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At least 397 records · Page 22Linked to original sources
USGS2005

Upper Auglaize watershed AGNPS modeling project

The Upper Auglaize Watershed agricultural non-point source modeling project was an interagency effort to use a Geographic Information System (GIS)-based modeling approach for assessing and reducing pollution from agricultural runoff and other non-point sources. This project applied the U.S. Department of Agriculture (USDA), Agricultural Research Service’s AGricultural Non-Point Source (AGNPS) suite of models to the Upper Auglaize River Watershed, a major watershed within the Maumee River Basin. This modeling project was conducted by an interagency team consisting of a partnership between the: (1) USDA, Agricultural Research Service (ARS); (2) USDA, Natural Resources Conservation Service (NRCS); (3) U.S. Army Corps of Engineers (USACE); (4) U.S. Geological Survey (USGS); (5) Ohio State University; (6) University of Toledo (UT); (7) Heidelberg College; (8) Ohio Department of Natural Resources (ODNR), Division of Soil and Water Conservation; (9) Ohio Environmental Protection Agency (OEPA); and (10) Allen, Auglaize, Van Wert, and Putnam Soil and Water Conservation Districts. The partnership was the first step in a process to eventually apply the model in a portioned subset of watersheds for the Maumee Basin, and then to link them to form a comprehensive basin-wide model This work was performed under the authority of Section 516(e) of the Water Resources Development Act (WRDA) of 1996, as amended, for the purpose of assisting State and local watershed managers with their evaluation, prioritization and implementation of alternatives for soil conservation, sediment trapping and non-point source pollution prevention in the Upper Auglaize River watershed. The project team, working in a cooperative effort, used the models to determine sediment sources, contributing locations, and the effect of application of best management practices (BMPs) on rates of sediment delivery to the mouth of the watershed. The results will be used to guide conservation incentive and land treatment programs. The team relied heavily on Geographic Information System (GIS)-based applications to expedite the application of the model. The results of the analysis demonstrated that the application of BMPs would have a positive effect on reducing the loadings of sediment leaving the mouth of the Upper Auglaize Watershed. An application of 17 percent new no-till acres and eight percent new grassland acres, when randomly applied to the watershed, reduced loadings at the mouth to 82 percent of the simulated existing condition loadings. No-till, conversion of cropland to grassland, other uses including grass buffers, and reforestation of parts of the watershed, were all shown by the model to have a measurable effect on reducing sediment loads. Conversion of all of the cropland in the watershed to no-till would reduce the average unit load (tons of sediment per acre) leaving the mouth of the watershed to a level that is 42 percent of the simulated existing condition load. Ephemeral gullies were found to be the primary source of erosion (72 percent), sediment yield (73 percent), and sediment loading (73 percent). Controlling sediment load means controlling gully erosion and possibly trapping sediment yield before it reaches the stream system. Most BMPs (e.g., no-till, conversion of cropland, etc.) that reduce sheet and rill erosion and its sediment yield will also reduce gully erosion and its sediment yield. However, grassed waterways, which have no effect on sheet and rill erosion, are frequently an effective BMP to prevent ephemeral gullies. And, of course, riparian vegetation and sediment traps would reduce the delivery ratios of all types of landscape erosion. New techniques were developed by the team to quantify the ephemeral gully erosion within the model. When calibrated to available stream gage data the model suggests that more (73% in the existing condition simulation) of the sediment load originates from ephemeral gully erosion than from traditional sheet and rill erosion. The model quantified the value of tile drainage in reducing the sediment load from the watershed. Loadings under drained conditions were always less than loadings under undrained conditions for otherwise identical land uses. The average sediment load of all alternatives for drained loadings was 89.2 percent of the load for the corresponding undrained loadings. The model established that while many conservation incentive programs treat tile drainage as a production practice, significant erosion and sediment control benefits are provided by the practice in comparison to cultivation in an undrained state.

Ohio↗
USGS1996

Assessment of severity and distribution of corrosive ground water in Pennsylvania

Relations between corrosive ground water, water chemistry, and geology in Pennsylvania were evaluated by use of a modified version of the Langelier Saturation Index (LSIsn) and a geologic contact dataset in a Geographic Information System. Water-chemistry information for water samples collected from 4,839 combined private and public-supply wells from 1900 to 1993 was used to calculate the LSIsn. Thirty-eight lithologic subgroups within four major rock types-carbonate, siliciclastic, crystalline, and unconsolidated-in Pennsylvania were grouped together if the mean of ranked LSIsn values were not significantly different. A water is considered corrosive if the LSIsn value is negative, preventing the precipitation of calcium carbonate, therefore, allowing corrosive reactions with the interior of piping systems. Statistical tests of the LSIsn values show the least corrosive waters are in the carbonate lithologic subgroup, and the most corrosive waters are in the quartzite lithologic subgroup. Approximately 58 percent of the 4,839 LSIsn values were considered moderately to extremely corrosive. A map showing the location of 4,839 wells and associated corrosivity range within 11 lithologic subgroups will aid in identifying potential areas of corrosive ground water in Pennsylvania.

Open-File Report↗
USGS2016

Flood-inundation map library for the Licking River and South Fork Licking River near Falmouth, Kentucky

Digital flood inundation maps for a 17-mile reach of Licking River and 4-mile reach of South Fork Licking River near Falmouth, Kentucky, were created by the U.S. Geological Survey (USGS) in cooperation with Pendleton County and the U.S. Army Corps of Engineers–Louisville District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Licking River at Catawba, Ky., (station 03253500) and the USGS streamgage on the South Fork Licking River at Hayes, Ky., (station 03253000). Current conditions (2015) for the USGS streamgages may be obtained online at the USGS National Water Information System site ( http://waterdata.usgs.gov/nwis ). In addition, the streamgage information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http:/water.weather.gov/ahps/ ). The flood hydrograph forecasts provided by the NWS are usually collocated with USGS streamgages. The forecasted peak-stage information, also available on the NWS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the Licking River reach and South Fork Licking River reach by using a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current (2015) stage-discharge relations for the Licking River at Catawba, Ky., and the South Fork Licking River at Hayes, Ky., USGS streamgages. The calibrated model was then used to calculate 60 water-surface profiles for a sequence of flood stages, at 2-foot intervals, referenced to the streamgage datum and ranging from an elevation near bankfull to the elevation associated with a major flood that occurred in the region in 1997. To delineate the flooded area at each interval flood stage, the simulated water-surface profiles were combined with a digital elevation model of the study area by using geographic information system software. The availability of these flood inundation maps for Falmouth, Ky., along with online information regarding current stages from the USGS streamgages and forecasted stages from the NWS, provides emergency management personnel and local residents with information that is critical for flood response activities such as evacuations, road closures, and post-flood recovery efforts.

Kentucky↗
USGS2019

Determination of study reporting limits for pesticide constituent data for the California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project, 2004–2018—Part 1: National Water Quality Schedules 2003, 2032, or 2033, and 2060

The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) is a long-term cooperative project designed to assess the quality of groundwater resources used for public and domestic drinking water supplies in the State of California, to monitor and evaluate changes to that quality, to investigate the human and natural factors controlling water quality, and to improve the availability of comprehensive groundwater quality data and information. Between May 18, 2004, and May 3, 2018, the GAMA-PBP collected 3001 groundwater samples for analysis of pesticide constituents by the U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL)(note that ‘pesticide constituents’ includes parent compounds and degradates). Of these samples, 2994 were analyzed for pesticide constituents on schedules 2003, 2032, or 2033 (65 to 84 constituents), and 840 were analyzed for pesticide constituents on schedule 2060 (58 constituents). The original dataset reported by the NWQL to the USGS National Water Information System (NWIS) database contained a total of 2,688 detections of 78 pesticide constituents and 253,825 non-detections. In this original dataset, 33 percent of the 3,001 samples analyzed had reported detections of one or more pesticide constituents. This report describes the GAMA-PBP data-quality objectives for pesticide data, the procedures used to establish study reporting limits, and use of those reporting limits to censor the data from the NWQL so that the final data published by the GAMA-PBP meet these data-quality objectives. The final GAMA-PBP dataset for samples collected from May 2004 to May 2018, after censoring, had a total of 1,632 detections of 37 pesticide constituents. In the final GAMA-PBP dataset, 25 percent of the 3,001 samples analyzed had detections of one or more pesticide constituents. The presence of pesticides in groundwater is commonly evaluated by calculating detection frequencies. Detection frequencies for pesticides are sensitive to detection limits and method performance for concentrations near those limits; therefore, the two primary data quality issues addressed in the GAMA-PBP data-quality objectives for pesticides are (1) establishing criteria for classifying data from the laboratory as detections or non-detections for the purpose of data reporting by the project and (2) accounting for changes in analytical methods or method performance over time. The GAMA-PBP addresses these issues by developing study reporting limits that are used as the boundary between detections and non-detections for the reporting of GAMA-PBP results. These reporting limits are defined from method detection limits (MDLs) provided by the NWQL, unless examination of results from laboratory set blanks (LSBs) and GAMA-PBP field blanks indicates that a higher concentration censoring limit is warranted. The GAMA-PBP selected the MDL as the primary choice for defining study reporting limits for consistency with U.S. Environmental Protection Agency (EPA) guidelines for reporting detections of pesticides and other organic constituents. A five-step procedure is used to develop study reporting limits and censor the GAMA-PBP dataset accordingly. The effect of the censoring at each step is described to provide information about the relative effect of each step on the overall censoring of the dataset. Steps 1 and 2 can be implemented at the time the data are received, whereas steps 3−5 require information accumulated over an extended period. Step 1: Reject results that were most likely the result of specific contamination instances attributable to unusual field or laboratory conditions during sample collection or processing. Two such instances were identified, leading to rejection of 25 detections, which were assigned a data-quality indicator code of “Q” for “reviewed and rejected” in the NWIS database. Step 2: Use the NWQL MDLs in effect at the time each sample was analyzed as the reporting limit. A total of 506 detections were censored on this basis. Step 3: Use the maximum MDL established by the NWQL during July 2004–August 2018 (MDLmax) as the reporting limit. The rationale for using the MDLmax as the reporting limit is based primarily on the observation that the concentrations of MDLs generally increased over time. A total of 438 detections were censored on this basis. Step 4: Use the LSBs to identify periods of greater potential laboratory contamination bias and define raised reporting limits to be used during those periods. These periods were defined by using a moving average detection frequency approach. For consistency with the NWQL procedures for defining raised reporting limits on the basis of detections in LSBs, the raised reporting limits were defined as equal to three times the highest concentration measured in an LSB during the period. A total of 25 detections in groundwater samples analyzed during periods of increased laboratory contamination bias were censored. Step 5: Use the LSBs and field blanks to identify potential contamination bias from field or laboratory processes outside of the time periods identified in step 4. The NWQL protocols were used to define the MDLs from blanks analyzed outside of the periods identified in step 4. If an MDL defined from blanks was greater than the MDLmax, the MDL defined from blanks was used to censor the data. One constituent had a study reporting limit defined on this basis, and a total of 62 detections in groundwater samples were censored. As of 2019, the USGS NWIS database does not have the capability to store both the original value reported by the NWQL and the final value published by the GAMA-PBP that reflects application of the quality-control censoring described in this report. In the interim, while this capability is developed, the 1,031 results censored in steps 2−5 are blocked from public release in NWIS, and the GAMA-PBP has published the original and final values in a USGS data release accompanying this report. The entire GAMA-PBP final dataset for pesticide constituents on schedules 2003, 2032, or 2033, or on schedule 2060 is publicly available in that USGS data release, through the USGS GAMA-PBP public web portal, and through the California State Water Resources Control Board GAMA public groundwater information system.

California↗
USGS2003

Precipitation-Runoff Simulations of Current and Natural Streamflow Conditions in the Methow River Basin, Washington

Management of the water resources of the Methow River Basin is changing in response to the listing of three species of fish under the Endangered Species Act and the Washington State-legislated watershed-planning process. This report describes the construction and calibration of an enhanced precipitation-runoff model for the Methow River Basin and evaluates the model as a predictive tool for assessing the current and natural streamflow conditions. This study builds upon a previous precipitation-runoff model for the Methow River Basin and validates the current model using a new, more extensive streamflow data network. The major enhancement was the simulation of current flow conditions with the addition of irrigation diversions, returns, and application. The Geographic Information System Weasel characterized the physical properties of the basin and the Modular Modeling System, using the Precipitation-Runoff Modeling System, simulated the hydrologic flow. Streamflow was simulated for water years 1992-2001 to calibrate the model to measured streamflows. A sensitivity analysis was completed using nonlinear regression to determine hydrologic parameters pertinent to the modeling results. Simulated and measured streamflow generally showed close agreement, especially during spring runoff from snowmelt. Low-flow or baseflow periods, most restrictive to fish habitation, were simulated reasonably well yet possessed the most uncertainty. Simulations of annual mean streamflow as a percentage of measured annual mean streamflow for the 10-year calibration period at six of the seven streamflow-gaging stations ranged from -35.2 to +26.2 percent, with 65 percent of the simulated values within 15 percent. One station was intentionally calibrated to over-simulate discharge (simulated discharge greater than measured discharge) in order to compensate for observed channel losses not simulated by the model. Simulation of water years 1960-2001 demonstrated great variability in monthly streamflow statistics. The simulated mean monthly flows for 11 streamflow-gaging stations were an average of 2.5 percent higher for water years 1992-2001 than for the entire simulation period. If water year 2001, an extreme drought year, is omitted, simulated mean monthly flows for the 11 streamflow-gaging stations were an average of 9.0 percent higher than for the entire simulation period. The calibrated model also examined the effects of irrigation-canal seepage on streamflow. Irrigation-canal seepage contributed to streamflow throughout the year, with the greatest effect during the irrigation season. Management of the water resources of the Methow River Basin is changing in response to the listing of three species of fish under the Endangered Species Act and the Washington State-legislated watershed-planning process. This report describes the construction and calibration of an enhanced precipitation-runoff model for the Methow River Basin and evaluates the model as a predictive tool for assessing the current and natural streamflow conditions. This study builds upon a previous precipitation-runoff model for the Methow River Basin and validates the current model using a new, more extensive streamflow data network. The major enhancement was the simulation of current flow conditions with the addition of irrigation diversions, returns, and application. The Geographic Information System Weasel characterized the physical properties of the basin and the Modular Modeling System, using the Precipitation-Runoff Modeling System, simulated the hydrologic flow. Streamflow was simulated for water years 1992-2001 to calibrate the model to measured streamflows. A sensitivity analysis was completed using nonlinear regression to determine hydrologic parameters pertinent to the modeling results. Simulated and measured streamflow generally showed close agreement, especially during spring runoff from snowmelt. Low-flow or baseflow periods, most restrictive to fish habitation

Water-Resources Investigations Report↗
USGS2016

Methods for estimating selected spring and fall low-flow frequency statistics for ungaged stream sites in Iowa, based on data through June 2014

A statewide study was led to develop regression equations for estimating three selected spring and three selected fall low-flow frequency statistics for ungaged stream sites in Iowa. The estimation equations developed for the six low-flow frequency statistics include spring (April through June) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and fall (October through December) 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years. Estimates of the three selected spring statistics are provided for 241 U.S. Geological Survey continuous-record streamgages, and estimates of the three selected fall statistics are provided for 238 of these streamgages, using data through June 2014. Because only 9 years of fall streamflow record were available, three streamgages included in the development of the spring regression equations were not included in the development of the fall regression equations. Because of regulation, diversion, or urbanization, 30 of the 241 streamgages were not included in the development of the regression equations. The study area includes Iowa and adjacent areas within 50 miles of the Iowa border. Because trend analyses indicated statistically significant positive trends when considering the period of record for most of the streamgages, the longest, most recent period of record without a significant trend was determined for each streamgage for use in the study. Geographic information system software was used to measure 63 selected basin characteristics for each of the 211streamgages used to develop the regional regression equations. The study area was divided into three low-flow regions that were defined in a previous study for the development of regional regression equations. Because several streamgages included in the development of regional regression equations have estimates of zero flow calculated from observed streamflow for selected spring and fall low-flow frequency statistics, the final equations for the three low-flow regions were developed using two types of regression analyses—left-censored and generalized-least-squares regression analyses. A total of 211 streamgages were included in the development of nine spring regression equations—three equations for each of the three low-flow regions. A total of 208 streamgages were included in the development of nine fall regression equations—three equations for each of the three low-flow regions. A censoring threshold was used to develop 15 left-censored regression equations to estimate the three fall low-flow frequency statistics for each of the three low-flow regions and to estimate the three spring low-flow frequency statistics for the southern and northwest regions. For the northeast region, generalized-least-squares regression was used to develop three equations to estimate the three spring low-flow frequency statistics. For the northeast region, average standard errors of prediction range from 32.4 to 48.4 percent for the spring equations and average standard errors of estimate range from 56.4 to 73.8 percent for the fall equations. For the northwest region, average standard errors of estimate range from 58.9 to 62.1 percent for the spring equations and from 83.2 to 109.4 percent for the fall equations. For the southern region, average standard errors of estimate range from 43.2 to 64.0 percent for the spring equations and from 78.1 to 78.7 percent for the fall equations. The regression equations are applicable only to stream sites in Iowa with low flows not substantially affected by regulation, diversion, or urbanization and with basin characteristics within the range of those used to develop the equations. The regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system application. StreamStats allows users to click on any ungaged stream site and compute estimates of the six selected spring and fall low-flow statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged site are provided. StreamStats also allows users to click on any Iowa streamgage to obtain computed estimates for the six selected spring and fall low-flow statistics.

Iowa↗
USGS2008

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.

Scientific Investigations Report↗
USGS2011

An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.

Florida↗
USGS2018

Clarifying regional hydrologic controls of the Marañón River, Peru through rapid assessment to inform system-wide basin planning approaches

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.

Marañón River↗
USGS2009

Archive of digital boomer and CHIRP seismic reflection data collected during USGS field activity 08LCA03 in Lake Panasoffkee, Florida, May 2008

In May of 2008, the U.S. Geological Survey (USGS) conducted geophysical surveys in Lake Panasoffkee, located in central Florida, as part of the USGS Lakes and Coastal Aquifers (LCA) study. This report serves as an archive of unprocessed digital boomer and Compressed High Intensity Radar Pulse (CHIRP)* seismic reflection data, trackline maps, navigation files, Field Activity Collection System (FACS) logs, Geographic Information System (GIS) files, and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (a relative increase in signal amplitude) digital images of the seismic profiles and geospatially corrected interactive profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report. *Due to poor data acquisition conditions associated with the lake bottom sediments, only two CHIRP tracklines were collected during this field activity. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Example SU processing scripts and USGS software for viewing the SEG-Y files (Zihlman, 1992) are provided. The USGS Florida Integrated Science Center (FISC) - St. Petersburg assigns a unique identifier to each cruise or field activity. For example, 08LCA03 tells us the data were collected in 2008 for the Lakes and Coastal Aquifers (LCA) study and the data were collected during the third field activity for that study in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. The naming convention used for each seismic line is as follows: yye##a, where 'yy' are the last two digits of the year in which the data were collected, 'e' is a 1-letter abbreviation for the equipment type (for example, b for boomer and c for CHIRP), '##' is a 2-digit number representing a specific track, and 'a' is a letter representing the section of a line if recording was prematurely terminated or rerun for quality or acquisition problems. The boomer plate is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and, when discharged, emits a short acoustic pulse, or shot, which propagates through the water, sediment column, or rock beneath. The acoustic energy is reflected at density boundaries (such as the seafloor, sediment, or rock layers beneath the seafloor), detected by the receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). In this way, a two-dimensional (2-D) vertical profile of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the boomer acquisition geometry. The EdgeTech SB-424 CHIRP system used for this survey has a vertical resolution of 4 - 8 cm, a penetration depth that is usually less than 2 m beneath the seafloor, and uses a signal of continuously varying frequency. The towfish is a sound source and receiver, which is typically towed 2 - 5 m above the seafloor. The acoustic energy is reflected at density boundaries (such as the seafloor or sediment layers beneath the seafloor), detected by a receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.125 s) and recorded for specific intervals of time (for example, 50 ms); the resulting profile is a two-dimensional vertical image of the shallow geologic structure beneath the ship track. Figure 2 displays the acquisition geometry for the CHIRP system. Refer to table 1 for a summary of acquisition parameters and table 2 for trackline statistics.

Florida↗
USGS2010

Analysis of California Condor (Gymnogyps californianus) use of six management units using location data from global positioning system transmitters, southern California, 2004-09-Initial report

This report provides an analysis of California Condor (Gymnogyps californianus) space use of six management units in southern California (Hopper Mountain and Bitter Creek National Wildlife Refuges, Wildlands Conservancy-Wind Wolves Preserve, Tejon Mountain Village Specific Plan, California Condor Study Area, and the Tejon Ranch excluding Tejon Mountain Village Specific Plan and California Condor Study Area). Space use was analyzed to address urgent management needs using location data from Global Positioning System transmitters. The U.S. Fish and Wildlife Service provided the U.S. Geological Survey with location data (2004-09) for California Condors from Global Positioning System transmitters and Geographic Information System data for the six management units in southern California. We calculated relative concentration of use estimates for each management unit for each California Condor (n = 21) on an annual basis (n = 39 annual home ranges) and evaluated resource selection for the population each year using the individual as our sampling unit. The most striking result from our analysis was the recolonization of the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units during 2008. During 2004-07, the home range estimate for two (25 percent) California Condors overlapped the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units (n = 8), and use within the annual home range generally was bimodal and was concentrated on the Bitter Creek and Hopper Mountain National Wildlife Refuges. However, 10 (77 percent) California Condor home ranges overlapped the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units during 2008 (n = 13), and by 2009, the home range of every condor carrying a Global Positioning System transmitter (n = 14) overlapped these management units. Space use was multimodal within the home range during 2008-09 and was concentrated on Hopper Mountain Refuge in the south, Bittercreek Refuge and the Wind Wolves Preserve in the northwest, and the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units in the northeast. Recolonization of the Tejon Mountain Village Specific Plan, California Condor Study Area, and Tejon Ranch management units reestablished traditional condor movement and foraging patterns in southern California and provides the travel corridor (approximately 20 kilometers wide) for recolonization of the northeastern part of the species historical range.

Open-File Report↗