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USGS2019

The future is now: Amplicon sequencing and sequence capture usher in the conservation genomics era

The genomics revolution has initiated a new era of population genetics where genome-wide data are frequently used to understand complex patterns of population structure and selection. However, the application of genomic tools to inform management and conservation has been somewhat rare outside a few well studied species. Fortunately, two recently developed approaches, amplicon sequencing and sequence capture, have the potential to significantly advance the field of conservation genomics. Here, amplicon sequencing refers to highly multiplexed PCR followed by high-throughput sequencing (e.g., GTseq), and sequence capture refers to using capture probes to isolate loci from reduced-representation libraries (e.g., Rapture). Both approaches allow sequencing of thousands of individuals at relatively low costs, do not require any specialized equipment for library preparation, and generate data that can be analyzed without sophisticated computational infrastructure. Here, we discuss the advantages and disadvantages of each method and provide a decision framework for geneticists who are looking to integrate these methods into their research programme. While it will always be important to consider the specifics of the biological question and system, we believe that amplicon sequencing is best suited for projects aiming to genotype <500 loci on many individuals (>1,500) or for species where continued monitoring is anticipated (e.g., long-term pedigrees). Sequence capture, on the other hand, is best applied to projects including fewer individuals or where >500 loci are required. Both of these techniques should smooth the transition from traditional genetic techniques to genomics, helping to usher in the conservation genomics era.

Molecular Ecology Resources↗

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↗

USGS2002

CMGTooL user's manual

During the past several years, the sediment transport group in the Coastal and Marine Geology Program (CMGP) of the U. S. Geological Survey has made major revisions to its methodology of processing, analyzing, and maintaining the variety of oceanographic time-series data. First, CMGP completed the transition of the its oceanographic time-series database to a self-documenting NetCDF (Rew et al., 1997) data format. Second, CMGP’s oceanographic data variety and complexity have been greatly expanded from traditional 2-dimensional, single-point time-series measurements (e.g., Electro-magnetic current meters, transmissometers) to more advanced 3-dimensional and profiling time-series measurements due to many new acquisitions of modern instruments such as Acoustic Doppler Current Profiler (RDI, 1996), Acoustic Doppler Velocitimeter, Pulse-Coherence Acoustic Doppler Profiler (SonTek, 2001), Acoustic Bacscatter Sensor (Aquatec, 1001001001001001001). In order to accommodate the NetCDF format of data from the new instruments, a software package of processing, analyzing, and visualizing time-series oceanographic data was developed. It is named CMGTooL. The CMGTooL package contains two basic components: a user-friendly GUI for NetCDF file analysis, processing and manipulation; and a data analyzing program library. Most of the routines in the library are stand-alone programs suitable for batch processing. CMGTooL is written in MATLAB computing language (The Mathworks, 1997), therefore users must have MATLAB installed on their computer in order to use this software package. In addition, MATLAB’s Signal Processing Toolbox is also required by some CMGTooL’s routines. Like most MATLAB programs, all CMGTooL codes are compatible with different computing platforms including PC, MAC, and UNIX machines (Note: CMGTooL has been tested on different platforms that run MATLAB 5.2 (Release 10) or lower versions. Some of the commands related to MAC may not be compatible with later releases of MATLAB). The GUI and some of the library routines call low-level NetCDF file I/O, variable and attribute functions. These NetCDF exclusive functions are supported by a MATLAB toolbox named NetCDF, created by Dr. Charles Denham . This toolbox has to be installed in order to use the CMGTooL GUI. The CMGTooL GUI calls several routines that were initially developed by others. The authors would like to acknowledge the following scientists for their ideas and codes: Dr. Rich Signell (USGS), Dr. Chris Sherwood (USGS), and Dr. Bob Beardsley (WHOI). Many special terms that carry special meanings in either MATLAB or the NetCDF Toolbox are used in this manual. Users are encouraged to read the documents of MATLAB and NetCDF for references.

Open-File Report↗

USGS2003

USGS Digital Spectral Library splib05a

We have assembled a digital reflectance spectral library of spectra that covers wavelengths from the ultraviolet to near-infrared along with sample documentation. The library includes samples of minerals, rocks, soils, physically constructed as well as mathematically computed mixtures, vegetation, microorganisms, and man-made materials. The samples and spectra collected were assembled for the purpose of using spectral features for the remote detection of these and similar materials.

Open-File Report↗

USGS2013

SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data

SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (e.g., microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains 3 analysis modules along with a fourth control module that can automate analyses of large volumes of data. The modules are used to 1) identify the subset of paired-end sequences that pass Illumina quality standards, 2) align paired-end reads into a single composite DNA sequence, and 3) identify sequences that possess microsatellites (both simple and compound) conforming to user-specified parameters. The microsatellite search algorithm is extremely efficient, and we have used it to identify repeats with motifs from 2 to 25bp in length. Each of the 3 analysis modules can also be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc.). We demonstrate use of the program with data from the brine fly Ephydra packardi (Diptera: Ephydridae) and provide empirical timing benchmarks to illustrate program performance on a common desktop computer environment. We further show that the Illumina platform is capable of identifying large numbers of microsatellites, even when using unenriched sample libraries and a very small percentage of the sequencing capacity from a single DNA sequencing run. All modules from SSR_pipeline are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, and Windows).

Journal of Heredity↗

USGS1993

The U. S. Geological Survey, Digital Spectral Library: Version 1 (0.2 to 3.0um)

We have developed a digital reflectance spectral library, with management and spectral analysis software. The library includes 498 spectra of 444 samples (some samples include a series of grain sizes) measured from approximately 0.2 to 3.0 um . The spectral resolution (Full Width Half Maximum) of the reflectance data is <= 4 nm in the visible (0.2-0.8 um) and <= 10 nm in the NIR (0.8-2.35 um). All spectra were corrected to absolute reflectance using an NIST Halon standard. Library management software lets users search on parameters (e.g. chemical formulae, chemical analyses, purity of samples, mineral groups, etc.) as well as spectral features. Minerals from borate, carbonate, chloride, element, halide, hydroxide, nitrate, oxide, phosphate, sulfate, sulfide, sulfosalt, and the silicate (cyclosilicate, inosilicate, nesosilicate, phyllosilicate, sorosilicate, and tectosilicate) classes are represented. X-Ray and chemical analyses are tabulated for many of the entries, and all samples have been evaluated for spectral purity. The library also contains end and intermediate members for the olivine, garnet, scapolite, montmorillonite, muscovite, jarosite, and alunite solid-solution series. We have included representative spectra of H2O ice, kerogen, ammonium-bearing minerals, rare-earth oxides, desert varnish coatings, kaolinite crystallinity series, kaolinite-smectite series, zeolite series, and an extensive evaporite series. Because of the importance of vegetation to climate-change studies we have include 17 spectra of tree leaves, bushes, and grasses. The library and software are available as a series of U.S.G.S. Open File reports. PC user software is available to convert the binary data to ascii files (a separate U.S.G.S. open file report). Additionally, a binary data files are on line at the U.S.G.S. in Denver for anonymous ftp to users on the Internet. The library search software enables a user to search on documentation parameters as well as spectral features. The analysis system includes general spectral analysis routines, plotting packages, radiative transfer software for computing intimate mixtures, routines to derive optical constants from reflectance spectra, tools to analyze spectral features, and the capability to access imaging spectrometer data cubes for spectral analysis. Users may build customized libraries (at specific wavelengths and spectral resolution) for their own instruments using the library software. We are currently extending spectral coverage to 150 um. The libraries (original and convolved) will be made available in the future on a CD-ROM.

Open-File Report↗

USGS1990

Reference manual for generation and analysis of Habitat Time Series: version II

The selection of an instream flow requirement for water resource management often requires the review of how the physical habitat changes through time. This review is referred to as 'Time Series Analysis." The Tune Series Library (fSLIB) is a group of programs to enter, transform, analyze, and display time series data for use in stream habitat assessment. A time series may be defined as a sequence of data recorded or calculated over time. Examples might be historical monthly flow, predicted monthly weighted usable area, daily electrical power generation, annual irrigation diversion, and so forth. The time series can be analyzed, both descriptively and analytically, to understand the importance of the variation in the events over time. This is especially useful in the development of instream flow needs based on habitat availability. The TSLIB group of programs assumes that you have an adequate study plan to guide you in your analysis. You need to already have knowledge about such things as time period and time step, species and life stages to consider, and appropriate comparisons or statistics to be produced and displayed or tabulated. Knowing your destination, you must first evaluate whether TSLIB can get you there. Remember, data are not answers . This publication is a reference manual to TSLIB and is intended to be a guide to the process of using the various programs in TSLIB. This manual is essentially limited to the hands-on use of the various programs. a TSLIB use interface program (called RTSM) has been developed to provide an integrated working environment where the use has a brief on-line description of each TSLIB program with the capability to run the TSLIB program while in the user interface. For information on the RTSM program, refer to Appendix F. Before applying the computer models described herein, it is recommended that the user enroll in the short course "Problem Solving with the Instream Flow Incremental Methodology (IFIM)." This course is offered by the Aquatic Systems Branch of the National Ecology Research Center. For more information about the TSLIB software, refer to the Memorandum of Understanding. Chapter 1 provides a brief introduction to the Instream Flow Incremental Methodology and TSLIB. Other chapters in this manual provide information on the different aspects of using the models. The information contained in the other chapters includes (2) acquisition, entry, manipulation, and listing of streamflow data; (3) entry, manipulation, and listing of the habitat-versus-streamflow function; (4) transferring streamflow data; (5) water resources systems analysis; (6) generation and analysis of daily streamflow and habitat values; (7) generation of the time series of monthly habitats; (8) manipulation, analysis, and display of month time series data; and (9) generation, analysis, and display of annual time series data. Each section includes documentation for the programs therein with at least one page of information for each program, including a program description, instructions for running the program, and sample output. The Appendixes contain the following: (A) sample file formats; (B) descriptions of default filenames; (C) alphabetical summary of batch-procedure files; (D) installing and running TSLIB on a microcomputer; (E) running TSLIB on a CDC Cyber computer; (F) using the TSLIB user interface program (RTSM); and (G) running WATSTORE on the USGS Amdahl mainframe computer. The number for this version of TSLIB--Version II-- is somewhat arbitrary, as the TSLIB programs were collected into a library some time ago; but operators tended to use and manage them as individual programs. Therefore, we will consider the group of programs from the past that were only on the CDC Cyber computer as Version 0; the programs from the past that were on both the Cyber and the IBM-compatible microcomputer as Version I; and the programs contained in this reference manual as Version II.

Report↗

USGS1979

Rock Analysis Storage System (RASS), Saudi Arabia; an introduction to the system and sample submittal manual, 1978

The U.S. Geological Survey Saudi Arabian Mission has the responsibility for implementing a computer-based file known as the Rock Analysis Storage System (RASS), which is principally a geochemical data bank or library. Geologic parameters are necessarily provided for, but are far from comprehensive; nevertheless, nine years of operation in the U.S. has demonstrated that the simplicity of the version described herein has helped induce many scientists frequently to use the system. Their extensive participation has proved the system to be adequate for the reduction of data and consequent publication of scientific papers.

Open-File Report↗

USGS2007

Using simulated historical time series to prioritize fuel treatments on landscapes across the United States: The LANDFIRE prototype project

Canopy and surface fuels in many fire-prone forests of the United States have increased over the last 70 years as a result of modern fire exclusion policies, grazing, and other land management activities. The Healthy Forest Restoration Act and National Fire Plan establish a national commitment to reduce fire hazard and restore fire-adapted ecosystems across the USA. The primary index used to prioritize treatment areas across the nation is Fire Regime Condition Class (FRCC) computed as departures of current conditions from the historical fire and landscape conditions. This paper describes a process that uses an extensive set of ecological models to map FRCC from a departure statistic computed from simulated time series of historical landscape composition. This mapping process uses a data-driven, biophysical approach where georeferenced field data, biogeochemical simulation models, and spatial data libraries are integrated using spatial statistical modeling to map environmental gradients that are then used to predict vegetation and fuels characteristics over space. These characteristics are then fed into a landscape fire and succession simulation model to simulate a time series of historical landscape compositions that are then compared to the composition of current landscapes to compute departure, and the FRCC values. Intermediate products from this process are then used to create ancillary vegetation, fuels, and fire regime layers that are useful in the eventual planning and implementation of fuel and restoration treatments at local scales. The complex integration of varied ecological models at different scales is described and problems encountered during the implementation of this process in the LANDFIRE prototype project are addressed.

Ecological Modelling↗

USGS2021

Hyperspectral narrowband data propel gigantic leap in the earth remote sensing

Hyperspectral narrowbands (HNBs) capture data as nearly continuous “spectral signatures” rather than a “few spectral data points” along the electromagnetic spectrum as with multispectral broadbands (MBBs). Almost all of satellite remote sensing of the Earth in the twentieth century was conducted using MBB data from sensors such as the Landsat-series, Advanced Very High-Resolution Radiometer (AVHRR), SPOT (Système Pour l’Observation de la Terre), and the Indian Remote Sensing (IRS) satellites. These systems typically provide 4 to 9 broad spectral wavebands spread from 400 to 2500 nm, often with one or two additional bands in the thermal range. Significant advances in the study of the Earth have been made based on these data [Thenkabail et al., 2018a,b,c,d; Thenkabail et al., 2015a,b,c]. Possibilities of great advances that can be made using HNB data over MBB data are well established based on studies conducted using hyperspectral sensors such as the hand-held spectroradiometers, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and spaceborne Earth Observing -1 (EO-1) Hyperion [Thenkabail 2018a,b,c,d]. The twenty-first century is already seeing the dawn of hyperspectral imaging data from sensors such as the German Aerospace Center’s (DLR’s) DESIS (DLR Earth Sensing Imaging Spectrometer) onboard the MUSES (Multi-User System for Earth Sensing) platform on the International Space Station (ISS), the polar-orbiting Italian Space Agency’s (ASI) PRISMA (PRecursore IperSpettrale della Missione Applicativa), and many other upcoming sensors such as the NASA Surface Biology and Geology (SBG) [Thenkabail et al., 2018a,b,c,d]. These satellites acquire data in hundreds of narrow spectral bands of 1 to 10 nm width, typically between 400 to 2500 nm; also future planned missions will be extending HNBs to the thermal (9,000 to 14,000 nm) electromagnetic spectrum. This expansion creates a quantum leap in new data, new information, and myriad possible new applications in the study of the Earth in addition to great advances in existing applications. Given the above, the objective of this article is to provide insights on the gigantic leap in our understanding, modeling, mapping, and monitoring of the Earth that can be made using HNB relative to MBB by focusing on agricultural and vegetation applications. We will address this in four aspects: 1. Comparison between HNB and MBB data; 2. Spectral libraries of agricultural crops; 3. HNB data analysis in general; and 4. HNB analysis using machine learning (ML) and cloud computing.

Photogrammetric Engineering and Remote Sensing.↗

USGS2015

Flood-inundation Maps for the Deerfield River, Franklin County, Massachusetts, from the Confluence with the Cold River Tributary to the Connecticut River

The U.S. Geological Survey developed flood elevations in cooperation with the Federal Emergency Management Agency for a 30-mile reach of the Deerfield River from the confluence of the Cold River tributary to the Connecticut River in the towns of Charlemont, Buckland, Shelburne, Conway, Deerfield, and Greenfield in Franklin County, Massachusetts to assist land owners, and emergency management workers prepare for and recover from floods. Peak flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using current [2015] stage-discharge relations at two U.S. Geological Survey streamgages in the study reach—Deerfield River at Charlemont, MA (01168500) and Deerfield River near West Deerfield, MA (01170000)—and from documented high-water marks from the tropical storm Irene flood, which had between a 1- and 0.2-percent AEP. The hydraulic model was used to compute water-surface profiles for flood stages referenced to the two streamgages. Two sets of flood-inundation map libraries were created from the modeled profiles. The library for the upstream, western portion of the modeled reach is 9.1 miles long, extends from just downstream of the confluence of the Deerfield River with the Cold River to just upstream of the confluence with Clesson Brook, and is calibrated to the Deerfield River at Charlemont, MA streamgage. The library for the downstream, eastern portion of the modeled reach is 8.9 miles long, extends from just downstream of the confluence of the Deerfield River with the South River to just upstream of the confluence with the Green River, and is calibrated to the Deerfield River near West Deerfield streamgage. Stages for mapped profiles of the upstream reach range from 8.7 feet (ft) at the local datum (525.6 ft when converted to the North American Vertical Datum of 1988 [NAVD 88]) to 25.7 ft (542.6 ft at NAVD 88) at the Charlemont streamgage, and stages for mapped profiles of the downstream reach range from 8.5 ft (165.2 ft at NAVD 88) to 29.0 ft (185.7 ft at NAVD 88) at the West Deerfield streamgage. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from 0.5-ft vertical accuracy light detection and ranging (lidar) data to create the two sets of flood-inundation maps. The availability of the flood-inundation maps at http://water.usgs.gov/osw/flood_inundation/, combined with information regarding current (near real-time) stage from the two U.S. Geological Survey streamgages in the study reach, can provide emergency management personnel and residents with information to aid in flood response activities, such as evacuations and road closures, and with postflood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

Massachusetts↗

USGS2005

Coral disease and health workshop: Coral histopathology II, July 12-14, 2005

The health and continued existence of coral reef ecosystems are threatened by an increasing array of environmental and anthropogenic impacts. Coral disease is one of the prominent causes of increased mortality among reefs globally, particularly in the Caribbean. Although over 40 different coral diseases and syndromes have been reported worldwide, only a few etiological agents have been confirmed; most pathogens remain unknown and the dynamics of disease transmission, pathogenicity and mortality are not understood. Causal relationships have been documented for only a few of the coral diseases, while new syndromes continue to emerge. Extensive field observations by coral biologists have provided substantial documentation of a plethora of new pathologies, but our understanding, however, has been limited to descriptions of gross lesions with names reflecting these observations (e.g., black band, white band, dark spot). To determine etiology, we must equip coral diseases scientists with basic biomedical knowledge and specialized training in areas such as histology, cell biology and pathology. Only through combining descriptive science with mechanistic science and employing the synthesis epizootiology provides will we be able to gain insight into causation and become equipped to handle the pending crisis. One of the critical challenges faced by coral disease researchers is to establish a framework to systematically study coral pathologies drawing from the field of diagnostic medicine and pathology and using generally accepted nomenclature. This process began in April 2004, with a workshop titled Coral Disease and Health Workshop: Developing Diagnostic Criteria co-convened by the Coral Disease and Health Consortium (CDHC), a working group organized under the auspices of the U.S. Coral Reef Task Force, and the International Registry for Coral Pathology (IRCP). The workshop was hosted by the U.S. Geological Survey, National Wildlife Health Center (NWHC) in Madison, Wisconsin and was focused on gross morphology and disease signs observed in the field. A resounding recommendation from the histopathologists participating in the workshop was the urgent need to develop diagnostic criteria that are suitable to move from gross observations to morphological diagnoses based on evaluation of microscopic anatomy. As a continuation of building the foundation and framework for coral disease diagnostics, the CDHC convened the Coral Disease and Health Workshop: Coral Histopathology II in Charleston, South Carolina, July 11-14, 2005. The workshop was hosted by the Department of Pathology and Laboratory Medicine at the Medical University of South Carolina, Charleston, SC which provided expertise, facilities and equipment in support of the workshop. All of the histological slides and related photographs used in the discussions were prepared and supplied by the IRCP. This workshop brought together 15 experts in veterinary and medical pathology and coral biology from national and international research institutes and government laboratories. The mission was to devise a standardized approach to examining microscopic anatomy and pathology of corals and a standardized nomenclature to facilitate accurate descriptions of the microscopic morphology of corals and enhance communication among specialists investigating causes of coral death. 2 The participants of this workshop deliberated for 3 days to refine the nomenclature for gross and microscopic anatomy of corals and systematically described microscopic changes associated with selected coral diseases. The findings and recommendations from the deliberations will be submitted to the research community for peer review. The standardized nomenclature and descriptions produced at this workshop will ultimately be made available to the scientific community through a variety of media including the World Wide Web. An exciting highlight of this meeting was provided by Professor Robert Ogilvie (MUSC Department of Cell Biology and Anatomy) when he introduced participants to a new digital technology that is revolutionizing histology and histopathology in the medical field. The Virtual Slide technology creates digital images of histological tissue sections by computer scanning actual slides in high definition and storing the images for retrieval and viewing. Virtual slides now allow any investigator with access to a computer and the web to view, search, annotate and comment on the same tissue sections in real time. Medical and veterinary slide libraries across the country are being converted into virtual slides to enhance biomedical education, research and diagnosis. The coral health and disease researchers at this workshop deem virtual slides as a significant way to increase capabilities in coral histology and a means for pathology consultations on coral disease cases on a global scale.

NOAA Technical Memorandum↗

USGS1995

Earth science photographs from the U.S. Geological Survey Library

This CD-ROM set contains 1,500 scanned photographs from the U.S. Geological Survey Library for use as a photographic glossary of elementary geologic terms. Scholars are encouraged to copy these public domain images into their reports or databases to enhance their presentations. High-quality prints and (or) slides are available upon request from the library. This CD-ROM was produced in accordance with the ISO 9660 standard; however, it is intended for use on DOS-based computer systems only.

Data Series↗

USGS2011

Programming PHREEQC calculations with C++ and Python a comparative study

The new IPhreeqc module provides an application programming interface (API) to facilitate coupling of other codes with the U.S. Geological Survey geochemical model PHREEQC. Traditionally, loose coupling of PHREEQC with other applications required methods to create PHREEQC input files, start external PHREEQC processes, and process PHREEQC output files. IPhreeqc eliminates most of this effort by providing direct access to PHREEQC capabilities through a component object model (COM), a library, or a dynamically linked library (DLL). Input and calculations can be specified through internally programmed strings, and all data exchange between an application and the module can occur in computer memory. This study compares simulations programmed in C++ and Python that are tightly coupled with IPhreeqc modules to the traditional simulations that are loosely coupled to PHREEQC. The study compares performance, quantifies effort, and evaluates lines of code and the complexity of the design. The comparisons show that IPhreeqc offers a more powerful and simpler approach for incorporating PHREEQC calculations into transport models and other applications that need to perform PHREEQC calculations. The IPhreeqc module facilitates the design of coupled applications and significantly reduces run times. Even a moderate knowledge of one of the supported programming languages allows more efficient use of PHREEQC than the traditional loosely coupled approach.

Conference Paper↗

USGS1983

Users guide for the Water Resources Division bibliographic retrieval and report generation system

The WRDBIB Retrieval and Report-generation system has been developed by applying Multitrieve (CSD 1980, Reston) software to bibliographic data files. The WRDBIB data base includes some 9 ,000 records containing bibliographic citations and descriptors of WRD reports released for publication during 1968-1982. The data base is resident in the Reston Multics computer and may be accessed by registered Multics users in the field. The WRDBIB Users Guide provides detailed procedures on how to run retrieval programs using WRDBIB library files, and how to prepare custom bibliographic reports and author indexes. Users may search the WRDBIB data base on the following variable fields as described in the Data Dictionary: Authors, organizational source, title, citation, publication year, descriptors, and the WRSIC (accession) number. The Users Guide provides ample examples of program runs illustrating various retrieval and report generation aspects. Appendices include Multics access and file manipulation procedures; a ' Glossary of Selected Terms'; and a complete ' Retrieval Session ' with step-by-step outlines. (USGS)

Open-File Report↗

USGS2015

Spatially explicit spectral analysis of point clouds and geospatial data

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python , it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

Computers & Geosciences↗

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↗

USGS2012

Flood inundation map library, Fort Kent, Maine

Severe flooding occurred in northern Maine from April 28 to May 1, 2008, and damage was extensive in the town of Fort Kent (Lombard, 2010). Aroostook County was declared a Federal disaster area on May 9, 2008. The extent of flooding on both the Fish and St. John Rivers during this event showed that the current Federal Emergency Management Agency (FEMA) Flood Insurance Study (FIS) and Flood Insurance Rate Map (FIRM) (Federal Emergency Management Agency, 1979) were out of date. The U.S. Geological Survey (USGS) conducted a study to develop a flood inundation map library showing the areas and depths for a range of flood stages from bankfull to the flood of record for Fort Kent to complement an updated FIS (Federal Emergency Management Agency, in press). Hydrologic analyses that support the maps include computer models with and without the levee and with various depths of backwater on the Fish River. This fact sheet describes the methods used to develop the maps and describes how the maps can be accessed.

Maine↗