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Tools for beach health data management, data processing, and predictive model implementation

This fact sheet describes utilities created for management of recreational waters to provide efficient data management, data aggregation, and predictive modeling as well as a prototype geographic information system (GIS)-based tool for data visualization and summary. All of these utilities were developed to assist beach managers in making decisions to protect public health. The Environmental Data Discovery and Transformation (EnDDaT) Web service identifies, compiles, and sorts environmental data from a variety of sources that help to define climatic, hydrologic, and hydrodynamic characteristics including multiple data sources within the U.S. Geological Survey and the National Oceanic and Atmospheric Administration. The Great Lakes Beach Health Database (GLBH-DB) and Web application was designed to provide a flexible input, export, and storage platform for beach water quality and sanitary survey monitoring data to compliment beach monitoring programs within the Great Lakes. A real-time predictive modeling strategy was implemented by combining the capabilities of EnDDaT and the GLBH-DB for timely, automated prediction of beach water quality. The GIS-based tool was developed to map beaches based on their physical and biological characteristics, which was shared with multiple partners to provide concepts and information for future Web-accessible beach data outlets.

Fact Sheet↗

Estimated historical distribution of grassland communities of the Southern Great Plains

The purpose of this project was to map the estimated distribution of grassland communities of the Southern Great Plains prior to Euro-American settlement. The Southern Great Plains Rapid Ecoregional Assessment (REA), under the direction of the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative, includes four ecoregions: the High Plains, Central Great Plains, Southwestern Tablelands, and the Nebraska Sand Hills. The REA advisors and stakeholders determined that the mapping accuracy of available national land-cover maps was insufficient in many areas to adequately address management questions for the REA. Based on the recommendation of the REA stakeholders, we estimated the potential historical distribution of 10 grassland communities within the Southern Great Plains project area using data on soils, climate, and vegetation from the Natural Resources Conservation Service (NRCS) including the Soil Survey Geographic Database (SSURGO) and Ecological Site Information System (ESIS). The dominant grassland communities of the Southern Great Plains addressed as conservation elements for the REA area are shortgrass, mixed-grass, and sand prairies. We also mapped tall-grass, mid-grass, northwest mixed-grass, and cool season bunchgrass prairies, saline and foothill grasslands, and semi-desert grassland and steppe. Grassland communities were primarily defined using the annual productivity of dominant species in the ESIS data. The historical grassland community classification was linked to the SSURGO data using vegetation types associated with the predominant component of mapped soil units as defined in the ESIS data. We augmented NRCS data with Landscape Fire and Resource Management Planning Tools (LANDFIRE) Biophysical Settings classifications 1) where NRCS data were unavailable and 2) where fifth-level watersheds intersected the boundary of the High Plains ecoregion in Wyoming. Spatial data representing the estimated historical distribution of grassland communities of the Southern Great Plains are provided as a 30 x 30-meter gridded surface (raster dataset). This information will help to address the priority management questions for grassland communities for the Southern Great Plains REA and can be used to inform other regional-level land management decisions.

Southern Great Plains↗

Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010

Groundwater recharge is one of the most difficult components of a water budget to ascertain, yet is an important boundary condition necessary for the quantification of water resources. In Minnesota, improved estimates of recharge are necessary because approximately 75 percent of drinking water and 90 percent of agricultural irrigation water in Minnesota are supplied from groundwater. The water that is withdrawn must be supplied by some combination of (1) increased recharge, (2) decreased discharge to streams, lakes, and other surface-water bodies, and (3) removal of water that was stored in the system. Recent pressure on groundwater resources has highlighted the need to provide more accurate recharge estimates for various tools that can assess the sustainability of long-term water use. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, used the Soil-Water-Balance model to calculate gridded estimates of potential groundwater recharge across Minnesota for 1996‒2010 at a 1-kilometer (0.621-mile) resolution. The potential groundwater recharge estimates calculated for Minnesota from the Soil-Water Balance model included gridded values (1-kilometer resolution) of annual mean estimates (that is, the means for individual years from 1996 through 2010) and mean annual estimates (that is, the mean for the 15-year period 1996−2010). The Soil-Water-Balance model uses a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated on a daily basis. A key advantage of this approach includes the use of commonly available geographic information system data layers that incorporate land cover, soil properties, and daily meteorological data to produce temporally and spatially variable gridded estimates of potential recharge. The Soil-Water-Balance model was calibrated by using a combination of parameter estimation techniques, making manual adjustments of model parameters, and using parameter values from previously published Soil-Water-Balance models. Each calibration simulation compared the potential recharge estimate from the model against base-flow estimates derived from three separate hydrograph separation techniques. A total of 35 Minnesota watersheds were selected for the model calibration. Meteorological data necessary for the model included daily precipitation, minimum daily temperature, and maximum daily temperature. All of the meteorological data were provided by the Daymet dataset, which included daily continuous surfaces of key climatological data. Land-cover data were provided by the 2001 and 2006 National Land Cover Database: the 2001 classification was used from 1994 through 2003, and the 2006 classification was used from 2004 through 2010. Soil data used in the model included hydrologic soils group and the available soil-water capacity. These soil data were obtained from the Natural Resources Conservation Service Soil Survey Geographic (SSURGO) database and the State Soil Geographic (STATSGO) database. The statewide mean annual potential recharge rate from 1996–2010 was 4.9 inches per year. Potential recharge estimates increased from west to east across Minnesota. The mean annual potential recharge estimates across Minnesota at a 1-km resolution for the overall simulation period (1996–2010) ranged from less than 0.1 to 17.8 inches per year. Some of the lowest potential recharge rates for the simulation period were in the Red River of the North Basin of northwestern Minnesota, and generally were between 1.0 and 1.5 inches per year. The highest potential recharge rates were in northeastern Minnesota and the Anoka Sand Plain in central Minnesota. Eighty-eight percent of the potential recharge rates (by grid cell) were between 2 and 8 inches per year from 1996–2010. Only about 3 percent of all the potential recharge estimates (by grid cell) were less than 2 inches per year, and 9 percent of estimates were greater than 8 inches per year. On an annual basis, however, potential recharge rates were as high as 27.2 inches per year. The highest annual mean recharge estimate across the State was for 2010, and the lowest mean recharge estimate was for 2003. Although precipitation variability partially explained the annual differences in potential recharge estimates, precipitation alone did not account for these differences, and other factors such as antecedent moisture conditions likely were important. Also, because precipitation gradients across the State can vary from year to year, the dominant land-cover class and hydrologic soil group combinations for a particular region had a large effect on the resulting potential recharge value. During 1996–2010, April had the greatest monthly mean potential recharge compared to all other months, accounting for a mean of 30 percent of annual potential recharge in this single month.

Minnesota↗

Predicting the probability and volume of postwildfire debris flows in the intermountain western United States

Empirical models to estimate the probability of occurrence and volume of postwildfire debris flows can be quickly implemented in a geographic information system (GIS) to generate debris-flow hazard maps either before or immediately following wildfires. Models that can be used to calculate the probability of debris-flow production from individual drainage basins in response to a given storm were developed using logistic regression analyses of a database from 388 basins located in 15 burned areas located throughout the U.S. Intermountain West. The models describe debris-flow probability as a function of readily obtained measures of areal burned extent, soil properties, basin morphology, and rainfall from short-duration and low-recurrence-interval convective rainstorms. A model for estimating the volume of material that may issue from a basin mouth in response to a given storm was developed using multiple linear regression analysis of a database from 56 basins burned by eight fires. This model describes debris-flow volume as a function of the basin gradient, aerial burned extent, and storm rainfall. Applications of a probability model and the volume model for hazard assessments are illustrated using information from the 2003 Hot Creek fire in central Idaho. The predictive strength of the approach in this setting is evaluated using information on the response of this fire to a localized thunderstorm in August 2003. The mapping approach presented here identifies those basins that are most prone to the largest debris-flow events and thus provides information necessary to prioritize areas for postfire erosion mitigation, warnings, and prefire management efforts throughout the Intermountain West.

Geological Society of America Bulletin↗

Sediment data from vibracores collected in 2016 from Fire Island, New York

Researchers from the U.S. Geological Survey (USGS) conducted a long-term coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related effects, post-storm beach response, and recovery. In April 2016, scientists from the USGS St. Petersburg Coastal and Marine Science Center conducted sediment sampling and geophysical surveys on Fire Island to characterize and quantify spatial variability in the subaerial geology with the goal of subsequently integrating onshore geology with other surf zone and nearshore datasets. This report, along with the accompanying USGS data release , serves as an archive of sediment data from 14 vibracores collected on April 10 and 11, 2016 (USGS Field Activity Number 2016–322–FA ), along 6 transects that extend from the upper to lower subaerial shoreface at Fire Island. Sedimentologic and stratigraphic metrics (for example, sediment texture or unit thicknesses) derived from these data can be used to assess spatial and temporal trends and may aid in understanding beach evolution. Data products include sample location tables, descriptive core logs, core photographs, results of sediment grain-size analyses, and geographic information system data files with accompanying formal Federal Geographic Data Committee metadata.

New York↗

Grfin Tools—User guide and methods for modeling landslide runout and debris-flow growth and inundation

The software package, Grfin Tools, can estimate potential runout from landslides or inundation from geophysical mass flows such as debris flows, lahars from volcanoes, and rock avalanches within a digital elevation model (DEM). Grfin is an acronym of gr owth + f low + in undation. The tools within this package apply simple, well-tested, empirical models of runout that are computationally efficient and require minimal parameters. These tools can be used individually (for example, to estimate debris-flow inundation) or in combination to represent a more complete series of linked processes, from landslide source areas, to unchannelized transport, to channelized flows. Grfin Tools can rapidly assess potential runout and inundation over large areas and the results are readily visualized in a geographic information system. Tools for assessing areas affected by runout and flow inundation include a height-to-length ( H / L ) ratio, angle-of-reach approach for estimating open-slope, unchannelized landslide runout, and volume-area scaling relations for assessing flow inundation in channels. Potential landslide areas that constitute the sources of runout or inundation can be delineated with topographic features, such as slope and (or) curvature, derived by the software package, or by employing potential sources derived from other landslide susceptibility models. Grfin Tools also has the capability to assess inundation from flows that grow volumetrically downstream. This is a vital feature, as larger flows commonly result in longer runout and larger inundation. The software uses empirically derived growth factors applied over upslope contributing source areas or upstream channel lengths to integrate the effects of various growth processes, such as channel entrainment, streambank failures, adjacent landslides, and hillslope erosion. Inundation follows a drainage network defined with a separate tool that uses topographic curvature to identify channel initiation locations. This document includes information on using Grfin Tools, the basis and methods underlying the tools and models, detailed descriptions of the software input and output files, and tips for handling special conditions such as roads and large water bodies. Multiple detailed examples illustrating different applications are also presented. Grfin Tools relies on the freely available TauDEM software package (Tarboton, 2005). The Grfin Tools software release is available from Cronkite-Ratcliff and others (2025).

Techniques and Methods↗

Uncertainty of groundwater vulnerability assessments for agricultural regions in Hawaii: Review

There are important challenges associated with assessing potential groundwater vulnerability hazards that may result from regional scale applications of agrochemicals. The increasing availability of Geographic Information System (GIS) software to those involved in assisting with landuse decisions has resulted in the widespread production of multicolored risk management maps for many environmentally sensitive issues. Soil-based GIS's have recently been coupled to various solute-leaching models to make near-surface groundwater vulnerability assessments for guidance in pesticide regulation in several states. In general, these assessments rest on soil, climatic, and chemical data that are extremely sparse and contain considerable uncertainty. It is also important to acknowledge the uncertainty associated with the transport/fate processes that are not accounted for by the modeling approach used to make the assessment. In this paper, we review the results from a series of papers that have focused on characterization of uncertainty in pesticide mobility estimates, using the attenuation and retardation indices (AF and RF), for the Pearl Harbor Basin on the Hawaiian island of Oahu. Relative to data error uncertainties, we discuss the impacts of: (i) soil, climatic, and chemical data base uncertainties, (ii) reductions in data base uncertainties, (iii) extrapolation of soil data base information based on soil taxonomy and soil survey, and (iv) importing information from outside the region of interest. Relative to model error uncertainties, we compare pesticide leaching estimates from the simple AF and RF mobility indices with simulations from the EPA's Pesticide Root Zone Model (PRZM) and field observations. Finally, we outline a Regional Integrated Risk Assessment approach for characterizing regional scale groundwater vulnerability for near-surface nonpoint sources.

Hawaii↗

Relative abundance and distribution of fishes within an established Area of Critical Environmental Concern, of the Amargosa River Canyon and Willow Creek, Inyo and San Bernardino Counties, California

The Amargosa River Canyon of San Bernardino and Inyo County, California, has been designated by the Bureau of Land Management as an Area of Critical Environmental Concern, due in part to its unique flora and fauna. As a task of the Area of Critical Environmental Concern implementation plan, a survey of native fishes was conducted from June 21 to August 12, 2010. Geographic Information System tools were used to map sampling locations, which were spaced at 50-meter intervals. Global Positioning Systems were used to locate sampling stations, and stations with adequate water for successful trapping were sampled with baited minnow traps. Amargosa River pupfish (Cyprinodon nevadensis amargosae) and speckled dace (Rhinichthys osculus spp.) were widespread throughout Armargosa River Canyon. Throughout the study area 8,558 pupfish were captured at 194 stations; 3,472 speckled dace were captured at 210 stations; 238 red-swamp crayfish (Procambarus clarkia) were captured at 83 stations; and 1,095 western mosquitofish (Gambusia affinus) were captured at 110 stations. Pupfish were most abundant in open water habitat with native riparian vegetation, and they were significantly less abundant where the stream was completely covered by cattails or where saltcedar (Tamarix sp.) dominated the riparian corridor. There was no relationship between stream cover and speckled dace distribution. Non-native western mosquitofish and red-swamp crayfish densities were significantly higher in stream reaches dominated by saltcedar. The continued spread of saltcedar threatens to negatively affect pupfish and potentially reduce speckled dace abundance throughout the Amargosa River Canyon. This study can serve as baseline information for observing native fish populations in the future, as related to potential changes to the Amargosa River Canyon ecosystem.

Open-File Report↗

Using systems thinking to inform management of imperiled species: A case study with sea turtles

Management of imperiled species facing spatiotemporally dynamic threats is difficult. Systems thinking can inform their management by quantifying the impacts that they face. We apply systems thinking to the Northern Gulf of Mexico (NGM) loggerhead ( Caretta caretta ) Recovery Unit (RU), one of the smallest subpopulations of loggerheads nesting in the USA. We characterized disturbances to nests, management actions, and hatchling production across 12 nesting beaches used by this RU to explore how hatchling production would increase if disturbances were mitigated. Annual hatchling production at sites ranged from 470 to 18,191 hatchlings/year. Washovers (19.3% nests/year), washouts (17.9% nests/year), and predation (13% nests/year) were the most common annual disturbances across sites. Focusing on the most impactful disturbances at just five sites could increase annual NGM RU hatchling production by 2.2–6.7%. Efforts to mitigate washovers and washouts are ongoing in Alabama, but these may be futile against tropical cyclones, which accounted for >80% of washouts in the present study, and further require careful examination of associated adverse side-effects. Efforts to mitigate predation are common throughout this RU, but require improved knowledge of predator ecology to reach full potential. Systems thinking allowed us to create a simple model for assessing disturbances and management strategies in terms of hatchling sea turtles. This model can be augmented to run dynamic simulations of how disturbances and management actions impact hatchling production, and can be applied to other species with similar reproductive strategies.

Alabama, Florida↗

User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2

Between 2002 and 2006, the Fort Collins Science Center (FORT) at the U.S. Geological Survey (USGS) conducted field surveys, organized workshops, and performed analysis of habitat for trout and shad in the Upper Delaware River Basin. This work culminated in the development of decision support system software (the Delaware River DSS–DRDSS, Bovee and others, 2007) that works in conjunction with the Delaware River Basin Commission’s reservoir operations model, OASIS, to facilitate comparison of the habitat and water-delivery effects of alternative operating scenarios for the Basin. This original DRDSS application was developed in Microsoft Excel and is available to all interested parties through the FORT web site ( http://www.fort.usgs.gov/Products/Software/DRDSS/ ). Initial user feedback on the original Excel-based DSS highlighted the need for a more user-friendly and powerful interface to effectively deliver the complex data and analyses encapsulated in the DSS. In order to meet this need, the USGS FORT and Northern Appalachian Research Branch (NARB) developed an entirely new graphical user interface (GUI) application. Support for this research was through the DOI WaterSmart program ( http://www.doi.gov/watersmart/html/index.php ) of which the USGS component is the National Water Census ( http://water.usgs.gov/watercensus/WaterSMART.html ). The content and methodology of the new GUI interface emulates those of the original DSS with a few exceptions listed below. Refer to Bovee and others (2007) for the original information. Significant alterations to the original DSS include: • We moved from Excel-based data storage and processing to a more powerful database back end powered by SQLite. The most notable effect of this is that the previous maximum temporal extent of 10 years has been replaced by a dynamic extent that can now cover the entire period of record for which we have data (1928–2000). • We incorporated interactive geographic information system (GIS) visualization and dynamic data processing. Previous habitat maps were generated outside of the DSS in an ad hoc process that the end user could not update or investigate. • The original bathymetric data collected in 2005 at the three main stem reaches was augmented with a higher resolution dataset collected in 2010. This new dataset was collected in order to conduct higher resolution (finer pixel size) two-dimensional (2D) hydrodynamic modeling for evaluating dwarf wedgemussel (DWM, Alasmidonta heterodon ) habitat. • Results charts are now substantially more interactive, dynamic, and accessible, which allows users to more easily focus on their particular topics of interest as well as drill down to the source data used to calculate given results.

Open-File Report↗

Flood recovery maps for the White River in Bethel, Stockbridge, and Rochester, Vermont, and the Tweed River in Stockbridge and Pittsfield, Vermont, 2014

From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from about 4 inches to more than 7 inches in the White River Basin. The rainfall resulted in severe flooding throughout the basin and significant damage along the White River and Tweed River. In response to the flooding, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in the flood recovery and restoration. This flood study includes a 20.7-mile reach of the White River from the downstream end at about 2,000 feet downstream from the State Route 107 bridge in the Village of Bethel, Vermont, to the upstream end at about 1,000 feet upstream from the River Brook Drive bridge in the Village of Rochester, Vt., and a 7.9-mile reach of the Tweed River from its mouth in Stockbridge, Vt., to the confluence of the West and South Branches of the Tweed River and continuing upstream on the South Branch Tweed River to the Pittsfield, Vt., town line. This report presents water-surface elevations determined for the study reaches using the U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model, also known as HEC– RAS. The water-surface elevations were determined for floods having a 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) and for the floodway. Eighteen high-water marks from Tropical Storm Irene were available along the studied reaches. The discharges in the Tropical Storm Irene HEC–RAS model were adjusted so that the resulting water-surface elevations matched the high-water mark elevations along the study reaches. This allowed for an estimation of the water-surface profile throughout the study area resulting from Tropical Storm Irene. From a comparison of the estimated water-surface profile of Tropical Storm Irene to the water-surface profiles of the 1- and 0.2-percent AEP floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the White River and Tweed River study reaches and exceeded the estimated 0.2-percent AEP flood in 16.7 of the 28.6 study reach miles. 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 18.2-centimeter vertical accuracy at the 95-percent confidence level and 1-meter horizontal resolution to delineate the area flooded for each water-surface profile.

Vermont↗

Quantifying human disturbance in watersheds: Variable selection and performance of a GIS-based disturbance index for predicting the biological condition of perennial streams

Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.

Ecological Indicators↗

Archive of digital boomer seismic reflection data collected during USGS field activity 02LCA02 in Lakes Ada, Crystal, Jennie, Mary, Rice, and Sylvan, Central Florida, July 2002

In July of 2002, the U.S. Geological Survey and St. Johns River Water Management District (SJRWMD) conducted geophysical surveys in Lakes Ada, Crystal, Jennie, Mary, Rice, and Sylvan, central Florida, as part of the USGS Lakes and Coastal Aquifers (LCA) study. This report serves as an archive of unprocessed digital boomer seismic reflection data, trackline maps, navigation files, Geographic Information System (GIS) files, and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Example SU processing scripts and USGS software for viewing the SEG-Y files (Zihlman, 1992) are also provided. The USGS Florida Integrated Science Center (FISC) - St. Petersburg assigns a unique identifier to each cruise or field activity. For example, 02LCA02 tells us the data were collected in 2002 for the Lakes and Coastal Aquifers (LCA) study and the data were collected during the second field activity for that study in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. The boomer plate is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and when discharged emits a short acoustic pulse, or shot, which propagates through the water, sediment column, or rock beneath. The acoustic energy is reflected at density boundaries (such as the seafloor, sediment, or rock layers beneath the seafloor), detected by the receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). In this way, a two-dimensional (2-D) vertical profile of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters. Table 2 lists trackline statistics. The unprocessed seismic data are stored in SEG-Y format (Barry and others, 1975). For a detailed description of the data format, refer to the SEG-Y Format page. See the How To Download SEG-Y Data page for download instructions. The printable profiles provided here are GIF images that were filtered and gained using Seismic Unix software. Refer to the Software page for details about the processing and examples of the processing scripts. The processed SEG-Y data were exported to Chesapeake Technology, Inc. (CTI) SonarWeb software to produce an interactive Web page of the profile, which allows the user to obtain a geographic location and depth from the profile for a curser position. This information is displayed in the status bar of the browser.

Florida↗

Distribution patterns of mercury in Lakes and Rivers of northeastern North America

We assembled 831 data points for total mercury (Hg t ) and 277 overlapping points for methyl mercury (CH 3 Hg + ) in surface waters from Massachussetts, USA to the Island of Newfoundland, Canada from State, Provincial, and Federal government databases. These geographically indexed values were used to determine: (a) if large-scale spatial distribution patterns existed and (b) whether there were significant relationships between the two main forms of aquatic Hg as well as with total organic carbon (TOC), a well know complexer of metals. We analyzed the catchments where samples were collected using a Geographical Information System (GIS) approach, calculating catchment sizes, mean slope, and mean wetness index. Our results show two main spatial distribution patterns. We detected loci of high Hg t values near urbanized regions of Boston MA and Portland ME. However, except for one unexplained exception, the highest Hg t and CH 3 Hg + concentrations were located in regions far from obvious point sources. These correlated to topographically flat (and thus wet) areas that we relate to wetland abundances. We show that aquatic Hg t and CH 3 Hg + concentrations are generally well correlated with TOC and with each other. Over the region, CH 3 Hg + concentrations are typically approximately 15% of Hg t . There is an exception in the Boston region where CH 3 Hg + is low compared to the high Hg t values. This is probably due to the proximity of point sources of inorganic Hg and a lack of wetlands. We also attempted to predict Hg concentrations in water with statistical models using catchment features as variables. We were only able to produce statistically significant predictive models in some parts of regions due to the lack of suitable digital information, and because data ranges in some regions were too narrow for meaningful regression analyses.

Maine, Massachusetts, New Brunswick, New Hampshire↗

A picture is worth a thousand plants: Using historic and repeat photography to quantify long-term change in drylands on the Colorado Plateau

This study analyzes over a century of plant community change on the Colorado Plateau (CP) using repeat photography (1910–2016) and various GIS (Geographic Information Systems) data. We examined 338 repeat photo pairs across three dominant vegetation communities: CP Blackbrush-Mormon-tea Shrubland (CP Blackbrush), Inter-Mountain Basins Semi-Desert Grassland and Big Sagebrush Shrubland (IM grasslands) and CP Pinyon-Juniper Woodland/Shrubland (PJ Woodland). Vegetation changes, including plant counts, plant size, patch shifts, patch size and live plant cover, were evaluated against photo pair time span and spatial covariates, including climate, topography, soil characteristics and land-use history using logistic regression. Responses varied significantly by community type, driven by interacting factors such as time since domestic grazing cessation, climate conditions, and geomorphic setting. CP Blackbrush and IM grasslands showed recovery with longer time since grazing cessation, with increases in plant numbers, patch size, and cover. PJ Woodlands showed mixed, context dependent responses. All communities exhibited increased growth on alluvial landforms, likely from deeper soils and better water availability. Human disturbances lead to a higher probability of patch shifts in CP Blackbrush and IM grasslands. These findings underscore utility of long-term datasets for understanding dryland ecosystem dynamics and highlight how land-use history, climate and geomorphology can inform conservation efforts on dryland ecosystems.

Colorado, Utah↗

The GIS weasel - An interface for the development of spatial information in modeling

The GIS Weasel is a map and Graphical User Interface (GUI) driven tool that has been developed as an aid to modelers in the delineation, characterization of geographic features, and their parameterization for use in distributed or lumped parameter physical process models. The interface does not require user expertise in geographic information systems (GIS). The user does need knowledge of how the model will use the output from the GIS Weasel. The GIS Weasel uses Workstation ArcInfo and its the Grid extension. The GIS Weasel will run on all platforms that Workstation ArcInfo runs (i.e. numerous flavors of Unix and Microsoft Windows).The GIS Weasel requires an input ArcInfo grid of some topographical description of the Area of Interest (AOI). This is normally a digital elevation model, but can be the surface of a ground water table or any other data that flow direction can be resolved from. The user may define the AOI as a custom drainage area based on an interactively specified watershed outlet point, or use a previously created map. The user is then able to use any combination of the GIS Weasel's tool set to create one or more maps for depicting different kinds of geographic features. Once the spatial feature maps have been prepared, then the GIS Weasel s many parameterization routines can be used to create descriptions of each element in each of the user s created maps. Over 200 parameterization routines currently exist, generating information about shape, area, and topological association with other features of the same or different maps, as well many types of information based on ancillary data layers such as soil and vegetation properties. These tools easily integrate other similarly formatted data sets.

Conference Paper↗

Surface-water, water-quality, and ground-water assessment of the Municipio of Carolina, Puerto Rico, 1997-99

To meet the increasing need for a safe and adequate supply of water in the municipio of Carolina, an integrated surface-water, water-quality, and ground-water assessment of the area was conducted. The major results of this study and other important hydrologic and water-quality features were compiled in a Geographic Information System and are presented in two 1:30,000-scale map plates to facilitate interpretation and use of the diverse water-resources data. Because the supply of safe drinking water was a critical issue during recent dry periods, the surface-water assessment portion of this study focused on analysis of low-flow characteristics in local streams and rivers. Low-flow characteristics were evaluated for one continuous-record gaging station, based on graphical curve-fitting techniques and log-Pearson Type III frequency analysis. Estimates of low-flow characteristics for seven partial-record stations were generated using graphical-correlation techniques. Flow-duration characteristics were computed for the one continuous-record gaging station and were estimated for the partial-record stations using the relation curves developed from the low-flow study. Stream low-flow statistics document the general hydrology under current land and water use. Low-flow statistics may substantially change as a result of streamflow diversions for public supply, and an increase in ground-water development, waste-water discharges, and flood-control measures; the current analysis provides baseline information to evaluate these impacts and develop water budgets. A sanitary quality survey of streams utilized 29 sampling stations to evaluate the sanitary quality of about 87 miles of stream channels. River and stream samples were collected on two occasions during base-flow conditions and were analyzed for fecal coliform and fecal streptococcus. Bacteriological analyses indicate that a significant portion of the stream reaches within the municipio of Carolina may have fecal coliform concentrations above the water-quality goal established by the Puerto Rico Environmental Quality Board (Junta de Calidad Ambiental de Puerto Rico) for inland surface waters. Sources of fecal contamination may include: illegal discharge of sewage to storm-water drains, malfunctioning sanitary sewer ejectors, clogged and leaking sewage pipes, septic tank leakage, unfenced livestock, and runoff from livestock pens. Long-term fecal coliform data at two sampling stations, Quebrada Blasina in Carolina and the Rio Grande de Loiza, downstream from the town of Trujillo Alto, indicate that the sanitary quality of Quebrada Blasina is and has generally been poor for more than a decade. The sanitary quality of the Rio Grande de Loiza has generally been in compliance with the water-quality goal standard fecal coliform concentrations established in July 1990 by the Puerto Rico Environmental Quality Board. Geologic, topographic, soil, hydrogeologic, and streamflow data were used to divide the municipio of Carolina into five hydrogeologic terranes. This integrated database was then used to evaluate the ground-water potential of each hydrogeologic terrane. Analysis suggests that areas with slopes greater than 15 degrees have relatively low ground-water development potential. Fractures may be locally important in enhancing the water-bearing properties in the hydrogeologic terranes containing igneous rocks. Potentiometric-surface elevations recorded in piezometers installed in the coastal area during this study were used to define ground-water flow directions in the hydrogeologic terranes composed of coastal plain clastic and limestone units. The resultant potentiometric map indicates that the coastal plain aquifer and streams in the lowland parts of the municipio of Carolina are hydraulically connected. The potentiometric map also indicates that ground-water discharge to the Rio Grande de Loiza, downstream from highway PR-3, has been enhanced by dredging of the streambed for

Water-Resources Investigations Report↗

2010 Petroleum resource assessment of the National Petroleum Reserve in Alaska (NPRA): GIS play maps

This report provides digital geographic information systems (GIS) files of maps for each of the 24 plays considered in the U.S. Geological Survey (USGS) 2010 updated petroleum resource assessment of the National Petroleum Reserve in Alaska (NPRA) (Houseknecht and others, 2010). These are the sample plays evaluated in a previous USGS assessment of the NPRA (Bird and Houseknecht, 2002a), maps of which were released in pdf format (Bird and Houseknecht, 2002b). The 2010 updated assessment of the NPRA evaluated each of the previously used 24 plays based on new geologic data available from exploration activities and scientific research. Quantitative assessments were revised for 11 plays, and no revisions were made for 9 plays. Estimates of the volume of technically recoverable, undiscovered oil, and nonassociated gas resources in these 20 plays are reported elsewhere (Houseknecht and others, 2010). Four plays quantitatively assessed in 2002 were eliminated from quantitative assessment for reasons explained by Houseknecht and others (2010). The NPRA assessment study area includes Federal and native onshore land and adjacent State offshore areas. A map showing the areal extent of each play was prepared by USGS geologists as a preliminary step in the assessment process. Boundaries were drawn on the basis of a variety of information, including seismic reflection data, results of exploration drilling, and regional patterns of rock properties. Play boundary polygons were captured by digitizing the play maps prepared by USGS geologists.

Alaska↗