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Results for “Environmental Software & Modeling”

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At least 145 records · Page 8Linked to original sources
USGS2012

Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.

Techniques and Methods↗
USGS2009

Mercury Loads in the South River and Simulation of Mercury Total Maximum Daily Loads (TMDLs) for the South River, South Fork Shenandoah River, and Shenandoah River: Shenandoah Valley, Virginia

Due to elevated levels of methylmercury in fish, three streams in the Shenandoah Valley of Virginia have been placed on the State's 303d list of contaminated waters. These streams, the South River, the South Fork Shenandoah River, and parts of the Shenandoah River, are downstream from the city of Waynesboro, where mercury waste was discharged from 1929-1950 at an industrial site. To evaluate mercury contamination in fish, this total maximum daily load (TMDL) study was performed in a cooperative effort between the U.S. Geological Survey, the Virginia Department of Environmental Quality, and the U.S. Environmental Protection Agency. The investigation focused on the South River watershed, a headwater of the South Fork Shenandoah River, and extrapolated findings to the other affected downstream rivers. A numerical model of the watershed, based on Hydrological Simulation Program-FORTRAN (HSPF) software, was developed to simulate flows of water, sediment, and total mercury. Results from the investigation and numerical model indicate that contaminated flood-plain soils along the riverbank are the largest source of mercury to the river. Mercury associated with sediment accounts for 96 percent of the annual downstream mercury load (181 of 189 kilograms per year) at the mouth of the South River. Atmospherically deposited mercury contributes a smaller load (less than 1 percent) as do point sources, including current discharge from the historic industrial source area. In order to determine how reductions of mercury loading to the stream could reduce methylmercury concentrations in fish tissue below the U.S. Environmental Protection Agency criterion of 0.3 milligrams per kilogram, multiple scenarios were simulated. Bioaccumulation of mercury was expressed with a site-specific exponential relation between aqueous total mercury and methylmercury in smallmouth bass, the indicator fish species. Simulations indicate that if mercury loading were to decrease by 98.9 percent from 189 to 2 kilograms per year, fish tissue methylmercury concentrations would drop below 0.3 milligrams per kilogram. Based on the simulations, the estimated maximum load of total mercury that can enter the South River without causing fish tissue methylmercury concentrations to rise above 0.3 milligrams per kilogram is 2.03 kilograms per year for the South River, and 4.12 and 6.06 kilograms per year for the South Fork Shenandoah River and Shenandoah River, respectively.

Scientific Investigations Report↗
USGS2013

NCWin — A Component Object Model (COM) for processing and visualizing NetCDF data

NetCDF (Network Common Data Form) is a data sharing protocol and library that is commonly used in large-scale atmospheric and environmental data archiving and modeling. The NetCDF tool described here, named NCWin and coded with Borland C + + Builder, was built as a standard executable as well as a COM (component object model) for the Microsoft Windows environment. COM is a powerful technology that enhances the reuse of applications (as components). Environmental model developers from different modeling environments, such as Python, JAVA, VISUAL FORTRAN, VISUAL BASIC, VISUAL C + +, and DELPHI, can reuse NCWin in their models to read, write and visualize NetCDF data. Some Windows applications, such as ArcGIS and Microsoft PowerPoint, can also call NCWin within the application. NCWin has three major components: 1) The data conversion part is designed to convert binary raw data to and from NetCDF data. It can process six data types (unsigned char, signed char, short, int, float, double) and three spatial data formats (BIP, BIL, BSQ); 2) The visualization part is designed for displaying grid map series (playing forward or backward) with simple map legend, and displaying temporal trend curves for data on individual map pixels; and 3) The modeling interface is designed for environmental model development by which a set of integrated NetCDF functions is provided for processing NetCDF data. To demonstrate that the NCWin can easily extend the functions of some current GIS software and the Office applications, examples of calling NCWin within ArcGIS and MS PowerPoint for showing NetCDF map animations are given.

Cartographic Journal↗
USGS2010

Bayesian Inference: with ecological applications

This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

Book↗
USGS2020

msocc: Fit and analyse computationally efficient multi‐scale occupancy models in R

Environmental DNA (eDNA) sampling is a promising tool for the detection of rare and cryptic taxa, such as aquatic pathogens, parasites and invasive species. Environmental DNA sampling workflows commonly rely on multi‐stage hierarchical sampling designs that induce complicated dependencies within the data. This complex dependence structure can be intuitively modelled with Bayesian multi‐scale occupancy models. However, current software for such models are computationally demanding, impeding their use. We present an r package, msocc , that implements a data augmentation strategy to fit fully Bayesian, computationally efficient multi‐scale occupancy models. The msocc package allows users to fit multi‐scale occupancy models, to estimate and visualize posterior summaries of site, sample and replicate‐level occupancy, and to compare different models using Bayesian information criterion. Additionally, we provide a supplemental web application that allows users to investigate study design for multi‐scale occupancy models and acts as a graphical user interface to the msocc package. The utility of the msocc package is illustrated on a published dataset and the functions in msocc are compared to the primary Bayesian toolkit for multi‐scale occupancy modelling, eDNAoccupancy , using various computational benchmarks. These benchmarks indicate that msocc is capable of fitting models 50 times faster than eDNAoccupancy . We hope that access to software that efficiently fits, analyses and conducts study design investigations for multi‐scale occupancy models facilitates their implementation by the research and wildlife management communities.

Methods in Ecology and Evolution↗
USGS2022

Coupling validation effort with in situ bioacoustic data improves estimating relative activity and occupancy for multiple species with cross-species misclassifications

The increasing complexity and pace of ecological change requires natural resource managers to consider entire species assemblages. Acoustic recording units (ARUs) require minimal cost and effort to deploy and inform relative activity, or encounter rates, for multiple species simultaneously. ARU-based surveys require post-processing of the recordings via software algorithms that assign a species label to each recording. The automated classification process can result in cross-species misidentifications that should be accounted for when employing statistical modelling for conservation decision-making. Using simulation and ARU-based detection counts from 17 bat species in British Columbia, Canada, we investigate three strategies for adjusting statistical inference for species misclassification: (a) ‘coupling’ ambiguous and unambiguous detections by validating a subset of survey events post-hoc, (b) using a calibration dataset on the software algorithm's (in)accuracy for species identification or (c) specifying informative Bayesian priors on classification probabilities. We explore the impact of different Bayesian prior specifications for the classification probabilities on posterior estimation. We then consider how the quantity of data validated post-hoc impacts model convergence and resulting inferences for bat species relative activity as related to nightly conditions and yearly site occupancy after accounting for site-level environmental variables. Coupled methods resulted in less bias and uncertainty when estimating relative activity and species classification probabilities relative to calibration approaches. We found that species that were difficult-to-detect and those that were often inaccurately identified by the software required more validation effort than more easily detected and/or identified species. Our results suggest that, when possible, acoustic surveys should rely on coupled validated detection information to account for false-positive detections, rather than uncoupled calibration datasets. However, if the assemblage of interest contains a large number of rarely detected or less prevalent species, an intractable amount of effort may be required, suggesting there are benefits to curating a calibration dataset that is representative of the observation process. Our findings provide insights into the practical challenges associated with statistical analyses of ARU data and possible analytical solutions to support reliable and cost-effective decision-making for wildlife conservation/management in the face of known sources of observation errors.

British Columbia↗
USGS2025

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado↗
USGS2021

A hidden Markov model for estimating age-specific survival when age and size are uncertain

Estimates of age-specific survival probabilities are needed for age-structured population models and to inform conservation decisions. However, determining the age of individuals in wildlife populations is often problematic. We present a hidden Markov model for estimating age-specific survival from capture–recapture or capture–recapture–recovery data when age is unknown and indicators of age, such as size and growth layer counts, are imprecise. The model is evaluated through simulations, and its implementation is illustrated with maximum likelihood and Bayesian approaches in commonly used software. The model is then applied to genetic capture–recapture data of Florida manatees to estimate age- and time-variant survival probabilities. The approach is broadly applicable to studies aiming to quantify age-specific effects of environmental change and management actions on population dynamics, including studies that rely on minimally invasive methods such as genetic and photo identification.

Ecology↗
USGS1996

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↗
USGS2014

Relations of water-quality constituent concentrations to surrogate measurements in the lower Platte River corridor, Nebraska, 2007 through 2011

The lower Platte River, Nebraska, provides drinking water, irrigation water, and in-stream flows for recreation, wildlife habitat, and vital habitats for several threatened and endangered species. The U.S. Geological Survey (USGS), in cooperation with the Lower Platte River Corridor Alliance (LPRCA) developed site-specific regression models for water-quality constituents at four sites (Shell Creek near Columbus, Nebraska [USGS site 06795500]; Elkhorn River at Waterloo, Nebr. [USGS site 06800500]; Salt Creek near Ashland, Nebr. [USGS site 06805000]; and Platte River at Louisville, Nebr. [USGS site 06805500]) in the lower Platte River corridor. The models were developed by relating continuously monitored water-quality properties (surrogate measurements) to discrete water-quality samples. These models enable existing web-based software to provide near-real-time estimates of stream-specific constituent concentrations to support natural resources management decisions. Since 2007, USGS, in cooperation with the LPRCA, has continuously monitored four water-quality properties seasonally within the lower Platte River corridor: specific conductance, water temperature, dissolved oxygen, and turbidity. During 2007 through 2011, the USGS and the Nebraska Department of Environmental Quality collected and analyzed discrete water-quality samples for nutrients, major ions, pesticides, suspended sediment, and bacteria. These datasets were used to develop the regression models. This report documents the collection of these various water-quality datasets and the development of the site-specific regression models. Regression models were developed for all four monitored sites. Constituent models for Shell Creek included nitrate plus nitrite, total phosphorus, orthophosphate, atrazine, acetochlor, suspended sediment, and Escherichia coli (E. coli) bacteria. Regression models that were developed for the Elkhorn River included nitrate plus nitrite, total Kjeldahl nitrogen, total phosphorus, orthophosphate, chloride, atrazine, acetochlor, suspended sediment, and E. coli. Models developed for Salt Creek included nitrate plus nitrite, total Kjeldahl nitrogen, suspended sediment, and E. coli. Lastly, models developed for the Platte River site included total Kjeldahl nitrogen, total phosphorus, sodium, metolachlor, atrazine, acetochlor, suspended sediment, and E. coli.

Nebraska↗
USGS2018

Geologic map of the Nepenthes Planum Region, Mars

This map product contains a map sheet at 1:1,506,000 scale that shows the geology of the Nepenthes Planum region of Mars, which is located between the cratered highlands that dominate the southern hemisphere and the less-cratered sedimentary plains that dominate the northern hemisphere. The map region contains cone- and mound-shaped landforms as well as lobate materials that are morphologically similar to terrestrial igneous or mud vents and flows. This map is part of an informal series of small-scale (large-area) maps aimed at refining current understanding of the geologic units and structures that make up the highland-to-lowland transition zone. The map base consists of a controlled Thermal Emission Imaging System (THEMIS) daytime infrared image mosaic (100 meters per pixel resolution) supplemented by a Mars Orbiter Laser Altimeter (MOLA) digital elevation model (463 meters per pixel resolution). The map includes a Description of Map Units and a Correlation of Map Units that describes and correlates units identified across the entire map region. The geologic map was assembled using ArcGIS software by Environmental Systems Research Institute ( http://www.esri.com ). The ArcGIS project, geodatabase, base map, and all map components are included online as supplemental data.

Scientific Investigations Map↗
USGS2008

Hierarchical modeling of bycatch rates of sea turtles in the western North Atlantic

Previous studies indicate that the locations of the endangered loggerhead Caretta caretta and critically endangered leatherback Dermochelys coriacea sea turtles are influenced by water temperatures, and that incidental catch rates in the pelagic longline fishery vary by region. We present a Bayesian hierarchical model to examine the effects of environmental variables, including water temperature, on the number of sea turtles captured in the US pelagic longline fishery in the western North Atlantic. The modeling structure is highly flexible, utilizes a Bayesian model selection technique, and is fully implemented in the software program WinBUGS. The number of sea turtles captured is modeled as a zero-inflated Poisson distribution and the model incorporates fixed effects to examine region-specific differences in the parameter estimates. Results indicate that water temperature, region, bottom depth, and target species are all significant predictors of the number of loggerhead sea turtles captured. For leatherback sea turtles, the model with only target species had the most posterior model weight, though a re-parameterization of the model indicates that temperature influences the zero-inflation parameter. The relationship between the number of sea turtles captured and the variables of interest all varied by region. This suggests that management decisions aimed at reducing sea turtle bycatch may be more effective if they are spatially explicit. ?? Inter-Research 2008.

Endangered Species Research↗
USGS2011

Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative

As part of the Great Lakes Restoration Initiative (GLRI) during 2009–10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L–THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program–Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.

Great Lakes Basin↗
USGS2016

Delineation of areas contributing groundwater to selected receiving surface water bodies for long-term average hydrologic conditions from 1968 to 1983 for Long Island, New York

To assist resource managers and planners in developing informed strategies to address nitrogen loading to coastal water bodies of Long Island, New York, the U.S. Geological Survey and the New York State Department of Environmental Conservation initiated a program to delineate a comprehensive dataset of groundwater recharge areas (or areas contributing groundwater), travel times, and outflows to streams and saline embayments on Long Island. A four-layer regional three-dimensional finite-difference groundwater-flow model of hydrologic conditions from 1968 to 1983 was used to provide delineations of 48 groundwater watersheds on Long Island. Sixteen particle starting points were evenly spaced within each of the 4,000- by 4,000-foot model cells that receive water-table recharge and tracked using forward particle-tracking analysis modeling software to outflow zones. For each particle, simulated travel times were grouped by age as follows: less than or equal to 10 years, greater than 10 years and less than or equal to 100 years, greater than 100 years and less than or equal to 1,000 years, and greater than 1,000 years; and simulated ending zones were grouped into 48 receiving water bodies, based on the New York State Department of Environmental Conservation Waterbody Inventory/Priority Waterbodies List. Areal delineation of travel time zones and groundwater contributing areas were generated and a table was prepared presenting the sum of groundwater outflow for each area.

New York↗
USGS2021

Simulation of groundwater budgets and travel times for watersheds on the north shore of Long Island Sound, with implications for nitrogen-transport studies

Aquatic systems in and around the Long Island Sound (LIS) provide a variety of ecological and economic benefits, but in some areas of the LIS, aquatic ecosystems have become degraded by excess nitrogen. A substantial fraction of the nitrogen inputs to the LIS are transported through the groundwater-flow system. Because groundwater travel times in surficial aquifers can exceed 100 years, multiyear lags are introduced between inputs at the water table in recharge areas and discharge to inland or coastal receiving waters. The U.S. Geological Survey, in cooperation with the Connecticut Department of Energy and Environmental Protection and the U.S. Environmental Protection Agency’s Long Island Sound Study, developed a steady-state groundwater model of the watersheds draining from the northern shore of the LIS for the purpose of calculating groundwater budgets and travel times to coastal waters. The model was developed by using the MODFLOW–NWT software and existing spatial data on aquifers, river networks, land-surface altitudes, land cover, groundwater recharge, and water use. Coastal waters were delineated on the basis of the National Wetland Inventory; all non-coastal waters were collectively termed “inland waters.” A coarse-resolution model was calibrated by using the PEST++ software, long-term records of water levels in 65 wells, stream altitudes from 477 streams, base-flow records for 14 streamgages that are relatively unaffected by withdrawals, and error metrics based on incorrectly simulated flooding and incorrectly simulated dry streams. The calibrated values were used in a fine-resolution model in which the mean absolute residuals were 4.5 meters for groundwater levels, 1.3 meters for stream altitudes, and 7,200 cubic meters per day (2.9 cubic feet per second) for base flow. About 89 percent of the terrestrial cells were correctly simulated with the water table below land surface, and nearly 90 percent of the cells representing streams were correctly simulated as having the water table above the stream bottom. Together, these metrics suggest that this model is robust for simulating regional-scale groundwater patterns. Simulated groundwater budgets were compiled for the entire study area, for each HUC12 (Hydrologic Unit Code no. 12) watershed and its adjacent coastal waters, if applicable, within the study area, and for 14 coastal-embayment watersheds. Most groundwater (90.6 percent of inflows) discharged to inland waters, with smaller fractions to coastal waters (7.0 percent) and well withdrawals (2.4 percent). When computed for HUC12 watersheds with coastal discharge, the portions of groundwater discharging to coastal waters ranged from 0.02 to 66 percent of groundwater outflows, with a median of 13 percent. Within priority-embayment watersheds, the portions of groundwater discharging to coastal waters ranged from 2 to 56 percent, with a median of 15 percent. Groundwater travel times also were simulated for the entire study area, for each HUC12 watershed and its adjacent coastal waters, if applicable, within the study area and for 14 priority coastal embayments. Within the entire study area, the median groundwater travel time was 1.9 years, with an interquartile range of 0.1 to 5.9 years. Sensitivity analysis of groundwater travel times within a subbasin in the study area indicates that the travel times are a function of the grid resolution, with coarser grids resulting in shorter median travel times. Travel times for groundwater discharging to coastal waters were similar to travel times for groundwater discharging to inland waters, with a median of 1.9 years. Median travel times for the HUC12 watersheds ranged from 0.9 to 53.5 years, with a median of 1.8 years. Among HUC12 watersheds that include coastal areas, travel times for groundwater discharging to coastal waters ranged from less than 1 to 61.6 years, with a median of 2.8 years. The HUC12 watersheds with the longest simulated travel times were in the urban area near New York City where the model performance is less accurate. Median travel times for groundwater discharging to coastal waters within the priority-embayment watersheds ranged from less than 1 to 18.6 years, with a median of 2.3 years. A more focused analysis was conducted for the Niantic River watershed to demonstrate the applicability of the regional model to local-scale nitrogen-transport analyses by using nitrogen-input and -attenuation rates from literature sources. Nitrogen inputs were estimated by using land-cover-based loading factors, and attenuation was estimated by using attenuation factors based on geologic zones and soil properties. Based on this analysis, groundwater transports an estimated 22,000 kilograms of nitrogen per year (2.9 kilograms of nitrogen per hectare per year) to streams, rivers, and coastal waters within the Niantic River watershed. Approximately 36 percent of discharging nitrogen is from atmospheric-deposition sources, 38 percent is from fertilizers, and 26 percent is from septic systems. Most of the groundwater-transported nitrogen (88 percent) discharges first to streams and rivers, with only 12 percent discharging directly to coastal waters. Travel times for groundwater-transported nitrogen ranged from less than 1 day to more than 100 years, with a median of 1.6 years.

Connecticut, New York, Rhode Island↗
USGS1988

Linear solvation energy relationships for toxicity of selected organic chemicals to Daphnia pulex and Daphnia magna

In the Laurentian Great Lakes, more than 300 contaminants have been identified in fish, other biota, water, and sediment. Current hazard assessment of these chemicals by the National Fisheries Research Center-Great Lakes is based on their toxicity, occurrence in the environment, and source. Although scientists at the Center have tested over 70 chemicals with the crustacean Daphnia pulex , the number of experimental data needed to screen the huge array of chemicals in the Great Lakes exceeds the practical capabilities of conducting bioassays. This limitation can be partly circumvented, however, by using mathematical models based on quantitative structure-activity relationships (QSAR) to provide rapid, inexpensive estimates of toxicity. Many properties of chemicals, including toxicity, bioaccumulation and water solubility are well correlated and can be predicted by equations of the generalized linear solvation energy relationships (LSER). The equation we used to model solute toxicity is Toxicity = constant + m VI/100 + s (π* + dδ) + b βm + a αm where VI = intrinsic (Van der Waals) molar volume; π* = molecular dipolarity/polarizability; δ = polarizability 'correction term'; βm = solute hydrogen bond acceptor basicity; and αm = solute hydrogen bond donor acidity. The subscript m designates solute monomer values for α and β. We applied the LSER model to 48-h acute toxicity data (measured as immobilization) for six classes of chemicals detected in Great Lakes fish. The following regression was obtained for Daphnia pulex (concentration = μM): log EC50 = 4.86 - 4.35 VI/100; N = 38, r2 = 0.867, sd = 0.403 We also used the LSER modeling approach to analyze to a large published data set of 24-h acute toxicity for Daphnia magna ; the following regression resulted, for eight classes of compounds (concentration = mM): log EC50 = 3.88 - 4.52 VI/100 - 1.62 π* + 1.66 βm - 0.916 αm; N = 62, r2 = 0.859, sd = 0.375 In addition we developed computer software that identifies chemical structures, estimates the LSER parameters, and predicts toxicity. The LSER models promise to be effective in differentiating between reactive and nonreactive toxicity behavior where other models have failed. Contaminants with reactive behavior are generally the most toxic and rank highest in hazard assessment of environmental chemicals.

Proceedings of the QSAR↗
USGS2001

All equal-area map projections are created equal, but some are more equal than others

High-resolution regional and global raster databases are currently being generated for a variety of environmental and scientific modeling applications. The projection of these data from geographic coordinates to a plane coordinate system is subject to significant areal error. Sources of error include users selecting an inappropriate projection or incorrect parameters for a given projection, algorithmic errors in commercial geographic information system (GIS) software, and errors resulting from the projection of data in the raster format. To assess the latter type of errors, the accuracy of raster projection was analyzed by two methods. First, a set of 12 one-degree by one-degree quadrilaterals placed at various latitudes was projected at several raster resolutions and compared to the projection of a vector representation of the same quadrilaterals. Second, several different raster resolutions of land cover data for Asia were projected and the total areas of 21 land cover categories were tabulated and compared. While equal-area projections are designed to specifically preserve area, the comparison of the results of the one-degree by one-degree quadrilaterals with the common equal area projections (e.g., the Mollweide) indicates a considerable variance in the one-degree area after projection. Similarly, the empirical comparison of land cover areas for Asia among various projections shows that total areas of land cover vary with projection type, raster resolution, and latitude. No single projection is best for all resolutions and all latitudes. While any of the equal-area projections tested are reasonably accurate for most applications with resolutions of eight-kilometer pixels or smaller, significant variances in accuracies appear at larger pixel sizes.

Cartography and Geographic Information Science↗
USGS1994

Wilderness monitoring and data management

In the last decade, increased public interest in natural areas has resulted in increased monitoring activity by federal wilderness managers to assess the status of wilderness values. Wilderness values are those large-scale entities of wilderness which comprise, in sum, wilderness character. Data collected through wilderness monitoring must support the maintenance of wilderness values. Wilderness monitoring must include the development of clear data management strategies and provisions for hypothesis testing. Unfortunately, some monitoring programs do not support the status assessment of wilderness values. Often wilderness monitoring programs have neglected even the most rudimentary principles of data management. This paper presents a model for wilderness monitoring, guidelines for data management, and an overview of a PC-compatible wilderness monitoring data base, the Monitoring Information Data Analysis System (MIDAS).

Environmental Software↗