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100 records · Page 6Linked to original sources
USGS2000

Obtaining Streamflow Statistics for Massachusetts Streams on the World Wide Web

A World Wide Web application has been developed to make it easy to obtain streamflow statistics for user-selected locations on Massachusetts streams. The Web application, named STREAMSTATS (available at http://water.usgs.gov/osw/streamstats/massachusetts.html ), can provide peak-flow frequency, low-flow frequency, and flow-duration statistics for most streams in Massachusetts. These statistics describe the magnitude (how much), frequency (how often), and duration (how long) of flow in a stream. The U.S. Geological Survey (USGS) has published streamflow statistics, such as the 100-year peak flow, the 7-day, 10-year low flow, and flow-duration statistics, for its data-collection stations in numerous reports. Federal, State, and local agencies need these statistics to plan and manage use of water resources and to regulate activities in and around streams. Engineering and environmental consulting firms, utilities, industry, and others use the statistics to design and operate water-supply systems, hydropower facilities, industrial facilities, wastewater treatment facilities, and roads, bridges, and other structures. Until now, streamflow statistics for data-collection stations have often been difficult to obtain because they are scattered among many reports, some of which are not readily available to the public. In addition, streamflow statistics are often needed for locations where no data are available. STREAMSTATS helps solve these problems. STREAMSTATS was developed jointly by the USGS and MassGIS, the State Geographic Information Systems (GIS) agency, in cooperation with the Massachusetts Departments of Environmental Management and Environmental Protection. The application consists of three major components: (1) a user interface that displays maps and allows users to select stream locations for which they want streamflow statistics (fig. 1), (2) a data base of previously published streamflow statistics and descriptive information for 725 USGS data-collection stations, and (3) an automated procedure that determines characteristics of the land-surface area (basin) that drains to the stream and inserts those characteristics into equations that estimate the streamflow statistics. Each of these components is described and guidance for using STREAMSTATS is provided below.

Fact Sheet↗
USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗
USGS2006

Atlantic Seaduck Project

Atlantic Seaduck Project is being conducted to learn more about the breeding and moulting areas of seaducks in northern Canada and more about their feeding ecology on wintering areas, especially Chesapeake Bay. Satellite telemetry is being used to track surf scoters wintering in Chesapeake Bay, Maryland and black scoters on migrational staging areas in New Brunswick, Canada to breeding and moulting areas in northern Canada. Various techniques used to capture the scoters included mist netting, night-lighting, and net capture guns. All captured ducks were transported to a veterinary hospital where surgery was conducted following general anaesthesia procedures. A PTT100 transmitter (39 g) manufactured by Microwave, Inc., Columbia, Maryland was implanted into the duck?s abdominal cavity with an external (percutaneous) antenna. Eight of the surf scoters from Chesapeake Bay successfully migrated to possible breeding areas in Canada and all 13 of the black scoters migrated to suspected breeding areas. Ten of the 11 black scoter males migrated to James Bay presumably for moulting. Updated information from the ARGOS Systems aboard the NOAA satellites on scoter movements was made accessible on the Patuxent Website. Habitat cover types of locations using GIS (Geographical Information Systems) and aerial photographs (in conjunction with remote sensing software) are currently being analyzed to build thematic maps with varying cosmetic layer applications. Many factors related to human population increases have been implicated in causing changes in the distribution and abundance of wintering seaducks. Analyses of the gullet (oesophagus and proventriculus) and the gizzard of seaducks are currently being conducted to determine if changes from historical data have occurred. Scoters in the Bay feed predominantly on the hooked mussel and several species of clams. The long-tailed duck appears to select the gem clam in greater amounts than other seaducks, but exhibits a diverse diet of other mollusks and crustaceans. Seaduck food habits in the Maritimes are decidedly different, where all three species of scoters feed extensively on the blue mussel. Understanding the feeding ecology of seaducks in wintering areas such as the Chesapeake Bay and the Maritimes will provide managers with a better understanding of the changes in the distribution and abundance of these ducks. Future studies will attempt to determine the effects of experimental diets varying in protein and energy levels on the physiology and behaviour of captive seaducks. An attempt will be made to determine if seaducks exhibit an endogenous rhythm in regard to body weight and condition during the winter. Foraging energetics in relation to different food sources found in the Chesapeake Bay will be measured in two large aquariums (dive tanks) with scoters and long-tailed ducks. The combined studies being conducted in the Atlantic Seaduck Project will greatly aid the conservation effort for seaducks presently being conducted throughout the world.

Book chapter↗
USGS2006

Rebuilding Mount St. Helens

On May 18, 1980, Mount St. Helens, Washington exploded in a spectacular and devastating eruption that shocked the world. The eruption, one of the most powerful in the history of the United States, removed 2.7 cubic kilometers of rock from the volcano's edifice, the bulk of which had been constructed by nearly 4,000 years of lava-dome-building eruptions. In seconds, the mountain's summit elevation was lowered from 2,950 meters to 2,549 meters, leaving a north-facing, horseshoe-shaped crater over 2 kilometers wide. Following the 1980 eruption, Mount St. Helens remained active. A large lava dome began episodically extruding in the center of the volcano's empty crater. This dome-building eruption lasted until 1986 and added about 80 million cubic meters of rock to the volcano. During the two decades following the May 18, 1980 eruption, Crater Glacier formed tongues of ice around the east and west sides of the lava dome in the deeply shaded niche between the lava dome and the south crater wall. Long the most active volcano in the Cascade Range with a complex 300,000-year history, Mount St. Helens erupted again in the fall of 2004 as a new period of dome building began within the 1980 crater. Between October 2004 and February 2006, about 80 million cubic meters of dacite lava erupted immediately south of the 1980-86 lava dome. The erupting lava separated the glacier into two parts, first squeezing the east arm of the glacier against the east crater wall and then causing equally spectacular crevassing and broad uplift of the glacier's west arm. Vertical aerial photographs document dome growth and glacier deformation. These photographs enabled photogrammetric construction of a series of high-resolution digital elevation models (DEMs) showing changes from October 4, 2004 to February 9, 2006. From the DEMs, Geographic Information Systems (GIS) applications were used to estimate extruded volumes and growth rates of the new lava dome. The DEMs were also used to quantify dome height variations, size of the magma conduit opening, and the mechanics of dome emplacement. Previous lava-dome-building eruptions at the volcano have persisted intermittently for years to decades. Over time, such events constructed much of the cone-shaped mountain seen prior to the May 18, 1980 eruption. Someday, episodic dome growth may eventually rebuild Mount St. Helens to its pre-1980 form.

Scientific Investigations Map↗
USGS2010

Regional Regression Equations to Estimate Flow-Duration Statistics at Ungaged Stream Sites in Connecticut

Multiple linear regression equations for determining flow-duration statistics were developed to estimate select flow exceedances ranging from 25- to 99-percent for six 'bioperiods'-Salmonid Spawning (November), Overwinter (December-February), Habitat Forming (March-April), Clupeid Spawning (May), Resident Spawning (June), and Rearing and Growth (July-October)-in Connecticut. Regression equations also were developed to estimate the 25- and 99-percent flow exceedances without reference to a bioperiod. In total, 32 equations were developed. The predictive equations were based on regression analyses relating flow statistics from streamgages to GIS-determined basin and climatic characteristics for the drainage areas of those streamgages. Thirty-nine streamgages (and an additional 6 short-term streamgages and 28 partial-record sites for the non-bioperiod 99-percent exceedance) in Connecticut and adjacent areas of neighboring States were used in the regression analysis. Weighted least squares regression analysis was used to determine the predictive equations; weights were assigned based on record length. The basin characteristics-drainage area, percentage of area with coarse-grained stratified deposits, percentage of area with wetlands, mean monthly precipitation (November), mean seasonal precipitation (December, January, and February), and mean basin elevation-are used as explanatory variables in the equations. Standard errors of estimate of the 32 equations ranged from 10.7 to 156 percent with medians of 19.2 and 55.4 percent to predict the 25- and 99-percent exceedances, respectively. Regression equations to estimate high and median flows (25- to 75-percent exceedances) are better predictors (smaller variability of the residual values around the regression line) than the equations to estimate low flows (less than 75-percent exceedance). The Habitat Forming (March-April) bioperiod had the smallest standard errors of estimate, ranging from 10.7 to 20.9 percent. In contrast, the Rearing and Growth (July-October) bioperiod had the largest standard errors, ranging from 30.9 to 156 percent. The adjusted coefficient of determination of the equations ranged from 77.5 to 99.4 percent with medians of 98.5 and 90.6 percent to predict the 25- and 99-percent exceedances, respectively. Descriptive information on the streamgages used in the regression, measured basin and climatic characteristics, and estimated flow-duration statistics are provided in this report. Flow-duration statistics and the 32 regression equations for estimating flow-duration statistics in Connecticut are stored on the U.S. Geological Survey World Wide Web application ?StreamStats? (http://water.usgs.gov/osw/streamstats/index.html). The regression equations developed in this report can be used to produce unbiased estimates of select flow exceedances statewide.

Scientific Investigations Report↗
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↗
USGS2014

Sea Level Affecting Marshes Model (SLAMM) ‐ New functionality for predicting changes in distribution of submerged aquatic vegetation in response to sea level rise

Introduction Submerged aquatic vegetation (SAV) is an ecologically important habitat world‐wide. In Pacific Northwest (PNW) estuaries, SAV in the lower intertidal and shallow subtidal habitats are dominated by the native seagrass, Zostera marina Linnaeus, 1753. Within this report, SAV and seagrass refer to Z. marina seagrass beds in PNW estuaries. Z. marina provides important habitat for juvenile salmon, dungeness crabs, migratory shore birds, and benthic assemblages (e.g., Philips, 1984; Williamson, 2006; Ferraro and Cole, 2007; Shaughnessy et al., 2012). Z. marina typically occurs in a narrow depth range. For example, in Oregon estuaries Zostera marina primarily occurs within the depth range of ‐1 to +1 m relative to Mean Lower Low Water (MLLW) (Young et al. 2012). Because of their narrow depth range, the distribution of these seagrass beds are potentially vulnerable to sea level rise (SLR) through increased water depths and associated reductions in underwater light levels, alterations in tidal variations, altered water movement and wave action, and increased seawater intrusion (Short and Neckles, 1999). The “Sea‐Level Affecting Marshes Model” (SLAMM) is a moderate resolution model used to predict the effects of sea level rise on marsh habitats (Craft et al. 2009). SLAMM has been used extensively on both the west coast (e.g., Glick et al., 2007) and east coast (e.g., Geselbracht et al., 2011) of the United States to evaluate potential changes in the distribution and extent of tidal marsh habitats. However, a limitation of the current version of SLAMM, (Version 6.2) is that it lacks the ability to model distribution changes in seagrass habitat resulting from sea level rise. Because of the ecological importance of SAV habitats, U.S. EPA, USGS, and USDA partnered with Warren Pinnacle Consulting to enhance the SLAMM modeling software to include new functionality in order to predict changes in Zostera marina distribution within Pacific Northwest estuaries in response to sea level rise. Specifically, the objective was to develop a SAV model that used generally available GIS data and parameters that were predictive and that could be customized for other estuaries that have GIS layers of existing SAV distribution. This report describes the procedure used to develop the SAV model for the Yaquina Bay Estuary, Oregon, appends a statistical script based on the open source R software to generate a similar SAV model for other estuaries that have data layers of existing SAV, and describes how to incorporate the model coefficients from the site‐specific SAV model into SLAMM to predict the effects of sea level rise on Zostera marina distributions. To demonstrate the applicability of the R tools, we utilize them to develop model coefficients for Willapa Bay, Washington using site‐specific SAV data.

Oregon↗
USGS2010

Land-Use Portfolio Modeler, Version 1.0

Natural hazards pose significant threats to the public safety and economic health of many communities throughout the world. Community leaders and decision-makers continually face the challenges of planning and allocating limited resources to invest in protecting their communities against catastrophic losses from natural-hazard events. Public efforts to assess community vulnerability and encourage loss-reduction measures through mitigation often focused on either aggregating site-specific estimates or adopting standards based upon broad assumptions about regional risks. The site-specific method usually provided the most accurate estimates, but was prohibitively expensive, whereas regional risk assessments were often too general to be of practical use. Policy makers lacked a systematic and quantitative method for conducting a regional-scale risk assessment of natural hazards. In response, Bernknopf and others developed the portfolio model, an intermediate-scale approach to assessing natural-hazard risks and mitigation policy alternatives. The basis for the portfolio-model approach was inspired by financial portfolio theory, which prescribes a method of optimizing return on investment while reducing risk by diversifying investments in different security types. In this context, a security type represents a unique combination of features and hazard-risk level, while financial return is defined as the reduction in losses resulting from an investment in mitigation of chosen securities. Features are selected for mitigation and are modeled like investment portfolios. Earth-science and economic data for the features are combined and processed in order to analyze each of the portfolios, which are then used to evaluate the benefits of mitigating the risk in selected locations. Ultimately, the decision maker seeks to choose a portfolio representing a mitigation policy that maximizes the expected return-on-investment, while minimizing the uncertainty associated with that return-on-investment. The portfolio model, now known as the Land-Use Portfolio Model (LUPM), provided the framework for the development of the Land-Use Portfolio Modeler, Version 1.0 software (LUPM v1.0). The software provides a geographic information system (GIS)-based modeling tool for evaluating alternative risk-reduction mitigation strategies for specific natural-hazard events. The modeler uses information about a specific natural-hazard event and the features exposed to that event within the targeted study region to derive a measure of a given mitigation strategy`s effectiveness. Harnessing the spatial capabilities of a GIS enables the tool to provide a rich, interactive mapping environment in which users can create, analyze, visualize, and compare different

Techniques and Methods↗
USGS2009

Groundwater availability of the Central Valley Aquifer, California

California's Central Valley covers about 20,000 square miles and is one of the most productive agricultural regions in the world. More than 250 different crops are grown in the Central Valley with an estimated value of $17 billion per year. This irrigated agriculture relies heavily on surface-water diversions and groundwater pumpage. Approximately one-sixth of the Nation's irrigated land is in the Central Valley, and about one-fifth of the Nation's groundwater demand is supplied from its aquifers. The Central Valley also is rapidly becoming an important area for California's expanding urban population. Since 1980, the population of the Central Valley has nearly doubled from 2 million to 3.8 million people. The Census Bureau projects that the Central Valley's population will increase to 6 million people by 2020. This surge in population has increased the competition for water resources within the Central Valley and statewide, which likely will be exacerbated by anticipated reductions in deliveries of Colorado River water to southern California. In response to this competition for water, a number of water-related issues have gained prominence: conservation of agricultural land, conjunctive use, artificial recharge, hydrologic implications of land-use change, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS Groundwater Resources Program made a detailed assessment of groundwater availability of the Central Valley aquifer system, that includes: (1) the present status of groundwater resources; (2) how these resources have changed over time; and (3) tools to assess system responses to stresses from future human uses and climate variability and change. This effort builds on previous investigations, such as the USGS Central Valley Regional Aquifer System and Analysis (CV-RASA) project and several other groundwater studies in the Valley completed by Federal, State and local agencies at differing scales. The principal product of this new assessment is a tool referred to as the Central Valley Hydrologic Model (CVHM) that accounts for integrated, variable water supply and demand, and simulates surface-water and groundwater-flow across the entire Central Valley system. The development of the CVHM comprised four major elements: (1) a comprehensive Geographic Information System (GIS) to compile, analyze and visualize data; (2) a texture model to characterize the aquifer system;(3) estimates of water-budget components by numerically modeling the hydrologic system with the Farm Process (FMP); and (4) simulations to assess and quantify hydrologic conditions.

Professional Paper↗
USGS2001

HAZUS 99 estimated annualized earthquake losses for the United States

Recent earthquakes around the world show a pattern of steadily increasing damages and losses. The increases are due primarily to two factors: 1) significant growth in urban areas that are prone to earthquakes; and 2) the vulnerability of the older building stock, even buildings that were constructed within the past twenty years. In the United States, earthquake risk has grown substantially with development, while the earthquake hazard has remained relatively constant. To understand the hazard, we study earthquake characteristics and locales in which they occur. To understand risk, we must include characteristics of the built environment in the locales where earthquakes occur, and we must assess potential damages to the built environment and the people who use it. That is a complex undertaking and one this study intends to advance. It is important to estimate the varying degrees of seismic risk throughout the United States because we need that understanding in order to make informed decisions on mitigation policies, priorities, strategies and funding levels—in both the public and private sectors. We can reduce earthquake losses to older buildings by rehabilitating them, and we can reduce earthquake losses in new buildings by applying seismic codes to their design and construction. However, decisions to spend money on either of those solutions require evidence of risk. In the absence of a nationally accepted criterion and methodology for comparing seismic risk across regions, a consensus on optimal mitigation approaches has been difficult to reach. We are all aware of regions with high hazard and high risk, such as Los Angeles, but there is growing recognition that some regions with low seismic hazard actually have high seismic risk, as is the case in New York City and Boston. This risk results, in part, from concentrations of buildings and infrastructure built without use of seismic codes or provisions. Additionally, mitigation policies and practices in the public and private sectors may not have been adopted because a community’s earthquake risk was not clearly demonstrated, and neither was the value of mitigation measures in reducing that risk. The low hazard/high risk problem exists in a number of areas in the U.S., where the infrequency of damaging earthquakes has been interpreted, wrongly, as lack of risk. While earth scientists work to increase knowledge about the hazard throughout the United States, structural engineers and other professionals work to enumerate the many factors that comprise risk. This study is one result of that endeavor. It is based on loss estimates generated by Hazards U.S. (HAZUS), a Geographic Information System (GIS)- based earthquake loss estimation tool, developed by the Federal Emergency Management Agency (FEMA) in cooperation with the National Institute of Building Sciences (NIBS). The HAZUS tool provides an approach to quantifying future earthquake losses that is national in scope, uniform in application, and comprehensive in its coverage of the built environment.

Report↗