An installation guide to the PC-based time-series data-management and plotting program BOB
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The Hydrologic Toolbox is a Windows-based desktop software program that provides a graphical and mapping interface for analysis of hydrologic time-series data with a set of widely used and standardized computational methods. The software combines the analytical and statistical functionality provided in the U.S. Geological Survey Groundwater and Surface-Water Toolboxes and provides several enhancements to these programs. The main analytical methods are the computation of hydrologic-frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10); the computation of design flows, including biologically based flows; the computation of flow-duration curves and duration hydrographs; eight computer-programming methods for hydrograph separation of a streamflow time series, including the Base-Flow Index (BFI), HYSEP, PART, and SWAT Bflow methods and Eckhardt’s two-parameter digital-filtering method; and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater-recharge values from streamflow data. Several of the statistical methods provided in the Hydrologic Toolbox are used primarily for computation of critical low-flow statistics. The Hydrologic Toolbox also facilitates retrieval of streamflow and groundwater-level time-series data from the U.S. Geological Survey National Water Information System and outputs text reports that describe their analyses. The Hydrologic Toolbox was developed by use of the DotSpatial geographic information system (GIS) programming library, which is part of the MapWindow project. DotSpatial is a nonproprietary, open-source program written for the .NET framework that includes a spatial data viewer and GIS capabilities. Advantages of the DotSpatial system include its pure .NET implementation for both the user interface and the GIS mapping engine, and thus the DotSpatial system simplifies software deployment and installation. In addition to combining the functionality of the separate Groundwater and Surface-Water Toolboxes, the Hydrologic Toolbox also organizes the functionality by theme (Groundwater Tools, Surface-Water Tools, and general Time-Series Tools). This report provides a description of how to build a Hydrologic Toolbox project and to download and manage hydrologic time-series data. It includes an overview of the analytical and statistical capabilities of the Hydrologic Toolbox and highlights the primary differences between the Hydrologic Toolbox and the Groundwater and Surface-Water Toolboxes. The report supplements information available in an extensive online Help manual and is intended to provide a set of instructions that will allow users to quickly develop skills to use the mapping, data-retrieval, and computational tools of the program.
The Geochemical Geodatabase of Sedimentary Strata (Coal, Coal-adjacent Rocks, Tuffaceous Oil Shale, Phosphate-rich Rocks) and Produced Water in the Uinta Region, Utah and Colorado, consists of compiled datasets acquired as part of the Carbon Ore, Rare Earth, and Critical Mineral (CORE-CM) Uinta Region assessment funded by the U.S. Department of Energy (DEFE0032046, 2021–2024; Birgenheier et al., 2024). The CORE-CM assessment focused on providing comprehensive geological and geochemical characterization of current and prospective sedimentary-hosted resources including coal, oil shale, phosphatic limestone, and produced water from oil and gas targets present in eastern Utah and northwestern Colorado (Figure 1). This Data Series includes a geodatabase that consists of analytical geochemical data collected September 2021 through December 2024 via portable X-ray fluorescence (pXRF), and laboratory measured analyses produced by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma optical emission spectroscopy (ICP-OES). The coal-related geochemical data are derived primarily from the Cretaceous Blackhawk Formation and Ferron Sandstone of Utah, and the Mesaverde Group of Colorado. Additional non-coal resources assessed include oil shale-bearing strata of the Eocene upper Green River Formation (Utah and Colorado), phosphate-rich limestone of the Permian Park City Formation (Utah) and produced water from oil and gas-bearing strata of the Eocene Green River and Wasatch Formations (Uinta Basin) and the Pennsylvanian Paradox Formation (Paradox Basin) (Table 1). The CORE-CM assessment included a wide range of lithologies present in the coal, oil shale, and phosphate geologic resource systems whether or not the specific lithology has current economic value. Geochemical analyses of produced water from oil and gas wells focused on current and emerging hydrocarbon targets in the central Uinta Basin and northern Paradox Basin. A total of 13,092 geochemical analyses from these geologic systems is provided in the included geodatabase. A series of coal quality data (e.g., composition and maceral analyses) is also included in the database and was digitized from archived coal samples from the Utah Geological Survey (Appendix A).
Newberry Volcano in central Oregon is a 3,100-square-kilometer (1,200-square-mile) shield-shaped composite volcano, occupying a location east of the main north-south trend of the High Cascades volcanoes and forming a transition between the High Lava Plains subprovince of the Basin and Range Province to the east and the Cascade Range to the west. Magnetic, gravity, and radiometric data have been gathered and assessed for the region around the volcano. These data have widely varying quality and resolution, even within a given dataset, and these limitations are evaluated and described in this release. Publicly available gravity data in general are too sparse to permit detailed modeling except along a few roads with high-density coverage. Likewise, magnetic data are also unsuitable for all but very local modeling, primarily because available data consist of a patchwork of datasets with widely varying line-spacing. Gravity data show only the broadest correlation with mapped geology, whereas magnetic data show moderate correlation with features only in the vicinity of Newberry Caldera. At large scales, magnetic data correlate poorly with both geologic mapping and gravity data. These poor correlations are largely due to the different sensing depths of the two potential fields methods, which respond to physical properties deeper than the surficial geology. Magnetic data derive from rocks no deeper than the Curie-point isotherm depth (10 to 15 kilometers, km, maximum), whereas gravity data reflect density-contrasts to 100 to 150 km depths. Radiometric data from the National Uranium Resource Evaluation (NURE) surveys of the 1980s have perhaps the coarsest line-spacing of all (as much as 10 km between lines) and are extremely “noisy” for several reasons inherent to this kind of data. Despite its shallow-sensing character, only a few larger anomalies in the NURE data correlate well with geologic mapping. The purpose of this data series release is to collect and place the available geophysical data in the hands of other investigators in a readily comprehensible form. All data-compilation, splicing, filtering, and overlay-map displays were accomplished with the commercial Geosoft™ system, Advanced Option. Images are provided in both JPG and PDF formats.
This data report presents oceanographic observations made in Massachusetts Bay (fig. 1) in August 1998 as part of the Massachusetts Bay Internal Wave Experiment (MBIWE98). MBIWE98 was carried out to characterize large-amplitude internal waves in Massachusetts Bay and to investigate the possible resuspension and transport of bottom sediments caused by these waves. This data report presents a description of the field program and instrumentation, an overview of the data through summary plots and statistics, and the time-series data in NetCDF format. The objective of this report is to make the data available in digital form and to provide summary plots and statistics to facilitate browsing of the data set. The existence of large-amplitude internal waves in Massachusetts Bay was first described by Halpern (1971). In summer when the water is stratified, packets of waves propagate westward into the bay on the flood (westward flowing) tide at about 0.5 m/s. The internal waves are observed in packets of 5-10 waves, have periods of 5-10 minutes and wavelengths of 200-400 m, and cause downward excursions of the thermocline of as much as 30 m. The waves are generated by interaction of the barotropic tide with Stellwagen Bank (Haury and others (1979). Several papers present analyses and interpretations of the data collected during the MBIWE98. Grosenbaugh and others (2002) report on the results of the horizontal array, Scotti and others (2005) describe a strategy for processing observations made by Acoustic Doppler Current Profilers (ADCPs) in the presence of short-wavelength internal waves, Butman and others (in press) describe the effect of these waves on sediment transport, and Scotti and others (in press) describe the energetics of the internal waves.
As part of the Louisiana Coastal Protection and Restoration Authority (CPRA) Barrier Island Comprehensive Monitoring Program, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a single-beam bathymetry survey around the Chandeleur Islands, Louisiana, in June 2015. The goal of the program is to provide long-term data on Louisiana’s barrier islands and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in this report, along with (1) USGS bathymetry data collected in 2013 as a part of the Barrier Island Evolution Research project covering the northern Chandeleur Islands, and (2) data collected in 2014 in collaboration with the Louisiana CPRA Barrier Island Comprehensive Monitoring Program around Breton Island, will be used to assess bathymetric change since 2006‒2007 as well as serve as a bathymetric control in supporting modeling of future changes in response to restoration and storm impacts. The survey area encompasses approximately 435 square kilometers of nearshore and back-barrier environments around Hewes Point, the Chandeleur Islands, and Curlew and Grand Gosier Shoals. This Data Series serves as an archive of processed single-beam bathymetry data, collected in the nearshore of the Chandeleur Islands, Louisiana, from June 17‒24, 2015, during USGS Field Activity Number 2015-317-FA. Geographic information system data products include a 200-meter-cell-size interpolated bathymetry grid, trackline maps, and xyz point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.
As part of the Barrier Island Comprehensive Monitoring Program (BICM), scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted a nearshore single-beam bathymetry survey along the south-central coast of Louisiana, from Raccoon Point to Point Au Fer Island, in July 2015. The goal of the BICM program is to provide long-term data on Louisiana’s coastline and use this data to plan, design, evaluate, and maintain current and future barrier island restoration projects. The data described in this report will provide baseline bathymetric information for future research investigating island evolution, sediment transport, and recent and long-term geomorphic change, and will support modeling of future changes in response to restoration and storm impacts. The survey area encompasses more than 300 square kilometers of nearshore environment from Raccoon Point to Point Au Fer Island. This data series serves as an archive of processed single-beam bathymetry data, collected from July 22–29, 2015, under USGS Field Activity Number 2015-320-FA. Geographic information system data products include a 200-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata.
A key requirement for implementing ecosystem-based management is to obtain timely information on significant fluctuations in the ecosystem (Botsford et al. 1997). However, obtaining all necessary information about physical and biological changes at appropriate temporal and spatial scales is a daunting task. Intuitively, one might assume that physical data are more important for the interpretation of ecosystem changes than biological data, but analyses of time series data suggest otherwise: physical data are more erratic and often confusing over the short term compared to biological data, which tend to fluctuate less on annual time scales (Hare & Mantua 2000). Even so, biological time-series may also be confusing when coexisting marine species respond differently to ecosystem variability. For example, while warming temperatures in the Gulf of Alaska following the 1976 to 1977 regime shift favored an increase in gadoids and flatfish, a variety of forage fish and pandalid shrimp species virtually disappeared (Anderson & Piatt 1999). Zooplankton communities in the Gulf of Alaska also demonstrated similar patterns of response (Francis et al. 1998). At the basin scale, favorable conditions for salmon in Alaska following the regime shift were matched inversely by poor conditions in the California Current (Francis et al. 1998). In marine birds, subtropical species increased, while subarctic ones decreased during a warming phase in the southern California Bight. Clearly, no single index can tell the whole story accurately. Multi-species, multi-region, and multi-trophic level approaches are needed to quantify fluctuations in marine ecosystem processes and in the distribution and abundance of its inhabitants, to determine critical parameter thresholds and to use this information in management and marine conservation.
Mapping croplands, including fallow areas, are an important measure to determine the quantity of food that is produced, where they are produced, and when they are produced (e.g. seasonality). Furthermore, croplands are known as water guzzlers by consuming anywhere between 70% and 90% of all human water use globally. Given these facts and the increase in global population to nearly 10 billion by the year 2050, the need for routine, rapid, and automated cropland mapping year-after-year and/or season-after-season is of great importance. The overarching goal of this study was to generate standard and routine cropland products, year-after-year, over very large areas through the use of two novel methods: (a) quantitative spectral matching techniques (QSMTs) applied at continental level and (b) rule-based Automated Cropland Classification Algorithm (ACCA) with the ability to hind-cast, now-cast, and future-cast. Australia was chosen for the study given its extensive croplands, rich history of agriculture, and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing. This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m normalized difference vegetation index 16-day composite time-series data for 16 years: 2000 through 2015. The products consisted of: (1) cropland extent/areas versus cropland fallow areas, (2) irrigated versus rainfed croplands, and (3) cropping intensities: single, double, and continuous cropping. An accurate reference cropland product (RCP) for the year 2014 (RCP2014) produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015. A comparison between the ACCA-derived cropland products (ACPs) for the year 2014 (ACP2014) versus RCP2014 provided an overall agreement of 89.4% (kappa = 0.814) with six classes: (a) producer’s accuracies varying between 72% and 90% and (b) user’s accuracies varying between 79% and 90%. ACPs for the individual years 2000–2013 and 2015 (ACP2000–ACP2013, ACP2015) showed very strong similarities with several other studies. The extent and vigor of the Australian croplands versus cropland fallows were accurately captured by the ACCA algorithm for the years 2000–2015, thus highlighting the value of the study in food security analysis. The ACCA algorithm and the cropland products are released through http://croplands.org/app/map and http://geography.wr.usgs.gov/science/croplands/algorithms/australia_250m.html
From April 13 to 20, 2013, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) conducted geophysical and sediment sampling surveys on Dauphin Island, Alabama, as part of Field Activity 13BIM01 . The objectives of the study were to quantify inorganic and organic accretion rates in back-barrier and mainland marsh and estuarine environments. Various field and laboratory methods were used to achieve these objectives, including subsurface imaging using Ground Penetrating Radar (GPR), sediment sampling, lithologic and microfossil analyses, and geochronology techniques to produce barrier island stratigraphic cross sections to help interpret the recent (last 2000 years) geologic evolution of the island. This data series report is an archive of GPR and associated Global Positioning System (GPS) data collected in April 2013 from Dauphin Island and adjacent barrier-island environments. In addition to GPR data, marsh core and vibracore data were also collected collected but are not reported (or included) in the current report. Data products, including elevation-corrected subsurface profile images of the processed GPR data, unprocessed digital GPR trace data, post-processed GPS data, Geographic Information System (GIS) files and accompanying Federal Geographic Data Committee (FGDC) metadata, can be downloaded from the Data Downloads page.
As part of the Barrier Island Monitoring Project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted nearshore geophysical surveys off Breton and Gosier Islands, Louisiana, in July and August of 2014. To assist the United States Fish and Wildlife Service (USFWS) with restoration planning efforts, the USGS was tasked with answering fundamental questions about the physical environment of the southern Chandeleur Islands, including the geology, morphology, and oceanography. Baseline data needed to answer these questions were either insufficient or missing. The USGS conducted a comprehensive geologic investigation in the summer of 2014, collecting geophysical and sedimentological data. Breton Island, located at the southern end of the Chandeleur Island chain in southeastern Louisiana, was recognized as a natural, globally significant nesting sanctuary for several bird species and was established as the Breton National Wildlife Refuge (NWR) in 1904. The areal extent of Breton Island has diminished 90 percent since 1920. Land loss is attributed to ongoing relative sea-level rise, diminished sediment supply, and storm impacts. The bird population on Breton Island has also declined over the years, most notably after Hurricane George in 1998 and after Hurricane Katrina in 2015; the latter completely submerged the island. Despite decreasing habitable acreage, migratory seabirds continue to return and nest on Breton Island. To prevent the island from being submerged in the future, and to protect, stabilize, and provide more nesting and foraging areas for the bird population, the USFWS proposed a restoration effort to rebuild Breton Island to its pre-Katrina footprint. This data series serves as an archive of processed interferometric swath and single-beam bathymetry data, and side-scan sonar data, collected in the nearshore of Breton and Gosier Islands, NWR, Louisiana. The data were collected during two USGS cruises (USGS Field Activity Numbers 2014-314-FA and 2014-317-FA) in July and August 2014. Geographic information system data products include a 100-meter-cell-size interpolated bathymetry grid, trackline maps, and point data files. Additional files include error analysis maps, Field Activity Collection System logs, and formal Federal Geographic Data Committee metadata. NOTE: These data are scientific in nature and are not to be used for navigation. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Remotely sensed, geographically referenced elevation measurements of the sea floor, acquired by boat- and aircraft-based survey systems, were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, for the area at Cape Canaveral. The work was conducted as part of a study to describe an updated bathymetric dataset collected in 2014 and compare it to previous data sets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems. Cape Canaveral Coastal System (CCCS) is a prominent feature along the Southeast U.S. coastline and is the only large cape south of Cape Fear, North Carolina. Most of the CCCS lies within the Merritt Island National Wildlife Refuge and included within its boundaries are the Cape Canaveral Air Force Station (CCAFS), NASA’s Kennedy Space Center (KSC), and a large portion of Canaveral National Seashore. The actual promontory of the modern cape falls within the jurisdictional boundaries of the CCAFS. Hydrographic survey data were collected August 18-20, 2014 ( USGS Field Activity Number 2014-324-FA ). The study covered a 20 kilometer (km) section of shoreline extending from Port Canaveral, Fla., to the northern end of the KSC property, and from the shoreline to about 2.5 km offshore. Data were acquired using both sound navigation and ranging (sonar) and light detection and ranging (lidar) systems. Two jet skis and a 17-foot (ft) outboard motor boat equipped with the USGS SANDS (System for Accurate Nearshore Depth Surveying) hydrographic system collected precision sonar data. The USGS airborne EAARL-B mapping system flown in a twin engine airplane was used to collect lidar data. The missions were synchronized so that there was temporal and spatial overlap between the sonar and lidar operations. Additional data were collected to evaluate water clarity to verify the ability of lidar to receive bathymetric returns. Both systems used differential Global Positioning System GPS and utilized the National Oceanic and Atmospheric Administration/National Geodetic Survey (NOAA/NGS) Continuously Operating Reference Station (CORS) station located at CCAFS was used as the reference station. This data series serves as an archive of processed single-beam sonar and lidar bathymetry data. Graphical Information System (GIS) data products include XYZ point bathymetry data files, a color coded bathymetry map, and interpolated bathymetry grid surface. Additional information includes an error analysis and formal Federal Geographic Data Committee (FGDC) metadata. For more information about similar projects, please visit the Barrier Island Evolution Web site.
This publication consists of two DVD-ROMs, both of which are presented here. This report describes data collected during the Spring 2001 Grays Harbor Sediment Transport Experiment, and provides additional information needed to interpret the data. Two DVDs accompany this report; both contain documentation in html format that assist the user in navigating through the data. DVD-ROM-1 contains a digital version of this report in .pdf format, raw Aquatec acoustic backscatter (ABS) data in .zip format, Sonar data files in .avi format, and coastal processes and morphology data in ASCII format. ASCII data files are provided in .zip format; bundled coastal processes ASCII files are separated by deployment and instrument; bundled morphology ASCII files are separated into monthly data collection efforts containing the beach profiles collected (or extracted from the surface map) at that time; weekly surface maps are also bundled together. DVD-ROM-2 contains a digital version of this report in .pdf format, the binary data files collected by the SonTek instrumentation, calibration files for the pressure sensors, and Matlab m-files for loading the ABS data into Matlab and cleaning-up the optical backscatter (OBS) burst time-series data.
In synoptic surveys of surface-water quality across the United States, a large group of organic chemicals associated with agricultural, household, and industrial waste have been detected. These chemicals are referred to collectively as chemicals of emerging concern (CECs) and include prescription drugs and antibiotics, over-the-counter medications, reproductive hormones, personal-care products, detergent metabolites, and flame retardants. The U.S. Geological Survey (USGS) collaborated with the U.S. Fish and Wildlife Service and the U.S. Environmental Protection Agency on a study to identify the presence of CECs in water and bottom-sediment samples collected during 2012 at 66 sites throughout the Great Lakes Basin. The 2012 effort is part of a long-term study that was initiated in 2010. The purposes of this report are to document the collection and analytical methods, provide the quality-assurance data and analyses, and provide the water and bottom-sediment data for this study of CECs in the Great Lakes Basin for 2012. A previous report documents data collected during 2010 and 2011. The methods used for chemical analyses were identical between the 2010–11 and 2012 studies, with the exception that a method to determine nontarget chemicals was used during 2010–11. The data from this study are published as a USGS Data Series Report to ensure adequate documentation of the original methods and provide a citable source for study data. This report contains no interpretations of the study data. The chemical data are as reported by the laboratory and have not been censored or adjusted unless otherwise noted. Field measurements were recorded and samples were collected in April and May and in September 2012, by U.S. Geological Survey, U.S. Fish and Wildlife Service, and U.S. Environmental Protection Agency personnel. Study sites included tributaries to the Great Lakes located near Duluth, Minnesota; King, Wisconsin; Green Bay, Wis.; Detroit, Michigan; Monroe, Mich.; Toledo, Ohio, and Rochester, New York. Water and bottom-sediment samples were analyzed at the USGS National Water Quality Laboratory in Denver, Colorado, for a broad suite of CECs. During this 2012 study, 140 environmental and 8 field duplicate samples of surface water and wastewater effluent, 1 field blank water sample, and 5 field spike water samples were collected or prepared. Water samples were analyzed at the USGS National Water Quality Laboratory using laboratory schedule 4433 for wastewater indicators, research method 8244 for pharmaceuticals, and laboratory schedule 4434 for steroid hormones, sterols, and bisphenol A. For wastewater indicators in unfiltered water, 61 of the 68 chemicals analyzed using laboratory schedule 4433 had detectable concentrations ranging from 0.002 to 64.4 micrograms per liter. Thirty-eight of the 48 chemicals analyzed using research method 8244 for pharmaceuticals in unfiltered water had detectable concentrations ranging from 0.002 to 3.32 micrograms per liter. Twelve of the 20 chemicals analyzed using laboratory schedule 4434 for steroid hormones, sterols, and bisphenol A in unfiltered water had detectable concentrations ranging from 0.43 to 120,000 nanograms per liter. During this study, 53 environmental samples, 4 field duplicate samples, and 8 field spike samples of bottom sediment and laboratory matrix-spike samples were analyzed for a wide variety of CECs at the USGS National Water Quality Laboratory using laboratory schedule 5433 for wastewater indicators; research method 6434 for steroid hormones, sterols, and bisphenol A; and research method 9008 for human-use pharmaceuticals and antidepressants. Forty of the 57 chemicals analyzed using laboratory schedule 5433 had detectable concentrations ranging from 1 to 49,000 micrograms per kilogram. Fourteen of the 20 chemicals analyzed using research method 6434 had detectable concentrations ranging from 0.04 to 24,940 nanograms per gram. Ten of the 20 chemicals analyzed using research method 9008 had detectable concentrations ranging from 0.59 to 197.5 micrograms per kilogram. Five of the 11 chemicals analyzed using research method 9008 had detectable concentrations ranging from 1.16 to 25.0 micrograms per kilogram.
Selected micrometeorological and soil-moisture data were collected at the Amargosa Desert Research Site adjacent to a low-level radio-active waste and hazardous chemical waste facility near Beatty, Nevada, 2001-05. Evapotranspiration data were collected from February 2002 through the end of December 2005. Data were col-lected in support of ongoing research to improve the understanding of hydrologic and contaminant-transport processes in arid environments. Micrometeorological data include solar radiation, net radiation, air temperature, relative humidity, saturated and ambient vapor pressure, wind speed and direction, barometric pressure, precipitation, near-surface soil temperature, soil-heat flux and soil-water content. All micrometeorological data were collected using a 10-second sampling interval by data loggers that output daily and hourly mean values. Daily maximum and minimum values are based on hourly mean values. Precipitation data output includes daily and hourly totals. Selected soil-moisture profiles at depth include periodic measurements of soil volumetric water-content measurements at nine neutron-probe access tubes to depths ranging from 5.25 to 29.25 meters. Evapotranspiration data include measurement of daily evapotranspiration and 15-minute fluxes of the four principal energy budget components of latent-heat flux, sensible-heat flux, soil-heat flux, and net radiation. Other data collected and used in equations to determine evapotranspiration include temperature and water content of soil, temperature and vapor pressure of air, and covariance values. Evapotranspiration and flux estimates during 15-minute intervals were calculated at a 0.1-second execution interval using the eddy covariance method. Data files included in this report contain the complete micrometeorological, soil-moisture, and evapotranspiration field data sets. These data files are presented in tabular Excel spreadsheet format. This report highlights selected data contained in the computer generated data files using figures, tables, and brief discussions. Instrumentation used for data collection also is described. Water-content profiles are shown to demonstrate variability of water content with depth. Time-series data are plotted to illustrate temporal variations in micrometeorological, soil-water content, and evapotranspiration data.
Across the country, public land managers make decisions each year that influence landscapes and ecosystems within their jurisdictions. Many of these decisions involve vegetation manipulations, which often are referred to as land treatments. These treatments include removal or alteration of plant biomass, seeding of burned areas, application of herbicides, and other activities. Data documenting these land treatments usually are stored at local management offices in various formats. Therefore, anyone interested in the types and effects of land treatments across multiple jurisdictions must first assemble the information, which can be difficult if data discovery and organization involve multiple local offices. A centralized system for storing and accessing the data helps inform land managers when making policy and management considerations and assists scientists in developing sampling designs and studies. The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey (USGS) as a comprehensive database incorporating tabular data, documentation, photographs, and spatial data about land treatments in a single system. It was developed over a period of several years and refined based on feedback from partner agencies and stakeholders. Currently, Bureau of Land Management (BLM) land treatment data are being entered by USGS personnel as part of a memorandum of understanding between the USGS and BLM. The LTDL has a website maintained by the USGS Forest and Rangeland Ecosystem Science Center where LTDL data can be viewed https://www.usgs.gov/apps/ltdl . The resources and information provided in this data series allow other agencies, organizations, and individuals to download an empty, stand-alone LTDL database to individual or networked computers. Data entered in these databases may be submitted to the USGS for possible inclusion in the online LTDL. Multiple computer programs are used to accomplish the objective of the LTDL. The support of an information-technology specialist or professionals familiar with Microsoft Access™, ESRI’s ArcGIS™, Python, Adobe Acrobat Professional™, and computer settings is essential when installing and operating the LTDL. After the program is operational, a critical element for successful data entry is an understanding of the difference between database tables and forms, and how to edit data in both formats. Complete instructions accompany the program, and they should be followed carefully to ensure the setup and operation of the database goes smoothly.