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USGS2013

An analysis of potential water availability from the Atwood, Leesville, and Tappan Lakes in the Muskingum River Watershed, Ohio

This report presents the results of a study to assess potential water availability from the Atwood, Leesville, and Tappan Lakes, located within the Muskingum River Watershed, Ohio. The assessment was based on the criterion that water withdrawals should not appreciably affect maintenance of recreation-season pool levels in current use. To facilitate and simplify the assessment, it was assumed that historical lake operations were successful in maintaining seasonal pool levels, and that any discharges from lakes constituted either water that was discharged to prevent exceeding seasonal pool levels or discharges intended to meet minimum in-stream flow targets downstream from the lakes. It further was assumed that the volume of water discharged in excess of the minimum in-stream flow target is available for use without negatively impacting seasonal pool levels or downstream water uses and that all or part of it is subject to withdrawal. Historical daily outflow data for the lakes were used to determine the quantity of water that potentially could be withdrawn and the resulting quantity of water that would flow downstream (referred to as “flow-by”) on a daily basis as a function of all combinations of three hypothetical target minimum flow-by amounts (1, 2, and 3 times current minimum in-stream flow targets) and three pumping capacities (1, 2, and 3 million gallons per day). Using both U.S. Geological Survey streamgage data and lake-outflow data provided by the U.S. Army Corps of Engineers resulted in analytical periods ranging from 51 calendar years for the Atwood Lake to 73 calendar years for the Leesville and Tappan Lakes. The observed outflow time series and the computed time series of daily flow-by amounts and potential withdrawals were analyzed to compute and report order statistics (95th, 75th, 50th, 25th, 10th, and 5th percentiles) and means for the analytical period, in aggregate, and broken down by calendar month. In addition, surplus-water mass curve data were tabulated for each of the lakes. Monthly order statistics of computed withdrawals indicated that, for the three pumping capacities considered, increasing the target minimum flow-by amount tended to reduce the amount of water that can be withdrawn. The reduction was greatest in the lower percentiles of withdrawal; however, increasing the flow-by amount had no impact on potential withdrawals during high flow. In addition, for a given target minimum flow-by amount, increasing the pumping rate increased the total amount of water that could be withdrawn; however, that increase was less than a direct multiple of the increase in pumping rate for most flow statistics. Potential monthly withdrawals were observed to be more variable and more limited in some calendar months than others. Monthly order statistics and means of computed daily mean flow-by amounts indicated that flow-by amounts generally tended to be lowest during June–October and February. Increasing the target minimum flow-by amount for a given pumping rate resulted in some small increases in the magnitudes of the mean and 50th percentile and lower order statistics of computed mean flow-by, but had no effect on the magnitudes of the higher percentile statistics. Increasing the pumping rate for a given target minimum flow-by amount resulted in decreases in magnitudes of higher-percentile flow-by statistics by an amount equal to the flow equivalent of the increase in pumping rate; however, some lower percentile statistics remained unchanged.

Ohio↗

USGS2015

Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line

A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability. The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps. The availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

Massachusetts↗

USGS1978

EROS Data Center Landsat digital enhancement techniques and imagery availability

The US Geological Survey's EROS Data Center (EDC) is experimenting with the production of digitally enhanced Landsat imagery. Advanced digital image processing techniques are used to perform geometric and radiometric corrections and to perform contrast and edge enhancements. The enhanced image product is produced from digitally preprocessed Landsat computer compatible tapes (CCTs) on a laser beam film recording system. Landsat CCT data have several geometric distortions which are corrected when NASA produces the standard film products. When producing film images from CCT's, geometric correction of the data is required. The EDC Digital Image Enhancement System (EDIES) compensates for geometric distortions introduced by Earth's rotation, variable line length, non-uniform mirror scan velocity, and detector misregistration. Radiometric anomalies such as bad data lines and striping are common to many Landsat film products and are also in the CCT data. Bad data lines or line segments with more than 150 contiguous bad pixels are corrected by inserting data from the previous line in place of the bad data. Striping, caused by variations in detector gain and offset, is removed with a destriping algorithm applied after digitally enhancing the data. Image enhancement is performed by applying a linear contrast stretch and an edge enhancement algorithm. The linear contrast enhancement algorithm is designed to expand digitally the full range of useful data recorded on the CCT over the range of 256 digital counts. This minimizes the effect of atmospheric scattering and saturates the relative brightness of highly reflecting features such as clouds or snow. It is the intent that no meaningful terrain data are eliminated by the digital processing. The edge enhancement algorithm is designed to enhance boundaries between terrain features that exhibit subtle differences in brightness values along edges of features. After the digital data have been processed, data for each Landsat band are recorded on black-and-white film with a laser beam film recorder (LBR). The LBR corrects for aspect ratio distortions as the digital data are recorded on the recording film over a preselected density range. Positive transparencies of MSS bands 4, 5, and 7 produced by the LBR are used to make color composite transparencies. Color film positives are made photographically from first generation black-and-white products generated on the LBR.

Canadian Journal of Remote Sensing↗

USGS2015

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989). This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the conterminous United States and compared to topographic metrics. A concurrent processing workflow is implemented using a Linux high-performance computing cluster to simultaneously process multiple subbasins, and thereby complete the work in a fraction of the time required for a single-process environment. In addition, similar metrics are generated for several levels of simplification of the hydrographic features to quantify the effects of simplification over the various landscape conditions. Objectives of this exploratory investigation are to quantify geometric characteristics of linear hydrographic features over the various terrain conditions within the conterminous United States and thereby illuminate relations between stream geomorphological conditions and cartographic representation. The synoptic view of these characteristics over regional watersheds that is afforded through concurrent processing, in conjunction with terrain conditions, may reveal patterns for classifying cartographic stream features into stream geomorphological classes. Furthermore, the synoptic measurement of the amount of change in geometric characteristics caused by the several levels of simplification can enable estimation of tolerance values that appropriately control simplification-induced geometric change of the cartographic features within the various geomorphological classes in the country. Hence, these empirically derived rules or relations could help generate multiscale-representations of features through automated generalization that adequately maintain surface drainage variations and patterns reflective of the natural stream geomorphological conditions across the country.

Conference Paper↗

USGS2023

Linear regression model documentation for computing water-quality constituent concentrations or densities using continuous real-time water-quality data for the Kansas River above Topeka Weir at Topeka, Kansas, November 2018 through June 2021

The Kansas River and its associated alluvial aquifer provide drinking water to more than 950,000 people in northeastern Kansas. Water suppliers that rely on the Kansas River as a water-supply source use physical and chemical processes to treat and remove contaminants before public distribution. An early-notification system of changing water-quality conditions allows water suppliers to proactively make decisions that affect water treatment. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas Water Plan), the Kansas Department of Health and Environment, The Nature Conservancy, the City of Lawrence, the City of Manhattan, the City of Olathe, the City of Topeka, WaterOne, and Evergy, began collecting water-quality data at the Kansas River above Topeka Weir at Topeka, Kansas (USGS site 06888990, hereafter referred to as the “Topeka site”), during November 2018 to develop linear regression models that relate continuous in situ water-quality sensor measurements to discretely sampled water-quality constituent concentrations or densities. The addition of the Topeka site expanded an existing water-quality monitoring network, which included the upstream Kansas River at Wamego, Kans., and downstream Kansas River at De Soto, Kans., sites. Linear regression analysis was used to develop models that compute real-time concentrations or densities for total dissolved solids, major ions, hardness as calcium carbonate, nutrients (nitrogen and phosphorus species), chlorophyll a , total suspended solids, suspended sediment, and Escherichia coli at the Topeka site using data collected during November 2018 through June 2021. Water-quality constituent concentrations or densities computed from the models documented in this report are available at the USGS National Real-Time Water-Quality website (https://nrtwq.usgs.gov), are useful to the public for cultural and recreational purposes, and can be used to guide water-treatment processes, compare conditions with Federal and State water-quality criteria, and characterize changes in Kansas River water-quality conditions through time.

Kansas↗

USGS2026

Multiple-well monitoring site adjacent to the Midway- Sunset and Buena Vista Oil Fields, Kern County, California

Groundwater quality in and around oil fields in the Southern San Joaquin Valley is of interest to many California residents that rely heavily on groundwater for domestic, commercial, and agricultural use. To help assess the effects of historical oil-field activities and natural geologic sources on groundwater near the southwest margins of the Kern County Groundwater Subbasin, a multiple-well monitoring site was installed near the administrative boundary between the Midway-Sunset and Buena Vista Oil Fields in Kern County, California. The installation of the Midway-Sunset Buena Vista multiple-well monitoring site (MSBV) supports regional analysis of the relations of oil and gas sources to groundwater quality by providing information about the geology, hydrology, geophysical properties, and water quality of the alluvial and upper Tulare aquifers in areas where groundwater data were limited. Data collected from the site included drill cuttings, whole core samples, sidewall core samples, mud-gas analysis, borehole geophysical logs, depth to water measurements, and water quality samples. Whole cores were scanned using dual energy computed tomography. Subsamples of selected cores were analyzed for density, porosity, specific retention, and bulk minerology. Thin sections of the subsamples were prepared, photographed, and examined. Two samples were analyzed using scanning electron microscope technology to examine the microporosity of diatomite laden sediment. Instrumentation installed in the wells collect hourly depth to water measurements. Analysis of the data show there is 355 feet of alluvium overlying the Tulare Formation at the well site. The contact between the two formations is an aquitard resulting in a perched aquifer in the alluvium and unconfined aquifer in the Tulare Formation. The alluvium is more heterogenous and finer grained than the Tulare Formation resulting in markedly higher porosity in the alluvium compared to the Tulare Formation. Higher specific retention observed in the alluvium is attributed to the finer grained sediment and greater abundance of reworked diatomite (as represented by opal-CT [cristobalite-tridymite]) compared to the Tulare Formation. Total dissolved solids (TDS) approached or exceeded 10,000 milligrams per liter (mg/L) in the alluvium from approximately 176 to 242 feet below land surface and at the top of the Amnicola clay at approximately 670 feet below land surface within the Tulare Formation. Elevated TDS, chloride, and boron concentrations in the alluvium and on top of the Amnicola clay likely reflect groundwater that is mixed with oil-field water. Water chemistry and modern-aged groundwater in the alluvial monitoring well (MSBV #3) are consistent with the oil-field water in the alluvium being derived from documented historical surface disposal of oil-field water upslope (northwest) of the site. Water chemistry and pre-modern groundwater age in the deeper Tulare monitoring well (MSBV #1) on top of the Amnicola clay are consistent with oil-field fluids derived from upslope natural geologic sources or old oil wells that leak in the subsurface. Shallow groundwater in the Tulare (MSBV #2) is not affected by mixing with oil-field sources.

EarthArXiv↗

USGS2021

Modeling seismic network detection thresholds using production picking algorithms

Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data‐driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well‐sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.

Seismological Research Letters↗

USGS2000

The 1999 Southern California Seismic Network bulletin

The Pasadena office of the U.S. Geological Survey (USGS), together with the Caltech Seismological Laboratory, operates a network of more than 350 remote seismometers in southern California called the S outhern C alifornia S eismic N etwork (SCSN). SCSN is part of TriNet, a cooperative project between the USGS, Caltech, and the California Division of Mines and Geology (CDMG). The TriNet project is halfway completed and is upgrading the existing network to digital, adding new stations, and developing real-time and earthquake-alert capabilities. Signals from the SCSN sites are telemetered to a central processing location at the Caltech Seismological Lab in Pasadena. Computers that detect and record thousands of earthquakes each year continuously monitor these signals. Phase arrival times for these events are picked by analysts and are archived along with digital seismograms. Data acquisition, processing, and archiving are achieved using the Caltech/USGS Seismic Processing (CUSP) system ( Dollar, 1989 ). These data have been compiled into the SCSN Catalog of Earthquakes, a list beginning in 1932 that currently contains more than 356,300 events. Waveform, phase, and catalog data are archived by the Southern California Earthquake Center Data Center (SCEC_DC). This data set is critical to the evaluation of earthquake hazards in California and to the advancement of geoscience as a whole.

California↗

USGS2000

Flow-velocity and depth data during peak discharge events at selected bridge crossings in North Carolina, 1964-98

Flow-velocity and depth data were collected from July 1996 through December 1998 during peak discharge events at 21 bridge crossings that are adjacent to U.S. Geological Survey streamgaging stations in North Carolina. These data were collected during measurements of peak discharges that had recurrence intervals ranging from less than 2 years to about 100 years. The velocity and depth data can be used to evaluate predicted flow velocities and scour depths that are computed as part of scour analyses at the selected bridge crossings.

North Carolina↗

USGS1999

Geographic information systems (GIS) compilation of geophysical, geologic, and tectonic data for the circum-North Pacific

The accompanying directory structure contains a Geographic Information Systems (GIS) compilation of geophysical, geological, and tectonic data for the Circum-North Pacific. This area includes the Russian Far East, Alaska, the Canadian Cordillera, linking continental shelves, and adjacent oceans. This GIS compilation extends from 120°E to 115°W, and from 40°N to 80°N. This area encompasses: (1) to the south, the modern Pacific plate boundary of the Japan-Kuril and Aleutian subduction zones, the Queen Charlotte transform fault, and the Cascadia subduction zone; (2) to the north, the continent-ocean transition from the Eurasian and North American continents to the Arctic Ocean; (3) to the west, the diffuse Eurasian-North American plate boundary, including the probable Okhotsk plate; and (4) to the east, the Alaskan-Canadian Cordilleran fold belt. This compilation should be useful for: (1) studying the Mesozoic and Cenozoic collisional and accretionary tectonics that assembled this continental crust of this region; (2) studying the neotectonics of active and passive plate margins in this region; and (3) constructing and interpreting geophysical, geologic, and tectonic models of the region. Geographic Information Systems (GIS) programs provide powerful tools for managing and analyzing spatial databases. Geological applications include regional tectonics, geophysics, mineral and petroleum exploration, resource management, and land-use planning. This CD-ROM contains thematic layers of spatial data-sets for geology, gravity field, magnetic field, oceanic plates, overlap assemblages, seismology (earthquakes), tectonostratigraphic terranes, topography, and volcanoes. The GIS compilation can be viewed, manipulated, and plotted with commercial software (ArcView and ArcInfo) or through a freeware program (ArcExplorer) that can be downloaded from http://www.esri.com for both Unix and Windows computers using the button below.

North Pacific↗

USGS1998

Sediment transport at gaging stations near Mount St. Helens, Washington, 1980-90. Data collection and analysis

River sedimentation caused by the May 18, 1980, eruption of Mount St. Helens, Washington, has been monitored in a continuing program by the U.S. Geological Survey. In this report, sediment discharge and changes in sediment transport are summarized from data collected at stream-gaging stations near Mount St. Helens during the years 1980 through 1990. The objectives of the monitoring program included collection of data for calculation of total sediment discharge, computation of daily suspended-sediment discharge, and detailed observations of unique sediment-laden flows. Over the 11-year period, most sediment data were collected at gaging stations on seven eruption affected streams: the Green River, the North and South Fork Toutle Rivers, the Toutle River, the Cowlitz River, Clearwater Creek, and the Muddy River. About 170 million tons of sediment (excluding volcanic debris flows) were transported in suspension from the Toutle River basin during water years 1980–90. Another 13 million tons were transported past the gaging stations on Muddy River in the upper Lewis River basin during water years 1982–90. Long-term reductions in sediment concentration occurred within most ranges of stream discharge at streams dominated by transport from the debris-avalanche deposit and at streams in drainage basins with extensive airfall deposits. Reductions in sediment concentration were less apparent at upper ranges of discharge in two streams dominated by lahar deposits, the South Fork Toutle River and the Muddy River. Bed material, suspended sediment, and bedload were sampled periodically and analyzed for size distributions. Bed material and bedload coarsened with time at some stations. Median particle sizes of suspended sediment did not show a simple relation with time. During water years 1980–84, bed material in the lower Toutle River was medium to coarse sand. During the same period, bed material in the North Fork Toutle River was coarse sand and fine gravel. By 1990, bedload samples collected in the North Fork Toutle River (downstream from the sediment-retention structure) were typically coarse gravel.

Washington↗

USGS2005

Hydrogeologic framework, ground-water quality, and simulation of ground-water flow at the Fair Lawn Well Field Superfund site, Bergen County, New Jersey

Production wells in the Westmoreland well field, Fair Lawn, Bergen County, New Jersey (the 'Fair Lawn well field Superfund site'), are contaminated with volatile organic compounds, particularly trichloroethylene, tetrachloroethylene, and 1,1,1-trichloroethane. In 1983, the U.S. Environmental Protection Agency (USEPA) placed the Westmoreland well field on its National Priority List of Superfund sites. In an effort to determine ground-water flow directions, contaminant-plume boundaries, and contributing areas to production wells in Fair Lawn, and to evaluate the effect of present pump-and-treat systems on flowpaths of contaminated ground water, the U.S. Geological Survey (USGS), in cooperation with the USEPA, developed a conceptual hydrogeologic framework and ground-water flow model of the study area. MODFLOW-2000, the USGS three-dimensional finite-difference model, was used to delineate contributing areas to production wells in Fair Lawn and to compute flowpaths of contaminated ground water from three potential contaminant sources to the Westmoreland well field. Straddle-packer tests were used to determine the hydrologic framework of, distribution of contaminants in, and hydrologic properties of water-bearing and confining units that make up the fractured-rock aquifer underlying the study area. The study area consists of about 15 square miles in and near Fair Lawn. The area is underlain by 6 to 100 feet of glacial deposits and alluvium that, in turn, are underlain by the Passaic Formation. In the study area, the Passaic Formation consists of brownish-red pebble conglomerate, medium- to coarse-grained feldspathic sandstone, and micaceous siltstone. The bedrock strata strike N. 9o E. and dip 6.5o to the northwest. The bedrock consists of alternating layers of densely fractured rocks and sparsely fractured rocks, forming a fractured-rock aquifer. Ground-water flow in the fractured-rock aquifer is anisotropic as a result of the interlayering of dipping water-bearing and confining units. Wells of similar depth aligned along the strike of the bedding intersect the same water-bearing units, but wells aligned along the dip of the bedding may intersect different water-bearing units. Consequently, wells aligned along strike are in greater hydraulic connection than wells aligned along dip. The Borough of Fair Lawn pumps approximately 770 million gallons per year from 13 production wells. Hydrographs from six observation wells ranging in depth from 162 to 505 feet in Fair Lawn show that water levels in much of the study area are affected by pumping. Straddle packers were used to isolate discrete intervals within six open-hole observation wells owned by the Fair Lawn Water Department. Transmissivity, water-quality, and static-water-level data were obtained from the isolated intervals. Measured transmissivity ranged from near 0 to 8,900 feet squared per day. The broad range in measured transmissivity is a result of the heterogeneity of the fractured-rock aquifer. Eight water-bearing units and eight confining units were identified in the study area on the basis of transmissivity. The water-bearing units range in thickness from 21 to 95 feet; the mean thickness is 50 feet. The confining units range in thickness from 22 to 248 feet; the mean thickness is 83 feet. Water-level and water-quality data indicate effective separation of water-bearing units by the confining units. Water-quality samples were collected from the six observation wells at 16 depth intervals isolated by the straddle packers in 2000 and 2001. Concentrations of volatile organic compounds generally were low in samples from four of the wells, but were higher in samples from a well in Fair Lawn Industrial Park and in a well in the Westmoreland well field. The digital ground-water flow model was used to simulate steady-state scenarios representing conditions in the study area in 1991 and 2000. These years were chosen because during the intervening period,

Scientific Investigations Report↗

USGS2008

Regression method for estimating long-term mean annual ground-water recharge rates from base flow in Pennsylvania

A method was developed for making estimates of long-term, mean annual ground-water recharge from streamflow data at 80 streamflow-gaging stations in Pennsylvania. The method relates mean annual base-flow yield derived from the streamflow data (as a proxy for recharge) to the climatic, geologic, hydrologic, and physiographic characteristics of the basins (basin characteristics) by use of a regression equation. Base-flow yield is the base flow of a stream divided by the drainage area of the basin, expressed in inches of water basinwide. Mean annual base-flow yield was computed for the period of available streamflow record at continuous streamflow-gaging stations by use of the computer program PART, which separates base flow from direct runoff on the streamflow hydrograph. Base flow provides a reasonable estimate of recharge for basins where streamflow is mostly unaffected by upstream regulation, diversion, or mining. Twenty-eight basin characteristics were included in the exploratory regression analysis as possible predictors of base-flow yield. Basin characteristics found to be statistically significant predictors of mean annual base-flow yield during 1971-2000 at the 95-percent confidence level were (1) mean annual precipitation, (2) average maximum daily temperature, (3) percentage of sand in the soil, (4) percentage of carbonate bedrock in the basin, and (5) stream channel slope. The equation for predicting recharge was developed using ordinary least-squares regression. The standard error of prediction for the equation on log-transformed data was 9.7 percent, and the coefficient of determination was 0.80. The equation can be used to predict long-term, mean annual recharge rates for ungaged basins, providing that the explanatory basin characteristics can be determined and that the underlying assumption is accepted that base-flow yield derived from PART is a reasonable estimate of ground-water recharge rates. For example, application of the equation for 370 hydrologic units in Pennsylvania predicted a range of ground-water recharge from about 6.0 to 22 inches per year. A map of the predicted recharge illustrates the general magnitude and variability of recharge throughout Pennsylvania.

Scientific Investigations Report↗

USGS2014

Potential postwildfire debris-flow hazards: a prewildfire evaluation for the Sandia and Manzano Mountains and surrounding areas, central New Mexico

Wildfire can drastically increase the probability of debris flows, a potentially hazardous and destructive form of mass wasting, in landscapes that have otherwise been stable throughout recent history. Although there is no way to know the exact location, extent, and severity of wildfire, or the subsequent rainfall intensity and duration before it happens, probabilities of fire and debris-flow occurrence for different locations can be estimated with geospatial analysis and modeling efforts. The purpose of this report is to provide information on which watersheds might constitute the most serious, potential, debris-flow hazards in the event of a large-scale wildfire and subsequent rainfall in the Sandia and Manzano Mountains. Potential probabilities and estimated volumes of postwildfire debris flows in the unburned Sandia and Manzano Mountains and surrounding areas were estimated using empirical debris-flow models developed by the U.S. Geological Survey in combination with fire behavior and burn probability models developed by the U.S. Department of Agriculture Forest Service. The locations of the greatest debris-flow hazards correlate with the areas of steepest slopes and simulated crown-fire behavior. The four subbasins with the highest computed debris-flow probabilities (greater than 98 percent) were all in the Manzano Mountains, two flowing east and two flowing west. Volumes in sixteen subbasins were greater than 50,000 square meters and most of these were in the central Manzanos and the western facing slopes of the Sandias. Five subbasins on the west-facing slopes of the Sandia Mountains, four of which have downstream reaches that lead into the outskirts of the City of Albuquerque, are among subbasins in the 98th percentile of integrated relative debris-flow hazard rankings. The bulk of the remaining subbasins in the 98th percentile of integrated relative debris-flow hazard rankings are located along the highest and steepest slopes of the Manzano Mountains. One of the subbasins is several miles upstream from the community of Tajique and another is several miles upstream from the community of Manzano, both on the eastern slopes of the Manzano Mountains. This prewildfire assessment approach is valuable to resource managers because the analysis of the debris-flow threat is made before a wildfire occurs, which facilitates prewildfire management, planning, and mitigation. In northern New Mexico, widespread watershed restoration efforts are being carried out to safeguard vital watersheds against the threat of catastrophic wildfire. This study was initiated to help select ideal locations for the restoration efforts that could have the best return on investment.

New Mexico↗

USGS2016

Groundwater-flow model for the Wood River Valley aquifer system, south-central Idaho

A three-dimensional numerical model of groundwater flow was developed for the Wood River Valley (WRV) aquifer system, Idaho, to evaluate groundwater and surface-water availability at the regional scale. This mountain valley is located in Blaine County and has a drainage area of about 2,300 square kilometers (888 square miles). The model described in this report can serve as a tool for water-rights administration and water-resource management and planning. The model was completed with support from the Idaho Department of Water Resources, and is part of an ongoing U.S. Geological Survey effort to characterize the groundwater resources of the WRV. A highly reproducible approach was taken for constructing the WRV groundwater-flow model. The collection of datasets, source code, and processing instructions used to construct and analyze the model was distributed as an R statistical-computing and graphics package. Flow in the WRV aquifer was simulated using the MODFLOW-USG groundwater flow model. The transient flow model simulates groundwater flow between 1995 and 2010. The model uses a 100-meter (328-feet) uniform grid spacing with 54,922 active model cells distributed over three model layers. A confining unit in the south-central part of the Bellevue fan necessitated the use of a multi-layer model. Specified-flow boundaries were used to simulate the groundwater inflows from each of the major tributary basins (also known as tributary basin underflow) and the areal recharge of precipitation and applied irrigation. Head‑dependent flow boundaries were used to simulate the stream-aquifer flow exchange in river reaches and the groundwater discharge at the outlet boundaries of Stanton Crossing and Silver Creek. The model was calibrated by adjusting aquifer hydraulic properties to match simulated and measured water levels and stream-aquifer flow exchange, using the parameter-estimation program PEST. The model reasonably simulated the measured water-table elevation, orientation, and gradients. Stream-aquifer flow exchange along river reaches also was reasonably simulated by the model. Inflow into the WRV aquifer system originates from three sources (from largest to smallest): Streamflow loss from the Big Wood River and Silver Creek, Areal recharge of precipitation and applied irrigation, and Tributary basin underflow. Outflow from the WRV aquifer system originates from five sources (from largest to smallest): Aquifer discharge into the Big Wood River and Silver Creek, Production-well pumping, Discharge across the water table into the vadose zone, Subsurface outflow beneath Silver Creek near Picabo, and Subsurface outflow beneath the Big Wood River near Stanton Crossing. Temporal changes in aquifer storage are most affected by areal recharge and groundwater pumping, and also contribute to changes in streamflow gains.

Idaho↗

USGS2017

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

Many approaches have been developed for measuring or estimating actual evapotranspiration ( ET a ), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ET a . Several remote sensing methods can be used to estimate ET a at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ET a estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ET a and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ET a that are currently applied successfully in the United States. The METRIC model can produce maps of ET a at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ET a against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ET a . The SSEBop model has been used to produce maps of ET a over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ET a estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ET a estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth Engine TM has been used to implement METRIC with automated calibration for regional-scale estimates of ET a using Landsat data. The U.S. Geological Survey also is using Google Earth Engine TM to implement SSEBop for estimating ET a in the United States at a continental scale using Landsat data.

Scientific Investigations Report↗

USGS2019

Development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania

Regression equations, which may be used to estimate flood flows at select annual exceedance probabilities, were developed for ungaged streams in Pennsylvania. The equations were developed using annual peak flow data through water year 2015 and basin characteristics for 285 streamflow gaging stations across Pennsylvania and surrounding states. The streamgages included active and discontinued continuous-record stations, as well as crest-stage partial-record stations, and required a minimum of 10 years of annual peak streamflow data for inclusion in the study. Explanatory variables significant at the 95-percent confidence level for one or more regression equations included the following basin characteristics: drainage area, maximum basin elevation, mean basin slope, percent storage, and the percentage of carbonate bedrock within a basin. The State was divided into five regions, and regional regression equations were developed to estimate flood flows associated with the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (which correspond to the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively). Although the regression equations can be used to estimate the magnitude of flood flows for most streams in the State, they are not valid for streams with drainage areas generally greater than 1,500 square miles or with substantial regulation, diversion, or mining activity within the basin. The regional regression equations will be incorporated into the U.S. Geological Survey StreamStats application ( https://water.usgs.gov/osw/streamstats/ ). Additionally, annual peak flow data for 356 streamgages initially considered for inclusion in the analysis for development of updated flood-flow regression equations were analyzed for the existence of trends; estimates of flood-flow magnitude and frequency were also computed for these streamgages. Estimates of flood-flow magnitude and frequency for streamgages substantially affected by upstream regulation are also presented.

Pennsylvania↗

USGS2024

Flood-inundation maps for the Cuyahoga River at Jaite, Ohio, 2024

Digital flood-inundation maps for a nearly 6-mile reach of the Cuyahoga River at Jaite, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the Northeast Ohio Regional Sewer District Board of Trustees. The maps depict estimates of the extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04206425 on the Cuyahoga River at Jaite, Ohio. Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The hydraulic model was calibrated to the current USGS streamgage data and then used to compute 15 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from 6 to 20 feet, which correspond to below “action stage” to “major flood stage” as reported by the National Weather Service. The simulated water-surface profiles were then used with a geographic information system digital elevation model derived from light detection and ranging data to delineate the areas flooded at each stage. These maps, along with current stage data from the USGS streamgage and forecasted high-flow stages from the National Weather Service, can provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Ohio↗