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USGS2014

Hydrogeologic framework and occurrence, movement, and chemical characterization of groundwater in Dixie Valley, west-central Nevada

Dixie Valley, a primarily undeveloped basin in west-central Nevada, is being considered for groundwater exportation. Proposed pumping would occur from the basin-fill aquifer. In response to proposed exportation, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation and Churchill County, conducted a study to improve the understanding of groundwater resources in Dixie Valley. The objective of this report is to characterize the hydrogeologic framework, the occurrence and movement of groundwater, the general water quality of the basin-fill aquifer, and the potential mixing between basin-fill and geothermal aquifers in Dixie Valley. Various types of geologic, hydrologic, and geochemical data were compiled from previous studies and collected in support of this study. Hydrogeologic units in Dixie Valley were defined to characterize rocks and sediments with similar lithologies and hydraulic properties influencing groundwater flow. Hydraulic properties of the basin-fill deposits were characterized by transmissivity estimated from aquifer tests and specific-capacity tests. Groundwater-level measurements and hydrogeologic-unit data were combined to create a potentiometric surface map and to characterize groundwater occurrence and movement. Subsurface inflow from adjacent valleys into Dixie Valley through the basin-fill aquifer was evaluated using hydraulic gradients and Darcy flux computations. The chemical signature and groundwater quality of the Dixie Valley basin-fill aquifer, and potential mixing between basin-fill and geothermal aquifers, were evaluated using chemical data collected from wells and springs during the current study and from previous investigations. Dixie Valley is the terminus of the Dixie Valley flow system, which includes Pleasant, Jersey, Fairview, Stingaree, Cowkick, and Eastgate Valleys. The freshwater aquifer in the study area is composed of unconsolidated basin-fill deposits of Quaternary age. The basin-fill hydrogeologic unit can be several orders of magnitude more transmissive than surrounding and underlying consolidated rocks and Dixie Valley playa deposits. Transmissivity estimates in the basin fill throughout Dixie Valley ranged from 30 to 45,500 feet squared per day; however, a single transmissivity value of 0.1 foot squared per day was estimated for playa deposits. Groundwater generally flows from the mountain range uplands toward the central valley lowlands and eventually discharges near the playa edge. Potentiometric contours east and west of the playa indicate that groundwater is moving eastward from the Stillwater Range and westward from the Clan Alpine Mountains toward the playa. Similarly, groundwater flows from the southern and northern basin boundaries toward the basin center. Subsurface groundwater flow likely enters Dixie Valley from Fairview and Stingaree Valleys in the south and from Jersey and Pleasant Valleys in the north, but groundwater connections through basin-fill deposits were present only across the Fairview and Jersey Valley divides. Annual subsurface inflow from Fairview and Jersey Valleys ranges from 700 to 1,300 acre-feet per year and from 1,800 to 2,300 acre-feet per year, respectively. Groundwater flow between Dixie, Stingaree, and Pleasant Valleys could occur through less transmissive consolidated rocks, but only flow through basin fill was estimated in this study. Groundwater in the playa is distinct from the freshwater, basin-fill aquifer. Groundwater mixing between basin-fill and playa groundwater systems is physically limited by transmissivity contrasts of about four orders of magnitude. Total dissolved solids in playa deposit groundwater are nearly 440 times greater than total dissolved solids in the basin-fill groundwater. These distinctive physical and chemical flow restrictions indicate that groundwater interaction between the basin fill and playa sediments was minimal during this study period (water years 2009–11). Groundwater in Dixie Valley generally can be characterized as a sodium bicarbonate type, with greater proportions of chloride north of the Dixie Valley playa, and greater proportions of sulfate south of the playa. Analysis of major ion water chemistry data sampled during the study period indicates that groundwater north and south of Township 22N differ chemically. Dixie Valley groundwater quality is marginal when compared with national primary and secondary drinking-water standards. Arsenic and fluoride concentrations exceed primary drinking water standards, and total dissolved solids and manganese concentrations exceed secondary drinking water standards in samples collected during this study. High concentrations of boron and tungsten also were observed. Chemical comparisons between basin-fill and geothermal aquifer water indicate that most basin-fill groundwater sampled could contain 10–20 percent geothermal water. Geothermal indicators such as high temperature, lithium, boron, chloride, and silica suggest that mixing occurs in many wells that tap the basin-fill aquifer, particularly on the north, south, and west sides of the basin. Magnesium-lithium geothermometers indicate that some basin-fill aquifer water sampled for the current study likely originates from water that was heated above background mountain-block recharge temperatures (between 3 and 15 degrees Celsius), highlighting the influence of mixing with warm water that was possibly derived from geothermal sources.

Nevada↗
USGS2014

An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri

Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed. Distinct basin characteristics were evaluated and selected for use on the basis of their theoretical relation to flow, results from previous studies, and the ability to reliably measure the basin characteristic using digital datasets and geographic information system (GIS) technology. The key basin characteristics determined or computed for each of the 39 basins upstream from the streamflow-gaging stations were drainage area, percent impervious area, main-channel slope based on the 10- and 85-percent length method, percentage of the basin area in storage (lakes, ponds, reservoirs, wetlands), the composite Natural Resources Conservation Service curve number estimated from a combination of the soil type data and land-use characteristics, and the streamflow variability index developed for the recently completed study of low-flow regression in Missouri. Characteristics of spatial and temporal rainfall distribution came from the next generation weather radar (NEXRAD) network. Procedures were developed for this study to convert the variable radar sweep rate into a 5-minute total rainfall hyetograph using data from the radar bin at the centroid of a given basin. Additional characteristics determined for each storm on the basin included the 5-day and 14-day antecedent rainfall, estimated from the mean of daily rainfall values from various rain gages in the area. The database of observed rainfall and runoff events for the 39 basins upstream from the streamflow-gaging stations was analyzed to compute the optimal storm-specific initial abstraction and constant loss values, as well as the time to peak, peak streamflow, and shape factor values of the GUH. The optimal storm-specific values were used to develop a regional regression equation for initial abstraction; conversely, the constant loss was estimated not by regression but from either a generalized or specific regional mean value. The optimal storm-specific values of GUH time to peak, GUH peak streamflow, and GUH shape factor were used to develop regression equations for the GUH. The regression equations for the GUH initially were tested alone, and then were combined with the appropriate regional regression equation for initial abstraction and both the generalized regional and specific regional mean constant loss values. For the GUH regression equations, the interquartile range was substantially smaller than the range spanned by the minimum and maximum values, which indicates most of the errors have much smaller variation, and the minimum and maximum values may be extreme outliers. The central tendency of the regressed errors for peak streamflow and runoff hydrograph volume were both approximately zero, which implies a generally unbiased estimation of these values. The mean and median of the regressed errors for time to peak streamflow were both small but greater than zero, which implies the GUH regression equations create a hydrograph that has a peak that is later in time than observed. Specifically, the regressed times indicate an offset of about 10 minutes, on average, from observed. The mean and median of the regressed errors for widths of the runoff hydrograph at 50 and 75 percent were less than zero, which implies the GUH tends to slightly underestimate these widths compared to the observed. The appropriate regional initial abstraction regression equation was combined with both the generalized and the specific regional mean constant loss values and the GUH regression equations. Both the generalized regional mean constant loss and specific regional mean constant loss forms of the basin-loss model worked equally well to model the observed runoff hydrograph based on the error analysis, and neither model seems to make a consistently better approximation. Both initial abstraction and constant loss models combined with the GUH regression equations were further validated using several storms available after the start of the project in early 2011 with similar but consistently higher error results. If these methods are used in an urban area in Missouri other than those examined in this study, advice to the user is given to consider using the generalized regional mean values. If these methods are used in an urban area that is a subbasin of one of the basins in this study, advice to the user is given to consider using the specific regional mean values. The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.

Missouri↗
USGS2021

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

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

Kansas, Missouri↗
USGS2024

Bathymetric and velocimetric surveys at highway bridges crossing the Missouri and Mississippi Rivers on the periphery of Missouri, June 13–22, 2022

Bathymetric and velocimetric data were collected by the U.S. Geological Survey, in cooperation with the Missouri Department of Transportation, near seven bridges at six highway crossings of the Missouri and Mississippi Rivers on the periphery of Missouri from June 13–22, 2022. A multibeam echosounder mapping system was used to obtain channel-bed elevations for river reaches about 1,640 feet longitudinally and generally extending laterally across the active channel from bank to bank during minor flood-flow conditions. These surveys provided channel geometry and hydraulic conditions at the time of the surveys and provided characteristics of scour holes that may be useful in developing or verifying predictive guidelines or equations for computing potential scour depth. These data also may be useful to the Missouri Department of Transportation as a minor flood-flow assessment of the bridges for stability and integrity issues with respect to bridge scour during floods. Bathymetric data were collected around every in-channel pier. Scour holes were present at most piers for which bathymetry could be obtained, except those on banks or surrounded by riprap. Occasionally, scour holes were minor and difficult to discern from nearby dunes and ripples. All bridge sites in this study were surveyed and documented in previous studies. Although partial exposure of substructural support elements was observed at several piers, at most sites the exposure most likely is minimal compared to the overall substructure that remains buried in bed material at these piers. The notable exceptions are piers 12 and 13 at structure L0135 on State Highway 51 at Chester, Illinois, where the bedrock material was fully exposed around the piers. The average difference between the bathymetric surfaces between 2022 and 2018 varied from 0.41 foot higher to 1.86 feet lower. Between 2022 and 2014, the average difference between the bathymetric surfaces varied from 1.02 feet higher to 4.69 feet lower. Only the two sites on the Missouri River and the Caruthersville site were surveyed in 2011; for those sites, the average difference between the bathymetric surfaces varied from 5.83 feet higher to 1.34 feet lower. The most substantial overall net gain of sediment in a reach was between 2011 and 2022 at structure A1700 near Caruthersville, Mo. (site 38). This result was expected because structure A1700 is downstream from the confluences of the Missouri and Ohio Rivers, and therefore subject to the largest streamflows, the largest streamflow fluctuations, and the most substantial sediment flux, as has historically been observed at this site. The presence of riprap blankets, pier size and nose shape, and alignment to flow had a substantial effect on the size of the scour hole observed for a given pier. Piers that were surrounded by riprap blankets had scour holes that were substantially smaller (to nonexistent) compared to piers at which no rock or riprap were present. New riprap blankets were surveyed at pier 3 of structure L0098 at Brownville, Nebraska, and at piers 15–18 of structure A1700 near Caruthersville, Mo., that effectively mitigated the scour holes historically observed at these piers. Narrow piers having round or sharp noses that were aligned with flow often had scour holes that were difficult to discern from nearby bed features, whereas piers having wide or blunt noses resulted in larger, deeper scour holes. Several of the structures had piers that were skewed to primary approach flow. Scour holes near these piers consistently displayed greater depth on the side of the pier with impinging flow and deposition on the leeward side of the pier.

Missouri↗
USGS2026

Analysis of alternative weir designs for improved passage of select fish at the U.S. Geological Survey streamgaging weir at Blackwells Mills, New Jersey

As the population of New Jersey continues to remain dense, the need for water supply will likely continue to be high, which can lead to water managers needing to make difficult decisions about managing drinking-water supply. Streamgaging weirs like the ones used by the U.S. Geological Survey (USGS) play a critical role in providing accurate and stable streamflow data, but their presence can affect the passage of diadromous fish species such as river herring ( Alosa pseudoharengus [alewife], Alosa aestivalis [blueback herring], and Alosa sapidissima [American shad]). In some situations, weirs existing in rivers and streams are no longer used because they were part of a farm irrigation system or some type of industrial operation. The weir at the USGS streamgage 01402000 Millstone River at Blackwells Mills, New Jersey, was purposefully built as a hydraulic-control structure that provides a precise and stable control for the measurement of stage and computation of continuous streamflow. To satisfy the dual need of maintaining accurate streamflow data and providing improved fish passage for select species of fish during migration season, the USGS proposed the development and evaluation of two alternative weir designs that would meet the criteria established for successful passage of American shad, alewife, and blueback herring during their yearly migration. The designs were also required to maintain adequate control of the upstream pool elevation necessary for the precise computation of streamflow used by State agencies for municipal water-supply purposes for surrounding communities. Two alternative weir design modifications were incorporated at the center of the Blackwells Mills weir and modeled using two-dimensional hydraulic modeling software and three-dimensional computational fluid-dynamics software to simultaneously evaluate conditions for passage of the target fish species and effects to streamflow computations at the streamgage. The models were calibrated to existing conditions around the weir location using surveyed-elevation data and recorded stage, streamflow, and velocity in the Millstone River. The alternative weir designs lowered the weir crest by 1.02 feet (ft) and the resulting simulations showed an effective increase in depth of 0.98 ft at the median streamflow of 251 cubic feet per second (ft 3 /s) and 0.96 ft at the 95-percent exceedance streamflow of 98 ft 3 /s. The alternative weir designs were also found to increase streamflow depth across the shallowest portions of the weir structure at the downstream anti-scour skirt by lowering the skirt about 4 inches, allowing for two or more body depths of water for American shad, alewife, and blueback herring at the median migration streamflow of 251 ft 3 /s. The alternative weir designs also reduced the highest stream velocities across the downstream weir sill and anti-scour skirt from about 9 to 10 feet per second, and the depth-averaged velocity to about 7 to 8 feet per second. The sensitivity of the weir with respect to the computation of streamflow was increased from about 1.8 cubic feet per second per hundredth foot to 1.6 cubic feet per second per hundredth foot for streamflows of about 10–100 cubic feet per second.

New Jersey↗
USGS1991

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

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

Conference Paper↗
USGS2002

Use of an Acoustic Doppler Current Profiler (ADCP) to Measure Hypersaline Bidirectional Discharge

The U.S. Geological Survey measures the exchange of flow between the north and south parts of Great Salt Lake, Utah, as part of a monitoring program. Turbidity and bidirectional flow through the breach in the causeway that divides the lake into two parts makes it difficult to measure discharge with conventional streamflow techniques. An acoustic Doppler current profiler (ADCP) can be used to more accurately define the angles of flow and the location of the interface between the layers of flow. Because of the high salinity levels measured in Great Salt Lake (60-280 parts per thousand), special methods had to be developed to adjust ADCP-computed discharges for the increased speed of sound in hypersaline waters and for water entrained at the interface between flow layers.

Conference Paper↗
USGS1976

Use of thermal-infrared imagery in ground-water investigations, northwestern Montana

Thermal-infrared imagery was used to locate ground-water inflow along a 50-mile (80-kilometre) reach of the Kootenai River and Lake Koocanusa and a 55-mi (88-km) reach of the Clark Fork of the Columbia River in northwestern Montana and northeastern Idaho. The imagery confirmed that measured streamflow gains below Noxon Rapids Dam, ranging from 1,000 to 2,500 cubic feet per second (28 to 71 cubic metres per second), resulted from inflow of ground water, which was about 2.5° Celsius warmer than surface water. The thermal scanner (8.5-11 micrometres) used in May 1972 and March 1973 was mounted in a twin-engined aircraft. On the March 1973 flight, the data were recorded in an analog format on magnetic tape in flight, later were converted to digital format, and then were computer processed using an assignment of patterns to indicate differences in water temperature. Thus, subtle temperature differences are much easier to identify than they are oh conventional film-negative displays. The output data from the image-processing program can be converted to temperature maps having an isotherm spacing of 0.5°C.

Montana↗
USGS1992

Map showing bottom topography of the Pacific Continental Margin, Cape Mendocino to Point Conception

All contours, geographic outlines, and political boundaries shown on this map of the bottom topography, or bathymetry, of the Pacific continental margin between 34? and 41? N. latitudes were plotted from digital data bases in the library of the U.S. Geological Survey (USGS)-National Oceanic and Atmospheric Administration (NOAA) Joint Office for Mapping and Research (JOMAR). These digital data were obtained and compiled from many sources; consequently, data quality varies within particular data bases as well as from one data base to another. Bathymetric contours were digitized from a map compiled by Chase and others (1981) and from the unpublished large scale versions of that map (T.E. Chase, unpub. maps, 1981). Data for the area seaward of the continental slope (~2000 m depth) were obtained primarily from the U.S. Coast and Geodetic Survey (C&GS) 1955 Pacific Exploratory Survey, a systematic and detailed (~8 -nmi trackline spacing) survey between Mexico and Canada. The USGS provided data from cruises S3-78-NC, S15-79-NC, L2-77-NC, Ll0-76-NC, and Bartlett 72. Data were also obtained from Scripps Institution of Oceanography cruises Merazine, Blue Flash, Kayak B, Scan I, and Seven Tow (Chase and Menard, 1971; Chase and others, 1975; Wilde and others, 1976; Wilde and others, 1978). The 200-m contour was derived from the National Ocean Survey charts 1306N-20 (1975), 1307N-l1B (1974a), 1307N-18B (1974b), and C&GS chart 1308N-12 (1969). Sea-floor depths were corrected for sound velocity in sea water using Matthew's (1939) tables. Onshore topographic contours were generated by computer from a modified version of 3-arc-second elevation data provided by the Defense Mapping Agency. The United States digital shoreline was obtained from the NOAA, NOS, Nautical Charting Division, National Atlas files. The coastline of Canada was digitized from Canadian Hydrographic Service bathymetric maps. The primary source of names of the sea floor features was the "Gazetteer of Undersea Features" (Defense Mapping Agency, 1990). Acknowledgments Christopher Hines assisted in the construction and verification of the digital data bases. Reviews and suggestions by Edward C. Escowitz and Florence Wong and advice provided by Will Stettner regarding the cartographic design substantially improved the quality of this map. References Cited Chase, T.E., and Menard, H.W., 1971, Bathymetric atlas of the northeastern Pacific Ocean: U.S. Naval Oceanographic Office Publication 1303, scale 1:2,000,000 at 33° latitude, 48 p. Chase, T.E., Wilde, Pat, and Normark, W.R., 1975, Oceanographic data of the Monterey Deep Sea Fan: San Diego, University of California, Institute of Marine Resources Publication TR 58, scale 1:898,524 at 35° latitude. Chase, T.E., Wilde, Pat, Normark, W.R., Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets. Coast and Geodetic Survey, 1969, Point St. George to Point Delgada: Coast and Geodetic Survey Bathymetric Map 1308N-12, scale 1:250,000. Defense Mapping Agency, 1990, Gazetteer of undersea features (4th ed.): Washington, D.C., Defense Mapping Agency. Matthews, D.J., 1939, Tables of the velocity of sound in pure water and sea water (2d ed.): London, Admiralty, Hydrographic Department, H.D. 282, 52 p. National Ocean Survey, 1974a, Vicinity Pt. Sur to Pt. Reyes: National Ocean Survey Bathymetric Map 1307N-11B, scale 1:250,000. National Ocean Survey, 1974b, Pt. Reyes to Tolo Bank: National Ocean Survey Bathymetric Map 1307N-18B, scale 1:250,000. National Ocean Survey, 1975, Cape San Martin to Point Conception: National Ocean Survey Bathymetric Map 1306N-20, scale 1:250,000. Wilde, Pat, Normark, W.R., and Chase, T.E., 1976, Oceanographic data off central California 37° to 40° North including the Delgada Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 92, scale 1 :864,581 at 38° latitude. Wilde, Pat, Chase, T.E., Holmes, M.L., Normark, W.R., Thomas, J.A., McCulloch, D.S., and Kulm, L.D., 1978, Oceanographic data off northern California-southern Oregon 40° to 43° North including the Gorda Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 251, scale 1:815,482 at 42° latitude.

IMAP↗
USGS1992

Map showing bottom topography of the Pacific Continental Margin, Strait of Juan de Fuca to Cape Mendocino

All contours, geographic outlines, and political boundaries shown on this map of the bottom topography, or bathymetry, of the Pacific continental margin between 34° and 41° N. latitudes were plotted from digital data bases in the library of the U.S. Geological Survey (USGS)-National Oceanic and Atmospheric Administration (NOAA) Joint Office for Mapping and Research (JOMAR). These digital data were obtained and compiled from many sources; consequently, data quality varies within particular data bases as well as from one data base to another. Bathymetric contours were digitized from a map compiled by Chase and others (1981) and from the unpublished large scale versions of that map (T.E. Chase, unpub. maps, 1981). Data for the area seaward of the continental slope (~2000 m depth) were obtained primarily from the U.S. Coast and Geodetic Survey (C&GS) 1955 Pacific Exploratory Survey, a systematic and detailed (~8 -nmi trackline spacing) survey between Mexico and Canada. The USGS provided data from cruises S3-78-NC, S15-79-NC, L2-77-NC, Ll0-76-NC, and Bartlett 72. Data were also obtained from Scripps Institution of Oceanography cruises Merazine, Blue Flash, Kayak B, Scan I, and Seven Tow (Chase and Menard, 1971; Chase and others, 1975; Wilde and others, 1976; Wilde and others, 1978). The 200-m contour was derived from the National Ocean Survey charts 1306N-20 (1975), 1307N-l1B (1974a), 1307N-18B (1974b), and C&GS chart 1308N-12 (1969). Sea-floor depths were corrected for sound velocity in sea water using Matthew's (1939) tables. Onshore topographic contours were generated by computer from a modified version of 3-arc-second elevation data provided by the Defense Mapping Agency. The United States digital shoreline was obtained from the NOAA, NOS, Nautical Charting Division, National Atlas files. The coastline of Canada was digitized from Canadian Hydrographic Service bathymetric maps. The primary source of names of the sea floor features was the "Gazetteer of Undersea Features" (Defense Mapping Agency, 1990). Acknowledgments Christopher Hines assisted in the construction and verification of the digital data bases. Reviews and suggestions by Edward C. Escowitz and Florence Wong and advice provided by Will Stettner regarding the cartographic design substantially improved the quality of this map. References Cited Chase, T.E., and Menard, H.W., 1971, Bathymetric atlas of the northeastern Pacific Ocean: U.S. Naval Oceanographic Office Publication 1303, scale 1:2,000,000 at 33° latitude, 48 p. Chase, T.E., Wilde, Pat, and Normark, W.R., 1975, Oceanographic data of the Monterey Deep Sea Fan: San Diego, University of California, Institute of Marine Resources Publication TR 58, scale 1:898,524 at 35° latitude. Chase, T.E., Wilde, Pat, Normark, W.R., Miller, C.P., Seekins, B.A., and Young, J.D., 1981, Offshore topography of the Western United States between 32° and 49° North latitudes: U.S. Geological Survey Open-File Report 81-443, scale 1:864,518 at 38° latitude, 2 sheets Coast and Geodetic Survey, 1969, Point St. George to Point Delgada: Coast and Geodetic Survey Bathymetric Map 1308N-12, scale 1:250,000. Defense Mapping Agency, 1990, Gazetteer of undersea features (4th ed.): Washington, D.C., Defense Mapping Agency. Matthews, D.J., 1939, Tables of the velocity of sound in pure water and sea water (2d ed.): London, Admiralty, Hydrographic Department, H.D. 282, 52 p. National Ocean Survey, 1974a, Vicinity Pt. Sur to Pt. Reyes: National Ocean Survey Bathymetric Map 1307N-11B, scale 1:250,000. National Ocean Survey, 1974b, Pt. Reyes to Tolo Bank: National Ocean Survey Bathymetric Map 1307N-18B, scale 1:250,000. National Ocean Survey, 1975, Cape San Martin to Point Conception: National Ocean Survey Bathymetric Map 1306N-20, scale 1:250,000. Wilde, Pat, Normark, W.R., and Chase, T.E., 1976, Oceanographic data off central California 37° to 40° North including the Delgada Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 92, scale 1 :864,581 at 38° latitude. Wilde, Pat, Chase, T.E., Holmes, M.L., Normark, W.R., Thomas, J.A., McCulloch, D.S., and Kulm, L.D., 1978, Oceanographic data off northern California-southern Oregon 40° to 43° North including the Gorda Deep Sea Fan: Berkeley, University of California, Lawrence Berkeley Laboratory Publication 251, scale 1:815,482 at 42° latitude.

IMAP↗
USGS2021

Improved scaling relationships for seismic moment and average slip of strike-slip earthquakes incorporating fault slip rate, fault width and stress drop

We develop a self‐consistent scaling model relating magnitude M w to surface rupture length ( ⁠L E ⁠ ), surface displacement D E ⁠ , and rupture width W E ⁠ , for strike‐slip faults. Knowledge of the long‐term fault‐slip rate S F improves magnitude estimates. Data are collected for 55 ground‐rupturing strike‐slip earthquakes that have geological estimates of L E ⁠ , D E ⁠ , and S F⁠ , and geophysical estimates of W E ⁠ . We begin with the model of Anderson et al. (2017) , which uses a closed form equation for the seismic moment of a surface‐rupturing strike‐slip fault of arbitrary aspect ratio and given stress drop, Δτ C ⁠ . Using W E estimates does not improve M w estimates. However, measurements of D E plus the relationship between Δτ C and surface slip provide an alternate approach to study W E ⁠ . A grid of plausible stress drop and width pairs were used to predict displacement and earthquake magnitude. A likelihood function was computed from within the uncertainty ranges of the corresponding observed M w and D E values. After maximizing likelihoods over earthquakes in length bins, we found the most likely values of W E for constant stress drop; these depend on the rupture length. The best‐fitting model has the surprising form W E ∝logL E —a gentle increase in width with rupture length. Residuals from this model are convincingly correlated to the fault‐slip rate and also show a weak correlation with the crustal thickness. The resulting model thus supports a constant stress drop for ruptures of all lengths, consistent with teleseismic observation. The approach can be extended to test other observable factors that might improve the predictability of magnitude from a mapped fault for seismic hazard analyses.

Bulletin of the Seismological Society of America↗
USGS2005

Trends in surface-water quality at selected National Stream Quality Accounting Network (NASQAN) stations, in Michigan

To demonstrate the value of long-term, water-quality monitoring, the Michigan Department of Environmental Quality (MDEQ), in cooperation with the U.S. Geological Survey (USGS), initiated a study to evaluate potential trends in water-quality constituents for selected National Stream Quality Accounting Network (NASQAN) stations in Michigan. The goal of this study is to assist the MDEQ in evaluating the effectiveness of water-pollution control efforts and the identification of water-quality concerns. The study included a total of nine NASQAN stations in Michigan. Approximately 28 constituents were analyzed for trend tests. Station selection was based on data availability, land-use characteristics, and station priority for the MDEQ Water Chemistry Monitoring Project. Trend analyses were completed using the uncensored Seasonal Kendall Test in the computer program Estimate Trend (ESTREND), a software program for the detection of trends in water-quality data. The parameters chosen for the trend test had (1) at least a 5-year period of record (2) about 5 percent of the observations censored at a single reporting limit, and (3) 40 percent of the values within the beginning one-fifth and ending one-fifth of the selected period. In this study, a negative trend indicates a decrease in concentration of a particular constituent, which generally means an improvement in water quality; whereas a positive trend means an increase in concentration and possible degradation of water quality. The results of the study show an overall improvement in water quality at the Clinton River at Mount Clemens, Manistee River at Manistee, and Pigeon River near Caseville. The detected trend for these stations show decreases in concentrations of various constituents such as nitrogen compounds, conductance, sulfate, fecal coliform bacteria, and fecal streptococci bacteria. The negative trend may indicate an overall improvement in agricultural practices, municipal and industrial wastewater-treatment processes, and effective regulations. Phosphorus data for most of the study stations could not be analyzed because of the data limitations for trend tests. The only station with a significant negative trend in total phosphorus concentration is the Clinton River at Mount Clemens. However, scatter-plot analyses of phosphorus data indicate decreasing concentrations with time for most of the study stations. Positive trends in concentration of nitrogen compounds were detected at the Kalamazoo River near Saugatuck and Muskegon River near Bridgeton. Positive trends in both fecal coliform and total fecal coliform were detected at the Tahquamenon River near Paradise. Various different point and nonpoint sources could produce such positive trends, but most commonly the increase in concentrations of nitrogen compounds and fecal coliform bacteria are associated with agricultural practices and sewage-plant discharges. The constituent with the most numerous and geographically widespread significant trend is pH. The pH levels increased at six out of nine stations on all the major rivers in Michigan, with no negative trend at any station. The cause of pH increase is difficult to determine, as it could be related to a combination of anthropogenic activities and natural processes occurring simultaneously in the environment. Trends in concentration of major ions, such as calcium, sodium, magnesium, sulfate, fluoride, chloride, and potassium, were detected at eight out of nine stations. A negative trend was detected only in sulfate and fluoride concentrations; a positive trend was detected only in calcium concentration. The major ions with the most widespread significant trends are sodium and chloride; three positive and two negative trends were detected for sodium, and three negative and two positive trends were detected for chloride. The negative trends in chloride concentrations outnumbered the positive trends. This result indicates a slight improvement in surface-water quality because chloride as a point source in natural water comes from deicing salt, sewage effluents, industrial wastes, and oil fields. For other major ions, such as magnesium and potassium, both positive and negative trends were detected. These changes in trends indicate changes in surface-water quality caused by a variety of point and non-point sources throughout Michigan, as well as natural changes in the environment.

Michigan↗
USGS2015

Flood-inundation maps for White River at Petersburg, Indiana

Digital flood-inundation maps for a 7.7-mile reach of the White River at Petersburg, Indiana, were created by the U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at White River at Petersburg, Ind. (03374000). Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site (PTRI3). Flood profiles were computed for the White River at Petersburg reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relations at the White River at Petersburg, Ind., and the White River above Petersburg, Ind. (03373890), gages. The calibrated hydraulic model was then used to compute 18 water-surface profiles for flood stages at approximately 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model to delineate the area flooded at each water level. The availability of these maps along with Internet information regarding current stage from the USGS streamgage at White River at Petersburg, Ind., and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.

Indiana↗
USGS2019

Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California

Accurate forecasts of the streamflow expected during late spring and summer in the Upper Klamath River Basin in southern-central Oregon and northern California are used by water management agencies to balance water allocations for agriculture, aquatic habitat, and hydropower-production needs. Streamflow forecasts are also used by irrigation farmers for planning. The forecasts are typically made twice a month starting as early in the water year as December. Multiple regression equations relating real-time snowpack and precipitation conditions to seasonal streamflow volumes have been used for many years in forecasting. However, with warming temperature trends and lower snowpack, such forecasts based on historical data could become less reliable in the future. If the timing and relation of snowpack and precipitation are outside of the range of the historical data used to create the equations, the forecasts become extrapolations. Statistical forecast equations are also limited in their ability to forecast streamflow in groundwater-dominated basins having inter-annual lag. As an additional method for seasonal streamflow forecasting, a physical-process-based hydrologic model employing the Precipitation-Runoff Modeling System (PRMS) was developed in cooperation with the U.S. Bureau of Reclamation for the Upper Klamath Basin in this study. The model was calibrated for the portion of the basin draining into Upper Klamath Lake. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed by the U.S. Geological Survey. It simulates daily streamflow, snow, solar radiation, evapotranspiration, surface-water, and groundwater processes within the basin. A model calibration and validation period for water years 2000–15 and water years 1984–99, respectively, was used. The model was calibrated and validated using measured streamflow, snowpack, evapotranspiration, and solar radiation data sets. Interpolated daily precipitation and air temperature data from 32 meteorological stations within and surrounding the Upper Klamath Basin were used as model input. Performance statistics, used to evaluate how well simulated daily streamflow matched with measured streamflow included percent bias, percent relative error, and root-mean-square error. The statistics were computed annually, monthly, for October–March, and for April–September. With the exception of the October–March period, percent bias statistics were all within plus or minus 5-percent for both the calibration and validation periods. Limitations to using the model are error in the precipitation and air temperature input time series data, which include measurement error and error in the spatial interpolation method. Other errors include measured daily streamflow data, which were adjusted for consumptive use losses to make them more closely resemble natural streamflow for calibration. The model developed for the Upper Klamath Basin can be used to forecast streamflow from the Sprague and Williamson River Basins and inflow to Upper Klamath Lake. Reliable forecasts at these locations are needed for managing water for irrigation, ecosystem health, and power production. Using the models in a forecast application requires assembling model input data sets of anticipated daily precipitation and minimum and maximum air temperature for the period after the date the forecast is made and the end of the forecasted period. These climate data sets can be based on historical or synthetic records, at the discretion of the forecaster. With the Ensemble Streamflow Prediction method, a suite of streamflow scenarios is simulated using multiple years of climate data as model input. The forecasted streamflow is determined from knowing the exceedance probabilities of the simulated streamflows. In this study, the model and the Ensemble Streamflow Prediction method were used to forecast the volume of inflow to Upper Klamath Lake for a 6-month period from April 1, 2015, to September 30, 2015, using a range of climate data sets based on El Niño Southern Oscillation (ENSO) criteria. Because 2015 was a warm phase ENSO period, climate data for 10 warm phase ENSO years from 1980 to 2010 were used as input to the model. The simulated April–September 2015 UKL inflow volume based on measured 2015 climate data was 482,000 acre-feet, which was very close to the 50th percent exceedance probability computed from 10 simulated scenarios that used warm phase ENSO climate input data from 1980–2010.

California, Oregon↗
USGS2009

Unique problems associated with seismic analysis of partially gas-saturated unconsolidated sediments

Gas hydrate stability conditions restrict the occurrence of gas hydrate to unconsolidated and high water-content sediments at shallow depths. Because of these host sediments properties, seismic and well log data acquired for the detection of free gas and associated gas hydrate-bearing sediments often require nonconventional analysis. For example, a conventional method of identifying free gas using the compressional/shear-wave velocity (V p /V s ) ratio at the logging frequency will not work, unless the free-gas saturations are more than about 40%. The P-wave velocity dispersion of partially gas-saturated sediments causes a problem in interpreting well log velocities and seismic data. Using the White, J.E. [1975. Computed seismic speeds and attenuation in rocks with partial gas saturation. Geophysics 40, 224-232] model for partially gas-saturated sediments, the difference between well log and seismic velocities can be reconciled. The inclusion of P-wave velocity dispersion in interpreting well log data is, therefore, essential to identify free gas and to tie surface seismic data to synthetic seismograms.

Marine and Petroleum Geology↗
USGS1936

The diurnal fluctuation in the ground‐water and flow of the Santa Ana River and its meaning

In the time alloted for this subject it will be impossible to discuss, in its entirety, all phases of the methods used in computing the loss of water by transpiration from native plant‐life along the Santa Ana River. The results of this work are published in Bulletin 44 of the Division of Water Resources, State of California. The present paper is confined to a discussion of the diurnal fluctuations that occur in the flow of the Santa Ana River and the adjacent ground‐water. On Figure 1 have, been plotted the gage‐height records for a short period (July 5–8, 1935) for eight southern California streams. These records have been selected at random from the large number of records filed in the local office of the United States Geological Survey. Some of these streams have a large drainage‐area, others are small; some are short and steep, others flat and long. The points of measurement range from 15 to 2950 feet above sea‐level. One of the streams (Mojave River) is in the desert‐region; the others drain into the Pacific Ocean. The object of Figure 1 is to demonstrate, that the diurnal fluctuation exists and is, to a large degree, similar at most points of measurement. As a rule, the maximum discharge occurs about 10 o'clock in the morning, and the minimum late in the afternoon. It is readily recognized that these fluctuations are in the main caused by the evaporation and transpiration‐loss in or adjacent to the stream‐channel.

California↗
USGS2011

National Climate Change and Wildlife Science Center project accomplishments: highlights

The National Climate Change and Wildlife Science Center (NCCWSC) has invested more than $20M since 2008 to put cutting-edge climate science research in the hands of resource managers across the Nation. With NCCWSC support, more than 25 cooperative research initiatives led by U.S. Geological Survey (USGS) researchers and technical staff are advancing our understanding of habitats and species to provide guidance to managers in the face of a changing climate. Projects focus on quantifying and predicting interactions between climate, habitats, species, and other natural resources such as water. Spatial scales of the projects range from the continent of North America, to a regional scale such as the Pacific Northwest United States, to a landscape scale such as the Florida Everglades. Time scales range from the outset of the 20th century to the end of the 21st century. Projects often lead to workshops, presentations, publications and the creation of new websites, computer models, and data visualization tools. Partnership-building is also a key focus of the NCCWSC-supported projects. New and on-going cooperative partnerships have been forged and strengthened with resource managers and scientists at Federal, tribal, state, local, academic, and non-governmental organizations. USGS scientists work closely with resource managers to produce timely and relevant results that can assist managers and policy makers in current resource management decisions. This fact sheet highlights accomplishments of five NCCWSC projects.

Fact Sheet↗
USGS2018

Implementation of MOVE.1, censored MOVE.1, and piecewise MOVE.1 low-flow regressions with applications at partial-record streamgaging stations in New Jersey

The U.S. Geological Survey (USGS) uses Maintenance of Variance Extension Type 1 (MOVE.1) regression to transfer streamflows measured at long-term continuous-record streamgaging stations to partial-record (PR) streamgaging stations where intermittent base-flow measurements are available. MOVE.1 regression is used widely throughout the hydrologic community to extend historic low flows and low-flow statistics at continuous-record streamgaging stations to streamgaging stations that have access to only a partial record of low flows. The method correlates base-flow measurements at PR streamgaging stations with daily mean streamflows measured at index stations that exhibit similar streamflow characteristics. Following changes in the computing platform for storing, processing, retrieving, and publishing National Water Information System (NWIS) hydrologic data, legacy Statistical Analysis System (SAS) code developed by the USGS to implement the MOVE.1 regression was no longer suitable for reading and processing NWIS streamflow data. To migrate the MOVE.1 program so that it could continue to read streamflow data using the new hydrologic data platform, the SAS code was re-written in R, an open source programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The work described in this report was performed in a study conducted by USGS in cooperation with the New Jersey Department of Environmental Protection. During migration from SAS to R, graphical and tabular output generated by the R script was compared to output produced by the legacy SAS code to ensure that equations used to perform the MOVE.1 regression remained the same. An option to perform censored MOVE.1 regression was added to extend the MOVE.1 methodology to cases where one or more measured continuous-record or PR streamgaging station flows are zero valued. In addition to permitting censored regression, the new R script includes an option to perform piecewise MOVE.1 regression when the relation between PR station and index station low flows varies significantly across the range of index station streamflows. Together with traditional MOVE.1 regression, censored, and piecewise MOVE.1 regression methods implemented by the R script offer less biased estimates than ordinary least squares regression for the annual 7-day 10-year and other low-flow statistics at PR stations for a range of base-flow conditions. The R script is used to implement the MOVE.1 regression methods across a variety of computing platforms.

New Jersey↗