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At least 73 records · Page 4Linked to original sources
USGS1981

Decentralized shared computers in the National Earthquake Hazards Reduction Program

The needs for computer analysis in the National Earthquake Program are varied, complex, and rapidly growing. Major sources of frustration have been the difficulty of keeping up with the required analysis, and the difficulties of sharing a wide variety of data and computer programs among several hundred researchers at dozens of institutions located throughout the U.S. A major effort is underway to create a similar computer environment running on many PDP 11/70 minicomputers located across the country that encourages widespread sharing of data and "software tools" without impeding the free flow of creative ideas in this research program. Large libraries of high-level tools are provided in a well documented manner. The tools can be readily combined into programs using a new interactive language, any compiled language, or, in many cases, the Shell command language of the UNIX** Timesharing System. New tools are easily written by any user. Major system tools provided include advanced general plotting programs and a relational indexed database. Extensions to the operating system include text overlays and an 830,000 baud graphics interface.

Open-File Report↗
USGS2013

Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach

The increasing availability of multi-scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model-assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the "hot" and "cold" reference conditions. The SSEBop model was used for computing ET for 12 years (2000-2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000-2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.

Journal of the American Water Resources Associatio↗
USGS2006

USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015

In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (hereafter also referred to as "the Center"). The Center has been the flagship research center for the USGS in the western United States for more than 50 years, and the Council recognizes that science priorities must be the primary consideration guiding critical decisions made about the future evolution of the Center. In developing this strategy, the working group consulted widely within the USGS and with external clients and collaborators, so that most stakeholders had an opportunity to influence the science goals and operational objectives. The Science Goals are to: Natural Hazards: Conduct natural-hazard research and assessments critical to effective mitigation planning, short-term forecasting, and event response. Ecosystem Change: Develop a predictive understanding of ecosystem change that advances ecosystem restoration and adaptive management. Natural Resources: Advance the understanding of natural resources in a geologic, hydrologic, economic, environmental, and global context. Modeling Earth System Processes: Increase and improve capabilities for quantitative simulation, prediction, and assessment of Earth system processes. The strategy presents seven key Operational Objectives with specific actions to achieve the scientific goals. These Operational Objectives are to: Provide a hub for technology, laboratories, and library services to support science in the Western Region. Increase advanced computing capabilities and promote sharing of these resources. Enhance the intellectual diversity, vibrancy, and capacity of the work force through improved recruitment and retention. Strengthen client and collaborative relationships in the community at an institutional level. Expand monitoring capability by increasing density, sensitivity, and efficiency and reducing costs of instruments and networks. Encourage a breadth of scientific capabilities in Menlo Park to foster interdisciplinary science. Communicate USGS science to a diverse audience.

Circular↗
USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗
USGS2024

Real-time invasive sea lamprey detection using machine learning classifier models on embedded systems

Invasive sea lamprey ( Petromyzon marinus ) has historically inflicted considerable economic and ecological damage in the Great Lakes and continues to be a major threat. Accurately monitoring sea lampreys are critical to enabling the deployment of more targeted and effective control measures to minimize the impact associated with this species. This paper presents the first stand-alone system for real-time detection of sea lamprey attachment on underwater surfaces through the use of classifier models deployed on a microcontroller system. A range of low-complexity models was explored: single-layer artificial neural networks, logistic regression, Gaussian Naive-Bayes, decision trees, random forest, and Scalable, Efficient, and Fast classifieR (SEFR). Threshold models tuned using a multi-objective optimization formulation were also considered. Classifier models were trained with a dataset generated through live animal testing and presented accuracies between 80 and 86%. The models were deployed on an Arduino microcontroller platform and compared in classification accuracy, detection performance, time complexity, and memory size using real-time detection testing. Classification accuracies between 65 and 75% were observed during validation. Models demonstrated good capture rates for lamprey attachments (63–85%), and average detection delays ranging from 9 to 36 s. A video demonstrating the operation of the system during a real-time validation test is also included in this work. While there is room for improving the accuracy of the system, this research presents the first step toward an electronic sea lamprey monitoring system that can provide a detailed view of sea lamprey activity enhancing control and conservation efforts across its entire range.

Neural Computing and Applications↗
USGS2009

An expert system for prediction of aquatic toxicity of contaminants

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

Book chapter↗
USGS2014

Metrics for comparing dynamic earthquake rupture simulations

Earthquakes are complex events that involve a myriad of interactions among multiple geologic features and processes. One of the tools that is available to assist with their study is computer simulation, particularly dynamic rupture simulation. A dynamic rupture simulation is a numerical model of the physical processes that occur during an earthquake. Starting with the fault geometry, friction constitutive law, initial stress conditions, and assumptions about the condition and response of the near‐fault rocks, a dynamic earthquake rupture simulation calculates the evolution of fault slip and stress over time as part of the elastodynamic numerical solution (Ⓔ see the simulation description in the electronic supplement to this article). The complexity of the computations in a dynamic rupture simulation make it challenging to verify that the computer code is operating as intended, because there are no exact analytic solutions against which these codes’ results can be directly compared. One approach for checking if dynamic rupture computer codes are working satisfactorily is to compare each code’s results with the results of other dynamic rupture codes running the same earthquake simulation benchmark. To perform such a comparison consistently, it is necessary to have quantitative metrics. In this paper, we present a new method for quantitatively comparing the results of dynamic earthquake rupture computer simulation codes.

Seismological Research Letters↗
USGS1975

WATSTORE: National Water Data Storage and Retrieval System of the U. S. Geological Survey; user's guide

The U.S. Geological Survey investigates the occurrence , quantity, quality, distribution, and movement of the surface and underground water resources of the Nation. The investigations, which are conducted by the Water Resources Division, of the Survey include: systematic collection, analysis, and interpretation of water data; investigation of in and agricultural water requirements; research and development to improve study techniques and methodologies to better understand the hydrologic principles that form the scientific basis of investigation; and publication and other forms of release to the public of results and data from these investigations. A large scale computerized storage and retrieval system is used by the Geological Survey to store and disseminate water data acquired through its many activities. The Geological Survey's National Water Data Storage and Retrieval System (WATSTORE) was implemented in November 1971. In addition to its data processing, storage, and retrieval capabilities, WATSTORE has the capability of providing computer-printed tables, computer-printed graphs, statistical analyses of data, and digital plots. The system is operated and maintained on the central computer facility of the Survey at its National Center, Reston, Va. an through approximately 50 terminals in Water Resources Division district an subdistrict offices located in major cities throughout the country. Asccess to WATSTORE is limited by hardware, available telephone lines, etc; for example, direct access is possible only through terminal equipment capable of interfacing with an IBM 370/155 computer. WATSTORE is now (1975) available to other Federal agencies and selected cooperators of the Geological Survey who acquire and(or) use water data. The WATSTORE User's Guide describes the systeb and how it operates.

Open-File Report↗
USGS2007

A new towed platform for the unobtrusive surveying of benthic habitats and organisms

Maps of coral ecosystems are needed to support many conservation and management objectives, as well as research activities. Examples include ground-truthing aerial and satellite imagery, characterizing essential habitat, assessing changes, and monitoring the progress of restoration efforts. To address some of these needs, the U.S. Geological Survey developed the Along-Track Reef-Imaging System (ATRIS), a boat-based sensor package for mapping shallow-water benthic environments. ATRIS consists of a digital still camera, a video camera, and an acoustic depth sounder affixed to a moveable pole. This design, however, restricts its deployment to clear waters less than 10 m deep. To overcome this limitation, a towed version has been developed, referred to as Deep ATRIS. The system is based on a light-weight, computer-controlled, towed vehicle that is capable of following a programmed diving profile. The vehicle is 1.3 m long with a 63-cm wing span and can carry a wide variety of research instruments, including CTDs, fluorometers, transmissometers, and cameras. Deep ATRIS is currently equipped with a high-speed (20 frames · s-1) digital camera, custom-built light-emitting-diode lights, a compass, a 3-axis orientation sensor, and a nadir-looking altimeter. The vehicle dynamically adjusts its altitude to maintain a fixed height above the seafloor. The camera has a 29° x 22° field-of-view and captures color images that are 1360 x 1024 pixels in size. GPS coordinates are recorded for each image. A gigabit ethernet connection enables the images to be displayed and archived in real time on the surface computer. Deep ATRIS has a maximum tow speed of 2.6 m · s-1and a theoretical operating tow-depth limit of 27 m. With an improved tow cable, the operating depth can be extended to 90 m. Here, we present results from the initial sea trials in the Gulf of Mexico and Biscayne National Park, Florida, USA, and discuss the utility of Deep ATRIS for map-ping coral reef habitats. Several example mosaics illustrate the high-quality imagery that can be obtained with this system. The images also reveal the potential for unobtrusive animal observations; fish and sea turtles are unperturbed by the presence of Deep ATRIS

Florida↗
USGS1987

Overview of the land analysis system (LAS)

The Land Analysis System (LAS) is a fully integrated digital analysis system designed to support remote sensing, image processing, and geographic information systems research. LAS is being developed through a cooperative effort between the National Aeronautics and Space Administration Goddard Space Flight Center and the U. S. Geological Survey Earth Resources Observation Systems (EROS) Data Center. LAS has over 275 analysis modules capable to performing input and output, radiometric correction, geometric registration, signal processing, logical operations, data transformation, classification, spatial analysis, nominal filtering, conversion between raster and vector data types, and display manipulation of image and ancillary data. LAS is currently implant using the Transportable Applications Executive (TAE). While TAE was designed primarily to be transportable, it still provides the necessary components for a standard user interface, terminal handling, input and output services, display management, and intersystem communications. With TAE the analyst uses the same interface to the processing modules regardless of the host computer or operating system. LAS was originally implemented at EROS on a Digital Equipment Corporation computer system under the Virtual Memorial System operating system with DeAnza displays and is presently being converted to run on a Gould Power Node and Sun workstation under the Berkeley System Distribution UNIX operating system.

Conference Paper↗
USGS2019

Near-field remote sensing of Alaskan Rivers

The U.S. Geological Survey (USGS) Geomorphology and Sediment Transport Laboratory (GSTL), in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL), acquired remotely sensed data from several Alaskan rivers in 2017 and 2018 with the goal of developing a methodology for measuring streamflow from a helicopter. CRREL operates a custom airborne lidar system that can be deployed in a helicopter-based pod (HeliPod). Data were collected with the HeliPod near existing USGS streamflow information stations on the Knik, Matanuska, Chena, and Salcha Rivers in both 2017 and 2018. Sites on the Tanana and Snow Rivers were added in 2018. In 2018, the HeliPod was modified to accommodate both a thermal infrared and a visible camera. The cameras were integrated with the flight management software to simultaneously acquire imagery with lidar. The Global Navigation Satellite System (GNSS) and inertial measurement unit (IMU) in the HeliPod were used to compute trajectories with precise position and orientation information needed for image orthorectification. The HeliPod sensors provide data for measuring river channel characteristics. Lidar can map the elevation of the water surface and thus be used to measure water-surface slopes and return intensity can be used to delineate the extent of the wetted river channel. Various approaches are currently being evaluated to estimate surface flow velocity from visible and thermal image time series. In this paper, we examine and compare water-surface elevation returns and slopes derived from the HeliPod lidar and found good agreement with measurements made using conventional field-based techniques.

Alaska↗
USGS1999

Computer Program for Point Location And Calculation of ERror (PLACER)

A program designed for point location and calculation of error (PLACER) was developed as part of the Quality Assurance Program of the Federal Highway Administration/U.S. Geological Survey (USGS) National Data and Methodology Synthesis (NDAMS) review process. The program provides a standard method to derive study-site locations from site maps in highwayrunoff, urban-runoff, and other research reports. This report provides a guide for using PLACER, documents methods used to estimate study-site locations, documents the NDAMS Study-Site Locator Form, and documents the FORTRAN code used to implement the method. PLACER is a simple program that calculates the latitude and longitude coordinates of one or more study sites plotted on a published map and estimates the uncertainty of these calculated coordinates. PLACER calculates the latitude and longitude of each study site by interpolating between the coordinates of known features and the locations of study sites using any consistent, linear, user-defined coordinate system. This program will read data entered from the computer keyboard and(or) from a formatted text file, and will write the results to the computer screen and to a text file. PLACER is readily transferable to different computers and operating systems with few (if any) modifications because it is written in standard FORTRAN. PLACER can be used to calculate study site locations in latitude and longitude, using known map coordinates or features that are identifiable in geographic information data bases such as USGS Geographic Names Information System, which is available on the World Wide Web.

Open-File Report↗
USGS2016

Identifying and preserving high-water mark data

High-water marks provide valuable data for understanding recent and historical flood events. The proper collection and recording of high-water mark data from perishable and preserved evidence informs flood assessments, research, and water resource management. Given the high cost of flooding in developed areas, experienced hydrographers, using the best available techniques, can contribute high-quality data toward efforts such as public education of flood risk, flood inundation mapping, flood frequency computations, indirect streamflow measurement, and hazard assessments. This manual presents guidance for skilled high-water mark identification, including marks left behind in natural and man-made environments by tranquil and rapid flowing water. This manual also presents pitfalls and challenges associated with various types of flood evidence that help hydrographers identify the best high-water marks and assess the uncertainty associated with a given mark. Proficient high-water mark data collection contributes to better understanding of the flooding process and reduces risk through greater ability to estimate flood probability. The U.S. Geological Survey, operating the Nation’s premier water data collection network, encourages readers of this manual to familiarize themselves with the art and science of high-water mark collection. The U.S. Geological survey maintains a national database at http://water.usgs.gov/floods/FEV/ that includes high-water mark information for many flood events, and local U.S. Geological Survey Water Science Centers can provide information to interested readers about participation in data collection and flood documentation efforts as volunteers or observers.

Techniques and Methods↗
USGS2005

Comparison of methods for estimating ground-water recharge and base flow at a small watershed underlain by fractured bedrock in the Eastern United States

This study by the U.S. Geological Survey (USGS), in cooperation with the Agricultural Research Service (ARS), U.S. Department of Agriculture, compared multiple methods for estimating ground-water recharge and base flow (as a proxy for recharge) at sites in east-central Pennsylvania underlain by fractured bedrock and representative of a humid-continental climate. This study was one of several within the USGS Ground-Water Resources Program designed to provide an improved understanding of methods for estimating recharge in the eastern United States. Recharge was estimated on a monthly and annual basis using four methods?(1) unsaturated-zone drainage collected in gravity lysimeters, (2) daily water balance, (3) water-table fluctuations in wells, and (4) equations of Rorabaugh. Base flow was estimated by streamflow-hydrograph separation using the computer programs PART and HYSEP. Estimates of recharge and base flow were compared for an 8-year period (1994-2001) coinciding with operation of the gravity lysimeters at an experimental recharge site (Masser Recharge Site) and a longer 34-year period (1968-2001), for which climate and streamflow data were available on a 2.8-square-mile watershed (WE-38 watershed). Estimates of mean-annual recharge at the Masser Recharge Site and WE-38 watershed for 1994-2001 ranged from 9.9 to 14.0 inches (24 to 33 percent of precipitation). Recharge, in inches, from the various methods was: unsaturated-zone drainage, 12.2; daily water balance, 12.3; Rorabaugh equations with PULSE, 10.2, or RORA, 14.0; and water-table fluctuations, 9.9. Mean-annual base flow from streamflow-hydrograph separation ranged from 9.0 to 11.6 inches (21-28 percent of precipitation). Base flow, in inches, from the various methods was: PART, 10.7; HYSEP Local Minimum, 9.0; HYSEP Sliding Interval, 11.5; and HYSEP Fixed Interval, 11.6. Estimating recharge from multiple methods is useful, but the inherent differences of the methods must be considered when comparing results. For example, although unsaturated-zone drainage from the gravity lysimeters provided the most direct measure of potential recharge, it does not incorporate spatial variability that is contained in watershed-wide estimates of net recharge from the Rorabaugh equations or base flow from streamflow-hydrograph separation. This study showed that water-level fluctuations, in particular, should be used with caution to estimate recharge in low-storage fractured-rock aquifers because of the variability of water-level response among wells and sensitivity of recharge to small errors in estimating specific yield. To bracket the largest range of plausible recharge, results from this study indicate that recharge derived from RORA should be compared with base flow from the Local-Minimum version of HYSEP.

Scientific Investigations Report↗
USGS2000

Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.

Conference Paper↗
USGS2021

Digital Twin Earth - Coasts: Developing a fast and physics-informed surrogate model for coastal floods via neural operators

Developing fast and accurate surrogates for physics-based coastal and ocean mod- els is an urgent need due to the coastal flood risk under accelerating sea level rise, and the computational expense of deterministic numerical models. For this purpose, we develop the first digital twin of Earth coastlines with new physics-informed machine learning techniques extending the state-of-art Neural Operator. As a proof-of-concept study, we built Fourier Neural Operator (FNO) surrogates on the simulations of an industry-standard coastal and ocean model – Nucleus for Euro- pean Modelling of the Ocean (NEMO). The resulting FNO surrogate accurately predicts the sea surface height in most regions while achieving upwards of 45x acceleration of NEMO. We delivered an open-source CoastalTwin platform in an end-to-end and modular way, to enable easy extensions to other simulations and ML-based surrogate methods. Our results and deliverable provide a promising approach to massively accelerate coastal dynamics simulators, which can enable scientists to efficiently execute many simulations for decision-making, uncertainty quantification, and other research activities.

Conference Paper↗
USGS2001

Evaluation of the fish passage effectiveness of the Bonneville I prototype surface collector using three-dimensional ultrasonic fish tracking - Final Report

This report describes tests conducted at Bonneville Dam on the Columbia River in the spring of 2000. The studies used three-dimensional (3D) acoustic telemetry and computational fluid dynamics (CFD) hydraulic modeling techniques to evaluate the response of outmigrating juvenile steelhead (Oncorhynchus mykiss) and yearling chinook (O. tshawytscha) to the Prototype Surface Collector (PSC) installed at Powerhouse I of Bonneville Dam in 1998 to test the concept of using a deep-slot surface bypass collector to divert downstream migrating salmon from turbines. The study was conducted by Pacific Northwest National Laboratory (PNNL), the Waterways Experiment Station of the U.S. Army Corp of Engineers (COE), Asci Corporation, and the U.S. Geological Survey (USGS), and was sponsored by COE’s Portland District. The goal of the study was to observe the three-dimensional behavior of tagged fish (fish bearing ultrasonic micro-transmitters) within 100 meters (m) of the surface flow bypass structure to test hypotheses about the response of migrants to flow stimuli generated by the presence of the surface flow bypass prototype and its operation. Research was done in parallel with radio telemetry studies conducted by USGS and hydroacoustic studies conducted by WES & Asci to evaluate the prototype surface collector.

Report↗
USGS2013

Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity

The composition, occurrence, distribution, and possible toxicity of chemical mixtures in the environment are research concerns of the U.S. Geological Survey and others. The presence of specific chemical mixtures may serve as indicators of natural phenomena or human-caused events. Chemical mixtures may also have ecological, industrial, geochemical, or toxicological effects. Chemical-mixture occurrences vary by analyte composition and concentration. Four related computer programs have been developed by the National Water-Quality Assessment Program of the U.S. Geological Survey for research of chemical-mixture compositions, occurrences, distributions, and possible toxicities. The compositions and occurrences are identified for the user-supplied data, and therefore the resultant counts are constrained by the user’s choices for the selection of chemicals, reporting limits for the analytical methods, spatial coverage, and time span for the data supplied. The distribution of chemical mixtures may be spatial, temporal, and (or) related to some other variable, such as chemical usage. Possible toxicities optionally are estimated from user-supplied benchmark data. The software for the analysis of chemical mixtures described in this report is designed to work with chemical-analysis data files retrieved from the U.S. Geological Survey National Water Information System but can also be used with appropriately formatted data from other sources. Installation and usage of the mixture software are documented. This mixture software was designed to function with minimal changes on a variety of computer-operating systems. To obtain the software described herein and other U.S. Geological Survey software, visit http://water.usgs.gov/software/.

Scientific Investigations Report↗