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At least 541 records · Page 30Linked to original sources
USGS2011

U.S. Geological Survey Community for Data Integration-NWIS Web Services Snapshot Tool for ArcGIS

U.S. Geological Survey (USGS) data resources are so vast that many scientists are unaware of data holdings that may be directly relevant to their research. Data are also difficult to access and large corporate databases, such as the National Water Information System (NWIS) that houses hydrologic data for the Nation, are challenging to use without considerable expertise and investment of time. The USGS Community for Data Integration (CDI) was established in 2009 to address data and information management issues affecting the proficiency of earth science research. A CDI workshop convened in 2009 identified common data integration needs of USGS scientists and targeted high value opportunities that might address these needs by leveraging existing projects in USGS science centers, in-kind contributions, and supplemental funding. To implement this strategy, CDI sponsored a software development project in 2010 to facilitate access and use of NWIS data with ArcGIS, a widely used Geographic Information System. The resulting software product, the NWIS Web Services Snapshot Tool for ArcGIS, is presented here.

Fact Sheet↗
USGS2014

Identifying resource manager information needs for the North Pacific Landscape Conservation Cooperative

Landscape Conservation Cooperatives (LCCs) are a network of 22 public-private partnerships, defined by ecoregion, that share and provide science to ensure the sustainability of land, water, wildlife and cultural resources in North America. LLCs were established by the U.S. Department of Interior (DOI) in recognition that response to climate change must be coordinated on a landscape-level basis because important resources, ecosystem processes and resource management challenges extend beyond national wildlife refuges, Bureau of Land Management lands, national parks, and even international boundaries. Therefore, DOI agencies must work with other Federal, State, Tribal (U.S. indigenous peoples), First Nation (Canadian indigenous peoples), and local governments, as well as private landowners, to develop landscape-level strategies for understanding and responding to climate change.

Alaska;British Columbia;California;Oregon;Washingt↗
USGS2013

Flood-inundation maps for the Iroquois River at Rensselaer, Indiana

Digital flood-inundation maps for a 4.0-mile reach of the Iroquois River at Rensselaer, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. 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 USGS streamgage 05522500, Iroquois River at Rensselaer, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at (http://waterdata.usgs.gov/in/nwis/uv?site_no=05522500). In addition, the National Weather Service (NWS) forecasts flood hydrographs at the Rensselaer streamgage. That forecasted peak-stage information, also available on the Internet (http://water.weather.gov/ahps/), may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the Iroquois River reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (June 27, 2012) stage-discharge relations at USGS streamgage 05522500, Iroquois River at Rensselaer, Ind., and high-water marks from the flood of July 2003. The calibrated hydraulic model was then used to determine nine water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Rensselaer, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗
USGS2013

Flood-inundation maps for the East Fork White River at Columbus, Indiana

Digital flood-inundation maps for a 5.4-mile reach of the East Fork White River at Columbus, Indiana, from where the Flatrock and Driftwood Rivers combine to make up East Fork White River to just upstream of the confluence of Clifty Creek with the East Fork White River, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. 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 of flooding corresponding to selected water levels (stages) at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. Current conditions at the USGS streamgage may be obtained on the Internet from the USGS National Water Information System (http://waterdata.usgs.gov/in/nwis/uv/?site_no=03364000&agency_cd=USGS&). The National Weather Service (NWS) forecasts flood hydrographs for the East Fork White River at Columbus, Indiana at their Advanced Hydrologic Prediction Service (AHPS) flood warning system Website (http://water.weather.gov/ahps/), that may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. The calibrated hydraulic model was then used to determine 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. 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 0.37-ft vertical accuracy and a 1.02 ft horizontal accuracy), in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Columbus, Indiana, and forecasted stream stages from the NWS will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.

Indiana↗
USGS2008

Facing Tomorrow's Challenges - An Overview

In 2007, the U.S. Geological Survey (USGS) developed a science strategy outlining the major natural-science issues facing the Nation in the next decade. The science strategy consists of six science directions of critical importance, focusing on areas where natural science can make a substantial contribution to the well-being of the Nation and the world. This fact sheet is an overview of the science strategy and describes how USGS research can strengthen the Nation with information needed to meet the challenges of the 21st century.

Fact Sheet↗
USGS2010

EAARL Coastal Topography-Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Mississippi and Alabama barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 8, 2008. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2023

Bioavailability and toxicity models of copper to freshwater life: The state of regulatory science

Efforts to incorporate bioavailability adjustments into regulatory water quality criteria in the United States have included four major procedures: hardness-based single-linear regression equations, water-effect ratios (WERs), biotic ligand models (BLMs), and multiple-linear regression models (MLRs) that use dissolved organic carbon, hardness, and pH. The performance of each with copper (Cu) is evaluated, emphasizing the relative performance of hardness-based versus MLR-based criteria equations. The WER approach was shown to be inherently highly biased. The hardness-based model is in widest use, and the MLR approach is the US Environmental Protection Agency's (USEPA's) present recommended approach for developing aquatic life criteria for metals. The performance of criteria versions was evaluated with numerous toxicity datasets that were independent of those used to develop the MLR models, including olfactory and behavioral toxicity, and field and ecosystem studies. Within the range of water conditions used to develop the Cu MLR criteria equations, the MLR performed well in terms of predicting toxicity and protecting sensitive species and ecosystems. In soft waters, the MLR outperformed both the BLM and hardness models. In atypical waters with pH <5.5 or >9, neither the MLR nor BLM predictions were reliable, suggesting that site-specific testing would be needed to determine reliable Cu criteria for such settings. The hardness-based criteria performed poorly with all toxicity datasets, showing no or weak ability to predict observed toxicity. In natural waters, MLR and BLM criteria versions were strongly correlated. In contrast, the hardness-criteria version was often out of phase with the MLR and, depending on waterbody and season, could be either strongly overprotective or underprotective. The MLR-based USEPA-style chronic criterion appears to be more generally protective of ecosystems than other models.

Environmental Toxicology and Chemistry↗
USGS2020

Modeling water quality in watersheds: From here to the next generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in‐stream water quality and process interactions, soil health and land management, and (peri‐)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

Water Resources Research↗
USGS2008

Users Manual for the Geospatial Stream Flow Model (GeoSFM)

The monitoring of wide-area hydrologic events requires the manipulation of large amounts of geospatial and time series data into concise information products that characterize the location and magnitude of the event. To perform these manipulations, scientists at the U.S. Geological Survey Center for Earth Resources Observation and Science (EROS), with the cooperation of the U.S. Agency for International Development, Office of Foreign Disaster Assistance (USAID/OFDA), have implemented a hydrologic modeling system. The system includes a data assimilation component to generate data for a Geospatial Stream Flow Model (GeoSFM) that can be run operationally to identify and map wide-area streamflow anomalies. GeoSFM integrates a geographical information system (GIS) for geospatial preprocessing and postprocessing tasks and hydrologic modeling routines implemented as dynamically linked libraries (DLLs) for time series manipulations. Model results include maps that depicting the status of streamflow and soil water conditions. This Users Manual provides step-by-step instructions for running the model and for downloading and processing the input data required for initial model parameterization and daily operation.

Open-File Report↗
USGS2024

Methods for computing water-quality concentrations and loads at sites operated by the U.S. Geological Survey Kansas Water Science Center

The U.S. Geological Survey (USGS) Kansas Water Science Center (KSWSC) has published time-series computations of water-quality concentrations and loads based on in situ sensor data since 1995. Water-quality constituent concentrations or densities are computed using regression models that relate in situ sensor values to laboratory analyses of periodically collected samples. These regression models currently (2024) follow no uniform published guidance and are individually documented through USGS reports. This report describes updated (2024) procedures designed to improve the consistency, quality, and timeliness of computed continuous water-quality data produced by the USGS KSWSC. Beginning in 2024, models developed by the USGS KSWSC that follow specific procedures and requirements related to sample collection, model fit, and model documentation outlined in this report are planned to be published and stored in the USGS National Real-Time Water Quality Data for the Nation Data Service. This report also describes USGS KSWSC procedures for evaluating and publishing time-series water-quality computations after initial model development and documentation. This guidance can be used to improve USGS KSWSC model development and data computation consistency and streamline the time-series water-quality computation process from model development to publication.

Open-File Report↗
USGS2012

Flood-inundation maps for the Saddle River from Rochelle Park to Lodi, New Jersey, 2012

Digital flood-inundation maps for a 2.75-mile reach of the Saddle River from 0.2 mile upstream from the Interstate 80 bridge in Rochelle Park to 1.5 miles downstream from the U.S. Route 46 bridge in Lodi, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). 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 Saddle River at Lodi, New Jersey (station 01391500). Current conditions for estimating near real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/nwis/uv?site_no=01391500 . The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the Saddle River at Lodi, New Jersey streamgage and documented high-water marks from recent floods. The hydraulic model was then used to determine 11 water-surface profiles for flood stages at the Saddle River streamgage at 1-ft intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the extent of the stage-discharge rating, which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84-ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

New Jersey↗
USGS2013

Flood-inundation maps for the Saddle River from Upper Saddle River Borough to Saddle River Borough, New Jersey, 2013

Digital flood-inundation maps for a 4.1-mile reach of the Saddle River from 0.6 miles downstream from the New Jersey-New York State boundary in Upper Saddle River Borough to 0.2 miles downstream from the East Allendale Road bridge in Saddle River Borough, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). 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 select water levels (stages) at the USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey. Current conditions for estimating near real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/nwis/uv?site_no=01390450. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations (in effect March 2013) at USGS streamgage 01390450, Saddle River at Upper Saddle River, New Jersey, and documented high-water marks from recent floods. The hydraulic model was then used to determine eight water-surface profiles for flood stages at 0.5-foot (ft) intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the upper extent of the stage-discharge rating which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84 ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps along with real-time streamflow data and information regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

New Jersey↗
USGS2005

The soil physics contributions of Edgar Buckingham

During 1902 to 1906 as a soil physicist at the USDA Bureau of Soils (BOS), Edgar Buckingham originated the concepts of matric potential, soil–water retention curves, specific water capacity, and unsaturated hydraulic conductivity ( K ) as a distinct property of a soil. He applied a formula equivalent to Darcy's law (though without specific mention of Darcy's work) to unsaturated flow. He also contributed significant research on quasi-empirical formulas for K as a function of water content, water flow in capillary crevices and in thin films, and scaling. Buckingham's work on gas flow in soils produced paradigms that are consistent with our current understanding. His work on evaporation elucidated the concept of self-mulching and produced sound and sometimes paradoxical generalizations concerning conditions that favor or retard evaporation. Largely overshadowing those achievements, however, is that he launched a theory, still accepted today, that could predict transient water content as a function of time and space. Recently discovered documents reveal some of the arguments Buckingham had with BOS officials, including the text of a two-paragraph conclusion of his famous 1907 report on soil water, and the official letter documenting rejection of that text. Strained interpersonal relations motivated the departure of Buckingham and other brilliant physicists (N.E. Dorsey, F.H. King, and Lyman Briggs) from the BOS during 1903 to 1906. Given that Buckingham and his BOS colleagues had been rapidly developing the means of quantifying unsaturated flow, these strained relations probably slowed the advancement of unsaturated flow theory.

Soil Science Society of America Journal↗
USGS1980

Handbook of acute toxicity of chemicals to fish and aquatic invertebrates : summaries of toxicity tests conducted at Columbia National Fisheries Research Laboratory, 1965-78

Acute toxicity is a major subject of research at Columbia National Fisheries Research Laboratory for evaluating the impact of toxic chemicals on fishery resources. The Laboratory has played a leading role in developing research technology for toxicity testing and data interpretation. In 1965-78, more than 400 chemicals were tested against a variety of invertebrates and fish species representative of both cold- and warm-water climates. The use of acute toxicity tests for assessing the potential hazard of chemical contaminants to aquatic organisms is well documented (Boyd 1957; Henderson et al. 1960; Sanders and Cope 1966; Macek and McAllister 1970). Static acute toxicity tests provide rapid and (within limits) reproducible concentration-response curves for estimating toxic effects of chemicals on aquatic organisms. These tests provide a database for determining relative toxicity of a large number of chemicals to a variety of species and for estimating acute effects of chemical spills on natural aquatic systems; they also assist in determining priority and design of additional toxicity studies. Acute toxicity tests usually provide estimates of the exposure concentration causing 50% mortality (LC50) to test organisms during a specified period of time. For certain invertebrates, the effective concentration is based on immobilization, or some other identifiable endpoint, rather than on lethality. The application of the LC50 has gained acceptance among toxicologists and is generally the most highly rated test for assessing potential adverse effects of chemical contaminants to aquatic life (Brungs and Mount 1978; American Institute for Biological Sciences 1978 a ). The literature contains numerous papers dealing with the acute toxicity of chemicals to freshwater organisms. However, there is a tremendous need for a concise compendium of toxicity data covering a large variety of chemicals and test species. This Handbook is a compilation of a large volume of acute toxicity data from the Columbia Laboratory and its field laboratories. It presents definitive acute toxicity data on 271 chemicals tested against a variety of freshwater invertebrates and fishes. The chemicals represent all major groups of pesticides, as well as numerous industrial chemicals. This compilation should serve as a useful database for the many agencies and organizations dealing with research and management programs concerned with the impact of chemicals on aquatic resources. The Columbia Laboratory has played a major role in developing currently used standard methodology for static acute toxicity testing. The use of standardized methodology greatly reduces variation in results. The data presented here have been carefully scrutinized to eliminate tests that failed to follow acceptable procedures. Handling of test organisms and procedures for static toxicity tests followed those described by Lennon and Walker (1964) and Macek and McAllister (1970), and conform well with those recommended by Brauhn and Schoettger (1975) and the Committee on Methods for Toxicity Tests with Aquatic Organisms (1975). The species of fish and invertebrates that were tested are listed in phylogenetic order in Tables 1 and 2. Fish were obtained from Federal and State hatcheries as either eggs or fry. Original stocks of invertebrates were collected and cultured from wild populations with no known source of contamination; these populations were replenished regularly. The invertebrates were cultured in the Laboratory by methods similar to those described by Sanders and Cope (1966). Test chemicals usually consisted of technical or analytical grade samples of known purity. Formulations of the chemicals were also tested when available. When purity of test chemicals was known, all calculated concentrations were based on percent active ingredients. Stock solutions were prepared immediately before each test, with commercial grade acetone as the carrier solvent. Occasionally, ethanol or dimethyl-formamide was substituted. Solvent concentrations did not exceed 0.5 mL/L in final dilution water. Test water (dilution water) was reconstituted from deionized water of at least 10 6 ohms resistivity by the addition of appropriate reagent grade chemicals (Marking 1969). Water was buffered to maintain a pH of 7.2 to 7.5, an alkalinity of 30 to 35 mg/L, and a hardness of 40 to 50 mg/L as CaCO 3 . Test water was mixed thoroughly and aerated before transfer into test chambers. Fish were acclimated to dilution water by gradually changing the water in acclimated tanks from 100% well water to 100% reconstituted water over a 1- to 3-day period at the desired testing temperature. Invertebrates were acclimated from well water to dilution water over a 4- to 6-h period. Toxicity tests were conducted under static conditions without aeration, and the organisms were not fed during acclimation or testing. Temperature of test solutions was maintained within ± 1°C of that required for a given test. Toxicity tests with fish were conducted in 18.9-liter (5-gal) wide-mouthed jars containing 15 liters of test solution. Fingerling fish weighing 0.2 to 1.5 g were tested at each concentration. Caution was taken not to exceed 0.8 g of test organisms per liter of solution. Duplicate test chambers were used to accommodate larger fish. Test chambers varied in size for invertebrates, depending on the species used; volume of test solution ranged from 0.25 to 4 liters. At least 10 organisms were exposed to each concentration for all definitive tests. At least six concentrations were used per toxicity test. The tests began upon initial exposure to the toxicant and continued for 96 h. Immobilization tests with invertebrates were conducted for only 48 h. The number of dead or affected organisms in each test chamber were recorded and the dead organisms were removed every 24 h; general observations on the condition of test organisms were also recorded at these times. Toxicity data were analyzed by a statistical method described by Litchfield and Wilcoxon (1949) to determine LC50 (theoretical estimate of the concentration lethal to 50% of the test animals) and 95% confidence intervals. This method is recommended by the American Public Health Association (1971) and by Sprague (1969) for determining median lethal concentrations. The procedure is easily modified for computing a single LC50 when replicate tests are performed.

Resource Publication↗
USGS2007

Understanding Ecosystems and Predicting Ecosystem Change

In 2007, the U.S. Geological Survey (USGS) developed a science strategy outlining the major natural science issues facing the Nation in the next decade. The science strategy consists of six science directions of critical importance, focusing on areas where natural science can make a substantial contribution to the well-being of the Nation and the world. This fact sheet focuses on understanding ecosystems and predicting ecosystem change, and how USGS research can strengthen the Nation with information needed to meet the challenges of the 21st century.

Fact Sheet↗
USGS2007

A National Program to Assess Hazards, Risk, and Resiliency

In 2007, the U.S. Geological Survey (USGS) developed a science strategy outlining the major natural science issues facing the Nation in the next decade. The science strategy consists of six science directions of critical importance, focusing on areas where natural science can make a substantial contribution to the well-being of the Nation and the world. This fact sheet focuses on a program to assess natural hazards and how USGS research can strengthen the Nation with information needed to meet the challenges of the 21st century.

Fact Sheet↗
USGS2004

Toward a scientifically rigorous basis for developing mapped ecological regions.

Despite the wide use of ecological regions in conservation and resource-management evaluations and assessments, a commonly accepted theoretical basis for ecological regionalization does not exist. This fact, along with the paucity of focus on ecological regionalization by professional associations, journals, and faculties, has inhibited the advancement of a broadly acceptable scientific basis for the development, use, and verification of ecological regions. The central contention of this article is that ecological regions should improve our understanding of geographic and ecological phenomena associated with biotic and abiotic processes occurring in individual regions and also of processes characteristic of interactions and dependencies among multiple regions. Research associated with any ecoregional framework should facilitate development of hypotheses about ecological phenomena and dominant landscape elements associated with these phenomena, how these phenomena are structured in space, and how they function in a hierarchy. Success in addressing the research recommendations outlined in this article cannot occur within an ad hoc, largely uncoordinated research environment. Successful implementation of this plan will require activities--coordination, funding, and education--that are both scientific and administrative in nature. Perhaps the most important element of an infrastructure to support the scientific work of ecoregionalization would be a national or international authority similar to the Water and Science Technology Board of the National Academy of Sciences.

Environmental Management↗
USGS2014

Flood-inundation maps for the West Branch Susquehanna River near the Boroughs of Lewisburg and Milton, Pennsylvania

Digital flood-inundation maps for an approximate 8-mile reach of the West Branch Susquehanna River from approximately 2 miles downstream from the Borough of Lewisburg, extending upstream to approximately 1 mile upstream from the Borough of Milton, Pennsylvania, were created by the U.S. Geological Survey (USGS) in cooperation with the Susquehanna River Basin Commission (SRBC). 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 the estimated areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 01553500, West Branch Susquehanna River at Lewisburg, Pa. In addition, the information has been provided to the Susquehanna River Basin Commission (SRBC) for incorporation into their Susquehanna Inundation Map Viewer (SIMV) flood warning system ( http://maps.srbc.net/simv/ ). The National Weather Service (NWS) forecasted peak-stage information ( http://water.weather.gov/ahps ) for USGS streamgage 01553500, West Branch Susquehanna River at Lewisburg, Pa., may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. Calibration of the model was achieved using the most current stage-discharge relations (rating number 11.1) at USGS streamgage 01553500, West Branch Susquehanna River at Lewisburg, Pa., a documented water-surface profile from the December 2, 2010, flood, and recorded peak stage data. The hydraulic model was then used to determine 26 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum ranging from 14 feet (ft) to 39 ft. Modeled flood stages, as defined by NWS, include Action Stage, 14 ft; Flood Stage, 18 ft; Moderate Flood Stage, 23 ft; and Major Flood Stage, 28 ft. Geographic information system (GIS) technology was then used to combine the simulated water-surface profiles with a digital elevation model (DEM) derived from light detection and ranging (lidar) data to delineate the area flooded at each water level. The availability of these maps, along with World Wide Web information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Pennsylvania↗