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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 739 records · Page 41Linked to original sources
USGS2010

EAARL Coastal Topography and Imagery-Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) topography, first-surface (FS) topography, and canopy-height (CH) datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg 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 the Naval Live Oaks Area in Florida's Gulf Islands National Seashore, acquired June 30, 2007. 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 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

Alerting the globe of consequential earthquakes

The primary ingredients on the hazard side of the equation include the rapid characterization of the earthquake source and quantifying the spatial distribution of the shaking, plus any secondary hazards an earthquake may have triggered. On the earthquake impact side, loss calculations require the aforementioned hazard assessments—and their uncertainties—as input, plus the quantification of the exposure and vulnerability of structures, infrastructure, and the affected inhabitants. Lastly, effectively communicating uncertain estimates of the resulting impacts on society requires careful consideration of its function and form. All these aspects of rapid earthquake information delivery entailed wide-ranging collaborative research and development among seismologists, earthquake engineers, geographers, social scientists, Information Technology professionals, and communication experts, leveraging diverse components and ingredients not achievable without extensive collaboration. I was very fortunate to be able to work on interesting and useful projects with many colleagues who got involved with them. Advances in content, its rapid delivery, and our ability to better communicate uncertain loss estimates greatly expanded the range of users and critical decision-makers who could directly benefit from rapid post-earthquake information. Moreover, in the critical user–developer feedback loop, we have intently followed requests from users to develop new ways of delivering the most-requested post-earthquake information within the limitations of the science and technology. Such new avenues and tools then motivated and prioritized additional research directions and developments.

Perspectives of Earth and Space Scientists↗
USGS2013

Flood-inundation maps for the Elkhart River at Goshen, Indiana

The U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs, created digital flood-inundation maps for an 8.3-mile reach of the Elkhart River at Goshen, Indiana, extending from downstream of the Goshen Dam to downstream from County Road 17. 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 nine selected water levels (stages) at the USGS streamgage at Elkhart River at Goshen (station number 04100500). Current conditions for the USGS streamgages in Indiana may be obtained on the Internet at http://waterdata.usgs.gov/ . In addition, stream stage data have been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/) . The NWS forecasts flood hydrographs at many places that are often colocated 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 relation at the Elkhart River at Goshen streamgage. The hydraulic model was then used to compute nine water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (5 ft) to greater than the highest recorded water level (13 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital-elevation model (DEM), derived from Light Detection and Ranging (LiDAR) data having a 0.37-ft vertical accuracy and 3.9-ft horizontal resolution 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 postflood recovery efforts.

Indiana↗
USGS2013

Flood-inundation maps for the DuPage River from Plainfield to Shorewood, Illinois, 2013

Digital flood-inundation maps for a 15.5-mi reach of the DuPage River from Plainfield to Shorewood, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the Will County Stormwater Management Planning Committee. 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 (gage heights or stages) at the USGS streamgage at DuPage River at Shorewood, Illinois (sta. no. 05540500). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05540500. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. The NWS-forecasted peak-stage information, also shown on the DuPage River at Shorewood inundation Web site, 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 then used to determine nine water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from NWS Action stage of 6 ft to the historic crest of 14.0 ft. The simulated water-surface profiles were then combined with a Digital Elevation Model (DEM) (derived from Light Detection And Ranging (LiDAR) data) by using a Geographic Information System (GIS) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage height 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 postflood recovery efforts.

Illinois↗
USGS2005

Retreating glacier fronts on the Antarctic Peninsula over the past half-century

The continued retreat of ice shelves on the Antarctic Peninsula has been widely attributed to recent atmospheric warming, but there is little published work describing changes in glacier margin positions. We present trends in 244 marine glacier fronts on the peninsula and associated islands over the past 61 years. Of these glaciers, 87% have retreated and a clear boundary between mean advance and retreat has migrated progressively southward. The pattern is broadly compatible with retreat driven by atmospheric warming, but the rapidity of the migration suggests that this may not be the sole driver of glacier retreat in this region.

Science↗
USGS2010

EAARL Coastal Topography and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and 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, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Assateague Island National Seashore in Maryland and Virginia, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. 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 aircraft, but the instrument was deployed on a Pilatus PC-6. 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↗
USGS2015

Flood-inundation maps for the St. Marys River at Decatur, Indiana

Digital flood-inundation maps for an 8.9-mile reach of the St. Marys River at Decatur, Indiana, were developed by the U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site ( http://water.usgs.gov/osw/flood_inundation/ ), depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) of the St. Marys River at Decatur (USGS station number 04181500). The maps are useful for estimating near-real-time areas of inundation by referencing concurrent USGS streamgage information at http://waterdata.usgs.gov/ . In addition, the streamgage information was provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service flood warning system ( http:/water.weather.gov/ahps/ ). NWS-forecasted peak-stage information may be used in conjunction with the maps developed during this study to show predicted areas of flood inundation. During 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 stage-discharge relation for the streamgage at St. Marys River at Decatur. The hydraulic model was used to compute 18 water-surface profiles for flood stages varied at 1-foot (ft) intervals and ranging from approximately bankfull (13 ft above gage datum) to greater than the highest recorded water level at the streamgage. To delineate the area of flood inundation for each modeled water level, maps were constructed in a geographic information system by combining the simulated water-surface profiles with a digital-elevation model derived from light detection and ranging (lidar) data. Estimated flood-inundation boundaries along each simulated profile were developed using HEC–GeoRAS software. The availability of these maps and associated Web mapping tools, along with the current river stage from USGS streamgages and forecasted flood stages from the NWS, provides emergency managers and residents with information that may be critical for flood-emergency planning and flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Indiana↗
USGS2010

EAARL Coastal Topography-Sandy Hook Unit, Gateway National Recreation Area, New Jersey, Post-Nor'Ida, 2009

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, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Sandy Hook Unit of Gateway National Recreation Area in New Jersey, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 2009. 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 aircraft, but the instrument was deployed on a Pilatus PC-6. 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↗
USGS2010

The ASTER data system: An overview of the data products in Japan and in the United States

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data system is a cooperative system, which is operated jointly by Japan’s Ministry of Economy, Trade, and Industry (METI) through its Earth Remote Sensing Data Analysis Center (ERSDAC), and by the National Aeronautics and Space Administration (NASA) primarily through its Goddard Space Flight Center (GSFC) and Land Processes (LP) Distributed Active Archive Center (DAAC). ASTER is a moderate-resolution land remote sensing system onboard the Earth Observing System (EOS) Terra spacecraft. ASTER-acquired data are received at the White Sands, New Mexico, ground receiving station, and then transmitted via land network to the EOS Data and Operations System (EDOS) within the Goddard DAAC, located at the GSFC. EDOS pre-processes raw ASTER data to Level-0 (L0) data, and sends them via the high-speed Asia-Pacific Advanced Network (APAN) to the ASTER Ground Data System (GDS) in Japan. ASTER GDS processes the L0 data to level-1 (L1) datasets; they distribute these data to users, and also use them to generate higher-level products for their user community. ASTER GDS sends a copy of all L1A data they produce to NASA’s LP DAAC, located at the U.S. Geological Survey’s Center for Earth Resources Observation and Science (EROS) near Sioux Falls, South Dakota. All L1 data received from Japan are ingested, archived, and available for users at LP DAAC. The LP DAAC also generates and distributes higher-level products from L1 data based on requests from users. To meet time-critical needs related to sensor health and performance, natural disasters, national emergencies, and certain field campaigns, the ASTER Expedited Data System (EDS) was developed, and is operated jointly by U.S. and Japanese partners.

Book chapter↗
USGS2021

Decision context as an essential component of population viability analysis

Population viability analysis (PVA) is a widely used tool that applies demographic data in simulation frameworks to assess extinction risk for species or populations. It is used in diverse conservation applications, including evaluating management effectiveness, relative risk of threats, and potential changes to protective status (Beissinger & McCullough, 2002 ), and can be a critical tool for making decisions with imperfect knowledge of the system state, often on limited timelines (Meine et al., 2006 ). Chaudhary and Oli ( 2020 ) recently developed a framework to appraise the quality of PVAs based on the presence of essential background, model, and analysis components. They evaluated 160 published PVAs and reported a decline in the quality of PVAs over time (1990−2017). We agree PVA studies should report unambiguous descriptions of their essential components (Table 1 in Chaudhary and Oli) and explicitly state the model's biological and statistical assumptions. The need for increased transparency in PVAs is evident. Morrison et al. ( 2016 ) reported that only 50% of PVAs published in peer-reviewed and gray literature were both reproducible and repeatable. Further, in an examination of 67 studies that used matrix population models (widely used in PVAs), Kendall et al. ( 2019 ) reported that models frequently contained misspecification errors. Given the rapid advancement of simulation techniques, updated guidance for PVA construction is warranted. However, we believe the essential PVA components identified by Chaudhary and Oli contain a critical omission: the decision context in which the PVA was created and its usefulness in that context. Quality and utility are not mutually exclusive; however, some models that do not meet idealized quality standards might still be valuable because they are useful and represent the best available science for a given decision context (hereafter, decision-support models). The definition of quality for decision-support models should be different than models developed for the purpose of learning (hereafter, heuristic models) and should incorporate how useful the model was, despite information gaps. We further argue that assessment questions should be used prospectively to guide modeling projects, rather than for retrospective comparison of model quality.

Conservation Biology↗
USGS2023

Global seismic networks operated by the U.S. Geological Survey

The U.S. Geological Survey (USGS) Global Seismographic Network (GSN) Program operates two thirds of the GSN, a network of state‐of‐the‐art, digital seismological and geophysical sensors with digital telecommunications. This network serves as a multiuse scientific facility and a valuable resource for research, education, and monitoring. The other one third of the GSN is funded by the National Science Foundation (NSF), and the operations of this component are overseen by EarthScope. This collaboration between the USGS, EarthScope, and NSF has allowed for the development and operations of the GSN to be a truly multiuse network that provides near real‐time open access data, facilitating fundamental discoveries by the Earth science community, supporting the earthquake hazards mission of the USGS, benefitting tsunami monitoring by the National Oceanic and Atmospheric Administration, and contributing to nuclear test monitoring and treaty verification. In this article, we describe the installation and evolution of the seismic networks operated by the USGS that ultimately led to the USGS portion of the GSN (100 stations under network codes IU, IC, and CU) as they are today and envision technological advances and opportunities to further improve the utility of the network in the future. This article focuses on the USGS‐operated component of the GSN; a companion article on the GSN stations funded by the NSF and operated by the Cecil and Ida Green Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California at San Diego by Davis et al. (2023) appears in this volume.

Seismological Research Letters↗
USGS2018

Climate Assessments and Scenario Planning (CLASP)

The NE CASC boasts an interdisciplinary array of scientists, from ecologists to biologists, hydrologists to climatologists, each contributing new, original academic research to advance our understanding of the impacts of climate change on wildlife and other natural resources in the Northeast. Needed was an outreach specialist who would interface directly with the management agencies who benefited from this research to aid the integration of this research into their management planning as part of adapting to climate change. A climatologist was preferred to address queries about climate modeling, climate change uncertainties, and other areas of climate science outside the expertise of NE CASC ecologists, biologists, and hydrologists. This person’s activities would include responding to inquiries, presenting climate science concepts at management workshops, gathering managers’ climate science needs, contributing to the climate portion of synthesis reports and other resources for managers, and collaborating with ecologists on interdisciplinary studies of climate change by providing climate data and guidance on interpretation. The objective was to relay and interpret the scientific findings most relevant to managers’ resources of concern and management activities around those resources to guide adjustments to their activities toward better protecting their resources of concern. As an outcome, managers often relied on synthesized climate science to be able to consider how climate trends affect their work, especially those thinking about climate change for the first time in the context of their work. This lays the groundwork for more detailed management-driven science delivery that can aid eventual implementation. Management groups reached by this project include land managers with the National Park Service, state fish and game departments and DNRs, and tribal environmental coordinators.

Report↗
USGS2024

U.S. Geological Survey Northern Rocky Mountain Science Center science highlights for fiscal year 2023

The U.S. Geological Survey (USGS) Northern Rocky Mountain Science Center is based in Bozeman, Montana, and has field offices in Glacier National Park, Mont.; Missoula, Mont.; and Knoxville, Tennessee. Our scientists respond to the natural resource management needs of Federal, Tribal, and State partners—directly engaging in the coproduction and application of integrated, interdisciplinary science—and perform place-based research throughout the northern Rocky Mountains, including Yellowstone and Glacier National Parks and the northern Great Plains. However, the scope and implications of our research extend across the Nation. Our research themes are as follows: (1) climate change and drought, (2) species at risk, (3) habitat in changing landscapes, and (4) invasive species and wildlife disease. This Fact Sheet highlights examples of dynamic partnerships and key advances in our themes in fiscal year 2023 (October 2022–September 2023).

Fact Sheet↗
USGS2012

Flood-inundation maps for the Leaf River at Hattiesburg, Mississippi

Digital flood-inundation maps for a 1.7-mile reach of the Leaf River were developed by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The Leaf River study reach extends from just upstream of the U.S. Highway 11 crossing to just downstream of East Hardy/South Main Street and separates the cities of Hattiesburg and Petal, Mississippi. 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-surface elevations (stages) at the USGS streamgage at Leaf River at Hattiesburg, Mississippi (02473000). Current conditions at the USGS streamgage may be obtained through the National Water Information System Web site at http://waterdata.usgs.gov/ms/nwis/uv/?site_no=02473000&PARAmeter_cd=00065,00060 . In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. The forecasted peak-stage information, available on the AHPS Web site, 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 Leaf River at Hattiesburg, Mississippi, streamgage and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water-surface elevation 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 0.6-foot vertical accuracy and 9.84-foot horizontal resolution] in order to delineate the area flooded at each 1-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Mississippi↗
USGS2013

Flood-inundation maps for the Wabash River at Terre Haute, Indiana

Digital flood-inundation maps for a 6.3-mi reach of the Wabash River from 0.1 mi downstream of the Interstate 70 bridge to 1.1 miles upstream of the Route 63 bridge, Terre Haute, Indiana, 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 select water levels (stages) at the USGS streamgage Wabash River at Terre Haute (station number 03341500). 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=03341500&agency_cd=USGS&p"). In addition, the same data are provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps//). Within this system, the NWS forecasts flood hydrographs for the Wabash River at Terre Haute 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 model was calibrated using the most current stage-discharge relation at the Wabash River at the Terre Haute streamgage. The hydraulic model was then used to compute 22 water-surface profiles for flood stages at 1-ft interval referenced to the streamgage datum and ranging from bank-full 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) to delineate the area flooded at each water level. The availability of these maps along with Internet information regarding the current stage from the USGS streamgage and forecasted stream stages from the NWS can 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↗
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

Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations

Scientific experts from different disciplines often struggle to mesh their specialized perspectives into the shared mindset that is needed to address difficult and persistent environmental, ecological, and societal problems. Many traditional graduate programs provide excellent research and technical skill training. However, these programs often do not teach a systematic way to learn team skills, nor do they offer a protocol for identifying and tackling increasingly integrated interdisciplinary (among disciplines) and transdisciplinary (among researchers and stakeholders) questions. As a result, professionals trained in traditional graduate programs (e.g., current graduate students and employed practitioners) may not have all of the collaborative skills needed to advance solutions to difficult scientific problems. In the present article, we illustrate a tractable, widely implementable structured process called RISE that accelerates the development of these missing skills. The RISE process (Route to Identifying, learning, and practicing interdisciplinary and transdisciplinary team Skills to address difficult Environmental problems) can be used by diverse teams as a tool for research, professional interactions, or training. RISE helps professionals with different expertise learn from each other by repeatedly asking team-developed questions that are tested using an interactive quantitative tool (e.g., agent-based models, machine learning, case studies) applied to a shared problem framework and data set. Outputs from the quantitative tool are then discussed and interpreted as a team, considering all team members’ perspectives, disciplines, and expertise. After this synthesis, RISE is repeated with new questions that the team jointly identified in earlier data interpretation discussions. As a result, individual perspectives, originally informed by disciplinary training, are complemented by a shared understanding of team function and elevated interdisciplinary knowledge.

BioScience↗
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↗