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USGS2018

Beyond the Kubler index

The value of peak width at half-height for the illite 001 XRD reflection is known as the Kubler index or the illite ‘crystallinity’ index. This measurement, which has been related to the degree of metamorphism of very low-grade, pelitic rocks, is a function of at least two crystal-chemical factors: (1) illite X-ray scattering domain size; and (2) illite structural distortions (especially swelling). Reynolds' NEWMOD computer program is used to construct a grid with which these two contributions to illite peak width can be determined independently from measurements of the 001 peak width at half-height and the Środoń intensity ratio. This method yields more information about changes undergone by illite during metamorphism than application of the Kubler index method alone.

Clay Minerals↗

USGS1995

Quality of wet deposition in the Grand Calumet River watershed, northwestern Indiana, June 30, 1992-August 31, 1993

Northwestern Indiana is one of the most heavily industrialized and largest steel-producing areas in the United States. High temperature processes, such as fossil-fuel combustion and steel production, release contaminants to the atmosphere that may result in wet deposition being a major contributor to major ion and trace-metal loadings in north- western Indiana and Lake Michigan. A wet-deposition collection site was established at the Gary (Indiana) Regional Airport in June 1992 to monitor the chemical quality of wet deposition. Weekly samples were collected at this site from June 30, 1992, through August 31, 1993, and were analyzed for pH, specific conductance, and selected major ions and trace metals. Forty-eight samples collected during the study were of sufficient volumes for some of the determinations to be performed. Median constituent concentrations were determined for samples collected during warm weather and cold weather (November 1 through March 31). Median concentrations were substituted for missing values from samples with insufficient volumes for analysis of all the constituents of interest. Constituent concentrations were converted to weekly loadings. Two values were calculated to provide a range for the weekly loading for samples with measured concentrations of constituents less than the method reporting limit. The minimum weekly loading was computed by substituting zero for the constituent concentration; the maximum weekly loading was computed by substituting the method reporting limit for the concentration. If all of the sample concentrations measured were greater than the method reporting limit, an annual loading value was computed. The annual loadings could be used to assist in estimating the contribution of wet deposition to the total annual constituent loadings in the Grand Calumet River in northwestern Indiana.

Indiana↗

USGS2011

Simulations of groundwater flow and particle-tracking analysis in the zone of contribution to a public-supply well in San Antonio, Texas

In 2006, a public-supply well in San Antonio, Texas, was selected for intensive study to assess the vulnerability of public-supply wells in the Edwards aquifer to contamination by a variety of compounds. A local-scale, steady-state, three-dimensional numerical groundwater-flow model was developed and used in this study to evaluate the movement of water and solutes from recharge areas to the selected public-supply well. Particle tracking was used to compute flow paths and advective traveltimes throughout the model area and to delineate the areas contributing recharge and zone of contribution for the selected public-supply well. The local-scale model grid has a finer vertical discretization than do previous regional Edwards aquifer models and incorporates refined parameter zones corresponding with multiple (10) hydrogeologic units representing the Edwards aquifer. In the Edwards aquifer, high matrix porosity and permeability likely are overshadowed by high permeability developed in structurally influenced karstic conduit systems that transmit water into, through, and out of the aquifer system. The complexity of the aquifer system in the local-scale study area is further increased by numerous faults with varying vertical displacements. The extensive faulting results in the juxtaposition of hydrogeologic units with differing hydraulic properties and has appreciable effects on groundwater flow in the Edwards aquifer. The local-scale model simulations use the MODFLOW Hydrogeologic-Unit Flow Package and include two hydrogeologic units with high hydraulic conductivities (one or more orders of magnitude higher than for the other simulated hydrogeologic units) that are intended to simulate fast flow paths attributable to karst features. The two “conduit” hydrogeologic units of the Edwards aquifer represent the lower 8 meters of the leached and collapsed members and the Kirschberg evaporite member of the Edwards Group. The MODFLOW Horizontal-Flow Barrier Package was used to simulate faults in the local-scale model. The assumption was made that the degree to which a fault acts as a barrier to groundwater flow is proportional to the fault displacement. The final calibrated hydraulic-conductance values ranged from 0.01 to 0.2 per day for fault displacements ranging from 0 to more than 100 percent of the total aquifer thickness. The calibrated steady-state simulation generally reproduces the spatial distribution of measured water-level altitudes. Simulated water-level altitudes were within 9.0 meters of measured water-level altitudes at 74 of the 84 wells used as targets for the local-scale model for the calibrated steady-state simulation. The overall mean absolute difference between simulated and measured water-level altitudes is 4.2 meters, and the mean algebraic difference is 1.9 meters. The simulated springflow for San Antonio Springs was 7.7 percent greater and for San Pedro Springs was 4.2 percent less than the median measured springflow. Simulated tritium concentrations were within 0.14 tritium units of measured tritium concentrations for 11 of the 13 local-scale study tritium observations from the 10 local-scale study wells used to calibrate the steady-state local-scale model, with a mean absolute difference between simulated and measured tritium concentrations of 0.11 tritium units and a mean algebraic difference of -0.04 tritium units. Simulated tritium concentrations in the selected public-supply well during November 2007 were within 0.09 tritium units of the measured concentrations, with the exception of the shallowest observation from the well. The steady-state simulation water budget indicates that recharge occurring in the local-scale study area accounts for 31.8 percent of the sources of water to the Edwards aquifer in the local-scale model area and that inflow through the model boundaries contributes 68.2 percent. Most of the flow into the local-scale model area through the model boundaries occurs through the western and southern boundaries, 58.2 and 39.6 percent, respectively. The largest discharges from the Edwards aquifer in the local-scale model area are boundary outflow (71.4 percent) and withdrawals by wells (24.9 percent). Most of the flow out of the local-scale model area through the model boundaries occurs through the southern and eastern boundaries, 54.2 and 39.6 percent, respectively. The simulated zones of contribution for the selected public-supply well, Timberhill well nest, and Zarzamora well nest extend to the north, northeast, and northwest from each site in the confined zone of the aquifer into the recharge zone, where all recharge to the aquifer occurs. The area contributing recharge for the selected public-supply well has the greatest extent. The area contributing recharge for the Timberhill well nest encompasses approximately the western one-half of the area contributing recharge for the selected public-supply well, and that for the Zarzamora well nest encompasses approximately the eastern two-thirds of the area contributing recharge for the selected public-supply well. Simulated particle ages ranged from less than 1 day to more than 1,900 years in the 10 local-scale study wells (13 local-scale study tritium observations) used to calibrate the local-scale model. The simulated mean particle ages for the tritium observations representing selected well depths (shallow, intermediate, and deep) ranged from 2.5 to 15 years. The minimum (youngest) mean particle ages for the selected public-supply well and the Timberhill monitoring wells were for the intermediate well depth, while the youngest mean particle age for the Zarzamora monitoring wells was for the intermediate and deep well depth. The maximum (oldest) mean particle ages for the selected public-supply well and the Zarzamora monitoring wells were for the shallow well depth. The mean of simulated particle ages for tritium observations representing well depths open to the simulated conduit hydrogeologic units was 3.8 years, whereas the mean of simulated particle ages for tritium observations representing well depths not open to the simulated conduit hydrogeologic units was 9.6 years. The effect of short-circuit pathways, for example karst conduits, in the flow system on the movement of young water to the selected public-supply well could greatly alter contaminant arrival times compared to what might be expected from advection in a system without short circuiting. In a forecasting exercise, the simulated concentrations showed rapid initial response at the beginning and end of chemical input, followed by more gradual response as older water moved through the system. The nature of karst groundwater flow, where flow predominantly occurs via conduit flow paths, could lead to relatively rapid water quality responses to land-use changes. Results from the forecasting exercise indicate that timescales for change in the quality of water from the selected public-supply well could be on the order of a few years to decades for land-use changes that occur over days to decades, which has implications for source-water protection strategies that rely on land-use change to achieve water-quality objectives.

Texas↗

USGS2017

Computing spatial correlation of ground motion intensities for ShakeMap

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

Computers & Geosciences↗

USGS2012

A simple method for estimating basin-scale groundwater discharge by vegetation in the basin and range province of Arizona using remote sensing information and geographic information systems

Groundwater is a vital water resource in the arid to semi-arid southwestern United States. Accurate accounting of inflows to and outflows from the groundwater system is necessary to effectively manage this shared resource, including the important outflow component of groundwater discharge by vegetation. A simple method for estimating basin-scale groundwater discharge by vegetation is presented that uses remote sensing data from satellites, geographic information systems (GIS) land cover and stream location information, and a regression equation developed within the Southern Arizona study area relating the Enhanced Vegetation Index from the MODIS sensors on the Terra satellite to measured evapotranspiration. Results computed for 16-day composited satellite passes over the study area during the 2000 through 2007 time period demonstrate a sinusoidal pattern of annual groundwater discharge by vegetation with median values ranging from around 0.3 mm per day in the cooler winter months to around 1.5 mm per day during summer. Maximum estimated annual volume of groundwater discharge by vegetation was between 1.4 and 1.9 billion m 3 per year with an annual average of 1.6 billion m 3 . A simplified accounting of the contribution of precipitation to vegetation greenness was developed whereby monthly precipitation data were subtracted from computed vegetation discharge values, resulting in estimates of minimum groundwater discharge by vegetation. Basin-scale estimates of minimum and maximum groundwater discharge by vegetation produced by this simple method are useful bounding values for groundwater budgets and groundwater flow models, and the method may be applicable to other areas with similar vegetation types.

Arizona↗

USGS2007

An initial-abstraction, constant-loss model for unit hydrograph modeling for applicable watersheds in Texas

Estimation of representative hydrographs from design storms, which are known as design hydrographs, provides for cost-effective, riskmitigated design of drainage structures such as bridges, culverts, roadways, and other infrastructure. During 2001?07, the U.S. Geological Survey (USGS), in cooperation with the Texas Department of Transportation, investigated runoff hydrographs, design storms, unit hydrographs,and watershed-loss models to enhance design hydrograph estimation in Texas. Design hydrographs ideally should mimic the general volume, peak, and shape of observed runoff hydrographs. Design hydrographs commonly are estimated in part by unit hydrographs. A unit hydrograph is defined as the runoff hydrograph that results from a unit pulse of excess rainfall uniformly distributed over the watershed at a constant rate for a specific duration. A time-distributed, watershed-loss model is required for modeling by unit hydrographs. This report develops a specific time-distributed, watershed-loss model known as an initial-abstraction, constant-loss model. For this watershed-loss model, a watershed is conceptualized to have the capacity to store or abstract an absolute depth of rainfall at and near the beginning of a storm. Depths of total rainfall less than this initial abstraction do not produce runoff. The watershed also is conceptualized to have the capacity to remove rainfall at a constant rate (loss) after the initial abstraction is satisfied. Additional rainfall inputs after the initial abstraction is satisfied contribute to runoff if the rainfall rate (intensity) is larger than the constant loss. The initial abstraction, constant-loss model thus is a two-parameter model. The initial-abstraction, constant-loss model is investigated through detailed computational and statistical analysis of observed rainfall and runoff data for 92 USGS streamflow-gaging stations (watersheds) in Texas with contributing drainage areas from 0.26 to 166 square miles. The analysis is limited to a previously described, watershed-specific, gamma distribution model of the unit hydrograph. In particular, the initial-abstraction, constant-loss model is tuned to the gamma distribution model of the unit hydrograph. A complex computational analysis of observed rainfall and runoff for the 92 watersheds was done to determine, by storm, optimal values of initial abstraction and constant loss. Optimal parameter values for a given storm were defined as those values that produced a modeled runoff hydrograph with volume equal to the observed runoff hydrograph and also minimized the residual sum of squares of the two hydrographs. Subsequently, the means of the optimal parameters were computed on a watershed-specific basis. These means for each watershed are considered the most representative, are tabulated, and are used in further statistical analyses. Statistical analyses of watershed-specific, initial abstraction and constant loss include documentation of the distribution of each parameter using the generalized lambda distribution. The analyses show that watershed development has substantial influence on initial abstraction and limited influence on constant loss. The means and medians of the 92 watershed-specific parameters are tabulated with respect to watershed development; although they have considerable uncertainty, these parameters can be used for parameter prediction for ungaged watersheds. The statistical analyses of watershed-specific, initial abstraction and constant loss also include development of predictive procedures for estimation of each parameter for ungaged watersheds. Both regression equations and regression trees for estimation of initial abstraction and constant loss are provided. The watershed characteristics included in the regression analyses are (1) main-channel length, (2) a binary factor representing watershed development, (3) a binary factor representing watersheds with an abundance of rocky and thin-soiled terrain, and (4) curve numb

Scientific Investigations Report↗

USGS1992

Map showing sediment isopachs in the deep-sea basins of the Pacific continental margin, Point Conception to Point Loma

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. 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. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. index map for I-2089-A See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1992

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Point Conception to Point Loma

IMAP↗

USGS1993

Map showing sediment isopachs in the deep-sea basins of the Pacific continental margin, Cape Mendocino to Point Conception

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. 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. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Cape Mendocino to Point Conception

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. 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. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing sediment isopachs in the deep-sea basins of the Pacific Continental Margin, Strait of Juan de Fuca to Cape Mendocino

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. 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. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS1993

Map showing depth to basement in the deep-sea basins of the Pacific continental margin, Strait of Juan de Fuca to Cape Mendocino

The U.S. Geological Survey conducted a series of cruises, EEZSCAN 84 (EEZ-SCAN 84 Scientific Staff, 1986), to collect reconnaissance data on the newly proclaimed Exclusive Economic Zone (EEZ), the area out to 200 nautical miles from the coastline of the United States. The cruises systematically surveyed the entire conterminous United States west coast EEZ using the Geological Long-Range Inclined Asdic (GLORIA) side-scan sonar, a 160-in 3 airgun seismic-reflection profiler, a 3.5-kHz high-resolution seismic-reflection profiler, a 10-kHz echo sounder, and a proton-precession magnetometer. The nominal trackline spacing throughout the survey was 30 km. Derivative maps of sediment thickness (I-2089-A, I-2090-A, I-2091-A) and depth to basement (I-2089-B, I-2090-B, I-2091-B) in the basins of the west coast EEZ were compiled from both the sonar-image dala and the deep-penetration seismic data obtained on these cruises. Only EEZ-SCAN 84 data were used for the map compilations because available data from other cruises in this region are sparsely located, have poor navigational control, or were obtained with seismic systems that were not powerful enough to resolve oceanic basement. For this map series, sediment thickness and depth to basement were determined only in the deep-ocean basin regions because the seismic system used on the EEZ-SCAN 84 cruises could not resolve oceanic basement beneath the thick sediments of the continental slope. All the data used to compile the maps are presented in the "Atlas of the Exclusive Economic Zone, Western Conterminous United States" (EEZ-SCAN 84 Scientific Staff, 1986). Basement Outcrops GLORIA imagery was used to locate areas of basement outcrop throughout the region. Where possible, sediment thickness on and immediately adjacent to basement outcrops was measured from seismic data. Where there was no bathymetric or seismic control, a seamount peak was assumed to have no sediment cover. A pattern is used on the map to indicate all basement outcrops. Data Reduction Acoustic basement in the basins, invariably oceanic Layer 2, was observed on all of the seismic records. One-way traveltime was measured from the sea floor to acoustic basement. Because the trackline spacing of about 30 km is relatively large compared to the data density along track, we chose to measure the sediment thickness every 0.5 hour or at an interval of approximately 7.5 km. Water depth was measured with a 10-kHz profiler. Depth to basement was calculated using the sea surface as the zero datum and adding the corrected water depth (Carter, 1980) to the sediment thickness. Acoustic travel times were converted to depths by first calculating a regression equation from the interval velocity versus depth data of Connard and others (1984). Their data base comprises a compilation of all available Deep Sea Drilling Project data plus wide-angle refraction data, which were collected in Cascadia Basin west of Oregon and represents the best data set available for the United States west coast EEZ. The regression equation was integrated to determine sediment thickness as a function of one-way traveltime . The resulting equation is z = 1400t + 0 .5t 2 where z is sediment thickness in meters, and t is one-way traveltime in seconds. Sediment thicknesses calculated using this equation were compared to values calculated from the general equation of Carlson and others (1986). Values for sediment thickness calculated by the two equations differed by no greater than 10 percent throughout the range of travel times. Bathymetry The bathymetry is from Chase and others (1981). The bathymetric data were compiled from a variety of sources, and data quality is inconsistent. Because of differences in navigational precision and density of coverage, the bathymetric contours of a feature may be at a different location than the corresponding isopleths derived from the EEZ-SCAN 84 data, or a feature may not be indicated on the bathymetry at all. These situations occur because either the feature is poorly located in the bathymetric data set or, especially in the outer EEZ, the bathymetric data are too sparse to have defined the existence of a feature. Acknowledgments Topographic digital data bases were corrected and verified by Christina Lief. Gerald Evenden developed the computer software system MAPGEN, used to compose this map. Reviews, suggestions, and technical contributions from Edward C. Escowitz and Florence Wong and advice about cartographic design from Will Stettner substantially improved the quality of this map. References Cited Carlson, R.L., Gangi, A.F., and Snow, K.R., 1986, Empirical reflection-traveltime/ depth and velocity/depth functions for the deep-sea sediment column: Journal of Geophysical Research, v. 91, no. B8, p. 8249-8266. Carter, D.J.T., 1980, Echo-sounding correction tables: Taunton, United Kingdom, Hydrographic Department, Ministry of Defence, 150 p. 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. Connard, G., Couch, R., Keeling , K., Roy, J., and Troseth, S., 1984, Abyssal plain and continental net-objective sedimentary thicknesses, in Kulm, L.D., and others, eds., Western North America continental margin and adjacent ocean floor off Oregon and Washington, Atlas 1 of Regional Atlas Series, Ocean Margin Drilling Program: Woods Hole, Mass., Marine Science International, sheet 7. EEZ-SCAN 84 Scientific Staff, 1986, Atlas of the Exclusive Economic Zone, Western Conterminous United States: U.S. Geological Survey Miscellaneous Investigations Series I-1792, scale 1:500,000, 152 p. See Also "U.S. Pacific West Coast Field Activities" (Paskevich and others, 2011; http://pubs.usgs.gov/of/2010/1332/htmldocs/pc/pc_overview.html). Paskevich, V.F., Wong, F.L., O?Malley, J.J., Stevenson, A.J., and Gutmacher, C.E., 2011, GLORIA sidescan-sonar imagery for parts of the U.S. Exclusive Economic Zone and adjacent areas: U.S. Geological Survey Open-File Report 2010?1332, available at http://pubs.usgs.gov/of/2010/1332/.

IMAP↗

USGS2004

Hydrologic and water-quality characteristics for Bear Creek near Silver Hill, Arkansas, and selected Buffalo River sites, 1999-2004

The purpose of this report is to describe and compare the hydrologic and water-quality characteristics of Bear Creek near Silver Hill, Arkansas, to two sites on the Buffalo River upstream from the confluence of Bear Creek, to a site on Calf Creek, a smaller tributary to the Buffalo River, to selected undeveloped sites across the Nation, and to a developed site in Arkansas. A better understanding of the hydrology and water quality of Bear Creek is of interest to many, including the National Park Service, which administers the Buffalo National River, to evaluate its effects on the hydrology and water quality of the Buffalo River. The streamflow at Bear Creek near Silver Hill varied seasonally and annually from January 1999 to March 2004. The mean annual streamflow at Bear Creek for calendar years 1999 to 2003 was 86.0 cubic feet per second. The highest annual mean streamflow occurred in 2002 (158 cubic feet per second) and the lowest annual mean streamflow occurred in 1999 (56.4 cubic feet per second). The mean annual streamflow for calendar years 1999 to 2003 at the Buffalo River near Boxley and Buffalo River near St. Joe was 102 and 881 cubic feet per second, respectively. Concentrations of nitrogen measured for Bear Creek generally were greater than concentrations measured at the two Buffalo River sites and were similar to concentrations measured at Calf Creek. Concentrations of phosphorus measured at Bear Creek generally were greater than concentrations measured at the two Buffalo River sites and were similar to concentrations measured at Calf Creek. Fecal indicator bacteria concentrations generally were greater at Bear Creek than concentrations measured at the Buffalo River and similar to concentrations at Calf Creek. Bear Creek had significantly greater suspended-sediment concentrations than the Buffalo River near Boxley and the Buffalo River near St. Joe and similar concentrations to Calf Creek. Nutrients, dissolved organic carbon, and suspended-sediment loads at Bear Creek and two Buffalo River sites varied because of differences in land use and contributing drainage area for each site. In general, the Buffalo River near St. Joe had the greatest annual loads of nutrients, dissolved organic carbon, and suspended sediment. The Buffalo River near Boxley had the least annual nutrient and suspended-sediment loads amongthe three sites. Buffalo River near Boxley had lesser annual loads than the other two sites probably because of the higher percentage of forested land in the basin and smaller contributing drainage area. Mean annual nutrient, dissolved organic carbon, and suspended- sediment yields computed for Bear Creek were greater than yields computed for both of the Buffalo River sites. Bear Creek had greater median annual nutrient yields than selected undeveloped basins across the Nation and less median annual nutrient yields than the Illinois River south of Siloam Springs, Arkansas, which is representative of a developed basin. Bear Creek had greater median annual flow-weighted nutrient concentrations than the Buffalo River near St. Joe, the Buffalo River near Boxley, and selected undeveloped sites across the Nation. Bear Creek had less median flow-weighted nutrient concentrations than the Illinois River.

Scientific Investigations Report↗

USGS2006

Water use and availability in the West Narragansett Bay area, coastal Rhode Island, 1995-99

During the 1999 drought in Rhode Island, belowaverage precipitation caused a drop in ground-water levels and streamflow was below long-term averages. The low water levels prompted the U. S. Geological Survey and the Rhode Island Water Resources Board to conduct a series of cooperative water-use studies. The purpose of these studies is to collect and analyze water-use and water-availability data in each drainage area in the State of Rhode Island. The West Narragansett Bay study area, which covers 118 square miles in part or all of 14 towns in coastal Rhode Island, is one of nine areas investigated as part of this effort. The study area includes the western part of Narragansett Bay and Conanicut Island, which is the town of Jamestown. The area was divided into six subbasins for the assessment of water-use data. In the calculation of hydrologic budget and water availability, the Hunt, Annaquatucket, and Pettaquamscutt River Basins were combined into one subbasin because they are hydraulically connected. Eleven major water suppliers served customers in the study area, and they supplied an average of 19.301 million gallons per day during 1995–99. The withdrawals from the only minor supplier, which was in the town of East Greenwich in the Hunt River Basin, averaged 0.002 million gallons per day. The remaining withdrawals were estimated as 1.186 million gallons per day from self-supplied domestic, commercial, industrial, and agricultural users. Return flows from self-disposed water (individual sewage-disposal systems) and permitted discharges accounted for 5.623 million gallons per day. Most publicly disposed water (13.711 million gallons per day) was collected by the Rhode Island Economic Development Corporation, and by the East Greenwich, Fields Point, Jamestown, Narragansett, and Scarborough wastewater-treatment facilities. This wastewater was disposed in Narragansett Bay outside of the study area. The PART program, a computerized hydrograph-separation application, was used to determine water availability in the study area on the basis of low flows measured at a nearby index station, the Pawcatuck River at Wood River Junction, Rhode Island. Water availability was defined as the 75th, 50th, and 25th percentiles of the total base flow; the base flow minus the 7-day, 10-year flow; and the base flow minus the Aquatic Base Flow at the index station. The base-flow contributions per unit area of sand and gravel deposits and of till were computed for June, July, August, and September for the index station and multiplied by the areas of sand and gravel and till in the subbasins. The calculated base flows at the index station were lowest in August at the 75th, 50th, and 25th percentiles for total base flow and for two additional low-flow scenarios. Because water withdrawals and use are greater during June, July, August, and September than at other times of the year, water availability was compared to water withdrawals in the subbasins for these summer months. Ratios were calculated by dividing the summer withdrawals by the water availability at the 75th, 50th, and 25th percentiles, and these percentiles of the base flow minus the two low flows for each subbasin. The closer this ratio is to one, the closer the withdrawals are to the estimated water available. These ratios allow comparisons of the use of water to the available water from one subbasin to another. The ratios were highest in July for the 50th percentile of the estimated gross yield minus the Aquatic Base Flow. The ratios ranged from 0.01 in the Providence and Seekonk subbasin to 0.38 in the Hunt-Annaquatucket-Pettaquamscutt subbasin for the 50th percentile of the gross yield minus the 7Q10 for August. A long-term (1941–2000) water budget was calculated for the study area to assess the basin inflows and outflows. The water withdrawals and return flows used in the budget were from 1995 through 1999. Inflow was assumed to equal outflow. The total water budget was 146.29 million gallons per day for the combined Hunt-Annaquatucket-Pettaquamscutt subbasin, 48.71 million gallons per day for the Greenwich Bay subbasin, 238.98 million gallons per day for the Providence and Seekonk Rivers subbasin, and 21.32 million gallons per day for the Conanicut Island subbasin. The estimated inflows from precipitation, streamflow from upstream basins, and wastewater return flow for the entire study area were 59.3, 38.5, and 2.2 percent, respectively. The estimated outflows for the study area from evapotranspiration, streamflow, and water withdrawals were 24.9, 73.9, and 1.2 percent, respectively.

Rhode Island↗

USGS2014

Water-quality variability and constituent transport and processes in streams of Johnson County, Kansas, using continuous monitoring and regression models, 2003-11

The population of Johnson County, Kansas increased by about 24 percent between 2000 and 2012, making it one of the most rapidly developing areas of Kansas. The U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began a comprehensive study of Johnson County streams in 2002 to evaluate and monitor changes in stream quality. The purpose of this report is to describe water-quality variability and constituent transport for streams representing the five largest watersheds in Johnson County, Kansas during 2003 through 2011. The watersheds ranged in urban development from 98.3 percent urban (Indian Creek) to 16.7 percent urban (Kill Creek). Water-quality conditions are quantified among the watersheds of similar size (50.1 square miles to 65.7 square miles) using continuous, in-stream measurements, and using regression models developed from continuous and discrete data. These data are used to quantify variability in concentrations and loads during changing streamflow and seasonal conditions, describe differences among sites, and assess water quality relative to water-quality standards and stream management goals. Water quality varied relative to streamflow conditions, urbanization in the upstream watershed, and contributions from wastewater treatment facilities and storm runoff. Generally, as percent impervious surface (a measure of urbanization) increased, streamflow yield increased. Water temperature of Indian Creek, the most urban site which is also downstream from wastewater facility discharges, was higher than the other sites about 50 percent of the time, particularly during winter months. Dissolved oxygen concentrations were less than the Kansas Department of Health and Environment minimum criterion of 5 milligrams per liter about 15 percent of the time at the Indian Creek site. Dissolved oxygen concentrations were less than the criterion about 10 percent of the time at the rural Blue River and Kill Creek sites, and less than 5 percent of the time at the other sites. Low dissolved oxygen at all sites generally coincided with lowest streamflow and warmer water temperatures. Hourly dissolved oxygen concentrations less than 5 milligrams per liter were measured at all sites every year, indicating that even under normal climate conditions in non-urban watersheds such as Kill Creek, dissolved oxygen concentrations may not meet State aquatic-life criterion. Specific conductance was nearly always highest in Indian and Mill Creeks, which were the most urban streams with the largest upstream discharges from wastewater treatment facilities. The largest chloride concentrations and variability were recorded at urban sites and during winter. Each winter during the study period, chloride concentrations in the most urban site, Indian Creek, exceeded the U.S. Environmental Protection Agency-recommended criterion of 230 milligrams per liter for at least 10 consecutive days. The U.S. Environmental Protection Agency-recommended ecoregion criterion for turbidity was exceeded 30 (Indian Creek) to 50 (Blue River) percent of the time. The highest average annual streamflow-weighted suspendedsediment concentration during the study period was in Mill Creek, which has undergone rapid development that likely contributed to higher sediment concentrations. One of the largest suspended-sediment load events in Indian Creek was recorded in early May 2007 when about 25 percent of the total annual sediment load was transported during a period of about 2.25 days. A simultaneous load event was recorded in Kill Creek, when about 75 percent of the total annual sediment load was transported. Sediment yields generally increased as percent impervious surface increased. Computed hourly total nitrogen and total phosphorus concentrations and yields and streamflow-weighted concentrations generally were largest in Indian and Mill Creeks. Annual percent contribution of total nitrogen in the Blue River from wastewater treatment facility discharges ranged from 19 percent in 2010 to 60 percent in 2006. Annual percent contribution of total nitrogen in Indian Creek from wastewater treatment facility discharges ranged from 35 percent in 2010 to 93 percent in 2006. The largest percent nutrient contributions from wastewater discharges coincided with the smallest annual precipitation and streamflow volume, resulting in less contribution originating from runoff. Fecal indicator bacteria Escherichia coli density at the urban Indian Creek site was usually the largest of the five monitoring sites, with an annual median density that consistently exceeded the State primary contact criterion value but was less than the secondary contact criterion. Less than 1 percent of the total annual bacteria load in the Blue River and Indian Creek originated from wastewater discharges, except during 2006 when about 6 percent of the Indian Creek load originated from wastewater. Continuous water-quality monitoring provides a foundation for comprehensive evaluation and understanding of variability and loading characteristics in streams in Johnson County. Because several directly measured parameters are strongly correlated with particular constituents of interest, regression models provide a valuable tool for evaluating variability and loading on the basis of computed continuous data. Continuous data are particularly useful for characterizing nonpoint-source contributions from stormwater runoff. Transmission of continuous data in real-time makes it possible to rapidly detect and respond to potential environmental concerns. As monitoring technologies continue to improve, so does the ability to monitor additional constituents of interest, with smaller measurement error, and at lower operational cost. Continuous water-quality data including model information and computed concentrations and loads during the study period are available at http://nrtwq.usgs.gov/ks/ .

Kansas↗

USGS2020

Regional regression equations for estimation of four hydraulic properties of streams at approximate bankfull conditions for different ecoregions in Texas

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, assessed statistical relations between hydraulic properties of streams at approximate bankfull conditions for different ecological regions (ecoregions) in Texas. Data from more than 103,000 records of measured discharge and ancillary hydraulic properties were assembled from summaries of discharge measurements for 424 U.S. Geological Survey streamgages in Texas. The data were subsequently subsetted at each streamgage for a streamgage-specific discharge interval centered on the estimated median annual peak discharge (0.5 annual exceedance probability) obtained from previously published regional regression equations in Texas in conjunction with the streamgage-specific sample median annual peak discharge for the period of record for each streamgage. Discharge measurements at gaged locations representing bankfull conditions (approximated from a discharge interval centered on the estimated median annual peak discharge at a given site) and associated watershed properties were subjected to rigorous statistical analysis. For most discharge measurements (where discharge is symbolically represented as Q ), the following hydraulic properties are available: cross-section area ( A ), water-surface top width ( B ), and reported mean velocity ( V ). Statewide summary statistics were computed by using these four hydraulic properties ( Q , A , B , and V ) and the following five watershed properties: (1) watershed area (contributing drainage area), (2) a multiple of main-channel slope (1,000 times main-channel slope), (3) mean annual precipitation, (4) drainage density, and (5) sinuosity ratio. From the initial set of 424 streamgages, summary statistics were computed for 372 selected streamgages in Texas and constitute the subsetted measurements dataset described in this report. Eight of the 10 ecoregions in Texas are represented in the statewide summary statistics. The resulting statistical relations, expressed as regression equations, can be used to estimate cross-section area, water-surface top width, discharge, and mean velocity of streams in different Texas ecoregions, at approximate bankfull conditions. In the regression equations, watershed properties were the independent variables for applicable watersheds, and predictions from the equations might be useful for estimating the four hydraulic properties at ungaged or unmonitored locations from selected characteristics measured at both the ungaged locations and gaged locations. Four regression equations to estimate the four hydraulic properties were identified as the preferred equations from this study. The four preferred equations use watershed area, mean annual precipitation, and aggregated ecoregion (treated as a categorical variable) to estimate the hydraulic properties, and justification is provided for this preference. For the four equations, the proportions of variance explained by the regression equations as measured by Nash-Sutcliffe efficiency are about 71 percent for cross-section area, 36 percent for top width, 76 percent for discharge, and 25 percent for mean velocity. Residual standard error (RSEs) of the regression equations are 0.252 log10 square feet for cross-section area, 0.319 log10 feet for top width, 0.247 log10 cubic feet per second for discharge, and 0.190 log10 feet per second for mean velocity, and the corresponding standard deviations of response are 0.465 log10 square feet, 0.397 log10 feet, 0.507 log10 cubic feet per second, and 0.220 log10 feet per second, respectively. The residual standard errors are less than the standard deviations as anticipated but show that the uncertainty reduction (percent change) for cross-section area is about −46 percent, about −20 percent for top width, about −51 percent for discharge, and about −14 percent for mean velocity.

Texas↗

USGS2013

Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China

Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.

Dongjiang↗

USGS2024

Estimating biogeochemical rates using a computationally efficient Lagrangian approach

Nutrient concentrations in many estuaries have increased over the past century due to increases in wastewater discharge and increased agricultural intensity, contributing to multiple environmental problems. Numerous biogeochemical and physical processes in estuaries influence nutrient concentrations during transport, resulting in complex spatial and temporal variability and challenges identifying predominant processes and their rates. Mechanistic models which require these rates to quantify biogeochemical processes become complex and difficult to calibrate as the number of processes and parameters grows, owing to the high dimensionality of the parameter space and the computational cost of simultaneously modeling the transport and transformations of constituents. We developed a modeling approach that decouples transport from transformations, enabling fast, data-driven exploration of the parameter space. The approach extracted information including water age, cumulative exposure to specific habitats, and mean water depth exposure from a hydrodynamic model. Using this information, a biogeochemical model was implemented to predict ammonium and nitrate concentrations in a Lagrangian frame. The model performed each simulation in milliseconds on a laptop computer, allowing the fitting of rate parameters for key transformations by optimization. The optimization used fixed station nitrate observations and the model was then validated against high-resolution mapping observations of ammonium and nitrate. The results suggest that the observed spatial and temporal variation can be largely represented with five transformation processes and their associated rates. Dissolved inorganic nitrogen (DIN) losses occurred only in shallow vegetated areas in the model, highlighting that biogeochemical processes in these areas should be included in DIN models.

California↗