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USGS2015

Seismic-hazard maps for the conterminous United States, 2014

The maps presented here provide an update to the 2008 data contained in U.S Geological Survey Scientific Investigations Map 3195 ( http://pubs.usgs.gov/sim/3195/ ).Probabilistic seismic-hazard maps were prepared for the conterminous United States for 2014 portraying peak horizontal acceleration and horizontal spectral response acceleration for 0.2- and 1.0-second periods with probabilities of exceedance of 10 percent in 50 years and 2 percent in 50 years. All of the maps were prepared by combining the hazard derived from spatially smoothed historical seismicity with the hazard from fault-specific sources. The acceleration values contoured are the random horizontal component. The reference site condition is firm rock, defined as having an average shear-wave velocity of 760 m/s in the top 30 meters corresponding to the boundary between NEHRP (National Earthquake Hazards Reduction program) site classes B and C. This data set represents the results of calculations of hazard curves for a grid of points with a spacing of 0.05 degrees in latitude and longitude. The grid of points was contoured to produce the final representation of the seismic hazard. These maps are intended to summarize the available quantitative information about seismic ground motion hazard for the conterminous United States from geologic and geophysical sources.

Scientific Investigations Map↗

USGS2022

Field-trip guide to continental arc to rift volcanism of the southern Rocky Mountains—Southern Rocky Mountain, Taos Plateau, and Jemez Mountains volcanic fields of southern Colorado and northern New Mexico

The southern Rocky Mountains of northern New Mexico and southern Colorado preserve the Oligocene to Pleistocene record of North American continental arc to rift volcanism. The 35–23 million year old (Ma) southern Rocky Mountain volcanic field (SRMVF), spectacularly preserved in the San Juan Mountains of southern Colorado, records the evolution of large andesitic stratovolcanoes to complex caldera clusters, from which at least 22 major ignimbrite sheets (each 150–5,000 cubic kilometers) were erupted. Outflow deposits of the SRMVF preserved along the broadly uplifted northwest flank of the northern Rio Grande rift basin (the San Luis Valley) provide critical structural and temporal constraints on the inception of crustal extension. Coincident with waning stages of SRMVF caldera-forming volcanism (~25.4 Ma), extensional tectonism was accompanied by a transition from bimodal early Miocene to intermediate-composition late Miocene and dominantly basaltic Pliocene rift volcanism of the Taos Plateau in the southern San Luis Basin. Concomitant rift volcanism in the Española Basin and bordering Jemez Mountains of northern New Mexico records a similar Miocene eruptive history dominated by intermediate-composition volcanism that transitioned locally to Pliocene rift-related basaltic volcanism of the Cerros del Rio volcanic field and culminated in eruptions of the iconic rhyolitic Pleistocene Bandelier Tuff and formation of the Valles Caldera along the northwestern rift-basin margin. This 6-day, 7-night field trip will focus, in broadly equal proportions, on rift-related extensional volcanism of the Jemez Mountains and Taos Plateau regions during the first half of the trip, and on caldera-forming volcanism of the southern Rocky Mountain volcanic field during the second half of the trip. The 35-million-year volcanic history of the region highlighted by new geologic mapping, high-resolution geochronology, petrologic, geochemical, and geophysical data facilitates discussion of (1) the magmatic response to the tectonic transition from subducted-slab arc to continental-rift volcanism; (2) the nature and temporal evolution of rift magmas; (3) fault controls on the spatial evolution of rift magmatism; (4) the diversity of continental-arc ignimbrite volcanism and associated lavas; (5) ignimbrite caldera structure and associated intrusions in three-dimension; (6) the role of recycled crystal mush and magmatic cumulates during growth of Cordilleran batholiths; and (7) high-precision geochronologic contributions to interpretation of relations between regional tectonic and volcanic processes. Most stops will be along roads, but there will be moderate hikes on trails of less than 1-hour duration covering 1–2 kilometers (0.6–1.2 miles) with modest elevation gain of <150 meters (<492 feet). The route will progress in reverse stratigraphic order, starting in the Jemez Mountains of New Mexico and proceed northward to San Luis Basin and San Luis Hills before turning west to the southeast and central San Juan Mountains. Our last full day takes us to the little-visited and only recently mapped, Bonanza caldera of the northeastern San Juan Mountains and on the final day, we leave the San Luis Valley to briefly explore the Tertiary subvolcanic plutons of the Collegiate Range along the west side of the Arkansas Valley rift valley, en route to Denver. The authors of all daily contributions acknowledge the helpful reviews by Amy Gilmer and Joe Colgan and thank Christine Chan and Jeremy Havens for assistance with figures, tables, and guidebook text.

Colorado, New Mexico↗

USGS2020

Estimating flood magnitude and frequency on gaged and ungaged streams in Maine

Accurate estimates of flood frequency and magnitude on rivers and streams in Maine are a key component of effective flood risk management, flood mitigation, and flood recovery programs for the State. Flood-frequency estimates are published here for 148 streamgages in and adjacent to Maine. Equations are provided for users to compute flood-frequency estimates at any location on a stream that does not have a streamgage. Estimates and equations are presented for peak flows with annual exceedance probabilities (AEPs) of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent. AEPs correspond to flood recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. New estimates use a regional skew coefficient of 0.02 with a standard error of prediction of 0.30 developed specifically for Maine as a part of this work. Equations are designed for use at ungaged sites without substantial flow regulation or urbanization in Maine, with drainage areas between 0.26 and 5,680 square miles. The equations were developed from streamflows and basin characteristics at 124 unregulated streamgages using generalized least-squares regression techniques. Explanatory variables used in the equations for computing peak flows are drainage area, percentage of area in the basin that contains wetlands, and basin mean 24-hour rainfall intensities. The average standard error of prediction (ASEP) for these equations ranges from −31.5 to 45.9 percent for the 50-percent AEP and from −34.2 to 52.0 percent for the 0.2-percent AEP. Equations that use only drainage area are provided for use in cases where lower accuracy is acceptable. The ASEP for estimating peak flows with these simpler equations ranges from −40 to 66 percent for the 50-percent AEP and from −44 to 79 percent for the 0.2-percent AEP. Final peak flows at unregulated streamgages are computed as weighted averages between the at-station peak flows and peak flows computed at those same sites using the regression equations. Peak flow estimates and equations presented here are accessible in the U.S. Geological Survey StreamStats application. StreamStats is a web application that computes selected basin characteristics and estimates of peak flows and other available streamflow statistics for user-selected streams in Maine.

Maine↗

USGS1997

An optimized network for phosphorus load monitoring for Lake Okeechobee, Florida

Phosphorus load data were evaluated for Lake Okeechobee, Florida, for water years 1982 through 1991. Standard errors for load estimates were computed from available phosphorus concentration and daily discharge data. Components of error were associated with uncertainty in concentration and discharge data and were calculated for existing conditions and for 6 alternative load-monitoring scenarios for each of 48 distinct inflows. Benefit-cost ratios were computed for each alternative monitoring scenario at each site by dividing estimated reductions in load uncertainty by the 5-year average costs of each scenario in 1992 dollars. Absolute and marginal benefit-cost ratios were compared in an iterative optimization scheme to determine the most cost-effective combination of discharge and concentration monitoring scenarios for the lake. If the current (1992) discharge-monitoring network around the lake is maintained, the water-quality sampling at each inflow site twice each year is continued, and the nature of loading remains the same, the standard error of computed mean-annual load is estimated at about 98 metric tons per year compared to an absolute loading rate (inflows and outflows) of 530 metric tons per year. This produces a relative uncertainty of nearly 20 percent. The standard error in load can be reduced to about 20 metric tons per year (4 percent) by adopting an optimized set of monitoring alternatives at a cost of an additional $200,000 per year. The final optimized network prescribes changes to improve both concentration and discharge monitoring. These changes include the addition of intensive sampling with automatic samplers at 11 sites, the initiation of event-based sampling by observers at another 5 sites, the continuation of periodic sampling 12 times per year at 1 site, the installation of acoustic velocity meters to improve discharge gaging at 9 sites, and the improvement of a discharge rating at 1 site.

Florida↗

USGS1996

Numerical simulation of solute transport in southwestern Salt Lake Valley, Utah

Contaminated ground water characterized by high concentrations of dissolved solids and dissolved sulfate, and in areas, by low pH and elevated concentrations of metals, is present near public-supply wells in the southwestern Salt Lake Valley. To provide State officials and water users with information concerning the potential movement of contaminated ground water to points of withdrawal in the area, an analysis of solute transport using computer models was done by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and local municipalities and water users. A three-dimensional solute-transport model was developed and couples with an existing ground-water flow model of Salt Lake Valley to simulate the movement of dissolved sulfate in ground water in southwestern Salt Lake Valley. Development and calibration of the transport model focused mainly on sulfate movement down-gradient from the Bingham Creek Reservoirs and the South Jordan evaporation ponds east of the mouth of Bingham Canyon. Estimates of transport parameters were adjusted during a calibration simulation representing conditions during 1965-93. After calibration, the transport model was used to simulate future sulfate movement for 1994-2043. Because of uncertainty in estimated transport-parameter values, three projection transport simulations incorporating a range of probable parameter values were done to evaluate future sulfate movement and changes in sulfate concentrations at selected public-supply wells. These projection simulations produced a possible range of computed transport rates and patterns. In general, the projection simulations indicated movement of the sulfate plume east of the Bingham Creek reservoir toward public-supply wells northeast of the reservoirs and then eastward toward the Jordan River. Ground water with high concentrations of sulfate east of the South Jordan evaporation ponds is simulated as moving west to east under the Jordan River towards public-supply wells during the final 25 years of the simulation period. An increase in sulfate concentration from 200 mg/l in 2006 to 4,100 mg/l in 2022 was the largest simulated increase at public-supply wells northeast of the reservoirs. An increase in sulfate concentration from 150 mg/l in 2024 to 340 mg/l in 2043 was the largest simulated increase at public-supply wells in the south-central Salt Lake Valley just east of the Jordan River.

Utah↗

USGS1978

A paleolimnological comparison of Burntside and Shagawa Lakes, northeastern Minnesota

The paleolimnological records of Burntside and Shagawa Lakes in northeastern Minnesota reveal that these two adjacent lakes have been limnologically distinct for many years prior to the late 19th century activities of white men that polluted Shagawa Lake. Although both lakes occur within the same vegetation type and share much of their water, the diatom stratigraphy of their bottom sediments indicates that Burntside Lake was less productive in its natural state than Shagawa Lake. The causes for this natural difference are not clearly known, but differences in relative size of drainage area and in bedrock geology may he responsible. Intensive white settlement around Shagawa Lake beginning in 1866 supplied nutrients that increased its productivity and finally supported the massive blooms of blue-green algae that characterize culturally eutrophic lakes. Burntside Lake was spared such intensive eutrophication, but its diatom record shows that nutrients derived from shoreside recreational cabins and related construction activity are increasing the lake's productivity. The results of this study show that paleolimnological studies may provide better comparative information for lake rehabilitation programs than do biological and chemical analyses of contemporary unpolluted water bodies.

Minnesota↗

USGS2015

Groundwater/surface-water interactions in the Bad River Watershed, Wisconsin

A groundwater-flow model was developed for the Bad River Watershed and surrounding area by using the U.S. Geological Survey (USGS) finite-difference code MODFLOW-NWT. The model simulates steady-state groundwater-flow and base flow in streams by using the streamflow routing (SFR) package. The objectives of this study were to: (1) develop an improved understanding of the groundwater-flow system in the Bad River Watershed at the regional scale, including the sources of water to the Bad River Band of Lake Superior Chippewa Reservation (Reservation) and groundwater/surface-water interactions; (2) provide a quantitative platform for evaluating future impacts to the watershed, which can be used as a starting point for more detailed investigations at the local scale; and (3) identify areas where more data are needed. This report describes the construction and calibration of the groundwater-flow model that was subsequently used for analyzing potential locations for the collection of additional field data, including new observations of water-table elevation for refining the conceptualization and corresponding numerical model of the hydrogeologic system. The study area can be conceptually divided into three primary hydrogeologic environments. The first encompasses the southern uplands with relatively low topographic relief, where groundwater-flow is unconfined and occurs primarily in sandy till and glacial outwash overlying Archean-aged crystalline bedrock. The second includes a transitional area of higher topographic relief and shallow depth to bedrock, in the vicinity of ridges formed by steeply dipping, early-Proterozoic aged metasedimentary units of the Marquette Range Supergroup (including the Ironwood Formation), and late-Proterozoic igneous units associated with the Midcontinent Rift System (MRS). Groundwater-flow in this area likely occurs primarily through connected networks of bedrock fractures that are not well characterized, and also in isolated pockets of Quaternary deposits. The third and last hydrogeologic environment includes lowlands along Lake Superior where a deep sandstone aquifer is confined by thick deposits of clay-rich till. Model input was compiled by using both published and unpublished data. Constant flux boundary conditions for the model perimeter were developed from a regional analytic element model described in appendix 1 of this report. Pumping from 26 high-capacity wells within the model area was included. The SFR stream network was developed from the National Hydrography Dataset (NHDPlus Version 2) and hydrography from the Wisconsin Department of Natural Resources (WDNR). Hydraulic conductivity values were determined for each model cell by interpolation from a network of pilot points, within zones representing major hydrogeologic units. Recharge to the groundwater system was estimated on a cell-by-cell basis by using the Soil Water Balance code (SWB), with gridded daily temperature and precipitation data for the period 1980–2011, and GIS coverages of soil and land-surface conditions. Estimated recharge varies considerably, following spatial patterns in the precipitation and soil hydrologic group inputs. The lowest recharge values occur in the Superior lowlands, whereas the highest values occur in the upland areas, especially those underlain by sandy soils, and in the vicinity of bedrock hills. The model was calibrated to groundwater-levels and base flows obtained from the USGS National Water Information System (NWIS) database, and groundwater-levels obtained from the WDNR and Band River Band well-construction databases. Calibration was performed via nonlinear regression by using the parameter-estimation software suite PEST. Groundwater levels and base-flow observations in the calibration dataset were well simulated by the calibrated model, with reasonable values of hydraulic conductivity. The pilot-point parameters that were most constrained by observations during model calibration coincided with the locations containing the most wells (head observations)—especially the population centers of Ashland, Mellen, and other communities along the major highway corridors. Results from the calibrated model illustrate differences in the nature of groundwater-ﬂow within the watershed. In the southern part of the watershed, where bedrock is shallow, groundwater ﬂow paths are relatively short, extending from local recharge areas to adjacent ﬁrst and second-order streams. In contrast, laterally continuous deposits of clay-rich till covering the Superior Lowlands isolate most smaller streams from the sandstone aquifer, allowing for longer ﬂow paths toward larger streams such as the Bad, Marengo, and White Rivers. Approximately three-quarters of all ﬁrst-order stream cells were dry in the Superior Lowlands, compared to only half of ﬁrst-order stream cells in the southern bedrock uplands. The model was used to delineate the groundwatershed for the Bad and Kakagon Rivers. “Groundwatershed” is deﬁned as the area contributing groundwater discharge to one of these streams and their tributaries. The groundwatershed was found to align closely with the surface-watershed, with the most notable exception occurring along the southwestern half of Birch Hill, where surface water drains southwest towards the Potato River, and groundwater ﬂows north and east towards Lake Superior. Similarly, the contributing area of groundwater-ﬂow to the Reservation was delineated. Results indicate the off-Reservation groundwater contributing area to be limited in comparison to the extent of the watershed, extending southward into the highlands underlain by MRS igneous rock units, but not further into the area underlain by the Marquette Range Supergroup. Stable isotope samples were collected from 54 wells within the watershed, to investigate sources of groundwater. Oxygen-18 (δ 18 O) values lower than -13.0 per mil were documented in the sampling, and likely indicate the presence of recharge water from the last glacial period (>9,500 years old) beneath the northern portion of the Reservation, in the vicinity of Odanah, Wisconsin. Finally, a new data-worth analysis of potential new monitoring-well locations was performed by using the model. The relative worth of new measurements was evaluated based on their ability to increase conﬁdence in model predictions of groundwater levels and base ﬂows at 35 locations, under the condition of a proposed open-pit iron mine. Results of the new data-worth analysis, and other inputs and outputs from the Bad River model, are available through an online dynamic web mapping service at ( http://wim.usgs.gov/badriver/ ).

Wisconsin↗

USGS2020

Modeling Escherichia coli in the Missouri River near Omaha, Nebraska, 2012–16

The city of Omaha, Nebraska, has a combined sewer system in some areas of the city. In Omaha, Nebr., a moderate amount of rainfall will lead to the combination of stormwater and untreated sewage or wastewater being discharged directly into the Missouri River and Papillion Creek and is called a combined sewer overflow (CSO) event. In 2009, the city of Omaha began the implementation of their Long Term Control Plan (LTCP) to mitigate the effects of CSOs on the Missouri River and Papillion Creek. As part of the LTCP, the city partnered with the U.S. Geological Survey (USGS) in 2012 to begin monitoring in the Missouri River. Since 2012, monthly discrete water-quality samples for many constituents have been collected from the Missouri River at four sites. At 3 of the 4 sites, water quality has been monitored continuously for selected constituents and physical properties. These discrete water-quality samples and continuous water-quality monitoring data (from July 2012 to 2020) have been collected to better understand the water quality of the Missouri River, how it is changing with time, how it changes upstream from the city of Omaha to downstream, and how it varies during base-flow conditions and during periods of runoff. The purpose of this report is to document the development of Escherichia coli ( E. coli ) concentration models for these four Missouri River sites. Analysis was completed using the first 5 years of data (through 2016) to determine if the current approach is sufficient to meet future analysis goals and to understand if proposed models such as Load Estimator (LOADEST) models will be able to represent water-quality changes in the Missouri River. Multiple linear regression models were developed to estimate E. coli concentration using LOADEST as implemented in the rloadest package in the R statistical software program. A set of explanatory variables, including streamflow and streamflow anomalies, precipitation, information about CSOs, and continuous water quality, were evaluated for potential inclusion in regression models. The best model at Missouri River at NP Dodge Park at Omaha, Nebr. (USGS station 412126095565201; hereafter “NP Dodge”) included basin explanatory variables of upstream antecedent precipitation index measured at Tekamah, Nebr.; decimal time; season; and turbidity. The best model at Missouri River at Freedom Park Omaha, Nebr. (USGS station 411636095535401; hereafter “Freedom Park”) included the same explanatory variables as the NP Dodge model with the addition of turbidity anomalies and flow anomalies. The best models at the two downstream sites (Missouri River near Council Bluffs, Iowa, USGS station 06610505 and Missouri River near La Platte, Nebr., USGS station 410333095530101) included the same explanatory variables as the Freedom Park model with the addition of local antecedent precipitation index as measured at Eppley Airport in Omaha, Nebr., and additional turbidity and flow anomalies. The final selected models were the best models given our modeling design constraint in which explanatory variables included in the model for the upstream site were included in the downstream models. Explanatory variables currently (2020) being collected and included in the selected models through 2016 explained 64–75 percent of the variability of E. coli concentration in the Missouri River. Explaining 64–75 percent of the variability might be considered low when working with physical constituents (total nitrogen or sediment), but with the natural variability of biological constituents such as E. coli , the uncertainty of E. coli laboratory measurements, and the added complexity of modeling in a large drainage basin with multiple sources, these results are adequate and indicate that the explanatory variables being collected and models such as LOADEST can represent water-quality changes in the Missouri River for E. coli concentration from 2012 to 2016.

Nebraska↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for North Bamyan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

North Bamyan Mineral District↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Parwan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the North Bamyan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Parwan Mineral District↗

USGS1999

Hydrogeology and analysis of aquifer characteristics in west-central Pinellas County, Florida

The U.S. Geological Survey, in cooperation with Pinellas County, Florida, conducted an investigation to describe the hydrogeology and analyze the aquifer characteristics in west-central Pinellas County. A production test well and four monitor wells were constructed in Pinellas County at Walsingham Park during 1996-97. Water-quality sampling, static and dynamic borehole geophysical surveys, and hydraulic tests were conducted at the wells to delineate the hydrogeology at Walsingham Park. A 9-day aquifer test was conducted to determine the hydraulic characteristics of the aquifer system and observe the changes in water quality due to pumping. A numerical model was constructed to simulate the aquifer test and calculate values for hydraulic conductivity and storage coefficient for permeable zones and confining units at Walsingham Park. Final calibrated values for hydraulic conductivity for the different permeable zones and confining units at the test site were 18 feet per day for Upper Zone A, 750 feet per day for Lower Zone A, 1 foot per day for Zone B, 1x10-4 feet per day for the intermediate confining unit, and 10 feet per day for the semiconfining unit separating Upper Zone A and Lower Zone A. Final calibrated values for storage coefficient were 3.1x10-4 for Upper Zone A, 8.6x10-5 for Lower Zone A, 2.6x10-5 for Zone B, 3.1x10-4 for the intermediate confining unit, and 4.3x10-5 for the semiconfining unit separating Upper Zone A and Lower Zone A. Estimates of transmissivity for Upper Zone A and Lower Zone A were about 2,500 and 37,500 feet squared per day, respectively.

Florida↗

USGS2008

Brain aromatase (Cyp19A2) and estrogen receptors, in larvae and adult pejerrey fish Odontesthes bonariensis: Neuroanatomical and functional relations

Although estrogens exert many functions on vertebrate brains, there is little information on the relationship between brain aromatase and estrogen receptors. Here, we report the cloning and characterization of two estrogen receptors, ?? and ??, in pejerrey. Both receptors' mRNAs largely overlap and were predominantly expressed in the brain, pituitary, liver, and gonads. Also brain aromatase and estrogen receptors were up-regulated in the brain of estradiol-treated males. In situ hybridization was performed to study in more detail, the distribution of the two receptors in comparison with brain aromatase mRNA in the brain of adult pejerrey. The estrogen receptors' mRNAs exhibited distinct but partially overlapping patterns of expression in the preoptic area and the mediobasal hypothalamus, as well as in the pituitary gland. Moreover, the estrogen receptor ??, but not ??, were found to be expressed in cells lining the preoptic recess, similarly as observed for brain aromatase. Finally, it was shown that the onset expression of brain aromatase and both estrogen receptors in the head of larvae preceded the morphological differentiation of the gonads. Because pejerrey sex differentiation is strongly influenced by temperature, brain aromatase expression was measured during the temperature-sensitive window and was found to be significantly higher at male-promoting temperature. Taken together these results suggest close neuroanatomical and functional relationships between brain aromatase and estrogen receptors, probably involved in the sexual differentiation of the brain and raising interesting questions on the origin (central or peripheral) of the brain aromatase substrate. ?? 2008 Elsevier Inc.

General and Comparative Endocrinology↗

USGS2015

Resilience and risk: a demographic model to inform conservation planning for polar bears

Climate change is having widespread ecological effects, including loss of Arctic sea ice. This has led to listing of the polar bear ( Ursus maritimus ) and other ice-dependent marine mammals under the U.S. Endangered Species Act (ESA). Methods are needed to evaluate the effects of climate change on population persistence to inform recovery planning for listed species. For polar bears, this includes understanding interactions between climate and secondary factors, such as subsistence harvest, which provide economic, nutritional, or cultural value to humans. We developed a matrix-based demographic model for polar bears that can be used for population viability analysis and to evaluate the effects of human-caused removals. This model includes density-dependence (the potential for a declining environmental carrying capacity), density-independent limitation, and sex- and age-specific harvest vulnerabilities. We estimated values of adult female survival (0.93–0.96), recruitment (number of yearling cubs per adult female; 0.1–0.3), and carrying capacity (>250 animals) that must be maintained for a hypothetical population to achieve a 90-percent probability of persistence over 100 years. We also developed a state-dependent management framework, based on harvest theory and the potential biological removal method, by linking the demographic model to simulated population assessments. This framework can be used to estimate the maximum sustainable rate of human-caused removals, including subsistence harvest, which maintains a population at its maximum net productivity level. The framework also can be used to calculate a recommended sustainable harvest rate, which generally is lower than the maximum sustainable rate and depends on management objectives, the precision and frequency of population data, and risk tolerance. The historical standard 4.5-percent harvest rate for polar bears, at a 2:1 male-to-female ratio, is reasonable under many biological and management conditions, although lower or higher rates may be appropriate in some cases. Our modeling results suggest that harvest of polar bears is unlikely to accelerate population declines that result from declining carrying capacity caused by sea-ice loss, provided that several conditions are met: (1) the sustainable harvest rate reflects the population’s intrinsic growth rate, and the corresponding harvest level is obtained by applying this rate to an estimate of population size; (2) the sustainable harvest rate reflects the quality of population data (e.g., lower harvest when data are poor); and (3) the level of human-caused removals can be adjusted. Finally, our results suggest that stopgap measures (e.g., further reduction or cessation of harvest when the population size is less than a critical threshold) may be necessary to minimize the incremental risk associated with harvest, if environmental conditions are deteriorating rapidly. We suggest that the demographic model and approaches presented here can serve as a template for conservation planning for polar bears and other species facing similar challenges.

Open-File Report↗

USGS2005

Development of property-transfer models for estimating the hydraulic properties of deep sediments at the Idaho National Engineering and Environmental Laboratory, Idaho

Because characterizing the unsaturated hydraulic properties of sediments over large areas or depths is costly and time consuming, development of models that predict these properties from more easily measured bulk-physical properties is desirable. At the Idaho National Engineering and Environmental Laboratory, the unsaturated zone is composed of thick basalt flow sequences interbedded with thinner sedimentary layers. Determining the unsaturated hydraulic properties of sedimentary layers is one step in understanding water flow and solute transport processes through this complex unsaturated system. Multiple linear regression was used to construct simple property-transfer models for estimating the water-retention curve and saturated hydraulic conductivity of deep sediments at the Idaho National Engineering and Environmental Laboratory. The regression models were developed from 109 core sample subsets with laboratory measurements of hydraulic and bulk-physical properties. The core samples were collected at depths of 9 to 175 meters at two facilities within the southwestern portion of the Idaho National Engineering and Environmental Laboratory-the Radioactive Waste Management Complex, and the Vadose Zone Research Park southwest of the Idaho Nuclear Technology and Engineering Center. Four regression models were developed using bulk-physical property measurements (bulk density, particle density, and particle size) as the potential explanatory variables. Three representations of the particle-size distribution were compared: (1) textural-class percentages (gravel, sand, silt, and clay), (2) geometric statistics (mean and standard deviation), and (3) graphical statistics (median and uniformity coefficient). The four response variables, estimated from linear combinations of the bulk-physical properties, included saturated hydraulic conductivity and three parameters that define the water-retention curve. For each core sample,values of each water-retention parameter were estimated from the appropriate regression equation and used to calculate an estimated water-retention curve. The degree to which the estimated curve approximated the measured curve was quantified using a goodness-of-fit indicator, the root-mean-square error. Comparison of the root-mean-square-error distributions for each alternative particle-size model showed that the estimated water-retention curves were insensitive to the way the particle-size distribution was represented. Bulk density, the median particle diameter, and the uniformity coefficient were chosen as input parameters for the final models. The property-transfer models developed in this study allow easy determination of hydraulic properties without need for their direct measurement. Additionally, the models provide the basis for development of theoretical models that rely on physical relationships between the pore-size distribution and the bulk-physical properties of the media. With this adaptation, the property-transfer models should have greater application throughout the Idaho National Engineering and Environmental Laboratory and other geographic locations.

Idaho↗

USGS1978

Preliminary appraisal of the geohydrologic aspects of drainage wells, Orlando area, central Florida

The Floridan aquifer contains two highly transmissive cavernous zones in the Orlando area: an upper producing zone about 150-600 feet below land surface; and a lower producing zone about 1,100-1,500 feet below land surface. Natural head differences are downward and there is hydraulic connection between the two producing zones. Drainage wells are finished open-end into the upper producing zone and emplace surface waters directly into that zone by gravity. Quantitatively, their use constitutes an effective method of artificial recharge. Their negative aspects relate to the probably poor, but unknown, quality of the recharge water. Caution is suggested in drawing definite and final conclusions on the overall geohydrologic and environmental effects of drainage wells prior to the collection and interpretation of a considerable quantity of new data. Though few ground-water pollution problems have been documented to date, the potential for such pollution should be seriously considered in light of the prob-able continuing need to use drainage wells; the probable volumes and quality of water involved; and the hydraulic relations between the two producing zones.

Florida↗

USGS2003

The effect of time on the weathering of silicate minerals: Why do weathering rates differ in the laboratory and field?

The correlation between decreasing reaction rates of silicate minerals and increasing duration of chemical weathering was investigated for both experimental and field conditions. Column studies, using freshly prepared Panola Granite, produced ambient plagioclase weathering rates that decreased parabolically over 6 years to a final rate of 7.0×10 −14 mol m −2 s −1 . In contrast, the corresponding plagioclase reaction rate for partially kaolinized Panola Granite, after reaching steady-state weathering after 2 months of reactions, was significantly less (2.1×10 −15 mol m −2 s −1 ). Both rates were normalized to plagioclase content and BET surface area. Extrapolation of decreasing rates for the fresh plagioclase with time indicated that several thousand years of reaction would be required to replicate the rate of the naturally weathered plagioclase under identical experimental conditions. Both rates would remain orders of magnitude faster than field weathering rates previously measured for a weathering profile in the Panola Granite. Additional trends in weathering rates with time were established from a tabulation of previously reported experimental and field rates for plagioclase, K-feldspar, hornblende and biotite. Discrepancies in the literature, produced by normalization of weathering rates with respect to surface areas measured by gas absorption (BET) and geometric methods, were overcome by developing a time-dependent roughness factor. Regression curves through the corrected rates produced strong correlations with time that were similar for the four silicate minerals. The average silicate weathering rate R (mol m −2 s −1 ) was described by the power function R=3.1×10 −13 t −0.61 "> R=3.1×10 -13 t -0.61 which was similar to the relationship describing the decrease in the fresh Panola plagioclase with time and suggesting control by transport-limited reaction. The time dependency of silicate weathering is discussed in terms of processes intrinsic to the silicate mineral and those extrinsic to the weathering environment. Intrinsic surface area, which increases with the duration of weathering, was shown to account for a third of the exponential decrease in the weathering rate shown by the above equation. Other factors, including progressive depletion of energetically reactive surfaces and accumulation of leached layers and secondary precipitates, must explain differences for fresh and weathered plagioclase reacting under identical experimental conditions. Extrinsic controls, including low permeability, high mineral/fluid ratios and increased solute concentrations, produce weathering reactions close to thermodynamic equilibrium under field conditions compared to highly unsaturated conditions during experimental reaction of fresh and weathered plagioclase. These differences explain the time-dependent difference in field and lab rates.

Chemical Geology↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Baghlan) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Baghlan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Baghlan Mineral District↗

USGS2013

Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for Bakhud) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the Bakhud area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.

Data Series↗