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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 793 records · Page 44Linked to original sources
USGS1988

A guide to commonly used map projections prepared for use in HyperCard, 1988

This guide briefly describes and illustrates the characteristics of 17 map projections commonly used to present thematic data. By means of simple sketches of the basic grid system of longitude and latitude known as the Earth's graticule, the guide shows examples of the following categories of map projections: planes (azimuthal), cones, cylinders, and miscellaneous. The text gives examples of thematic maps published by the U.S. Geological Survey that use various projections. The guide was created as a HyperCard "stack" for use only on the Macintosh family of computers. The guide consists of descriptive material only and does not contain a program for creating map projections.

Open-File Report↗
USGS2007

Methods for estimating magnitude and frequency of peak flows for natural streams in Utah

Estimates of the magnitude and frequency of peak streamflows is critical for the safe and cost-effective design of hydraulic structures and stream crossings, and accurate delineation of flood plains. Engineers, planners, resource managers, and scientists need accurate estimates of peak-flow return frequencies for locations on streams with and without streamflow-gaging stations. The 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence-interval flows were estimated for 344 unregulated U.S. Geological Survey streamflow-gaging stations in Utah and nearby in bordering states. These data along with 23 basin and climatic characteristics computed for each station were used to develop regional peak-flow frequency and magnitude regression equations for 7 geohydrologic regions of Utah. These regression equations can be used to estimate the magnitude and frequency of peak flows for natural streams in Utah within the presented range of predictor variables. Uncertainty, presented as the average standard error of prediction, was computed for each developed equation. Equations developed using data from more than 35 gaging stations had standard errors of prediction that ranged from 35 to 108 percent, and errors for equations developed using data from less than 35 gaging stations ranged from 50 to 357 percent.

Utah↗
USGS2025

Methods to determine streamflow statistics based on data through water year 2021 for selected streamgages in or near Wyoming

The U.S. Geological Survey (USGS), in cooperation with the Wyoming Water Development Office, developed streamflow statistics for streamgages in and near Wyoming. Statistics were computed for active (through September 30, 2021) and discontinued USGS streamgages with 10 or more years of daily mean streamflow record. Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Streamflow records from 615 streamgages were used to compute basic, seasonal, and flow-duration statistics; streamflow records from 387 streamgages were used to compute n -day statistics, which are streamflow statistics describing streamflow over a number of days ( n ), and statistics that can be used for regional regression. The streamflow statistics are provided in a USGS data publication that accompanies this report and through the USGS StreamStats web-based application ( https://www.usgs.gov/streamstats ).

Wyoming↗
USGS2003

Levels at streamflow gaging stations--A CD-ROM based training class

Streamgages record the elevation of the water surface above some reference surface, or datum. This datum is assumed to remain unchanged throughout the life of the gage. However, the elevation of gages and their supporting structures often change over time as a result of earthmovement, floods, ice, and debris. The surveying practice of leveling is used to establish datum for new gage structures and to check for vertical movement of those structures over time. Vertical changes in gage structures can affect stage-discharge relations and, thus, could result in incorrect discharge determinations. Datum checks are used to correct stage-discharge relations and allow the USGS to document gage datum throughout the life of a gage. This training presentation describes methods currently used by the U.S. Geological Survey to run levels at gaging stations. The presentation is narrated, but you control the pace of the presentation. If the computer you are using can view 'MPEG' videos you will be able to take advantage of videos found within the presentation. A test, found at the end of the presentation, can be taken to assess how well you understood the training material. The class is registered as class SW1307 with the National Training Center of the U.S. Geologcial Survey. The presentation was developed using Macromedia Director 8.5(1) and is contained in the file 'WRI-4002.exe', which should auto-launch after the CD-ROM is inserted in the PC. The program only runs on a windows-based personal computer (PC). A sound card and speakers are necessary to take advantage of the narration that accompanies the presentation. Text of narrations is provided, if you are unable to listen to the narrations. Instructions for installing and running the presentation are included in the file ' Intro.html'. The file 'Intro.html' is on the CD-ROM containing the presentation and is available from the presentation's help menu.

Water-Resources Investigations Report↗
USGS1989

Spectral analysis and filtering techniques in digital spatial data processing

A filter toolbox has been developed at the EROS Data Center, US Geological Survey, for retrieving or removing specified frequency information from two-dimensional digital spatial data. This filter toolbox provides capabilities to compute the power spectrum of a given data and to design various filters in the frequency domain. Three types of filters are available in the toolbox: point filter, line filter, and area filter. Both the point and line filters employ Gaussian-type notch filters, and the area filter includes the capabilities to perform high-pass, band-pass, low-pass, and wedge filtering techniques. These filters are applied for analyzing satellite multispectral scanner data, airborne visible and infrared imaging spectrometer (AVIRIS) data, gravity data, and the digital elevation models (DEM) data. -from Author

Photogrammetric Engineering and Remote Sensing↗
USGS2009

Streamflow-Characteristic Estimation Methods for Unregulated Streams of Tennessee

Streamflow-characteristic estimation methods for unregulated rivers and streams of Tennessee were developed by the U.S. Geological Survey in cooperation with the Tennessee Department of Environment and Conservation. Streamflow estimates are provided for 1,224 stream sites. Streamflow characteristics include the 7-consecutive-day, 10-year recurrence-interval low flow, the 30-consecutive-day, 5-year recurrence-interval low flow, the mean annual and mean summer flows, and the 99.5-, 99-, 98-, 95-, 90-, 80-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent flow durations. Estimation methods include regional regression (RRE) equations and the region-of-influence (ROI) method. Both methods use zero-flow probability screening to estimate zero-flow quantiles. A low flow and flow duration (LFFD) computer program (TDECv301) performs zero-flow screening and calculation of nonzero-streamflow characteristics using the RRE equations and ROI method and provides quality measures including the 90-percent prediction interval and equivalent years of record. The U.S. Geological Survey StreamStats geographic information system automates the calculation of basin characteristics and streamflow characteristics. In addition, basin characteristics can be manually input to the stand-alone version of the computer program (TDECv301) to calculate streamflow characteristics in Tennessee. The RRE equations were computed using multivariable regression analysis. The two regions used for this study, the western part of the State (West) and the central and eastern part of the State (Central+East), are separated by the Tennessee River as it flows south to north from Hardin County to Stewart County. The West region uses data from 124 of the 1,224 streamflow sites, and the Central+East region uses data from 893 of the 1,224 streamflow sites. The study area also includes parts of the adjacent States of Georgia, North Carolina, Virginia, Alabama, Kentucky, and Mississippi. Total drainage area, a geology factor, a climate factor, and two soil factors were used as explanatory variables in the RRE equations. Average deleted-residual prediction errors for the West-region RRE equations were 18 and 123 percent for the 10-percent flow duration and 7-consecutive-day, 10-year recurrence-interval low flow, respectively. Average deleted-residual prediction errors for RRE equations were 21 and 89 percent for the same respective flow quantiles in the Central+East region. The ROI method calculates unique multivariable regression equations for a site of interest using the flow and basin characteristics of 45 similar streamflow-data sites selected from the same region. These 45 sites are selected using a metric that measures similarity between the site of interest and the streamflow-data sites based on total drainage area, geology factor, and climate factor. The ROI method estimates streamflow characteristics using total drainage area, geology factor, and a soil factor as explanatory variables. Average deleted-residual prediction errors for the West-region ROI equations were 18 and 125 percent for the 10-percent duration and 7-consecutive-day, 10-year recurrence-interval low flow, respectively. Average deleted-residual prediction errors for ROI equations were 20 and 85 percent for the same respective flow quantiles in the Central+East region. In general, when compared to the RRE equations, the ROI method performs similarly in the West region and reduces streamflow-characteristic prediction errors by an average of about 7 percent in the Central+East region of Tennessee.

Scientific Investigations 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↗
USGS1991

Simulation of vertical compaction in models of regional ground-water flow

A new computer program was developed to simulate vertical compaction in models of regional ground-water flow. The program accounts for ground-water storage changes and compaction in discontinuous interbeds or in extensive confining beds. The new program is a package for the U.S. Geological Survey modular finite-difference ground-water flow model. Several features of the program make it useful for application in shallow unconfined flow systems. Geostatic load can be treated as a function of water-table elevation, and compaction is a function of computed changes in effective stress at the center of a model layer. Thickness of compressible sediments in an unconfined model layer can vary in proportion to saturated thickness. The new package was tested by comparison with an existing model of one-dimensional compaction.

Conference Paper↗
USGS1987

Simulation of flow in the Edwards Aquifer, San Antonio region, Texas, and refinement of storage and flow concepts

The Edwards aquifer is a complexly faulted, carbonate aquifer lying within the Balcones fault zone of south-central Texas. The aquifer is recharged mainly by streamflow losses in the outcrop area of the Edwards aquifer and is discharged by major springs located at considerable distances, as much as 150 mi, from the areas of recharge, and by wells. Groundwater flow within the Edwards aquifer of the San Antonio region was simulated to investigate concepts relating to the storage and flow characteristics. A general purpose, finite difference model, modified to provide the capability of representing barrier faults, was used to simulate groundwater flow and storage in the aquifer. The simulations investigated the effects of complex geologic structures and significant changes in transmissivity, anisotropy, and storage coefficient, with initial values based on concepts developed in previous studies. Results of the simulations confirmed the original estimates of transmissivity values (> 100 sq ft/sec) in the confined zone of the aquifer between San Antonio and Comal Springs. A storage coefficient of 0.05 in the unconfined zone of the aquifer produced the best simulation of water levels and springflow. A major interpretation resulting from the simulations is that two essentially independent areas of regional flow were identified in the west and central part of the study area. Flow from the two areas converges at Comal Springs. The directions of computed flux vectors reflected the presence of major barrier faults which locally deflect patterns of groundwater movement. The most noticeable deflection is the convergence of flow through the geologic structural opening, the Knippa gap, in eastern Uvalde County. A second significant interpretation is that groundwater flow in northeastern Bexar, Comal, and Hays Counties is diverted by barrier faults toward San Marcos Springs, a regional discharge point. (Lantz-PTT)

Texas↗
USGS1982

Triggering of large earthquakes by magma-chamber inflation, Izu Peninsula (Japan)

A close spatial and temporal association between three aseismic uplift episodes and subsequent large (M ≈ 7) earthquakes on the Izu Peninsula, Japan, suggests a causal relation. Quaternary geology, as well as studies by other workers, indicates a volcanic origin for the observed uplift, and we use a simple inflation model constrained by leveling data to compute the expected increments in normal and shear stress across faults that ruptured in the earthquakes. Using a Mohr-Coulomb criterion, we find that in two cases out of three, stress changes induced by inflation are in the correct sense to trigger failure. Although changes are no more than a few bars, they represent the equivalent of several decades to a century of secular stress buildup.

Izu Peninsula↗
USGS1992

Land cover mapping of the Upper Kuskokwim Resource Management Area, Alaska, using Landsat and a digital data base approach

Digital land cover and terrain data for the Upper Kuskokwim Resource Management Area in south-central Alaska were produced by the U.S. Geological Survey for the U.S. Bureau of Land Management. These and other environmental data were incorporated into a digital data base to assist in the production of a land cover map and to facilitate in the management and planning of the area. The digital data base is registered to a 50 m Universal Transverse Mercator grid and is stored on computer-compatible tape to facilitate transfer between different processing systems. The data base includes land cover classifications, terrain models (elevation, slope, aspect, solar illumination), autumn and winter Landsat multi-spectral scanner data, soils and surficial geology data, and area boundary. The spectral classification of Landsat multi-spectral scanner data resulted in seven major classes and 24 subclasses. Major classes were forest, shrubland, dwarf scrub, herbaceous, barren, water, and other.

Canadian Journal of Remote Sensing↗
USGS2022

A computer-aided approach for adapting stage-discharge ratings and characterizing uncertainties of streamflow data with discrete measurements

Relations between stage (water level) and discharge of streamflow through a natural channel are the result of time-varying processes, which are commonly described by time-varying stage-discharge ratings. Hydrographers with the U.S. Geological Survey successfully maintain the accuracy of streamflow data by manually applying time-tested approaches to adapt ratings to temporal changes in hydraulic conditions. The difficulty with the manual approach is that it is a subjective, time-consuming process that requires considerable skill and experience to implement. In addition, manual adjustments of ratings make quantification of resulting streamflow data uncertainties problematic. A computer-aided adaptive stage-discharge estimation approach is proposed to track sequential changes in the relation between stage and discharge at continuous-record streamgages. In this report, adaptations are based strictly on discrete measurement data that are then used to compute the magnitudes and uncertainties of streamflow. The approach entails the parameterization of a cubic regression spline (CRS) for the stage-discharge relation based on an existing rating or on a set of discrete measurements. A state-space model is then parameterized to track temporal changes in stage-discharge relations beginning with the initial CRS parameterization using discrete measurements. Finally, Kalman estimation is used with the state-space model to estimate the magnitude and uncertainty of flows. In a case study using data from streamgage U.S. Geological Survey 04122500 Marquette River at Scottville, Michigan, a five-parameter CRS model was estimated from data in an existing stage-discharge rating to provide an initial CRS parameter set for a state-space model. The initial CRS parameters were updated sequentially in a state-space model based on periodic discrete measurements of stage and discharge that spanned a 30-year period for this analysis. Additional analysis is needed to determine the timing of rapidly varying shifts more precisely in stage-discharge relations than the relatively infrequent discrete measurements currently enabled. Unit streamflow estimates based on flow in a local streamgaging network may provide a basis for adapting a stage-discharge rating at unit time intervals by augmenting discrete measurement data within the state-space model.

Michigan↗
USGS2000

Uncertainty estimation for resource assessment-an application to coal

The U.S. Geological Survey is conducting a national assessment of coal resources. As part of that assessment, a geostatistical procedure has been developed to estimate the uncertainty of coal resources for the historical categories of geological assurance: measured, indicated, inferred, and hypothetical coal. Data consist of spatially clustered coal thickness measurements from coal beds and/or zones that cover, in some cases, several thousand square kilometers. Our procedure involved trend removal, an examination of spatial correlation, computation of a sample semivariogram, and fitting a semivariogram model. This model provided standard deviations for the uncertainty estimates. The number of sample points (drill holes) in each historical category also was estimated. Measurement error in the thickness of the coal bed/zone was obtained from the fitted model or supplied exogenously. From this information approximate estimates of uncertainty on the historical categories were computed. We illustrate the methodology using drill hole data from the Harmon coal bed located in southwestern North Dakota. The methodology will be applied to approximately 50 coal data sets.

Mathematical Geology↗
USGS1976

The national coal-resources data system of the U.S. geological survey

The National Coal Resources Data System (NCRDS) was designed by the U.S. Geological Survey (USGS) to meet the increasing demands for rapid retrieval of information on coal location, quantity, quality, and accessibility. An interactive conversational query system devised by the USGS retrieves information from the data bank through a standard computer terminal. The system is being developed in two phases. Phase I, which currently is available on a limited basis, contains published areal resource and chemical data. The primary objective of this phase is to retrieve, calculate, and tabulate coal-resource data by area on a local, regional, or national scale. Factors available for retrieval include: state, county, quadrangle, township, coal field, coal bed, formation, geologic age, source and reliability of data, and coal-bed rank, thickness, overburden, and tonnage, or any combinations of variables. In addition, the chemical data items include individual values for proximate and ultimate analyses, BTU value, and several other physical and chemical tests. Information will be validated and deleted or updated as needed. Phase II is being developed to store, retrieve, and manipulate basic point source coal data (e.g., field observations, drill-hole logs), including geodetic location; bed thickness; depth of burial; moisture; ash; sulfur; major-, minor-, and trace-element content; heat value; and characteristics of overburden, roof rocks, and floor rocks. The computer system may be used to generate interactively structure-contour or isoline maps of the physical and chemical characteristics of a coal bed or to calculate coal resources. ?? 1976.

Computers & Geosciences↗
USGS2012

Methods for determining magnitude and frequency of floods in California, based on data through water year 2006

Methods for estimating the magnitude and frequency of floods in California that are not substantially affected by regulation or diversions have been updated. Annual peak-flow data through water year 2006 were analyzed for 771 streamflow-gaging stations (streamgages) in California having 10 or more years of data. Flood-frequency estimates were computed for the streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Low-outlier and historic information were incorporated into the flood-frequency analysis, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low outliers. Special methods for fitting the distribution were developed for streamgages in the desert region in southeastern California. Additionally, basin characteristics for the streamgages were computed by using a geographical information system. Regional regression analysis, using generalized least squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins in California that are outside of the southeastern desert region. Flood-frequency estimates and basin characteristics for 630 streamgages were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for the area of California outside of the desert region. The final regional regression equations are functions of drainage area and mean annual precipitation for four of the five regions. In one region, the Sierra Nevada region, the final equations are functions of drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression equations in all five regions range from 42.7 to 161.9 percent. For the desert region of California, an analysis of 33 streamgages was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the log-Pearson Type III distribution. The regional estimates were then used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins. The final regional regression equations are functions of drainage area. Average standard errors of prediction for these regression equations range from 214.2 to 856.2 percent. Annual peak-flow data through water year 2006 were analyzed for eight streamgages in California having 10 or more years of data considered to be affected by urbanization. Flood-frequency estimates were computed for the urban streamgages by fitting a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Regression analysis could not be used to develop flood-frequency estimation equations for urban streams because of the limited number of sites. Flood-frequency estimates for the eight urban sites were graphically compared to flood-frequency estimates for 630 non-urban sites. The regression equations developed from this study will be incorporated into the U.S. Geological Survey (USGS) StreamStats program. The StreamStats program is a Web-based application that provides streamflow statistics and basin characteristics for USGS streamgages and ungaged sites of interest. StreamStats can also compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in California.

California↗
USGS2017

Computing spatial correlation of ground motion intensities for ShakeMap

Modeling the spatial correlation of ground motion residuals, caused by coherent contributions from source, path, and site, can provide valuable loss and hazard information, as well as a more realistic depiction of ground motion intensities. The U.S. Geological Survey (USGS) software package, ShakeMap, utilizes a deterministic empirical approach to estimate median ground shaking in conjunction with observed seismic data. ShakeMap-based shaking estimates are used in concert with loss estimation algorithms to estimate fatalities and economic losses after significant seismic events around the globe. Incorporating the spatial correlation of ground motion residuals has been shown to improve seismic loss estimates. In particular, Park, Bazzuro, and Baker (Applications of Statistics and Probability in Civil Engineering, 2007) investigated computing spatially correlated random fields of residuals. However, for large scale ShakeMap grids, computational requirements of the method are prohibitive. In this work, a memory efficient algorithm is developed to compute the random fields and implemented using the ShakeMap framework. This new, iterative parallel algorithm is based on decay properties of an associated ground motion correlation function and is shown to significantly reduce computational requirements associated with adding spatial variability to the ShakeMap g round motion estimates. Further, we demonstrate and quantify the impact of adding peak ground motion spatial variability on resulting earthquake loss estimates.

Computers & Geosciences↗
USGS2021

A geology and geodesy based model of dynamic earthquake rupture on the Rodgers Creek‐Hayward‐Calaveras Fault System, California

The Hayward fault in California's San Francisco Bay area produces large earthquakes, with the last occurring in 1868. We examine how physics‐based dynamic rupture modeling can be used to numerically simulate large earthquakes on not only the Hayward fault, but also its connected companions to the north and south, the Rodgers Creek and Calaveras faults. Equipped with a wealth of images of this fault system, including those of its 3D geology and 3D geometry, in addition to inferences about its interseismic creep‐rate pattern and rock‐friction behavior, we use a finite‐element computer code to perform 3D dynamic earthquake rupture simulations. We find that the rock properties affect the locations and amount of slip produced in our simulated large earthquakes. Crucial factors that control rupture behavior in our modeling are the earthquake nucleation locations, the fault geometry, and the data that reveal where the fault system is creeping or locked. Our findings suggest that large Rodgers Creek‐Hayward‐Calaveras‐Northern Calaveras (RC‐H‐C‐NC) fault‐system earthquakes may result from dynamic rupture that starts in a locked part of the fault system, but is then stopped by the creeping parts, leading to high‐magnitude‐6 earthquakes; or, from dynamic rupture that starts in a locked part of the fault system, then cascades through some of the creeping parts, leading to magnitude‐7 earthquakes.

California↗
USGS2012

Science in support of the Deepwater Horizon response

This introduction to the Special Feature presents the context for science during the Deepwater Horizon oil spill response, summarizes how scientific knowledge was integrated across disciplines and statutory responsibilities, identifies areas where scientific information was accurate and where it was not, and considers lessons learned and recommendations for future research and response. Scientific information was integrated within and across federal and state agencies, with input from nongovernmental scientists, across a diverse portfolio of needs—stopping the flow of oil, estimating the amount of oil, capturing and recovering the oil, tracking and forecasting surface oil, protecting coastal and oceanic wildlife and habitat, managing fisheries, and protecting the safety of seafood. Disciplines involved included atmospheric, oceanographic, biogeochemical, ecological, health, biological, and chemical sciences, physics, geology, and mechanical and chemical engineering. Platforms ranged from satellites and planes to ships, buoys, gliders, and remotely operated vehicles to laboratories and computer simulations. The unprecedented response effort depended directly on intense and extensive scientific and engineering data, information, and advice. Many valuable lessons were learned that should be applied to future events.

Alabama, Florida, Louisiana, Mississippi, Texas↗