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At least 739 records · Page 41Linked to original sources
USGS2021

Establishment of a microsatellite genetic baseline for North American Atlantic sturgeon (Acipenser o. oxyrhinchus) and range-wide analysis of population genetics

Atlantic sturgeon ( Acipenser oxyrinchus oxyrinchus ) is a long-lived, anadromous species that is broadly distributed along the Atlantic coast of North America. Historic overharvest and habitat degradation resulted in significant declines to Atlantic sturgeon populations and, following decades of limited recovery, the species was listed under the Endangered Species Act of the United States in 2012. Given continued threats to recovery and limited information about population demography, there is a need for new tools to assist in Atlantic sturgeon conservation. Here, we present a range-wide microsatellite genetic baseline for North American Atlantic sturgeon that is comprised of 2510 individuals from 18 genetically distinct groups collected in 13 rivers and one estuary. Analysis of this baseline suggested that populations from the northern range of Atlantic sturgeon were more highly differentiated than those from the southern extent, where patterns of differentiation were complicated by rivers with genetically distinct spring and fall spawning runs and less geographic distance separating populations. Despite significant demographic bottleneck events, all populations showed at least moderate levels of genetic diversity across a suite of metrics. Additionally, individual-based assignment tests had over 80% accuracy for assigning individuals to their river of origin, highlighting the utility of this baseline for characterizing the composition of mixed-stock aggregations and understanding stock-specific vulnerability and recovery. The expanded spatial coverage of this baseline dataset enabled novel inferences about patterns of genetic differentiation and spawning phenology in Atlantic sturgeon which can be used to support conservation and management efforts.

Atlantic Coast↗
USGS2023

Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies

Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) to perform these checks and estimate probabilities that an analyst would publish or reject a site-specific trend model from a multi-site study. We trained these “model-checking models” (MCMs) using a national study of over 6000 trend models and tested the MCMs using a smaller set of novel trend models. Although the MCMs did not perform well enough to bypass analyst review entirely, we found incorporating an MCM into a larger evaluation workflow can reduce the number of trend models needing an analyst review by more than half.

Environmental Modeling and Software↗
USGS2014

Volcanology: Lessons learned from Synthetic Aperture Radar imagery

Twenty years of continuous Earth observation by satellite SAR have resulted in numerous new insights into active volcanism, including a better understanding of subsurface magma storage and transport, deposition of volcanic materials on the surface, and the structure and development of volcanic edifices. This massive archive of data has resulted in fundamental leaps in our understanding of how volcanoes work – for example, identifying magma accumulation at supposedly quiescent volcanoes, even in remote areas or in the absence of ground-based data. In addition, global compilations of volcanic activity facilitate comparison of deformation behavior between different volcanic arcs and statistical evaluation of the strong link between deformation and eruption. SAR data are also increasingly used in timely hazard evaluation thanks to decreases in data latency and growth in processing and analysis techniques. The existing archive of SAR imagery is on the cusp of being enhanced by a new generation of satellite SAR missions, in addition to ground-based and airborne SAR systems, which will provide enhanced temporal and spatial resolution, broader geographic coverage, and improved availability of data to the scientific community. Now is therefore an opportune time to review the contributions of SAR imagery to volcano science, monitoring, and hazard mitigation, and to explore the future potential for SAR in volcanology. Provided that the ever-growing volume of SAR data can be managed effectively, we expect the future application of SAR data to expand from being a research tool for analyzing volcanic activity after the fact, to being a monitoring and research tool capable of imaging a wide variety of processes on different temporal and spatial scales as those processes are occurring. These data can then be used to develop new models of how volcanoes work and to improve quantitative forecasts of volcanic activity as a means of mitigating risk from future eruptions.

Journal of Volcanology and Geothermal Research↗
USGS2007

Recent results on the spatiotemporal modelling and comparative analysis of Black Death and bubonic plague epidemics

Background: This work demonstrates the importance of spatiotemporal stochastic modelling in constructing maps of major epidemics from fragmentary information, assessing population impacts, searching for possible etiologies, and performing comparative analysis of epidemics. Methods: Based on the theory previously published by the authors and incorporating new knowledge bases, informative maps of the composite space-time distributions were generated for important characteristics of two major epidemics: Black Death (14th century Western Europe) and bubonic plague (19th-20th century Indian subcontinent). Results: The comparative spatiotemporal analysis of the epidemics led to a number of interesting findings: (1) the two epidemics exhibited certain differences in their spatiotemporal characteristics (correlation structures, trends, occurrence patterns and propagation speeds) that need to be explained by means of an interdisciplinary effort; (2) geographical epidemic indicators confirmed in a rigorous quantitative manner the partial findings of isolated reports and time series that Black Death mortality was two orders of magnitude higher than that of bubonic plague; (3) modern bubonic plague is a rural disease hitting harder the small villages in the countryside whereas Black Death was a devastating epidemic that indiscriminately attacked large urban centres and the countryside, and while the epidemic in India lasted uninterruptedly for five decades, in Western Europe it lasted three and a half years; (4) the epidemics had reverse areal extension features in response to annual seasonal variations. Temperature increase at the end of winter led to an expansion of infected geographical area for Black Death and a reduction for bubonic plague, reaching a climax at the end of spring when the infected area in Western Europe was always larger than in India. Conversely, without exception, the infected area during winter was larger for the Indian bubonic plague; (5) during the Indian epidemic, the disease disappeared and reappeared several times at most locations; in Western Europe, once the disease entered a place, it lasted a time proportional to the population and then disappeared for several years (this on-and-off situation lasted more than three centuries); and (6) on average, Black Death moved much faster than bubonic plague to reach virgin territories, despite the fact that India is only slightly larger in area than Western Europe and had a railroad network almost instantly moving infected rats, fleas, and people from one end of the subcontinent to the other. Conclusions: These findings throw new light on the spatiotemporal characteristics of the epidemics and need to be taken into consideration in the scientific discussion concerning the two devastating diseases and the lessons learned from them. ?? 2007 The Royal Institute of Public Health.

Public Health↗
USGS2012

Pyrethroid insecticides in bed sediments from urban and agricultural streams across the United States

Pyrethroid insecticides are hydrophobic compounds that partition to streambed sediments and have been shown to cause toxicity to non-target organisms; their occurrence is well documented in parts of California, but there have been limited studies in other urban and agricultural areas across the United States. To broaden geographic understanding of pyrethroid distributions, bed sediment samples were collected and analyzed from 36 streams in 25 states, with about 2/3 of the sites in urban areas and 1/3 in agricultural areas. At least one pyrethroid (of the 14 included in the analysis) was detected in 78% of samples. Seven pyrethroids were detected in one or more samples. Bifenthrin was the most frequently detected (58% of samples), followed by permethrin (31%), resmethrin (17%), and cyfluthrin (14%). The other three detected pyrethroids (cyhalothrin, cypermethrin and delta/tralomethrin) were found in two or fewer of the samples. Concentrations ranged from 0.3 to 180 ng g -1 dry weight. The number of pyrethroids detected were higher in the urban samples than in the agricultural samples, but the highest concentrations of individual pyrethroids were split between urban and agricultural sites. The pyrethroids detected in the agricultural areas generally followed use patterns. Predicted toxicity was greater for urban areas and attributed to bifenthrin, cyfluthrin and cypermethrin, while in agricultural areas the toxicity was mainly attributed to bifenthrin.

Journal of Environmental Monitoring↗
USGS2021

USGS National Water Quality Monitoring Network

What is the U.S. Geological Survey National Water Quality Monitoring Network? Understanding the water quality of U.S. streams and rivers requires consistent data collection and analysis over decades. The U.S. Geological Survey’s (USGS) National Water Quality Network (NWQN) was established to facilitate national-scale understanding of surface-water quality conditions through the collection of comparable data in large rivers and small streams in different geographic and land-use settings. Data collected by the NWQN support the needs of Federal, State, and local stakeholders tasked with managing our Nation’s water resources.

Fact Sheet↗
USGS1974

A computer system for the storage and retrieval of gravity data, Kingdom of Saudi Arabia

A computer system has been developed for the systematic storage and retrieval of gravity data. All pertinent facts relating to gravity station measurements and computed Bouguer values may be retrieved either by project name or by geographical coordinates. Features of the system include visual display in the form of printer listings of gravity data and printer plots of station locations. The retrieved data format interfaces with the format of GEOPAC, a system of computer programs designed for the analysis of geophysical data.

Open-File Report↗
USGS1988

Benthic macrofauna and ancillary data for San Francisco Bay, California, March to November 1987

Benthic macrofauna and ancillary data were collected during 1987 as part of the U.S. Geological Survey Regional Effects Monitoring Program in San Francisco Bay, California. Data were collected during five cruises at 2-month intervals from March through November. Benthic macrofauna for identification of species and sediment for size analysis were sampled at eight stations. Ancillary data, which consisted of salinity, temperature, dissolved-oxygen concentrations, and suspended sediment, were collected at 12 stations. Salinity and temperature were measured at three stations that coincided with continuous water quality monitors. Abundances and geographical distributions of a newly introduced species of clam were measured. (USGS)

Open-File Report↗
USGS2004

Generalized estimates from streamflow data of annual and seasonal ground-water-recharge rates for drainage basins in New Hampshire

This report presents regression equations to estimate generalized annual and seasonal ground-water-recharge rates in drainage basins in New Hampshire. The ultimate source of water for a ground-water withdrawal is aquifer recharge from a combination of precipitation on the aquifer, ground-water flow from upland basin areas, and infiltration from streambeds to the aquifer. An assessment of ground-water availability in a basin requires that recharge rates be estimated under `normal' conditions and under assumed drought conditions. Recharge equations were developed by analyzing streamflow, basin characteristics, and precipitation at 55 unregulated continuous record stream-gaging stations in New Hampshire and in adjacent states. In the initial step, streamflow records were analyzed to estimate a series of annual and seasonal ground-water-recharge components of streamflow in each drainage basin evaluated in this study. Regression equations were then developed relating the series of annual and seasonal ground-water-recharge values to the corresponding series of annual and seasonal precipitation values as determined at the centroid of each drainage basin. This resulted in one equation for each of the 55 basins for each of the four seasonal periods and the annual period, or a total of 275 regression equations. Average annual and seasonal precipitation data for 1961-90 were then used to compute a set of normalized ground-water-recharge values that reflected the long-term average annual and seasonal variations (normalized) and mean recharge characteristics of each drainage basin. Ordinary-least-squares regression was applied in the process of selecting 10 out of 93 possible basin and climatic characteristics for further testing in the development of the equations for computing the generalized estimate of annual and seasonal ground-water recharge based on the set of normalized recharge values. Generalized-least-squares regression was used for the final parameter estimation and error evaluation. The following basin and climatic characteristics were found to be statistically significant predictors for at least one of the dependent variables: average annual, summer, and spring precipitation as determined at U.S. Geological Survey stream-gaging stations; average annual basin-centroid precipitation; average mean annual basin temperature; average minimum winter basin temperature; percent coniferous forest in a basin; percent mixed coniferous and deciduous forest in a basin; average fall basin-centroid precipitation; and average annual snowcover. These 10 basin and climatic characteristics were selected because they were statistically significant based on several statistical parameters that evaluated which combination of characteristics contributed the most to the predictive accuracy of the regression-equation models. A geographic information system is required to measure the values of the predictor variables for the equations developed in the study. The average annual normalized ground-water recharge was 21.0 in. This value was determined by generalized-least-squares (GLS) regression analysis for all of the basins used in the normalized ground-water recharge analysis for precipitation from 1961-90. The average winter (January 1-March 15) ground-water recharge was 4.3 in., average spring (March 16-May 31) ground-water recharge was 9.0 in., average summer (June 1-October 31) ground-water recharge was 4.0 in., and average fall (November 1-December 31) ground-water recharge was 3.6 in. Normalized ground-water recharge ranged annually from 12.3 to 31.8 in., for winter from 2.30 to 7.82 in., for spring from 5.16 to 13.7 in., for summer from 1.45 to 10.2 in., and for fall from 2.21 to 6.06 in.

New Hampshire↗
USGS1998

Large-area mapping of biodiversity

The age of discovery, description, and classification of biodiversity is entering a new phase. In responding to the conservation imperative, we can now supplement the essential work of systematics with spatially explicit information on species and assemblages of species. This is possible because of recent conceptual, technical, and organizational progress in generating synoptic views of the earth's surface and a great deal of its biological content, at multiple scales of thematic as well as geographic resolution. The development of extensive spatial data on species distributions and vegetation types provides us with a framework for: (a) assessing what we know and where we know it at meso-scales, and (b) stratifying the biological universe so that higher-resolution surveys can be more efficiently implemented, coveting, for example, geographic adequacy of specimen collections, population abundance, reproductive success, and genetic dynamics. The land areas involved are very large, and the questions, such as resolution, scale, classification, and accuracy, are complex. In this paper, we provide examples from the United States Gap Analysis Program on the advantages and limitations of mapping the occurrence of terrestrial vertebrate species and dominant land-cover types over large areas as joint ventures and in multi-organizational partnerships, and how these cooperative efforts can be designed to implement results from data development and analyses as on-the-ground actions. Clearly, new frameworks for thinking about biogeographic information as well as organizational cooperation are needed if we are to have any hope of documenting the full range of species occurrences and ecological processes in ways meaningful to their management. The Gap Analysis experience provides one model for achieving these new frameworks.

Conference Paper↗
USGS2018

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

River Research and Applications↗
USGS1987

Trend analysis of monthly sulfur dioxide emissions in the conterminous United States, 1975-1984

Trends in monthly sulfur dioxide emissions for the 48 conterminous United States during the decade 1975-1984 are identified using a robust nonparametric procedure. Statistically significant downward trends are indicated in 32 States, upward trends appear in 10 States, and no significant trend is apparent in six States. Geographically, a distinct regional pattern of emission increases and decreases is evident with declines dominating the Eastern and Western States; increases aligning longitudinally from border to border in most of the Great Plains States, in several New England States, and in Georgia; and no trends frequently occurring in proximity to the upward trending emissions in the Plains States. A time-series decomposition of the monthly values indicates that one distinct emissions pattern commonly occurred through the period of record. This pattern is characterized by an initial emissions increase that peaks between 1977 and 1978, followed by a shallow and undulating decrease though the end of 1984. It is suggested that this signature represents the 'national' trend for the period. In addition, five regions of coherent sulfur dioxide emissions behavior are defined on the basis of seasonal occurrence of maximum and minimum emission loadings. A winter-summer, latitudinal opposition is apparent in the timing of emissions maxima, whereas an equinox-summer, longitudinal opposition is apparent in the timing of emissions minima.Trends in monthly sulfur dioxide emissions for the 48 conterminous United States during the decade 1975-1984 are identified using a robust nonparametric procedure. Statistically significant downward trends are indicated in 32 States, upward trends appear in 10 States, and no significant trend is apparent in six States. Geographically, a distinct regional pattern of emission increases and decreases is evident with declines dominating the Eastern and Western States; increases aligning longitudinally from border to border in most of the Great Plains States, in several New England States, and in Georgia; and no trends frequently occurring in proximity to the upward trending emissions in the Plains States. A time-series decomposition of the monthly values indicates that one distinct emissions pattern commonly occurred through the period of record. This pattern is characterized by an initial emissions increase that peaks between 1977 and 1978, followed by a shallow and undulating decrease through the end of 1984. It is suggested that this signature represents the 'national' trend for the period. Additional study results are discussed.

Atmospheric Environment↗
USGS2022

The socioecology of fear: A critical geographical consideration of human-wolf-livestock conflict

Animal fear can be an important driver of ecological community structure: predators affect prey not only through predation, but by inducing changes in behavior and distribution—a phenomenon evocatively called the “ecology of fear.” The return of wolves to the western United States is a notable instance of such dynamics, yet plays out in a complex socio-ecological system where efforts to mitigate impacts on livestock rely on manipulating wolves’ fear of people. Examining Washington state’s efforts to affect wolf behavior to reduce livestock predation, we argue that this approach to coexistence with wolves is predicated on relations of fear: people, livestock, and wolves can arguably share landscapes with minimal conflict, as long as wolves are adequately afraid. We introduce the “socioecology of fear” as an interdisciplinary framework for examining the interwoven social and ecological processes of human-wildlife conflict management. Beyond frequently-voiced ideas about wolves’ “innate” fear, we examine how fear is (re)produced through human-wolf interactions and deeply shaped by human social processes. We contribute to the Critical Physical Geography project by integrating critical social analysis with ecological theory, conducted through collaborative interdisciplinary dialogue. Such integrative practice is essential for understanding the complex challenges of managing wildlife in the Anthropocene.

Washington↗
USGS2015

Methods for estimating the magnitude and frequency of peak streamflows at ungaged sites in and near the Oklahoma Panhandle

This report presents the results of a cooperative study by the U.S. Geological Survey and the Oklahoma Department of Transportation to estimate the magnitude and frequency of peak streamflows from regional regression equations for ungaged stream sites in and near the Oklahoma Panhandle. These methods relate basin characteristics (physiographic and climatic attributes) to selected peak streamflow frequency statistics with the 50-, 20-, 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probabilities. These relations were developed based on data from 32 selected streamflow-gaging stations in the Oklahoma Panhandle and in neighboring parts of Colorado, Kansas, New Mexico, and Texas. The basin characteristics for the selected streamflow-gaging stations were determined by using a geographic information system and the Oklahoma StreamStats application. Peak-streamflow frequency statistics were computed from annual peak-streamflow records from the irrigated period of record from water year 1978 through water year 2014. Generalized-least-squares multiple-linear regression analysis was used to formulate regression relations between peak-streamflow frequency statistics and basin characteristics. Contributing drainage area was the only basin characteristic determined to be statistically significant for all percentage of annual exceedance probabilities and was the only basin characteristic used in regional regression equations for estimating peak-streamflow frequency statistics on unregulated streams in and near the Oklahoma Panhandle. The regression model pseudo-coefficient of determination, converted to percent, for the Oklahoma Panhandle regional regression equations ranged from about 38 to 63 percent. The standard errors of prediction and the standard model errors for the Oklahoma Panhandle regional regression equations ranged from about 84 to 148 percent and from about 76 to 138 percent, respectively. These errors were comparable to those reported for regional peak-streamflow frequency regression equations for the High Plains areas of Texas and Colorado. The root mean square errors for the Oklahoma Panhandle regional regression equations (ranging from 3,170 to 92,000 cubic feet per second) were less than the root mean square errors for the Oklahoma statewide regression equations (ranging from 18,900 to 412,000 cubic feet per second); therefore, the Oklahoma Panhandle regional regression equations produce more accurate peak-streamflow statistic estimates for the irrigated period of record in the Oklahoma Panhandle than do the Oklahoma statewide regression equations. The regression equations developed in this report are applicable to streams that are not substantially affected by regulation, impoundment, or surface-water withdrawals. These regression equations are intended for use for stream sites with contributing drainage areas less than or equal to about 2,060 square miles, the maximum value for the independent variable used in the regression analysis.

Colorado, Kansas, New Mexico, Oklahoma, Texas↗
USGS1988

Knowledge-based GIS techniques applied to geological engineering

A knowledge-based geographic information system (KBGIS) approach which requires development of a rule base for both GIS processing and for the geological engineering application has been implemented. The rule bases are implemented in the Goldworks expert system development shell interfaced to the Earth Resources Data Analysis System (ERDAS) raster-based GIS for input and output. GIS analysis procedures including recoding, intersection, and union are controlled by the rule base, and the geological engineering map product is generted by the expert system. The KBGIS has been used to generate a geological engineering map of Creve Coeur, Missouri.

Photogrammetric Engineering and Remote Sensing↗
USGS2002

Factors controlling storm impacts on coastal barriers and beaches - A preliminary basis for near real-time forecasting

Analysis of ground conditions and meteorological and oceanographic parameters for some of the most severe Atlantic and Gulf Coast storms in the U.S. reveals the primary factors affecting morphological storm responses of beaches and barrier islands. The principal controlling factors are storm characteristics, geographic position relative to storm path, timing of storm events, duration of wave exposure, wind stress, degree of flow confinement, antecedent topography and geologic framework, sediment textures, vegetative cover, and type and density of coastal development. A classification of commonly observed storm responses demonstrates the sequential interrelations among (1) land elevations, (2) water elevations in the ocean and adjacent lagoon (if present), and (3) stages of rising water during the storm. The predictable coastal responses, in relative order from high frequency beach erosion to low frequency barrier inundation, include: beach erosion, berm migration, dune erosion, washover terrace construction, perched fan deposition, sheetwash, washover channel incision, washout formation, and forced and unforced ebb flow. Near real-time forecasting of expected storm impacts is possible if the following information is available for the coast: a detailed morphological and topographic characterization, accurate storm-surge and wave-runup models, the real-time reporting of storm parameters, accurate forecasts of the storm position relative to a particular coastal segment, and a conceptual model of geological processes that encompasses observed morphological changes caused by extreme storms.

Journal of Coastal Research↗
USGS2009

TerraLook: A GIS-ready time-series of satellite imagery

The goal of TerraLook is to provide satellite images that anyone can use to see changes in the Earth's surface over time. Landsat and other satellites have been collecting images of the Earth from Space for more than 35 years. TerraLook allows users to create their own collections of georeferenced simulated natural-color JPEG images from Landsat (circa 1975, 1990, 2005) and ASTER (2000 to present) at no charge. The simulated natural colors in TerraLook images are consistently processed so that images from these time periods can be easily compared. TerraLook images are bundled with stands- compliant metadata, a world file, and an outline of each image's ground footprint, enabling their use in Geographic Information Systems and Web mapping applications. Different ArcGIS solutions were developed to use with TerraLook Collections. For ArcGIS and ArcGIS Explorer users, project files are available to permit TerraLook Collections to be easily integrated into GIS projects of educational curricula for visual analysis. A Pythion Script is available to extract vector data, such as country boundaries, protected areas, hydrography, and populated places, from global datasets to create extended TerraLook collections. Users can add local data, included ground photography, to the TerraLook Collections, These localized collections can be easily shared. An ArcGIS Publisher tool is provided with the ArcMap project file for publishing documents for use with the free ArcReader application.

Conference Paper↗
USGS2012

Application of Wind Fetch and Wave Models for Habitat Rehabilitation and Enhancement Projects

Models based upon coastal engineering equations have been developed to quantify wind fetch length and several physical wave characteristics including significant height, length, peak period, maximum orbital velocity, and shear stress. These models were used to quantify differences in proposed island construction designs for three Habitat Rehabilitation and Enhancement Projects (HREPs) in the U.S. Army Corps of Engineers St. Paul District (Capoli Slough and Harpers Slough) and St. Louis District (Swan Lake). Weighted wind fetch was calculated using land cover data supplied by the Long Term Resource Monitoring Program (LTRMP) for each island design scenario for all three HREPs. Figures and graphs were created to depict the results of this analysis. The difference in weighted wind fetch from existing conditions to each potential future island design was calculated for Capoli and Harpers Slough HREPs. A simplistic method for calculating sediment suspension probability was also applied to the HREPs in the St. Paul District. This analysis involved determining the percentage of days that maximum orbital wave velocity calculated over the growing seasons of 2002–2007 exceeded a threshold value taken from the literature where fine unconsolidated sediments may become suspended. This analysis also evaluated the difference in sediment suspension probability from existing conditions to the potential island designs. Bathymetric data used in the analysis were collected from the LTRMP and wind direction and magnitude data were collected from the National Oceanic and Atmospheric Administration, National Climatic Data Center. These models are scheduled to be updated to operate using the most current Environmental Systems Research Institute ArcGIS Geographic Information System platform, and have several improvements implemented to wave calculations, data processing, and functions of the toolbox.

Conference Paper↗