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At least 433 records · Page 24Linked to original sources
USGS2024

Atlantic salmon (Salmo salar) culture manual

The primary objective of the Atlantic Salmon Research Program established at the U.S. Geological Survey Tunison Laboratory of Aquatic Science as mandated by the Great Lakes Restoration Initiative is to restore Atlantic salmon (Linnaeus, 1758; Salmo salar ) into Lake Ontario. This objective focuses on evaluating the survival of stocked Atlantic salmon in current Lake Ontario conditions to create a genetic strain that is robust to overcome current physiological and physical barriers. To complete this goal, new and innovative hatchery techniques based on past successful methods and protocols to grow Atlantic salmon to various life stages are described in this standard operating manual.

Techniques and Methods↗
USGS2023

Modeling the effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine-dominant estuary

The effects of large-scale interior headland restoration on tidal hydrodynamics and salinity transport in an open coast, marine dominant estuary (Grand Bay, Alabama, U.S.A) are investigated using a two-dimensional model, the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM). Three restoration alternatives are simulated for present-day conditions, as well as under 0.5 m of sea level rise (SLR). Model results show that the restoration alternatives have no impact on tidal range within the estuary but change maximum tidal velocities by ±5 cm/s in the present-day scenarios and by ±7 cm/s in the scenarios with 0.5 m of SLR. Differences in average salinity concentrations for simulated tropical and frontal seasons show increases and decreases on the order of 2 pss in the embayments surrounding the restoration alternatives; differences were larger (on the order of ±4 pss) for the scenarios with 0.5 m of SLR. There were minimal changes in average salinity outside of the estuary and no changes offshore. The size and position of the alternatives played a role in the salinity response as a result of changing the estuarine shoreline geometry and affecting the fetch within the bay. SLR was more impactful in increasing exposure to low salinity values (i.e., less than 5 pss) than the presence of the restoration alternatives. Overall, the modeled results indicate that these large-scale restoration actions have limited and localized impacts on the hydrodynamics and salinity patterns in this open coast estuary. The results also demonstrate the nonlinear response of salinity to SLR, with increases and decreases in the maximum, mean and minimum daily salinity concentrations from present-day conditions. This nonlinear response was a result of changes in the directions of the residual currents, which affected salinity transport.

Alabama↗
USGS2015

U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2014 annual report

This is the seventh report produced by the U.S. Geological Survey (USGS) for the Wyoming Landscape Conservation Initiative (WLCI) to detail annual activities conducted by the USGS for addressing specific management needs identified by WLCI partners. In FY2014, there were 26 projects, including a new one that was completed, two others that were also completed, and several that entered new phases or directions. The 26 projects fall into several categories: (1) synthesizing and analyzing existing data to identify current conditions on the landscape and using the data to develop models for projecting past and future landscape conditions; (2) monitoring indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms underlying wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. The new (completed) project was the development and publication of a public outreach piece for visitors of Fossil Butte National Monument. The final product was a USGS Fact Sheet that capitalized on previously collected elk-monitoring data to interpret the ecology of the Monument’s elk population and the importance of the Monument’s habitats to this highly visible wildlife species. One of the completed projects entailed developing and evaluating a synthetic approach to high-resolution satellite imagery for use in effectiveness monitoring, which culminated in a journal article. The other completed project was a coalescing of two similar tasks under data and information management that pertain to Web application development and the development of outreach and graphic products into a single integrated project that focuses on developing and maintaining/upgrading Web applications and other tools for visualizing, mapping, and using geospatial data. Major accomplishments for FY2014 included several publications, including Part B of an energy resources map that (with Part A) depicts coal, wind, oil, gas, oil shale, uranium, and solar energy production in the WLCI region. Two published works associated with sage-grouse included a Wildlife Monograph on prioritizing species’ habitats across large landscapes, multiple seasons, and novel areas (using sage-grouse in Wyoming as an example), and a USGS Data Series report that includes both the data used in the habitat-prioritization models and the habitat prioritization models developed for sage-grouse. Our Science Team also published a framework for conducting large, collaborative projects that rely on geospatial data, and a paper that describes the efficacy of fusing satellite data collected at various resolutions for measuring and monitoring vegetation changes. These products are all invaluable tools for maximizing the efficiency and effectiveness of managing species of concern, conducting future landscape-scale assessments, and monitoring status and trends of landscape conditions. Other highlights of FY2014 included a renewed effort to gather and analyze wildlife and habitat status and trend data for the WLCI Interagency Monitoring Database (IAMD) to assess long-term trends and cumulative effects associated with land-use and climate changes. Water-monitoring efforts included drilling four new groundwater-monitoring wells in the Green and New Fork River basins near the proposed Normally Pressured Lance Formation energy development, and continued data collection at established water-monitoring sites. Three additional wells were sampled as part of the Wyoming Groundwater Monitoring Network, bringing the total to 19 Network wells sampled in the WLCI region since 2010. Combined, these water-monitoring efforts can help to identify potential changes in water quality or levels that may result from land-use changes. Major terrestrial monitoring accomplishments included processing satellite imagery from 1985−2010 to develop a historical perspective of long-term vegetation changes, which can serve as a basis for monitoring current and future trends in sagebrush steppe. Such data are crucial tools for agencies tasked with sage-grouse management and conservation. The USGS WLCI Science Team also continued monitoring and testing methods for evaluating WLCI habitat treatments designed to promote aspen regeneration and enhance sage-grouse habitat, and to assess how those treatments influence invasive species distributions and ungulate herbivory. Highlights included analyzing field data collected to elucidate the relationships between sage-grouse habitat use and the proximity of energy infrastructure, and using new instruments to measure productivity responses of aspen woodlands to various factors. Numerous FY2014 accomplishments specifically addressed agency needs to manage and conserve Wyoming’s wildlife species of concern. A pygmy rabbit habitat model and Wyoming distribution map were completed to identify factors associated with rabbit habitat occupancy. Previous work on sage-grouse population dynamics was expanded to better understand the factors that drive long-term viability of sage-grouse populations and to develop a tool that helps to identify key factors limiting sage-grouse persistence in Wyoming. Field work and data analyses continued for elucidating the relationships between sagebrush songbird abundance and productivity, the intensity of energy development, and community dynamics of nest predators. For the mule deer study, mixed mountain shrublands important to migrating and wintering mule deer were mapped and delivered to WLCI partners. Additionally, the relationships between energy development and crucial winter habitat for mule deer were evaluated, and a new phase of work was implemented to better understand relationships between plant phenology and mule deer migration movements. Finally, initial analyses of data collected to evaluate fish-community composition in relation to habitat quality indicate that water quality, as measured by concentrations of hydrocarbons, water temperature, and others parameters, has been diminished in subwatersheds with higher levels of energy development. Overall, the outcomes and products of these wildlife studies contribute significantly to the information and tools needed for addressing effects of land-use changes on Wyoming’s species of concern. Finally, capabilities of the WLCI Web site and the USGS ScienceBase infrastructure were maintained and upgraded to help ensure access to and efficient use of all the WLCI data, products, assessment tools, and outreach materials that have been developed. Of particular note is the completion of three Web applications developed for mapping (1) the 1900−2008 progression of oil and gas development;(2) the predicted distributions of Wyoming’s Species of Greatest Conservation Need; and (3) the locations of coal and wind energy production, sage-grouse distribution and core management areas, and alternative routes for transmission lines within the WLCI region. Collectively, these applications tools provide WLCI planners and managers with powerful tools for better understanding the distributions of wildlife species and potential alternatives for energy development.

Wyoming↗
USGS2025

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia↗
USGS2019

Employing an ecosystem services framework to deliver decision ready science

Public land managers have limited information to allow for the integration and balancing of multiple objectives in land management decisions including the social (cultural and health), economic (monetary and nonmonetary), and environmental aspects. In this article, we document an approach to consider the many facets of decision making by incorporating them into a decision context using an ecosystem services framework. This analysis is based on a multi-partner project led by the US Geological Survey and the US Fish and Wildlife Service to provide land management decision support for the Great Dismal Swamp National Wildlife Refuge. It is an integrated ecologic-economic analysis of baseline (current) and potential future quantities, qualities, and values of selected ecosystem services from the Refuge. Alternative management scenarios are modeled to consider the impact of specific management actions or natural disturbances on priority ecosystem services. We examine the benefits and challenges of using this framework. Key lessons learned from this effort include the mismatch in timing between physical and social science; the challenge of integrating methods from multiple disciplines; the importance of frequent communication to overcome siloed research; and the utility of an integrating framework for ecosystem services and supporting tools such as the dynamic ecosystem model.

Advances in Ecological Research↗
USGS2016

Uncertainty in biological monitoring: a framework for data collection and analysis to account for multiple sources of sampling bias

Biological monitoring programmes are increasingly relying upon large volumes of citizen-science data to improve the scope and spatial coverage of information, challenging the scientific community to develop design and model-based approaches to improve inference. Recent statistical models in ecology have been developed to accommodate false-negative errors, although current work points to false-positive errors as equally important sources of bias. This is of particular concern for the success of any monitoring programme given that rates as small as 3% could lead to the overestimation of the occurrence of rare events by as much as 50%, and even small false-positive rates can severely bias estimates of occurrence dynamics. We present an integrated, computationally efficient Bayesian hierarchical model to correct for false-positive and false-negative errors in detection/non-detection data. Our model combines independent, auxiliary data sources with field observations to improve the estimation of false-positive rates, when a subset of field observations cannot be validated a posteriori or assumed as perfect. We evaluated the performance of the model across a range of occurrence rates, false-positive and false-negative errors, and quantity of auxiliary data. The model performed well under all simulated scenarios, and we were able to identify critical auxiliary data characteristics which resulted in improved inference. We applied our false-positive model to a large-scale, citizen-science monitoring programme for anurans in the north-eastern United States, using auxiliary data from an experiment designed to estimate false-positive error rates. Not correcting for false-positive rates resulted in biased estimates of occupancy in 4 of the 10 anuran species we analysed, leading to an overestimation of the average number of occupied survey routes by as much as 70%. The framework we present for data collection and analysis is able to efficiently provide reliable inference for occurrence patterns using data from a citizen-science monitoring programme. However, our approach is applicable to data generated by any type of research and monitoring programme, independent of skill level or scale, when effort is placed on obtaining auxiliary information on false-positive rates.

Methods in Ecology and Evolution↗
USGS2018

Revised recommended methods for analyzing crater size-frequency distributions

Impact crater populations crucially help us to understand solar system dynamics, planetary surface histories, and surface modification processes. A single previous effort to standardize how crater data are displayed in graphs, tables, and archives, was in a 1978 NASA report by the Crater Analysis Techniques Working Group, published in 1979 in Icarus . The report had a significant lasting effect, but later decades brought major advances in statistical and computer sciences while the crater field has remained fairly stagnant. In this new work, we revisit the fundamental techniques for displaying and analyzing crater population data and demonstrate better statistical methods that can be used. Specifically, we address (1) how crater size-frequency distributions (SFDs) are constructed, (2) how error bars are assigned to SFDs, and (3) how SFDs are fit to power laws and other models. We show how the new methods yield results similar to those of previous techniques in that the SFDs have familiar shapes but better account for multiple sources of uncertainty. We also recommend graphic, display, and archiving methods that reflect computers' capabilities and fulfill NASA's current requirements for Data Management Plans.

Meteoritics and Planetary Science↗
USGS2024

The state of the science and practice of stream restoration in the Chesapeake: Lessons learned to inform better implementation, assessment and outcomes

The Chesapeake Bay Program’s (CBP) Science and Technical Advisory Committee (STAC) organized and led a workshop on the science and practice of stream restoration in order to summarize the state of knowledge in order to identify ways to improve stream restoration outcomes. The workshop identified a general framework for explaining the main factors leading to stream restoration outcomes: stream degradation has occurred, leading to regulatory and policy motivations that prioritize project goals, which leads to restoration approaches, assessment and monitoring efforts, and ultimately stream restoration outcomes. In the Chesapeake Bay watershed, stream restoration often occurs in response to Clean Water Act (CWA) mandates to reduce nitrogen, phosphorus, and sediment loads to the Bay. Reviews of stream restoration outcomes summarized at the workshop showed that, in general, stream restorations have led to minimal improvement to stream aquatic biota, effective ‘stabilization’ of channel form over time, moderate improvements to water quality, and short-term negative impacts to riparian vegetation. The fundamental finding of the workshop was that often the primary goal of stream restoration projects is to improve geomorphic stability in the restored reach and downstream water quality, and not to improve local ecological conditions through ‘uplift’ (improvement of one or more ecosystem functions through a restorative activity; a term defined in Appendix D), and therefore these projects often do not improve aquatic macroinvertebrate or fish communities. This conflict in goals is a shortcoming of the currently most common regulatory driver for stream restoration (reducing downstream loads of N, P, and sediment) that could be addressed directly through diversifying goals to include biotic uplift, as biological benefit is an assumed condition for the permitting and crediting of stream restoration projects. It is also likely that current understanding of stressors and drivers of stream ecosystem health is insufficient, and that reach-scale restoration focused on geomorphic restoration is not removing the actual sources of stream health impairment that may arise in the upstream watershed. More science could help to identify how to improve the ecological condition of streams through management. The outcome of stream restoration monitoring has revealed that while geomorphic and hydrodynamic functions of stream restoration projects may be achieved, biotic stream function improvements remain elusive. As such, ensuring uplift may be achieved by avoiding restoration projects that risk resources in higher-quality streams and riparian corridors. Reach-scale restoration often does not effectively mitigate the watershed-scale stressors of stream ecosystems. If a desired outcome of stream restoration includes ecological uplift, then focusing efforts on improving stream ecology could help meet that goal.

Chesapeake Bay watershed↗
USGS2024

Groundwater-Surface water interactions research: Past trends and future directions

Interactions between groundwater and surface water sustain groundwater-dependent ecosystems and regulate river temperature and biogeochemical cycles, amongst many other processes. These interactions occur in freshwater environments including rivers, springs, lakes, and wetlands, and in coastal environments via tidal pumping, submarine groundwater discharge, and seawater intrusion. Here, we explore groundwater-surface water interactions research using bibliometric analyses of titles, abstracts, and keywords from 20,275 journal papers published between 1970 and 2023 extracted from Scopus. Analyses show that research into groundwater-surface water interactions is highly multi-disciplinary, with growing contributions from the social and biological sciences. The number of groundwater-surface water interactions papers is rapidly increasing with over 1200 papers published per year since 2020. Drawing on our data-driven approach and expert knowledge, we synthesise current research trends and identify critical future research directions. Despite the thousands of papers on groundwater-surface water interactions, important processes are still difficult to quantify or predict at meaningful spatial scales to inform water-resources management. We see benefits in future groundwater-surface water interactions research focusing on: (1) using new technologies including internet-of-things-based sensors, uncrewed vehicles, and remote-sensing approaches for data collection to inform groundwater-surface water interactions at large scales, (2) seeking approaches to upscale site-specific findings to better inform management, and (3) continuing the movement towards multi-disciplinary investigations to better inform the understanding of groundwater-surface water interactions and processes that will enable better management outcomes.

Journal of Hydrology↗
USGS2025

Review of the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2014–20

Executive Summary The Hiram M. Chittenden (Ballard) Locks and Lake Washington Ship Canal connect freshwater Lake Washington and saline Shilshole Bay of Puget Sound in Seattle, Washington. The locks and canal allow for ships to traverse this reach. Anadromous salmonids also migrate through, transitioning between saline and freshwater environments, and making use of a fish ladder at the locks when traveling upstream. WEST Consultants, Inc., constructed a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) simulating flow, water temperature, and salinity for the Ballard Locks and the Lake Washington Ship Canal. An initial model was built for calendar years 2014–15, and the model was updated using a more recent and modern dataset for calendar years 2016–20. The U.S. Army Corps of Engineers requested that the U.S. Geological Survey review this model and its documentation to evaluate the technical aspects of its development and calibration. Findings from this review include the following: Overall, the Lake Washington Ship Canal CE-QUAL-W2 model was well-documented and constructed largely following typical model-development methods. The Lake Washington Ship Canal model was built with CE-QUAL-W2 model version 4.5, compiled and released by Portland State University in April 2021. CE-QUAL-W2 updates and improvements are regularly released with bug fixes and new features, so any model updates would benefit from the use of the most-recent software release. The model grid that represents the Lake Washington Ship Canal bathymetry was 9.2 kilometers (5.7 miles) long, matching the expected length of the waterway. The deepest model segments were near sampling site LLLW (Large Locks site) near the locks. Lake Union is reported to constitute most of the volume of the Lake Washington Ship Canal and is depicted as such in the model grid. The model includes several water outflows at Ballard Locks, including the large and small locks, a saltwater drain, a spillway, smolt flumes, and a fish ladder. Flows from the spillway, smolt flumes, and fish ladder were combined into one structure outflow in the model and assigned one withdrawal elevation from the Lake Washington Ship Canal. The smolt flume and spillway withdraw from the same elevation, but the fish ladder flow withdraws from a higher elevation in Lake Washington Ship Canal, and that flow could be separated into its own withdrawal. The model input files were created using the Coordinated Universal Time standard instead of the more typical choice of using local standard time. This is not incorrect, but sub-daily results would need to be converted to local time for science-communication purposes. The meteorological dataset had some unexpected anomalies, such as a baseline shift in the wind-speed dataset. Other nearby meteorological datasets could be used instead or used to correct the current meteorological inputs. The upstream boundary was configured with water-temperature data from a continuous monitor buoy in Lake Washington. The boundary salinity was set at 0 parts per thousand for the duration of the model simulation. A more realistic estimate of salinity at the upstream boundary could be constructed using data from the same buoy. Saline inflow at the downstream boundary of the Lake Washington Ship Canal model through lock exchanges at the large lock was included as a tributary in the model. Salinity and temperature inputs in this tributary at the large locks were set as constant values for the entire simulation. Saline inflow through the small lock was not included in the model because few data were available, and the input was likely to be small because of the smaller surface area and volume of the small lock relative to the large lock. The model did not include any flow, water temperature, or salinity inputs to the Lake Washington Ship Canal other than at the locks and at the upstream boundary. Any point sources, small tributaries, or stormwater inputs were omitted from the model. It is unclear whether this is a substantial omission relative to model results. Most model parameters were set as defaults or to reasonable values. However, the value of the WINDH parameter, the height of the wind speed measurement, was different than the height of the meteorological site. Compared to measured data, the model simulated water-surface elevations and water temperatures with reasonable accuracy. Differences in the modeled and measured salinities revealed some opportunities to improve the simulation of salinity, both baseline salinity and the salinity maxima in summer and autumn.

Washington↗
USGS2012

Flood-inundation maps for Sweetwater Creek from above the confluence of Powder Springs Creek to the Interstate 20 bridge, Cobb and Douglas Counties, Georgia

Digital flood-inundation maps for a 10.5-mile reach of Sweetwater Creek, from about 1,800 feet above the confluence of Powder Springs Creek to about 160 feet below the Interstate 20 bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with Cobb County, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Sweetwater Creek near Austell, Georgia (02337000). Current stage at this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Sweetwater Creek near Austell (02337000), which is available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineering Centers River Analysis System (HEC–RAS) software for Sweetwater Creek and was used to compute flood profiles for a 10.5-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Sweetwater Creek near Austell streamgage (02337000), as well as high-water marks collected during annual peak-flow events in 1982 and 2009. The hydraulic model was then used to determine 21 water-surface profiles for flood stages at the Sweetwater Creek streamgage at 1-foot intervals referenced to the streamgage datum and ranging from just above bankfull stage (12.0 feet) to approximately 1.2 feet above the highest recorded water level at the streamgage (32.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from contour data (8-foot horizontal resolution), in Cobb County, and USGS National Elevation Dataset (31-foot horizontal resolution), in Douglas County—to delineate the area flooded for each 1-foot increment of stream stage. The availability of these maps, when combined with real-time information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, 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.

Georgia↗
USGS2012

Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia

Digital flood-inundation maps for a 6.9-mile reach of Suwanee Creek, from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with Gwinnett County, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Suwanee Creek at Suwanee, Georgia (02334885). Current stage at this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system ( http://water.weather.gov/ahps/ ). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Suwanee Creek at Suwanee (02334885), available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC-RAS software for Suwanee Creek and was used to compute flood profiles for a 6.9-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Suwanee Creek at Suwanee streamgage (02334885). The hydraulic model was then used to determine 19 water-surface profiles for flood stages at the Suwanee Creek streamgage at 0.5-foot intervals referenced to the streamgage. The profiles ranged from just above bankfull stage (7.0 feet) to approximately 1.7 feet above the highest recorded water level at the streamgage (16.0 feet). 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 5.0-foot horizontal resolution - to delineate the area flooded for each 0.5-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.

Georgia↗
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↗
USGS2014

Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana

Digital flood-inundation maps for a reach of the North Branch Elkhart River at Cosperville, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, Detroit District. 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 04100222, North Branch Elkhart River at Cosperville, 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=04100222 . In addition, 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 AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the North Branch Elkhart River at Cosperville, Ind. NWS AHPS-forecast peak-stage information 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 North Branch Elkhart River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and preliminary high-water marks from the flood of March 1982. The calibrated hydraulic model was then used to determine four 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 (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [LiDAR]) 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 04100222, North Branch Elkhart River at Cosperville, Ind., and forecast stream stages from the NWS AHPS, 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↗
USGS2024

Novel data in recreation monitoring—Summary proceedings from interagency workshops in 2019 and 2023

Two interagency workshops were held in 2019 and 2023 in Fort Collins, Colorado, to discuss the use of novel data in recreation monitoring. During the workshops, the phrase “novel data in recreation monitoring” was primarily used to refer to data from social media, mobile device applications, and other online secondary sources. The goals of these workshops were to share information across agencies and researchers on the state of the science and applications for using novel data and to collectively discuss best practices for using novel data for understanding recreation on public lands and waters. Presentations during the workshops focused on use-cases, current applications, and the current state of research (as of the time of the workshops) for using novel data in recreation monitoring. Group discussions during the workshops focused on the strengths and limitations of novel data sources, potential approaches for integrating new and emerging data sources and methods with traditional approaches, and research and management needs. This report provides the proceedings of the 2019 and 2023 interagency workshops on novel data in recreation monitoring.

Scientific Investigations Report↗
USGS2020

Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment

The US Fish and Wildlife Service has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of a species’ current status and predicted future status. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, recovery planning, etc. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting species conservation decisions in current data and cutting edge analytical and modeling techniques. Here we describe a novel analysis of available data to assess current condition of eastern black rail across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future conditions under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With results of these data analyses and predictive modeling, the US Fish and Wildlife Service concluded that protections of the Endangered Species Act were warranted for this subspecies.

Endangered Species Research↗
USGS1979

A selected bibliography of remote sensing applications to soil science

The bibliography contains approximately 200 references dealing with the application of remote sensing technology to the identification and analysis of soils. The scientific papers and reports listed describe procedures and methods used in data collection and include specific applications of those data to soil studies. Most citations discuss current work from 1970 to 1978 and all references are categorized according to the type of remotely sensed data used and their application.

Report↗
USGS2008

Impacts of Low-Flow and Stream-Temperature Changes on Endangered Atlantic Salmon - Current Research

Recent climate studies in New England and the northeastern United States have shown evidence of physical changes over time, including trends toward earlier snowmelt runoff, decreasing river ice, and increasing spring water temperatures. A U.S. Geological Survey (USGS) study funded by the National Global Warming and Wildlife Science Center will be investigating changes in summer low streamflows and stream temperatures and the potential effects of those changes on endangered Atlantic salmon populations. The study also will evaluate management options that would be most likely to mitigate the effects of any changes in streamflow and temperature.

Fact Sheet↗