chapter are to 1) help biologists or field personnel recognize the signs that indicate a crime may have been committed, and 2) to give readers a basic understanding of how a wildlife crime scene is processed. This chapter is not intended to give readers the tools to investigate a crime scene alone, but will hopefully make them a valuable asset to law enforcement agents who respond to the scene. An effectively processed case, resulting in prosecution of a suspect, supports the law as a deterrent to future acts that could endanger the conservation of wildlife.

Techniques and Methods↗

USGS2014

Trails through time: A geologist's guide to Jefferson County open space parks

Introduction Jefferson County straddles one of the most conspicuous and important geographic and geologic boundaries in western North America, the eastern flank of the Rocky Mountains. To the east you can travel 1,100 miles across Great Plains and Central Lowlands before you sight the western foothills of the Appalachians. If you travel in the other direction you will cross or skirt mountain range after mountain range until you sight the Coast Range near San Francisco, more than 900 miles to the west. Many of these mountains have different ages and origins than the Colorado mountains, but they are all part of the great mountain belt called the North American Cordillera that extends along the western edge of the continent from Alaska through Mexico. What is the reason for the remarkably straight and abrupt eastern flank of the Colorado Front Range? The brief answer is that it marks the edge of a block of ancient metamorphic and igneous rocks that has been uplifted relative to younger flat-laying sedimentary rocks that underlie the plains to the east. During the uplift, the sedimentary rocks along the boundary have been uplifted and tilted eastward to form the discontinuous line of hogback ridges that parallel the mountain front. Erosion during and after the uplift has removed the sedimentary rocks that once lay above the harder rocks of the mountain uplift, carved the scenic peaks and mountain canyons in the hard crystalline rocks of uplifted block, and worn away the softer layers of sedimentary rocks of the plains, but left a few of the harder upturned layers along the mountain front as hogback ridges. Jefferson County Open Space Parks, as well as other nearby parks and National Forest lands, offer marvelous opportunities to explore the geologic story behind this singular landscape. At first the distribution of rocks of different ages and types seems almost random, but careful study of the rocks and landscape features reveals a captivating geologic story, a history that tells of the building of the foundations of the continent, the rise and destruction of longvanished mountain ranges, the ebb and flow of ancient seas, and the constant shaping and reshaping of the landscape in response to the never-ending interplay between uplift and erosion. This historical account is constantly being improved and expanded as new evidence accumulates and new interpretations evolve.

Colorado↗

USGS2015

Comparison of U.S. net import reliance for nonfuel mineral commodities—A 60-year retrospective (1954–1984–2014)

Introduction The economic vitality and national security of the United States depend on the reliable supply of numerous nonfuel mineral commodities. Over the past six decades, many of these commodities have been sourced increasingly from outside the United States. The mix of commodities for which the United States is import dependent has changed as technologies have advanced, as substitute materials have been developed, and as world economies have changed. Although reliance on imports is only one of the many factors that determine supply risk, a clear, long-term trend has emerged from the data compiled and published by the U.S. Geological Survey, National Minerals Information Center (USGS–NMIC), and its predecessor organizations. Because the global distribution of mineral resources and reserves is not uniform, the United States has always been import reliant for some mineral commodities. Essentially, the type of commodities and the countries from which they are sourced determine risk related to import dependence. In light of projections that 2.5 billion to 3 billion people globally could move into the middle class by 2030, the demand for many types of mineral commodities is likely to continue to increase. Recent concerns regarding so-called “critical minerals” have been driven by market dislocations in the rare-earth-element supply chain in 2010 that resulted from a short-term policy decision by the Government of the People’s Republic of China to limit exports. That policy has since been changed as a result of actions by the World Trade Organization, but the events that followed, such as higher prices and intensive efforts to diversify sources of supply, illustrate the underlying issues of supply risk and the influence that disruptions can have on supply. These factors are often used in the classification of a mineral commodity as “critical.” The USGS–NMIC collects, analyzes, and disseminates information on a monthly, quarterly, or annual basis for more than 90 nonfuel mineral commodities from more than 180 countries. These data indicate that from 1954 through 2014 there was (1) a clear increase in the number and type of nonfuel mineral commodities for which the United States was net import reliant, (2) an increase in the percentage of import reliance for individual nonfuel mineral commodities, and (3) a shift in the geographic distribution of the source countries.

Fact Sheet↗