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USGS2019

A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

Geoscientific Model Development↗

USGS2021

Flood-inundation maps for the Blue River near Red Bridge Road, Kansas City, Missouri, 2019

Digital flood-inundation maps for a 4.6-mile reach of the Blue River near Red Bridge Road in Kansas City, Missouri, were created by the U.S. Geological Survey (USGS), in cooperation with the City of Kansas City, Missouri. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 06893195, Blue River at Red Bridge Road, Kansas City, Mo. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the Johnson County, Kansas, StormWatch Automated Local Elevation in Real Time Flood Warning System at https://www.stormwatch.com . Flood profiles were computed for the Blue River reach by means of a one-dimensional model for simulating water-surface profiles with steady-state flow computations. The model was calibrated by using the current stage-streamflow relations at the upstream USGS streamgage 06893150, Blue River at Blue Ridge Boulevard Extension, Kansas City, Mo., and the downstream streamgage 06893500, Blue River at Kansas City, Mo. The hydraulic model was then used to compute 37 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 11 ft, or near bankfull, to 47 ft at the reference streamgage 06893195. The upper stage for the map library exceeds the stage corresponding to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood) in the model reach. The simulated water-surface profiles were then combined with a geographic information system digital elevation model with a maximum 10-centimeter vertical root mean square error and 4.0-ft horizontal resolution to delineate the area flooded at each water level. The availability of these maps, along with real-time internet information regarding current stage from the USGS streamgage, will help guide emergency management personnel and residents in flood mitigation, preparedness and planning, flood-response activities such as evacuations and road closures, and any postflood recovery efforts.

Kansas, Missouri↗

USGS2022

U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data

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.

Techniques and Methods↗

USGS1996

The Modular Modeling System (MMS): User's Manual

The Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide the research and operational framework needed to support development, testing, and evaluation of physical-process algorithms and to facilitate integration of user-selected sets of algorithms into operational physical-process models. MMS uses a module library that contains modules for simulating a variety of water, energy, and biogeochemical processes. A model is created by selectively coupling the most appropriate modules from the library to create a 'suitable' model for the desired application. Where existing modules do not provide appropriate process algorithms, new modules can be developed. The MMS user's manual provides installation instructions and a detailed discussion of system concepts, module development, and model development and application using the MMS graphical user interface.

Open-File Report↗

USGS2025

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences↗

USGS2008

Information science and technology developments within the National Biological Information Infrastructure

Whether your vantage point is that of an office window or a national park, your view undoubtedly encompasses a rich diversity of life forms, all carefully studied or managed by some scientist, resource manager, or planner. A few simple calculations-the number of species, their interrelationships, and the many researchers studying them-and you can easily see the tremendous challenges that the resulting biological data presents to the information and computer science communities. Biological information varies in format and content: it may pertain to a particular species or an entire ecosystem; it can contain land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents, the National Biological Information Infrastructure (NBII) ( http://www.nbii.gov ) was established in 1993 on the recommendation of the National Research Council (National Research Council 1993). The NBII is designed to address these issues on a national scale, and through international partnerships. This paper discusses current information and computer science efforts within the National Biological Information Infrastructure Program, and future computer science research endeavors that are needed to address the ever-growing issues related to our nation's biological concerns.

Science and Technology Libraries↗

USGS2006

USGS Information Technology Strategic Plan: Fiscal Years 2007-2011

Introduction: The acquisition, management, communication, and long-term stewardship of natural science data, information, and knowledge are fundamental mission responsibilities of the U.S. Geological Survey (USGS). USGS scientists collect, maintain, and exchange raw scientific data and interpret and analyze it to produce a wide variety of science-based products. Managers throughout the Bureau access, summarize, and analyze administrative or business-related information to budget, plan, evaluate, and report on programs and projects. Information professionals manage the extensive and growing stores of irreplaceable scientific information and knowledge in numerous databases, archives, libraries, and other digital and nondigital holdings. Information is the primary currency of the USGS, and it flows to scientists, managers, partners, and a wide base of customers, including local, State, and Federal agencies, private sector organizations, and individual citizens. Supporting these information flows is an infrastructure of computer systems, telecommunications equipment, software applications, digital and nondigital data stores and archives, technical expertise, and information policies and procedures. This infrastructure has evolved over many years and consists of tools and technologies acquired or built to address the specific requirements of particular projects or programs. Developed independently, the elements of this infrastructure were typically not designed to facilitate the exchange of data and information across programs or disciplines, to allow for sharing of information resources or expertise, or to be combined into a Bureauwide and broader information infrastructure. The challenge to the Bureau is to wisely and effectively use its information resources to create a more Integrated Information Environment that can reduce costs, enhance the discovery and delivery of scientific products, and improve support for science. This Information Technology Strategic Plan for the USGS outlines key information technology (IT) strategic goals and objectives that will support the Bureau's science mission, while also aligning with the Department of the Interior (DOI) IT Strategic Plan and the DOI Government Performance and Results Act (GPRA) Strategic Plan.

Circular↗

USGS2023

Flood-inundation maps for Fourmile Creek at Silver Grove, Kentucky

Digital flood-inundation maps for a 3.4-mile reach of Fourmile Creek at Silver Grove, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Silver Grove and the U.S. Army Corps of Engineers Louisville District. Because the City of Silver Grove is subject to flooding from Fourmile Creek and the Ohio River (backwater flooding up Fourmile Creek), a set of flood-inundation maps was created, including maps for each flooding source considered independently and for possible scenarios involving flooding from both sources combined. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamgage) at the USGS streamgage on Fourmile Creek at Grays Crossing at Silver Grove, Ky. (station number 03238785), and the USGS streamgage on Fourmile Creek at Highway 8 at Silver Grove, Ky. (station number 03238798). Near-real-time stages at these streamgages can be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/ . The USGS streamgage on the Ohio River at Cincinnati, Ohio (station number 03255000), is also important in this study because the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS; https://water.weather.gov/ahps/ ) forecasts flood hydrographs for this site (NWS AHPS site CCNO1). The peak-stage information forecast by the NWS AHPS can be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. Flood profiles were computed for the Fourmile Creek study reach by means of a one-dimensional, step-backwater hydraulic model (HEC-RAS) developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating number 1.1) at USGS streamgage 03238785, Fourmile Creek at Grays Crossing at Silver Grove, Ky. The model was then used to compute water-surface profiles for 83 combinations of flood stages on the Ohio River and Fourmile Creek ranging from approximately base flow to greater than a 2-percent annual exceedance probability flood in the model reach. An additional 50 water-surface profiles were computed for backwater-only flooding (from the Ohio River) for flood elevations (referenced to the North American Vertical Datum of 1988 [NAVD 88]) at 1-foot intervals referenced to USGS streamgage 03238798, Fourmile Creek at Highway 8 at Silver Grove, Ky.; these elevations ranged from approximately normal pool (460 ft, NAVD 88) to approximately a 0.2-percent annual exceedance probability flood (509 ft, NAVD 88) on the Ohio River. The computed water-surface profile information was then combined with a digital elevation model derived from light detection and ranging (lidar) data to delineate the approximate flooded areas. The digital flood-inundation maps are available through the USGS Flood Inundation Mapper application ( https://fim.wim.usgs.gov/fim/ ), which presents map libraries and provides detailed information on flood extent and depths for selected sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the USGS streamgages on Fourmile Creek at Silver Grove, Ky., and forecasted stream stages from the NWS AHPS, are intended to provide information that can help inform the public about potential flooding and provide emergency management personnel with a tool to efficiently manage emergency flood operations, such as evacuations and road closures, and assist in postflood recovery efforts.

Kentucky↗

USGS2019

Flood-inundation maps for a 23-mile reach of the Medina River at Bandera, Texas, 2018

In 2018, the U.S. Geological Survey (USGS), in cooperation with the Bandera County River Authority and Groundwater District and the Texas Water Development Board, studied floods through the period of record to create a library of flood-inundation maps for the Medina River at Bandera, Texas. Digital flood-inundation maps for a 23-mile reach of the Medina River at and near Bandera, from the confluence with Winans Creek to English Crossing Road, were developed. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to a range of different gage heights (gage height is commonly referred to as “stage,” or the water-surface elevation at a streamflow-gaging station) at USGS streamflow-gaging station 08178880 Medina River at Bandera, Tex. (hereinafter referred to as the “Bandera station”). Water-surface profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The stage-discharge (streamflow) relation effective in 2018 was used to calibrate the model, and stages from four recent flood events were used to independently validate the model. The calibrated hydraulic model was then used to compute 29 water-surface profiles for stages at 1-foot (ft) increments referenced to the station datum and ranging from 10 ft (near bankfull) to 38 ft, which exceeds the major flood stage of the National Weather Service Advanced Hydrologic Prediction Service of 24 ft. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.4-ft vertical accuracy and 1.6-ft horizontal resolution) to delineate the area flooded for stages ranging from 10 to 38 ft. The digital flood-inundation maps are delivered through the USGS Flood Inundation Mapper application that presents map libraries and provides detailed information on flood-inundation extents and stages for modeled sites. The flood-inundation maps developed in this study, in conjunction with the real-time stage data from the Bandera station, are intended to help guide the public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post-flood recovery efforts.

Scientific Investigations Report↗

USGS2018

Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine

As the global population increases, we face increasing demand for food and nutrition. Remote sensing can help monitor food availability to assess global food security rapidly and accurately enough to inform decision-making. However, advances in remote sensing technology are still often limited to multispectral broadband sensors. Although these sensors have many applications, they can be limited in studying agricultural crop characteristics such as differentiating crop types and their growth stages with a high degree of accuracy and detail. In contrast, hyperspectral data contain continuous narrowbands that provide data in terms of spectral signatures rather than a few data points along the spectrum, and hence can help advance the study of crop characteristics. To better understand and advance this idea, we conducted a detailed study of five leading world crops (corn, soybean, winter wheat, rice, and cotton) that occupy 75% and 54% of principal crop areas in the United States and the world respectively. The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. The authors first developed a first-of-its-kind comprehensive Hyperion-derived Hyperspectral Imaging Spectral Library of Agricultural crops (HISA) of these crops in the US based on USDA Cropland Data Layer (CDL) reference data. Principal Component Analysis was used to eliminate redundant bands by using factor loadings to determine which bands most influenced the first few principal components. This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. Crop types and crop growth stages were classified using linear discriminant analysis (LDA) and support vector machines (SVM) in the Google Earth Engine cloud computing platform using the 30 optimal HNBs (OHNBs). The best overall accuracies were between 75% to 95% in classifying crop types and their growth stages, which were achieved using 15–20 HNBs in the majority of cases. However, in complex cases (e.g., 4 or more crops in a Hyperion image) 25–30 HNBs were required to achieve optimal accuracies. Beyond 25–30 bands, accuracies asymptote. This research makes a significant contribution towards understanding modeling, mapping, and monitoring agricultural crops using data from upcoming hyperspectral satellites, such as NASA’s Surface Biology and Geology mission (formerly HyspIRI mission) and the recently launched HysIS (Indian Hyperspectral Imaging Satellite, 55 bands over 400–950 nm in VNIR and 165 bands over 900–2500 nm in SWIR), and contributions in advancing the building of a novel, first-of-its-kind global hyperspectral imaging spectral-library of agricultural crops (GHISA: www.usgs.gov/WGSC/GHISA).

Remote Sensing↗

USGS2025

Pysochron: A Python-based solution for calculating cosmogenic 26Al/10Be isochron burial ages

Cosmogenic 26 Al/ 10 Be isochron burial dating is a powerful tool for dating sediment burial over the past several million years. By measuring in-situ 26 Al and 10 Be in a suite of samples from the same depth in a buried deposit, it is possible to quantify the inventory of cosmogenic nuclides produced after burial, date the burial of shallow sediments, identify sediment reworking, and calculate paleo-erosion rates. While this approach has been used to date materials around the world for over a decade, few published codes exist for performing 26 Al/ 10 Be isochron calculations. The isochron calculation options that are available typically rely on numerous files and libraries, rendering modification and troubleshooting difficult. Moreover, the widespread use of proprietary programming languages – and their associated addon packages – can place an additional financial burden on an already costly endeavor. Pysochron ( https://code.usgs.gov/recon/pysochron ) provides a solution to these issues. In its base form, it exists as a single script that can be easily modified, upgraded, and shared. Because it was developed in an open-source environment, all required computational packages are available free of charge. A user-friendly interface allows rapid modification of calculation parameters, and an automated commentary on isochron results provides insights and recommendations. Pysochron has been validated with 40 published cosmogenic 26 Al/ 10 Be burial isochrons around the world, with burial ages ranging from ∼5 Ma to ∼180 ka. As such, it is a promising option for members of the cosmogenic nuclide community seeking a straightforward, cost-effective, and flexible solution to isochron burial dating challenges.

Quaternary Geochronology↗

USGS2025

Evaluating Three-Dimensional Elevation Program lidar consistency and accuracy at scale using cloud-native, open-source methods

The U.S. Geological Survey three-dimensional elevation program (3DEP) has significantly expanded national lidar coverage, necessitating scalable, reproducible methods for assessing data quality across diverse terrains and acquisition conditions. This study introduces a cloud-native, open-source workflow designed to evaluate the geometric accuracy and consistency of 3DEP lidar data sets at a national scale. Leveraging tools such as the Point Data Abstraction Library, Open3D, and Amazon Web Services infrastructure, the workflow integrates global navigation satellite system‐surveyed ground control points and terrestrial laser scanning data to validate airborne lidar collections. Two case studies demonstrate the application of this process. In Puerto Rico, the process identified vertical biases and inconsistencies in vegetated areas, while in Iowa and Arizona, the process confirmed high vertical accuracy with minimal bias. The results underscore the effectiveness of combining cloud computing with open-source tools to perform large-scale lidar data quality assessments. This process offers a reproducible, efficient solution for nationwide validation of 3DEP data sets, supporting enhanced decision-making in geospatial applications.

Photogrammetric Engineering and Remote Sensing↗

USGS2008

The GIS Weasel: An interface for the development of geographic information used in environmental simulation modeling

The GIS Weasel is a freely available, open-source software package built on top of ArcInfo Workstation?? [ESRI, Inc., 2001, ArcInfo Workstation (8.1 ed.), Redlands, CA] for creating maps and parameters of geographic features used in environmental simulation models. The software has been designed to minimize the need for GIS expertise and automate the preparation of the geographic information as much as possible. Although many kinds of data can be exploited with the GIS Weasel, the only information required is a raster dataset of elevation for the user's area of interest (AOI). The user-defined AOI serves as a starting point from which to create maps of many different types of geographic features, including sub-watersheds, streams, elevation bands, land cover patches, land parcels, or anything else that can be discerned from the available data. The GIS Weasel has a library of over 200 routines that can be applied to any raster map of geographic features to generate information about shape, area, or topological association with other features of the same or different maps. In addition, a wide variety of parameters can be derived using ancillary data layers such as soil and vegetation maps.

Computers & Geosciences↗

USGS2020

Flood-inundation maps for Dardenne Creek in St. Charles County, Missouri, 2019

Digital flood-inundation maps for a 9.9-mile reach of Dardenne Creek, St. Charles County, Missouri, were created by the U.S. Geological Survey (USGS), in cooperation with the Missouri Department of Transportation, St. Charles County, and the Cities of O’Fallon and St. Peters, Mo. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgages 05514860 Dardenne Creek at Old Town St. Peters, Mo., and 05587450 Mississippi River at Grafton, Illinois. Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ ahps2/ hydrograph.php? wfo= lsx&gage= drcm7 and https://water.weather.gov/ ahps2/ hydrograph.php? wfo= lsx&gage= grfi2 , which also forecasts flood hydrographs at these sites (sites DRCM7 and GRFI2). Flood profiles were computed for the Dardenne Creek stream reach by means of a one-dimensional model for simulating water-surface profiles with steady-state flow computations. The model was calibrated by using the current stage-streamflow relation at the USGS streamgages 05514840 Dardenne Creek at O’Fallon, Mo., and 05514860 Dardenne Creek at Old Town St. Peters, Mo., and the documented high-water marks from the flood of December 2015. The hydraulic model was then used to compute 17 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 16 ft, or near bankfull, to 32 ft at the reference streamgage 05514860. Stages in the lower Dardenne Creek can be affected by backwater from the Mississippi River; therefore, several sets of water-surface profiles were developed representing the extent of varying levels of backwater as referenced to the USGS streamgage 05587450 on the Mississippi River at Grafton, Ill. The upper stage for each map library exceeds the stage corresponding to the estimated 0.2-percent annual exceedance probability flood (500-year recurrence interval flood) at the streamgage location. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.26-ft vertical accuracy and 0.71-ft horizontal resolution) to delineate the area flooded at each water level. The availability of these maps, along with real-time information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood mitigation, preparedness and planning, flood-response activities such as evacuations and road closures, and postflood recovery efforts.

Missouri↗

USGS1995

Images of Kilauea East Rift Zone eruption, 1983-1993

This CD-ROM disc contains 475 scanned photographs from the U.S. Geological Survey Hawaii Observatory Library. The collection represents a comprehensive range of the best photographic images of volcanic phenomena for Kilauea's East Rift eruption, which continues as of September 1995. Captions of the images present information on location, geologic feature or process, and date. Short documentations of work by the USGS Hawaiian Volcano Observatory in geology, seismology, ground deformation, geophysics, and geochemistry are also included, along with selected references. The CD-ROM was produced in accordance with the ISO 9660 standard; however, it is intended for use only on DOS-based computer systems.

Data Series↗

USGS2018

Flood-inundation maps for the South Platte River at Fort Morgan, Colorado, 2018

In 2017, the U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board (CWCB), studied floods in the historic record to produce a library of flood-inundation maps for the South Platte River at Fort Morgan, Colorado. Digital flood-inundation maps for a 4.5-mile (7.2-kilometers) reach of the South Platte River at Fort Morgan from Morgan County Road 16 to Morgan County Road 20.5, were created. The flood-inundation maps depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage on the South Platte River at Fort Morgan (streamgage number 06759500). Water-surface profiles were computed for the stream reach by means of a one-dimensional, step-backwater model. The September 15, 2013, and May 20, 2017, floods were used to calibrate the model, and the June 15, 2015, and May 29, 2017, floods were used to independently validate the model. Nine pressure transducers were deployed to record the stage at nine different locations along the reach and to document the floods of May 20 and 29, 2017, at the South Platte River at Fort Morgan streamgage. The hydraulic model was then used to compute 16 water-surface profiles for flood stages at 1-foot (ft; 0.3-meter [m]) intervals referenced to the streamgage datum and ranging from 12 ft (3.66 m) or below bankfull to 27 ft (8.23 m), which is 1 ft (0.3 m) greater than the highest recorded water level (25.73 ft [7.84 m] on September 15, 2013) at the South Platte River at Fort Morgan streamgage during its period of record; the 2013 flood exceeds the major flood stage of 21.5 ft (6.55 m) by more than 4 ft (1.2 m), as defined by the National Weather Service. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.37-ft [0.11-m] vertical accuracy and 3.28-ft [1.00-m] horizontal resolution) to delineate the area flooded for stages ranging from 12 to 27 ft (3.66 to 8.23 m). These flood-inundation maps, in conjunction with the real-time stage data from the USGS streamgage on the South Platte River at Fort Morgan, are intended to help guide the general public in taking individual safety precautions and provide emergency management personnel with a tool to efficiently manage emergency flood operations and post flood recovery efforts.

Colorado↗

USGS2013

Development of flood profiles and flood-inundation maps for the Village of Killbuck, Ohio

Digital flood-inundation maps for a reach of Killbuck Creek near the Village of Killbuck, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with Holmes County, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the USGS streamgage Killbuck Creek near Killbuck (03139000) and were completed as part of an update to Federal Emergency Management Agency Flood-Insurance Study. The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. The digital maps also have been submitted for inclusion in the data libraries of the USGS interactive Flood Inundation Mapper. Data from the streamgage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating a steady-state step-backwater model to an established streamgage rating curve. The step-backwater model then was used to determine water-surface-elevation profiles for 10 flood stages at the streamgage with corresponding streamflows ranging from approximately the 50- to 0.2-percent annual exceedance probabilities. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas.

Ohio↗

USGS1991

Spatial Data Transfer Standard and efforts to develop a federal Profile for Vector Data

The ongoing efforts to create a more accessible and user friendly Spatial Data Transfer Standard include the development of a Profile for Vector Data and the development of a library of public domain software tools to support the encoding and decoding process. A profile is, in effect, a limited subset of the standard. The best way to use the standard is to first define a profile containing a limited number of the standard's options and then to design encoding/decoding software around those options. Limiting the standard's optionality will make it easier to develop encoding/decoding software. The success of any standard depends upon acceptance by the user community. Accordingly, the development of a library of software tools is being coordinated by the U.S. Geological Survey. When complete, the library will assist users in interfacing with the standard. The software tools will include the capability to encode and decode specific vector data formats into and out of the standard's Vector Profile. With the formal National Institute of Standards and Technology review of the standard coming to a close on July 10, 1991, the likelihood that the standard will be approved as a Federal Information Processing Standard in early 1992 is high. Having such a standard in place is a great/step forward and will allow users to transfer digital spatial data sets in a variety of formats between dissimilar computer systems. The standard's conformance requirements must be understood by all Federal agencies distributing or using spatial data.

Conference Paper↗