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Research about Ohio River

Source-linked reports with geographic coverage including Ohio River.

12 recordsLinked to original sources
USGS2017

Spatial and temporal genetic analysis of Walleyes in the Ohio River

Previous genetic analyses have shown that Walleyes Sander vitreus in the upper Ohio River comprise two distinct genetic strains: (1) fish of Great Lakes origin that were stocked into the Ohio River basin and (2) a remnant native strain (Highlands strain). Resource agencies are developing management strategies to conserve and restore the native strain within the upper reaches of the Ohio River. Hybridization between strains has impacted the genetic integrity of the native strain. To better understand the extent and effects of hybridization on the native strain, we used mitochondrial DNA and microsatellite markers to evaluate the spatial (river sections) and temporal (pre- and poststocking) genetic diversity of Ohio River Walleyes. Contemporary Lake Erie Walleyes and archival museum specimens collected from the Ohio River basin were used for comparison to contemporary Ohio River samples. Although there was evidence of hybridization between strains, most of the genetic diversity within the Ohio River was partitioned by basin of origin (Great Lakes versus the Ohio River), with greater similarity among river sections than between strains within the same section. Results also suggested that the native strain has diverged from historical populations. Furthermore, notable decreases in measures of genetic diversity and increased relatedness among native-strain Walleyes within two sections of the Ohio River may be related to stocking aimed at restoration of the Highlands strain. Our results suggest that although the Highlands strain persists within the Ohio River, it has diverged over time, and managers should consider the potential impacts of future management practices on the genetic diversity of this native strain.

Ohio River↗
USGS2015

Late Quaternary chronostratigraphic framework of terraces and alluvium along the lower Ohio River, southwestern Indiana and western Kentucky, USA

The lower Ohio River valley is a terraced fluvial landscape that has been profoundly influenced by Quaternary climate change and glaciation. A modern Quaternary chronostratigraphic framework was developed for the lower Ohio River valley using optically stimulated luminescence (OSL) dating and allostratigraphic mapping to gain insights into the nature of fluvial responses to glacial–interglacial/stadial–interstadial transitions and Holocene climate change. River deposits, T0 (youngest) to T7 (oldest), were mapped along a 75 km reach of the lower Ohio River and were dated using 46 OSL and 5 radiocarbon samples. The examination of cores combined with OSL and radiocarbon dating shows that fluvial sediments older than marine oxygen isotope stage (MIS) 2 are present only in the subsurface. Aggradation during MIS 6 (Illinoian glaciation) filled the valley to within ∼7 m of the modern floodplain, and by ∼114 ka (MIS 5e/Sangamon interglacial) the Ohio River had scoured the MIS 6 sediments to ∼22 m below the modern floodplain surface. There were no fluvial sediments in the valley with ages between MIS 5e and the middle of MIS 3. The MIS 3 ages (∼39 ka) and stratigraphic position of T5 deposits suggest the Ohio River aggraded 8–14 m during MIS 4 or MIS 3. Near the end of MIS 3, the Ohio River incised the mid Last Glacial (mid-Wisconsinan) deposits ∼10 m and began aggrading again by ∼30 ka. Aggradation continued into MIS 2, with maximum MIS 2 aggradation occurring before ∼21 ka, which is coincident with the global Last Glacial Maximum (LGM). As the Ohio River adjusted to changing fluxes in sediment load and discharge following the LGM, it formed a sequence of fill-cut terraces in the MIS 2 outwash that get progressively younger with decreasing elevation, ranging in age from ∼21 ka to ∼13 ka. From ∼14 ka to ∼13 ka the Ohio River rapidly incised ∼3 m to form a new terrace, and by ∼12 ka at the onset of the Holocene, the Ohio River established a meandering channel pattern. The river formed a broad floodplain surface from ∼12 ka to ∼6 ka, and then incised ∼1 m and formed a fill-cut terrace from ∼6 ka to ∼5 ka. After ∼5 ka, likely in response to mid-Holocene drought in North America, the Ohio River incised ∼5 m, and by ∼4 ka the river began aggrading again. The Ohio River has aggraded ∼4 m since aggradation began at ∼4 ka. The chronostratigraphic framework and reconstructed history developed here suggest that the lower Ohio River is highly sensitive to glacial–interglacial transitions and abrupt Holocene climate change and responds rapidly to these allogenic forcings.

Indiana, Kentucky↗
USGS2015

An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio

Between July 2013 and June 2014, the U.S. Geological Survey (USGS) made 10 streamflow measurements on the Ohio River about 1.5 miles (mi) downstream from the Hannibal Lock and Dam (near Hannibal, Ohio) and 11 streamflow measurements near the USGS Sardis gage (station number 03114306) located approximately 2.4 mi upstream from Sardis, Ohio. The measurement results were used to assess the accuracy of modeled or computed instantaneous streamflow time series created and supplied by the USGS, U.S. Army Corps of Engineers (USACE), and National Weather Service (NWS) for the Ohio River at Hannibal Lock and Dam and (or) at the USGS streamgage. Hydraulic or hydrologic models were used to create the modeled time series; index-velocity methods or gate-opening ratings coupled with hydropower operation data were used to create the computed time series. The time step of the various instantaneous streamflow time series ranged from 15 minutes to 24 hours (once-daily values at 12:00 Coordinated Universal Time [UTC]). The 15-minute time-series data, computed by the USGS for the Sardis gage, also were downsampled to 1-hour and 24-hour time steps to permit more direct comparisons with other streamflow time series. To facilitate comparisons between measurement results and time-series data, streamflows corresponding to the times of the streamflow measurements were computed from the time-series data by time-based linear interpolation. Prior to doing interpolations, measurement times for the Hannibal Lock and Dam location were adjusted for traveltime to account for the fact that the streamflow measurements were made about 1.5 mi downstream from the location corresponding to the modeled/computed time-series data. Measured and interpolated streamflows were tabulated along with residuals (the difference between measured and interpolated streamflows) and selected summary statistics. Overall, streamflows interpolated from the USGS computed 15-minute time-series data (hereafter referred to as the USGS 15-minute time-series data) had the smallest root-mean-square error (RMSE) (3,939 cubic feet per second [ft 3 /s]) and the second smallest mean absolute residual (2,636 ft 3 /s), whereas streamflows interpolated from the USACE 12 UTC time series had the largest RMSE (14,590 ft 3 /s) and the largest mean absolute residual (10,800 ft 3 /s). The larger RMSEs for streamflows interpolated from the USACE 12 UTC time series likely resulted in part from the coarser time step of that time series. Streamflows interpolated from the USGS downsampled 1-hour time series had the second smallest RMSE (4,025 ft 3 /s) and the smallest mean absolute residual (2,600 ft 3 /s). Somewhat surprisingly, streamflows interpolated from the NWS 6-hour model time series had the third smallest RMSE (4,483 ft 3 /s) and mean absolute residual (4,050 ft 3 /s) in spite of being determined from a time series with a coarser time step than the USACE 1-hour modeled and computed time series. Measured streamflows at the Sardis gage and at the Hannibal Lock and Dam measurement location were plotted versus residuals (expressed as a percentage of the measured streamflows) of corresponding interpolated time-series streamflow values. Results for each of the time series exhibited some anomaly, possibly indicating the need and (or) potential for improvement in the streamflow computational/modeling processes. Streamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage

Ohio↗
USGS2013

Evaluation of the groundwater-flow model for the Ohio River alluvial aquifer near Carrollton, Kentucky, updated to conditions in September 2010

The Ohio River alluvial aquifer near Carrollton, Ky., is an important water resource for the cities of Carrollton and Ghent, as well as for several industries in the area. The groundwater of the aquifer is the primary source of drinking water in the region and a highly valued natural resource that attracts various water-dependent industries because of its quantity and quality. This report evaluates the performance of a numerical model of the groundwater-flow system in the Ohio River alluvial aquifer near Carrollton, Ky., published by the U.S. Geological Survey in 1999. The original model simulated conditions in November 1995 and was updated to simulate groundwater conditions estimated for September 2010. The files from the calibrated steady-state model of November 1995 conditions were imported into MODFLOW-2005 to update the model to conditions in September 2010. The model input files modified as part of this update were the well and recharge files. The design of the updated model and other input files are the same as the original model. The ability of the updated model to match hydrologic conditions for September 2010 was evaluated by comparing water levels measured in wells to those computed by the model. Water-level measurements were available for 48 wells in September 2010. Overall, the updated model underestimated the water levels at 36 of the 48 measured wells. The average difference between measured water levels and model-computed water levels was 3.4 feet and the maximum difference was 10.9 feet. The root-mean-square error of the simulation was 4.45 for all 48 measured water levels. The updated steady-state model could be improved by introducing more accurate and site-specific estimates of selected field parameters, refined model geometry, and additional numerical methods. Collection of field data to better estimate hydraulic parameters, together with continued review of available data and information from area well operators, could provide the model with revised estimates of conductance values for the riverbed and valley wall, hydraulic conductivities for the model layer, and target water levels for future simulations. Additional model layers, a redesigned model grid, and revised boundary conditions could provide a better framework for more accurate simulations. Additional numerical methods would identify possible parameter estimates and determine parameter sensitivities.

Kentucky↗
USGS2009

An initial investigation of multidimensional flow and transverse mixing characteristics of the Ohio River near Cincinnati, Ohio

Two-dimensional hydrodynamic and transport models were applied to a 34-mile reach of the Ohio River from Cincinnati, Ohio, upstream to Meldahl Dam near Neville, Ohio. The hydrodynamic model was based on the generalized finite-element hydrodynamic code RMA2 to simulate depth-averaged velocities and flow depths. The generalized water-quality transport code RMA4 was applied to simulate the transport of vertically mixed, water-soluble constituents that have a density similar to that of water. Boundary conditions for hydrodynamic simulations included water levels at the U.S. Geological Survey water-level gaging station near Cincinnati, Ohio, and flow estimates based on a gate rating at Meldahl Dam. Flows estimated on the basis of the gate rating were adjusted with limited flow-measurement data to more nearly reflect current conditions. An initial calibration of the hydrodynamic model was based on data from acoustic Doppler current profiler surveys and water-level information. These data provided flows, horizontal water velocities, water levels, and flow depths needed to estimate hydrodynamic parameters related to channel resistance to flow and eddy viscosity. Similarly, dye concentration measurements from two dye-injection sites on each side of the river were used to develop initial estimates of transport parameters describing mixing and dye-decay characteristics needed for the transport model. A nonlinear regression-based approach was used to estimate parameters in the hydrodynamic and transport models. Parameters describing channel resistance to flow (Manning’s “n”) were estimated in areas of deep and shallow flows as 0.0234, and 0.0275, respectively. The estimated RMA2 Peclet number, which is used to dynamically compute eddy-viscosity coefficients, was 38.3, which is in the range of 15 to 40 that is typically considered appropriate. Resulting hydrodynamic simulations explained 98.8 percent of the variability in depth-averaged flows, 90.0 percent of the variability in water levels, 93.5 percent of the variability in flow depths, and 92.5 percent of the variability in velocities. Estimates of the water-quality-transport-model parameters describing turbulent mixing characteristics converged to different values for the two dye-injection reaches. For the Big Indian Creek dye-injection study, an RMA4 Peclet number of 37.2 was estimated, which was within the recommended range of 15 to 40, and similar to the RMA2 Peclet number. The estimated dye-decay coefficient was 0.323. Simulated dye concentrations explained 90.2 percent of the variations in measured dye concentrations for the Big Indian Creek injection study. For the dye-injection reach starting downstream from Twelvemile Creek, however, an RMA4 Peclet number of 173 was estimated, which is far outside the recommended range. Simulated dye concentrations were similar to measured concentration distributions at the first four transects downstream from the dye-injection site that were considered vertically mixed. Farther downstream, however, simulated concentrations did not match the attenuation of maximum concentrations or cross-channel transport of dye that were measured. The difficulty of determining a consistent RMA4 Peclet was related to the two-dimension model assumption that velocity distributions are closely approximated by their depth-averaged values. Analysis of velocity data showed significant variations in velocity direction with depth in channel reaches with curvature. Channel irregularities (including curvatures, depth irregularities, and shoreline variations) apparently produce transverse currents that affect the distribution of constituents, but are not fully accounted for in a two-dimensional model. The two-dimensional flow model, using channel resistance to flow parameters of 0.0234 and 0.0275 for deep and shallow areas, respectively, and an RMA2 Peclet number of 38.3, and the RMA4 transport model with a Peclet number of 37.2, may have utility for emergency-planning purposes. Emergency-response efforts would be enhanced by continuous streamgaging records downstream from Meldahl Dam, real-time water-quality monitoring, and three-dimensional modeling. Decay coefficients are constituent specific.

Kentucky, Ohio↗
USGS2006

Velocity, bathymetry, and transverse mixing characteristics of the Ohio River upstream from Cincinnati, Ohio, October 2004–March 2006

Velocity, bathymetry, and transverse (cross-channel) mixing characteristics were studied in a 34-mile study reach of the Ohio River extending from the lower pool of the Captain Anthony Meldahl Lock and Dam, near Willow Grove, Ky, to just downstream from the confluence of the Licking and Ohio Rivers, near Newport, Ky. Information gathered in this study ultimately will be used to parameterize hydrodynamic and water-quality models that are being developed for the study reach. Velocity data were measured at an average cross-section spacing of about 2,200 feet by means of boat-mounted acoustic Doppler current profilers (ADCPs). ADCP data were postprocessed to create text files describing the three-dimensional velocity characteristics in each transect. Bathymetry data were measured at an average transect spacing of about 800 feet by means of a boat-mounted single-beam echosounder. Depth information obtained from the echosounder were postprocessed with water-surface slope and elevation information collected during the surveys to compute stream-bed elevations. The bathymetry data were written to text files formatted as a series of space-delimited x-, y-, and z-coordinates. Two separate dye-tracer studies were done on different days in overlapping stream segments in an 18.3-mile section of the study reach to assess transverse mixing characteristics in the Ohio River. Rhodamine WT dye was injected into the river at a constant rate, and concentrations were measured in downstream cross sections, generally spaced 1 to 2 miles apart. The dye was injected near the Kentucky shoreline during the first study and near the Ohio shoreline during the second study. Dye concentrations were measured along transects in the river by means of calibrated fluorometers equipped with flow-through chambers, automatic temperature compensation, and internal data loggers. The use of flow-through chambers permitted water to be pumped continuously out of the river from selected depths and through the fluorometer for measurement as the boat traversed the river. Time-tagged concentration readings were joined with horizontal coordinate data simultaneously captured from a differentially corrected Global Positioning System (GPS) device to create a plain-text, comma-separated variable file containing spatially tagged dye-concentration data. Plots showing the transverse variation in relative dye concentration indicate that, within the stream segments sampled, complete transverse mixing of the dye did not occur. In addition, the highest concentrations of dye tended to be nearest the side of the river from which the dye was injected. Velocity, bathymetry, and dye-concentration data collected during this study are available for Internet download by means of hyperlinks in this report. Data contained in this report were collected between October 2004 and March 2006.

Ohio↗
USGS2001

Calibration and validation of a two-dimensional hydrodynamic model of the Ohio River, Jefferson County, Kentucky

The quantification of current patterns is an essential component of a Water Quality Analysis Simulation Program (WASP) application in a riverine environment. The U.S. Geological Survey (USGS) provided a field validated two-dimensional Resource Management Associates-2 (RMA-2) hydrodynamic model capable of quantifying the steady-flowpatterns in the Ohio River extending from river mile 590 to 630 for the Ohio River Valley Water Sanitation Commission (ORSANCO) water-quality modeling efforts on that reach. Because of the hydrodynamic complexities induced by McAlpine Locks and Dam (Ohio River mile 607), the model was split into two segments: an upstream reach, which extended from the dam upstream to the upper terminus of the study reach at Ohio River mile 590; and a downstream reach, which extended from the dam downstream to a lower terminus at Ohio River mile 636. The model was calibrated to a low-flow hydraulic survey (approximately 35,000 cubic feet per second (ft 3 /s)) and verified with data collected during a high-flow survey (approximately 390,000 ft 3 /s). The model calibration and validation process included matching water-surface elevations at 10 locations and velocity profiles at 30 cross sections throughout the study reach. Based on the calibration and validation results, the model is a representative simulation of the Ohio River steady-flow patterns below discharges of approximately 400,000 ft 3 /s.

Kentucky↗
USGS1999

Occurrence, distribution, and trends of volatile organic compounds in the Ohio River and its major tributaries, 1987-96

The Ohio River is a source of drinking water for more than 3 million people. Thus, it is important to monitor the water quality of this river to determine if contaminants are present, their concentrations, and if water quality is changing with time. This report presents an analysis of the occurrence, distribution, and trends of 21 volatile organic compounds (VOCs) along the main stem of the Ohio River and its major tributaries from 1987 through 1996. The data were collected by the Ohio River Valley Water Sanitation Commission's Organics Detection System, which monitors daily for VOCs at 15 stations. Various statistical methods were applied to basinwide data from all monitoring stations and to data from individual monitoring stations. For the basinwide data, one or more VOCs were detected in 45 percent of the 44,837 river-water samples. Trichloromethane, detected in 26 percent of the samples, was the most frequently detected VOC followed by benzene (11 percent), methylbenzene (6.4 percent), and the other 18 VOCs, which were detected in less than 4 percent of the samples. In samples from 8 of the 15 monitoring stations, trichloromethane was also the most frequently detected VOC. These stations were generally near large cities along the Ohio River. The median trichloromethane concentration was 0.3 microgram per liter (μg/L), and concentrations ranged from less than 0.1 to 125.3 μg/L. Most of the VOCs had median detected concentrations that ranged from 0.1 to 0.4 μg/L for the basinwide data and for samples from individual stations. Samples from stations in the upstream part of the basin and from the Kanawha River had the highest median concentrations. Ninety-nine percent of the detected VOC concentrations were within U.S. Environmental Protection Agency drinking-water regulations. Of the 268 exceedances of drinking-water regulations, 188 were due to the detection of 1,2-dichloroethane prior to 1993 in samples from the monitoring station near Paducah, Ky. Time trend analyses indicated that most VOCs had no trend in samples at most monitoring stations because they were detected infrequently. At one or more stations, 14 VOCs had decreasing trends in monthly mean concentrations that ranged from -0.01 to -0.42 μ/L per year. Nine VOCs had significant decreasing trends in percentage detection that ranged from -1.08 to -12.90 percent per year. These trends suggest that source-control efforts are working and that water quality is improving.

Ohio River↗
USGS1973

Aquifer diffusivity of the Ohio River alluvial aquifer by the flood-wave response method

Aquifer diffusivity (T/S) was calculated for 10 sites in the alluvial aquifer adjacent to the Ohio River by observing the response of the aquifer to a flood wave in the river. The calculated type curves matched the observed aquifer response reasonably well at eight of the 10 sites. The diffusivities ranged from 0.4 ft 2 sec -1 to 10.3 ft 2 sec -1 and were generally in agreement with diffusivity values calculated from pump-test methods at two of the sites. Interference from pumping 1/2 mile upstream from one site and localized aquifer inhomogeneity at another site precluded calculation of diffusivity. Determining the shape of the ground-water recession curve may be difficult, but it can be done satisfactorily by collecting water-level data during an extended period of ground-water discharge and transposing the average recession curve to the flood period being analyzed. The flood-wave response method for estimating aquifer diffusivity provides a relatively inexpensive technique for obtaining a significant part of the data needed to predict the aquifer's response to river and pumping stresses.

Ohio River↗
USGS1961

Time of travel of water in the Ohio River, Pittsburgh to Cincinnati

This report presents a procedure for estimating the time of travel of water in the Ohio River from Pittsburgh, Pa., to Cincinnati, Ohio, under various river stage conditions. This information is primarily for use by civil defense officials and by others concerned with problems involving travel time of river water. Tables and charts are presented to show, for a particular stage or discharge at Cincinnati, the average time it would take for water to travel through the entire reach from Pittsburgh, or through successive intermediate segments of the reach. For example, when the discharge at Cincinnati is 200,000 cfs, travel time from Pittsburgh to Cincinnati, a distance of 470 miles, averages about 7 days; and for discharges of more than 200,000 cfs, the travel time decreases very slowly with increasing discharge. When the discharge is 30,000 cfs, travel time is about 28 days; and for discharges of less than 30,000 cfs, the travel time increases very rapidly with decreasing discharge. Estimates of travel time at low discharge are subject to large errors. Statistical analysis of the possible variations of upstream discharge for a given discharge at Cincinnati indicates that the shortest probable travel time from Pittsburgh to Cincinnati ranges from 56 percent of that under average conditions when the discharge at Cincinnati is 15,000 cfs to 93 percent of that under average conditions when the discharge at Cincinnati is 894,000 cfs. A chart showing the time distribution of flow at Cincinnati is presented so that the probable travel time of Ohio River water can be determined for any time of the year. This chart provides information which, when applied to the time-of-travel chart, shows that the most probable travel time of water from Pittsburgh to Cincinnati ranges from 160 hours in February to 1,250 hours in September. Also presented is a flow-duration curve that can be used to predict future discharges and, subsequently, times of travel, for use in long-range planning. The procedure used to compute time of travel is described in sufficient detail to make it usable as a guide for similar studies of other rivers that have deans and pools in the reach being studied. The computations for the time-of-travel charts were made as follows: (a) by dividing the reach between Pittsburgh and Cincinnati into four subreaches with a full-range streamgaging station at or near the ends of each; (b) by computing for each subreach mean velocities corresponding to various discharges at Cincinnati, using data obtained from river survey maps and data available from gaging station operations; (c) by assuming that any mass of contaminated water would travel at a rate equal to that of the mean velocity of the river water.

Ohio River↗
USGS1961

An aquifer test in the southwestern part of the Louisville area, Kentucky

The unconsolidated sand and gravel deposits along the Ohio River at Louisville, Ky. contain a large quantity of ground water. Parts of the aquifer have been overdeveloped in recent years, however, and at the present time great emphasis is being placed on proper location, development, and use of ground-water supplies. The present trend of industrial growth is to the southwest of the city in the undeveloped area along the Ohio River, where the yields to individual wells are higher and relatively large supplies can be developed. The average coefficient of permeability and storage coefficient of the aquifer here are 1,500 gallons per day per square foot and 0.2, respectively.

Kentucky↗