Geology topics

G. F. Koltun

Publications and source records attributed to G. F. Koltun.

At least 19 recordsLinked to original sources

USGS2025

Potential water-quality and hydrology stressors on freshwater mussels with development of environmental DNA assays for selected mussels and macroinvertebrates in Big Darby Creek Basin, Ohio, 2020–22

The richness and abundance of freshwater mussels in the Big Darby Creek Basin has declined in recent decades, according to survey results published by the Ohio Biological Survey. In October 2016, a major mussel die-off of undetermined cause reportedly affected over 50 miles of Big Darby Creek; however, fishes and other wildlife were not noticeably impacted. Pollution, habitat destruction, climate change, and hydrologic modification have all been theorized as potential reasons for the widespread declines in freshwater mussel populations in North America. To better understand potential stressors to mussels and other aquatic organisms in the Big Darby Creek Basin, the U.S. Geological Survey, in cooperation with the Ohio Water Development Authority, evaluated water quality and temporal changes in hydrology at selected locations. In addition, environmental deoxyribonucleic acid (eDNA) quantitative polymerase chain reaction (qPCR) assays were developed to detect the presence of selected mussels and macroinvertebrates using stream water. Time-weighted average concentrations of pesticides, organic wastewater compounds (OWCs), and polycyclic aromatic hydrocarbons (PAHs) were determined for selected locations within the Big Darby Creek Basin. Passive samplers designed to mimic the respiratory exposure of aquatic organisms and the bioconcentration of organic contaminants into their fatty tissues were deployed three times annually at three sites within the Big Darby Creek Basin in 2020 and 2021. Analyses were done for 204 pesticide compounds, 38 OWCs, and 33 PAHs. Of the 204 pesticide compounds, 70 were detected in at least one sample; 30 were detected in all samples. Herbicides and herbicide degradates were the pesticides most frequently detected and also had some of the highest concentrations of the pesticides detected in this study. Three herbicides (atrazine, ametryn, and metribuzin) were detected in at least 88 percent of samples and two fungicides (azoxystrobin and propiconazole) were detected in all samples. Of the 38 OWCs, 24 were detected in at least one sample; however, only one ( N , N -diethyltoluamide [DEET]) was detected in all samples. Of the 33 PAHs, 29 were detected in at least one sample; 12 were detected in all samples. A continuous water-quality monitor was operated seasonally on Big Darby Creek above Georgesville, Ohio, from 2020 to 2022. Dissolved oxygen concentrations generally followed a daily cycle, peaking in early evening and troughing around sunrise. There were occasional 24-hour swings in dissolved oxygen concentration that had a range exceeding 10 milligrams per liter. However, dissolved oxygen concentrations never fell below Ohio’s aquatic life criteria for warmwater habitats (outside of mixing zones) of 4.0 milligrams per liter as an instantaneous minimum and 5.0 milligrams per liter as a minimum 24-hour average. The Ohio water-quality criteria for temperatures are 29.4 degrees Celsius as an instantaneous maximum and 27.8 degrees Celsius as a 24-hour average maximum. In 2020, there were 10 days when the maximum instantaneous value for temperature was exceeded and 3 consecutive days when the maximum 24-hour average temperature was exceeded. Streamflow time-series data from three gaging stations within the Big Darby Creek Basin were evaluated for trends in annual flow statistics and daily nonexceedance probabilities over time. In general, the evaluation of streamflow conditions at the Big Darby Creek gage (with 97 years of record) indicated that streamflow changed between water years 1922 and 2021. During that time span, flows in general increased, the number of high-flow pulses became more frequent, and low-flow pulses and extreme low-flow periods became less frequent. The only strong indication of trends over time in annual flow statistics for the relatively short records for the other two gages (on Little Darby Creek, with 25 years of record, and Hellbranch Run, with 29 years of record) was that as time went on, reversals between rising and falling periods became more frequent. The U.S. Geological Survey Ohio Water Microbiology Laboratory developed eDNA qPCR assays to detect Epioblasma rangiana (northern riffleshell mussels), Chimarra obscura (a species of caddisfly), Maccaffertium pulchellum (a species of mayfly), and optimized a preexisting eDNA qPCR assay to detect for Ptychobranchus fasciolaris (kidneyshell mussels). The assays were validated by using environmental sampling methods. Assay sensitivity was established by determining the limits of detection and quantification. Water samples were collected at 12 sites in the Big Darby Creek Basin between 2020 and 2022 and analyzed for eDNA with the qPCR assays developed for this study.

Ohio↗

USGS2025

Changes in phosphorus concentration and flux from 2011 to 2023 in major U.S. tributaries to the Laurentian Great Lakes

Reducing phosphorus (P) flux to the Great Lakes is critical for improving water quality and controlling eutrophication. We used 13 water years (2011–2023) of U.S. Geological Survey data from 24 major U.S. tributaries (representing 47% of the U.S. Great Lakes watershed area) to evaluate temporal changes in orthophosphate (PO 4 -P) and total P (TP) using Weighted Regressions on Time, Discharge, and Season. We assessed actual and flow-normalized P concentrations and fluxes. Between 2011 and 2023, P concentrations and fluxes declined in many tributaries, although the extent and significance of these declines varied. Decreases were more common and statistically likely for TP than PO 4 -P, and several high-loading watersheds had modest or non-significant changes. Flow-normalized PO 4 -P:TP flux ratios increased in over half the tributaries, suggesting that even where P reductions occurred, reductions in the more bioavailable P fraction were proportionally smaller. Actual P fluxes were strongly correlated with streamflow, and year-to-year variability in actual fluxes was, on average, three times greater than variability related to trends in flow-normalized fluxes. This underscores the role of hydrology in modulating P export and highlights how changing precipitation and runoff patterns can obscure or counteract management progress. Spring accounted for the largest share of annual P flux in most tributaries, though many showed declining spring contributions. Our basin-wide analysis reveals that while management efforts may have yielded progress in reducing TP in many watersheds, additional strategies would be needed to address PO 4 -P reductions and account for changing hydrology, especially in high-contributing watersheds.

Journal of Great Lakes Research↗

USGS2024

Low-flow statistics computed for streamflow gages and methods for estimating selected low-flow statistics for ungaged stream locations in Ohio, water years 1975–2020

A study was conducted by the U.S. Geological Survey, in cooperation with the Ohio Water Development Authority and the Ohio Environmental Protection Agency, to compute low-flow frequency, flow-duration, and harmonic mean flow statistics for long-term streamflow gages and to develop regression equations to estimate those statistics at unregulated, ungaged stream locations in Ohio. The flow statistics were computed with data collected after the 1974 water year because upward trends and statistically significant step changes (occurring after the late 1960s but before 1975) in annual flow statistics were detected at many candidate gages in Ohio. A total of 180 continuous-record gages in Ohio and bordering States were identified as having at least 10 years of daily flow records during the analytical period (water years 1975–2020). Also identified were five low-flow partial-record gages in Ohio that had instantaneous low flows that correlated strongly with daily streamflows at one of the continuous-record gages (also referred to as index gages). For continuous-record gages, the following flow statistics were computed: annual and seasonal minimum 1-, 7-, 30-, and 90-day flows with 2-, 5-, 10-, 20-, and 50-year recurrence intervals; annual and seasonal 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent duration flows; and the harmonic mean flow. For partial-record gages, estimates were made for annual and seasonal minimum 1-, 7-, 30-, and 90-day low flows with 2-, 10-, and 20-year recurrence intervals and annual and seasonal 98-, 95-, 90-, 85-, and 80-percent duration flows. The drainage basin of each gage was inspected for anthropogenic or karst features that could appreciably affect or regulate low flows. That inspection resulted in data from 53 of the 180 continuous-record gages and the 5 low-flow partial-record gages being categorized as “unregulated” and subsequently used in regression analyses to develop equations for estimating low-flow statistics. Two hundred and sixty potential explanatory variables were tested for this study. In most cases, a streamflow-variability index (SVI) was chosen as the sole explanatory variable for the regression analyses to predict the harmonic mean and annual and seasonal low-flow yields. The exceptions were for one of the September–November low-flow yield statistics and all the December–February yield statistics. Drainage area, decimal longitude, and usually SVI were chosen as the explanatory variables for those exceptions and to predict the 80-percent duration flows. The SVI values used in the model were estimated from a geospatial grid of SVI values developed for this study by using an empirical Bayesian kriging regression prediction. Observations for continuous-record gages used in the regression analyses were weighted as a function of their record length. Weights for partial-record gages were estimated based on the weights determined for their index gages. Equations for low-flow yields were developed by using censored regressions with a censoring level of 0.00001 cubic foot per second per square mile. Numerical constraints were placed on the yield equations if they could compute yields less than the yield censoring level or if the yields did not monotonically decrease with increasing SVI. Logistic-regression equations were developed, with SVI and drainage area as explanatory variables, to estimate the probability that the low-flow statistics were greater than the flow censoring level (0.01 cubic foot per second). The regression equations presented in this report were developed for implementation in the Ohio StreamStats application. The equations are applicable to unregulated streams in Ohio and are not applicable to streams with karst drainage features, diversions, regulation, or other anthropogenic activities that can appreciably affect low flow. The equations were developed by using observations with a range of SVI values from 0.41 to 1.23 log10 cubic foot per second and a range of drainage areas from 0.21 to 540 square miles. The applicability of the equations outside these ranges is not known.

Ohio↗

USGS2024

Analysis of water use associated with hydraulic fracturing and determination of baseline water quality in watersheds within the shale play of eastern Ohio, 2021–23

The U.S. Geological Survey, in cooperation with the Ohio Department of Natural Resources, performed a two-part study to (1) assess water use and temporal trends and changes in streamflow, and to (2) characterize 2021–23 baseline water quality, as they relate to oil and gas extraction activities in selected eastern Ohio watersheds. Between calendar years 2010 and 2019, hydraulic fracturing water withdrawals totaling about 27,168 million gallons were reported at 643 locations in Ohio. In 2021, wells developed with hydraulic fracturing were the source of most of the oil and gas produced in Ohio. Daily streamflow time-series data from seven study gages and two reference gages were used to assess temporal trends and changes in streamflow. The study gages were in basins with reported water withdrawals for hydraulic fracturing. The reference gages, which have long periods of record and were subject to minimal streamflow regulation, were in nearby basins with no hydraulic fracturing water withdrawals. Trend slopes for the period of record annual minimum and median daily streamflows and for annual daily streamflow nonexceedance probabilities less than 0.9 were all uniformly positive at the study and reference gages. This trend indicates a consistently increasing pattern over the periods of record, except for high flows. In addition, analyses of annual streamflow statistics showed no general indication that low flows or extreme low flows at the reference or study gages have lowered, become more frequent, or lengthened in duration since 2010, when records for hydraulic fracturing water withdrawals began in Ohio. In fact, in almost all cases, the opposite was indicated. Nonexceedance percentiles of daily streamflows were compared between the full and pre-2012 periods of record for reference and study gages. The streamflows associated with nonexceedance percentiles in the lower quartile of daily streamflows determined for the full period of record were larger than or equal to those determined for the pre-2012 period of record for all study and reference gages. This indicates that low flows did not decrease during the post-2011 period of record when water was withdrawn for hydraulic fracturing. Water-quality data were collected eight times at each of eight sampling sites (six of which were colocated with the study gages). Sampling was done during a variety of flow conditions to assess baseline water quality. In 2021, the 8 sampling sites had drainage basins that were wholly or partially within 7 of the 10 most active counties in Ohio for oil and gas development. As part of the record of baseline conditions, water-quality data were used to assess (1) water types based on major-ion chemistry; (2) sources of salinity to streams; (3) exceedances of aquatic life use criteria; and (4) the correlations between water chemistry and drainage-basin characteristics, such as density of oil and gas wells, density of wastewater treatment plants, or the percentage of different types of land cover (agriculture, developed, forest). Seven of the water-quality sampling sites were designated as coal-mine impacted based on criteria developed for assessing mine-drainage impacts in Ohio. Mine drainage from historical coal mining in the region likely affected the quality of these streams and complicated the use of some constituents typically used as indicators of oil and gas influence. Based on major-ion chemistry, three main types of water were in the study area―sulfate (three sites), calcium-bicarbonate (one site), and mixed bicarbonate-chloride (four sites) type waters. One site had samples with a higher proportion of sodium and chloride ions than other stream samples, indicating potential contamination with oil-field brine or road salt. Binary mixing curves revealed that 11 samples from 4 of the sampling sites likely contained a component of brine. The results of the baseline assessment of surface-water quality in the study area showed no exceedances of Ohio Environmental Protection Agency aquatic life use criteria. Spearman’s rank correlation coefficients indicated no significant positive correlations with the density of vertical or horizontal oil and gas wells.

Ohio↗

USGS2023

Potential drivers of change in fluxes of nutrients and total suspended solids in the upper White River Basin, Indiana, Water Years 1997–2019

The U.S. Geological Survey and The Nature Conservancy previously collaborated to evaluate changes and trends in the concentrations and flux of nutrients (total phosphorus, as phosphorus; nitrate plus nitrite, as nitrogen; and total Kjeldahl nitrogen, as nitrogen) and total suspended solids (TSS) at three study gages located on the upper White River at Muncie, near Nora, and near Centerton, Indiana. That work is extended and updated using 3 additional years of data (through 2020) and newer estimation methods. In addition, information is provided about climatic and anthropogenic factors that could influence the concentrations and fluxes of nutrients and TSS in the upper White River Basin.

Indiana↗

USGS2023

Trends in environmental, anthropogenic, and water-quality characteristics in the upper White River Basin, Indiana

The U.S. Geological Survey (USGS), in cooperation with The Nature Conservancy, undertook a study to update and extend results from a previous study (Koltun, 2019, https://doi.org/10.3133/sir20195119 ), using data from 3 additional years and newer estimation methods. Koltun (2019) assessed trends in streamflow, precipitation, and estimated annual mean concentrations and flux of nitrate plus nitrite, total Kjeldahl nitrogen, total phosphorus, and total suspended solids (TSS) for USGS streamflow gages on the upper White River at Muncie, near Nora, and near Centerton, Indiana. Annual mean and maximum daily streamflows had statistically significant upward trends at all study gages between water years 1978 and 2020. An abrupt increase in streamflow occurred around water year 2001. Annual total precipitation at the Indianapolis International Airport increased between calendar years 1932 and 2020 at an average rate of 0.089 inches per year. The current study assessed the magnitude, direction, and likelihood of change in flow-normalized concentrations and flux of TSS, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen between water years 1997 and 2019. With two exceptions, concentration and flux changes that were statistically significant in Koltun (2019, https://doi.org/10.3133/sir20195119 ), which reported changes between water years 1997 and 2017, still have the same statistically significant change directions. The reliability of the current trend result for TSS is uncertain because of a large gap in the TSS record for the Centerton gage. For each constituent, spatial patterns were examined in the sampled distribution of nutrient and TSS concentration data from 20 mainstem, tributary, and distributary locations in the upper White River Basin. The largest median concentrations of TSS, total phosphorus, and total Kjeldahl nitrogen were associated with mainstem upper White River sites downstream from Indianapolis. The median total phosphorus and total Kjeldahl nitrogen concentrations were elevated relative to bracketing upstream/downstream mainstem sites at the upper White River site immediately downstream from Muncie. Data on several anthropogenic factors that could influence the concentrations and fluxes of nutrients and TSS were gathered and analyzed to better understand the factors’ spatial and temporal variations. Those anthropogenic factors included population, land cover, cropping and operational tillage practices, fertilizer application, and upgrades to wastewater treatment systems and delivery processes.

Indiana↗

USGS2021

Assessment of runoff volume reduction associated with soil amendments added to portions of highway median-strip catchments in Ohio, 2018–20

The U.S. Geological Survey installed 10 rain gages and 12 calibrated H-flumes to measure rainfall and runoff volumes at 10 locations in Ohio Department of Transportation highway median-strip catchments. Data were collected to facilitate comparisons of rainfall and runoff volumes at study sites before and after stormwater best management practices (BMPs) were installed and between sites with different BMPs. The BMP treatments comprised removing the top layer of the existing soil, rototilling the remaining soil to a 6-inch depth, mixing the soils with one of two soil amendments (compost with sand or shale) at one of two thicknesses (4 inches or 6 inches), topping with a compost blanket, seeding, and installing erosion control matting. The overall treatment used at a given study site is referred to as “BMP.” At two locations where soil amendments were installed, a second “control” site was installed to measure runoff from an adjacent catchment in the same median strip where no soil amendment was installed. This no-treatment option (no soil amendment) was considered its own class of BMP. Rainfall and runoff data were collected during periods when air temperatures were above freezing (including all months except January, February, and parts of December and March) from 2018 to 2020. The data collection period for each study site was divided into “pre-BMP” and “post-BMP” periods. Equipment to measure rainfall and runoff was installed and data were collected from April to December 2018 before installation of soil amendments (the pre-BMP period). The post-BMP period started between April and May of 2019 at the first measured rainfall after soil amendments were installed. Rainfall and runoff monitoring continued through September 2020. For control sites, the post-BMP periods were assigned to start with the first measured rainfall in the 2019 data collection season. A rainfall-runoff “event” was defined as beginning at the time of the first measured rainfall and ending when rainfall and runoff (if any) ceased and remained ceased for at least 3 hours. A value referred to as “event runoff percentage,” defined as the total volume of runoff during an event expressed as a percentage of the total volume of rainfall falling over the catchment, was computed for each event. The distribution of rainfall totals associated with events was similar between the pre-BMP and post-BMP periods; however, there were appreciable between-site differences in the distribution of event runoff percentages during the pre-BMP and post-BMP periods. Empirical distribution function (EDF) tests were performed with and without data from events that resulted in no runoff to determine whether the distribution of event runoff percentages changed from the pre-BMP period to the post-BMP period. The null hypothesis that the EDFs of event runoff percentages were equal in the pre-BMP and post-BMP periods was rejected ( α =0.05) in at least one of the two tests for four sites (one site with a shale amendment and three sites with sand amendments). Mean event runoff percentages at each of those four sites decreased from the pre-BMP period to the post-BMP period. The null hypothesis that the EDFs of event runoff percentages were equal was not rejected for the other six sites’ draining catchments with soil amendments or the two control sites. EDF tests performed on event rainfall totals indicated no statistically significant changes between the pre-BMP and post-BMP period distributions for any of the sites. Double-mass analyses of cumulative runoff were performed for two pairs of closely spaced sites (each pair located in a common median strip): one site in each pair drained a catchment where soil amendments were installed, and the other (a control) drained a catchment without soil amendments. Those double-mass analyses indicated a small reduction in runoff from the pre-BMP to post-BMP period at the site whose catchment received the sand and compost amendment, but no perceptible reduction in runoff at the site whose catchment received the shale and compost amendment. Regression analyses indicated that (a) three rainfall factors (event rainfall totals, total rainfall for the previous 7 days, and a cross product of the factors) and the intercept term were the four most important factors explaining event runoff percentages, (b) the effect of amendment type on event runoff percentage was small in comparison to the rainfall and intercept terms, (c) event runoff percentages tended to be lower for sites with shale amendments than sites with sand amendments; however, event runoff percentages tended to be lower for control sites than for sites with shale or sand amendments, and (d) event runoff percentages increased with increasing amendment thickness. The counterintuitive results that event runoff percentages increased with increasing amendment thickness and that control sites tended to have lower event runoff percentages than sites draining soil-amended catchments likely reflects unmeasured factors that existed at the sites before BMPs were installed rather than the effect of the BMP treatments. Although not definitive, some support for the conclusion that the sand amendment was generally more effective at reducing runoff than the shale amendment was provided by results from the EDF tests, double-mass analyses, and runoff statistics.

Ohio↗

USGS2021

Estimated total phosphorus loads for selected sites on Great Lakes tributaries, water years 2014–2018

Monthly and annual total phosphorus loads were estimated for water years 2014 through 2018 for 23 streamgaged (gaged) sites on tributaries to the Great Lakes. Processing and regression methods described by Robertson and others (2018) were used with discrete and continuous data collected during water years 2011 and 2018 to update regression models for estimating instantaneous flux with the same form of equations as published by Robertson and others (2018). Monthly and water year average fluxes for all but two of the 23 gage sites were estimated using a weighted combination of results from surrogate models (which have streamflow, turbidity, and seasonal indicators as explanatory variables) and unit-value (UV)-flow models which have only UV streamflow and seasonal indicators as explanatory variables. Two of the gage sites had extensive periods of missing turbidity records, so average flux estimates for those stations were based solely on results from UV-flow models. For most sites, estimated loads of total phosphorus were computed and summed for water years 2014–2018. The cumulative loads were used to compute yields and flow-weighted mean concentrations for water years 2014–2018. The estimated cumulative total phosphorus loads for water years 2014–2018 ranged from 112 to 11,500 metric tons. The Maumee River site (U.S. Geological Survey gage number 04193500) had the largest estimated cumulative load for water years 2014–2018 and the third largest estimated flow-weighted mean concentration. In fact, the estimated cumulative load at the Maumee River site was more than three times larger than the second largest estimated cumulative load. Estimated average annual total phosphorus yields and flow-weighted mean concentrations for water years 2014–2018 ranged from 0.016 metric tons per square kilometer to 0.771 metric tons per square kilometer and 0.033 milligram per liter to 0.466 milligram per liter, respectively. The Cattaraugus Creek gage site (U.S. Geological Survey gage number 04213500) had the highest estimated average annual total phosphorus yield and flow-weighted mean concentration. The average annual total phosphorus yield at the Cattaraugus Creek gage site was almost twice as large as the second largest estimated yield.

Illinois, Indiana, Michigan, Minnesota, New York, ↗

USGS2020

Trends in streamflow, nutrients, and total suspended solids in the Upper White River Basin, Indiana

The U.S. Geological Survey, in partnership with The Nature Conservancy, analyzed existing water-quality and streamflow data from three locations in the Upper White River Basin, Indiana, to estimate annual mean concentrations and fluxes and to identify and quantify changes in water quality and streamflow over time. Water-quality data used in the analyses were collected between water years 1992 and 2017. Annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus as phosphorus, nitrate plus nitrite as nitrogen, and total Kjeldahl nitrogen as nitrogen were estimated for U.S. Geological Survey streamgage locations in Indiana on the Upper White River at Muncie, near Nora, and near Centerton. In addition, flow-normalized annual mean-daily concentrations and fluxes of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated and used to assess changes in these constituents between water years 1997 and 2017. Flow normalization is a process that attempts to remove the effects of year-to-year variation in streamflow on concentrations and fluxes without removing the effects associated with seasonal and long-term (multiyear) trends in streamflow.

Indiana↗

USGS2019

Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana

The U.S. Geological Survey (USGS), in cooperation with The Nature Conservancy, completed a study to estimate and assess trends in streamflow and annual mean concentrations and flux of nutrients (nitrate plus nitrite, total Kjeldahl nitrogen, and total phosphorus) and total suspended solids at three USGS streamgages (hereafter referred to as “study gages”) on the Upper White River at Muncie (USGS station 03347000), near Nora (USGS station 03351000), and near Centerton (USGS station 03354000), Indiana. Water-quality data used in the analyses were collected by several agencies between calendar years 1991 and 2017, and streamflow (discharge) data were collected by the USGS. For most of the water-quality constituents, there were suitable data to facilitate an analysis of the 26-year period extending from calendar years 1991 to 2017 (water years 1992 to 2017); however, shorter analytical periods were necessary for total Kjeldahl nitrogen for the study gages at Muncie and near Centerton and for total suspended solids for the study gage near Centerton. Temporal trends in streamflows at the study gages for the period extending from water years 1978 to 2017 were assessed using Exploration and Graphics for RivEr Trends (EGRET) and Mann-Kendall and Pettitt tests. With just one exception, the annual maximum and mean daily streamflows and the annual minimum 7-day mean streamflows at the study gages demonstrated upward trends (increasing streamflows) in the EGRET analyses. The exception was the annual 7-day minimum streamflow at the study gage near Nora, which indicated no trend. Mann-Kendall tests also indicated that the average trend for the annual maximum daily, annual mean daily, and annual 7-day minimum streamflow statistics between water years 1978 and 2017 was upward at each of the study gages; however, only the trends in the annual mean daily streamflows at the study gage at Muncie and the annual maximum daily streamflows at the study gages near Nora and near Centerton were statistically significant at a 0.05 probability level. The Pettitt tests indicated that a statistically significant step trend (abrupt change) in annual mean daily streamflows occurred at each of the study gages around water year 2001. The seasonal distributions of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentrations at the study gages were evaluated to identify patterns and other distinguishing characteristics by examining boxplots of concentrations as a function of month of the year. Seasonal distributions of nitrate plus nitrite concentrations and total suspended solids concentrations differed from each other but were generally similar among the three study gages for a given constituent. Median concentrations of nitrate plus nitrite were highest during the January–June months, whereas median concentrations of total suspended solids were highest during June and July. Seasonal distributions of total phosphorus concentrations were similar at the study gages near Nora and near Centerton, but the seasonal distribution was noticeably different at the study gage at Muncie, which had monthly median concentrations that were substantially lower than at the two downstream study gages (near Nora and near Centerton). The seasonal distribution of total Kjeldahl nitrogen concentrations differed in pattern among the three study gages; however, in general, some of the higher monthly median total Kjeldahl nitrogen concentrations at each study gage were associated with the late spring and summer periods. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method implemented in EGRET was used to estimate water-year annual mean daily concentrations and flux of nutrients and total suspended solids, as well as estimates of concentrations and flux that were “normalized” to remove the effect of year-to-year variation in streamflow. The approximate coefficients of determination for the WRTDS regression models ranged from a high of 0.82 for total phosphorus for the study gage near Centerton to a low of 0.19 for nitrate plus nitrite for the study gage near Nora. Loads and yields of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated for analytical periods consisting of the longest periods of concurrent record at the three study gages. Loads of each of the constituents increased sequentially from the most upstream study gage to the most downstream study gage; however, the same was not true for yields. The highest yields of total suspended solids, total phosphorus, and total Kjeldahl nitrogen occurred at the most upstream study gage (at Muncie); however, the highest yield of nitrate plus nitrite occurred at the most downstream study gage (near Centerton). WRTDS bootstrap tests were used to assess the magnitude, direction, and likelihood of changes in annual flow-normalized mean daily concentrations and flux of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen at the study gages between water years 1997 and 2017. Changes in flow-normalized concentrations and flux of the constituents between water years 1997 and 2017 were mostly downward (decreasing). The exceptions were likely to highly likely upward (increasing) changes in (1) flow-normalized annual mean daily concentration and annual flux for total suspended solids and total phosphorus at the study gage at Muncie, (2) flow-normalized annual mean daily total phosphorus concentration at the study gage near Centerton, (3) flow-normalized annual flux of total phosphorus at the study gage near Centerton, and (4) flow-normalized annual mean daily nitrate plus nitrite concentration at the study gage near Centerton. Although an upward change in flow-normalized nitrate plus nitrite concentrations was likely at the study gage near Centerton, flow-normalized annual flux of nitrate plus nitrite at that study gage was determined to have a highly likely downward change. EGRET and Exploration and Graphics for RivEr Trends Confidence Intervals (EGRETci) analyses can be used to improve our understanding of how concentrations and flux change as functions of time and streamflow, as well as provide information on how the relations between streamflow and constituent concentrations have changed within the calendar year between any 2 years included in the analyses. Examples of those uses, illustrating changes between calendar years 1992 and 2017, were given for total suspended solids concentrations at the study gage near Nora and for nitrate plus nitrite concentrations at the study gage near Centerton.

Indiana↗

USGS2019

Flood-frequency estimates for Ohio streamgages based on data through water year 2015 and techniques for estimating flood-frequency characteristics of rural, unregulated Ohio streams

Estimates of the magnitudes of annual peak streamflows with annual exceedance probabilities of 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, and 0.002 (equivalent to recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively) were computed for 391 streamgages in Ohio and adjacent states based on data collected through the 2015 water year. The flood-frequency estimates were computed following guidance outlined in Bulletin 17C, developed by the Advisory Committee on Water Information. The Bulletin 17C guidelines retain the basic statistical framework of the superseded Bulletin 17B guidelines; however, the Bulletin 17C guidelines add several enhancements including an improved method of moments approach for fitting the log-Pearson Type III (LPIII) distribution to the flood peaks (called the expected moments algorithm), a generalization of the Grubbs Beck low-outlier test (called the Multiple Grubbs Beck test) that permits identification of multiple potentially influential low floods, and new methods for estimating regional skew and uncertainty. Equations for estimating flood-frequency characteristics at ungaged sites on rural, unregulated streams in Ohio were developed with a two-step process involving ordinary least-squares and generalized least-squares regression techniques. Data from 333 streamgages with 10 or more years of unregulated record were screened for redundancy and a regression dataset was selected that was composed of flood-frequency and basin-characteristic data for 275 streamgages in Ohio and adjacent states. Two sets of equations were developed—one set, referred to as the “simple model,” uses regression region and drainage area as regressor variables, and a second set, referred to as the “full model,” uses regression region, drainage area, main-channel slope, and the percentage of the watershed covered by water and wetlands as regressor variables. The average standard errors of prediction ranged from about 40.5 to 46.5 percent for the simple-model equations and from about 37.2 to 40.3 percent for the full-model equations. For sites meeting the rural, unregulated criteria, flood-frequency estimates determined by means of LPIII analyses are reported along with weighted flood-frequency estimates, computed as a function of the LPIII estimates and the regression estimates. For sites with homogenous periods of regulation, flood-frequency estimates determined by means of LPIII analyses are reported. Ninety-five percent confidence limits are reported for all estimates. Values of regressor variables were determined from digital spatial datasets by means of a geographic information system (GIS). The GIS datasets and the new full-model equations have been incorporated into Ohio’s StreamStats application, a web-based, GIS-backed system designed to facilitate the estimation of streamflow statistics at ungaged locations on streams. Seasonal patterns in peak flows were assessed for 295 streamgages in Ohio. Annual peak flows occurred most frequently between January and April, with March having the highest frequency of occurrence. The month with the fewest number of annual peaks was October. Peak-of-record flows occurred most frequently in March, followed by January (months in which two of Ohio’s most severe widespread floods in recent history occurred). None of the peak-of-record flows occurred in October and only two occurred in November. Temporal trend in annual peak flows were assessed for 133 streamgages on unregulated streams in Ohio with 30 or more years of systematic record. Trends were assessed by computing the rank correlation (as measured with the two-sided Kendall’s tau statistic) between time and annual peak flows. Weak but statistically significant trends were indicated at 15 of the 133 streamgages. Of the 15 streamgages with significant trend in annual peak flows, 12 had an upward trend (positive tau) and 3 had a downward trend (negative tau). All 12 streamgages with positive tau values were at latitudes north of 40°33', and streamgages with negative tau values were at latitudes south of 40°33'.

Ohio↗

USGS2017

Geospatial tools effectively estimate nonexceedance probabilities of daily streamflow at ungauged and intermittently gauged locations in Ohio

Study region The state of Ohio in the United States, a humid, continental climate. Study focus The estimation of nonexceedance probabilities of daily streamflows as an alternative means of establishing the relative magnitudes of streamflows associated with hydrologic and water-quality observations. New hydrological insights for the region Several methods for estimating nonexceedance probabilities of daily mean streamflows are explored, including single-index methodologies (nearest-neighboring index) and geospatial tools (kriging and topological kriging). These methods were evaluated by conducting leave-one-out cross-validations based on analyses of nearly 7 years of daily streamflow data from 79 unregulated streamgages in Ohio and neighboring states. The pooled, ordinary kriging model, with a median Nash–Sutcliffe performance of 0.87, was superior to the single-site index methods, though there was some bias in the tails of the probability distribution. Incorporating network structure through topological kriging did not improve performance. The pooled, ordinary kriging model was applied to 118 locations without systematic streamgaging across Ohio where instantaneous streamflow measurements had been made concurrent with water-quality sampling on at least 3 separate days. Spearman rank correlations between estimated nonexceedance probabilities and measured streamflows were high, with a median value of 0.76. In consideration of application, the degree of regulation in a set of sample sites helped to specify the streamgages required to implement kriging approaches successfully.

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USGS2016

Estimation of upstream water use with Ohio’s StreamStats application

This report describes the analytical methods and results of a pilot study to enhance the Ohio StreamStats application by adding the ability to obtain water-use information for selected areas in the northeast quadrant of Ohio. Water-use estimates are determined in StreamStats through a simple multistep process. Water-use data used to develop the Ohio StreamStats water-use application were obtained from the Ohio Department of Natural Resources (ODNR) and 2010 countywide estimates of self-supplied domestic water use (hereafter referred to as “domestic water use”) compiled by the U.S. Geological Survey (USGS). With the exception of domestic water uses, monthly time series of reported water uses for 2005–2012 are used to calculate average monthly and average annual withdrawals. Domestic water use is estimated from the USGS 2010 countywide estimates, assuming that water use is distributed uniformly in space and time. Consumptive-use coefficients are used to estimate net withdrawals and facilitate computation of return flows. Temporary water-use registrations for hydraulic fracturing are tabulated separately from the other water uses. Water-use indices are computed by dividing average annual net withdrawals (with and without temporary registrations) by the mean October streamflow estimated with StreamStats. The water-use indices are intended to provide metrics of potential consumptive water use.

Scientific Investigations Report↗

USGS2016

Hydrologic and hydraulic analyses for the Black Fork Mohican River Basin in and near Shelby, Ohio

Hydrologic and hydraulic analyses were done for selected reaches of five streams in and near Shelby, Richland County, Ohio. The U.S. Geological Survey (USGS), in cooperation with the Muskingum Watershed Conservancy District, conducted these analyses on the Black Fork Mohican River and four tributaries: Seltzer Park Creek, Seltzer Park Tributary, Tuby Run, and West Branch. Drainage areas of the four stream reaches studied range from 0.51 to 60.3 square miles. The analyses included estimation of the 10-, 2-, 1-, and 0.2-percent annual-exceedance probability (AEP) flood-peak discharges using the USGS Ohio StreamStats application. Peak discharge estimates, along with cross-sectional and hydraulic structure geometries, and estimates of channel roughness coefficients were used as input to step-backwater models. The step-backwater water models were used to determine water-surface elevation profiles of four flood-peak discharges and a regulatory floodway. This study involved the installation of, and data collection at, a streamflow-gaging station (Black Fork Mohican River at Shelby, Ohio, 03129197), precipitation gage (Rain gage at Reservoir Number Two at Shelby, Ohio, 405209082393200), and seven submersible pressure transducers on six selected river reaches. Two precipitation-runoff models, one for the winter events and one for nonwinter events for the headwaters of the Black Fork Mohican River, were developed and calibrated using the data collected. With the exception of the runoff curve numbers, all other parameters used in the two precipitation-runoff models were identical. The Nash-Sutcliffe model efficiency coefficients were 0.737, 0.899, and 0.544 for the nonwinter events and 0.850 and 0.671 for the winter events. Both of the precipitation-runoff models underestimated the total volume of water, with residual runoff ranging from -0.27 inches to -1.53 inches. The results of this study can be used to assess possible mitigation options and define flood hazard areas that will contribute to the protection of life and property. This study could also assist emergency managers, community officials, and residents in determining when flooding may occur and planning evacuation routes during a flood.

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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

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USGS2015

Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio

This report presents the results of a study to provide information on the hydrologic effects of potential 21st-century changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio (from Circleville, Ohio, to the headwaters). A precipitation-runoff model, calibrated on the basis of historical climate and streamflow data, was used to simulate the effects of climate change on streamflows and reservoir water levels at several locations in the basin. Two levels of simulations were done. The first level of simulation (level 1) accounted only for anticipated 21st-century changes in climate and operations of three City of Columbus upground reservoirs located in northwest Delaware County, Ohio. The second level of simulation (level 2) accounted for development-driven changes in land cover and water use in addition to changes in climate and reservoir operations. A statistical change-factor approach was used to construct future climate time series that were used in the precipitation-runoff model to compute time series of future streamflows and reservoir water levels. Monthly change factors were computed by determining differences or fractional changes between baseline historical climate time series and future climate time series consisting of outputs from selected global climate models that were included in the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 (CMIP3). Eight sets of change factors were determined on the basis of outputs from four global climate models, each of which was run under two greenhouse-gas scenarios (the “A1b” and “A2” scenarios from the Intergovernmental Panel on Climate Change’s 4th assessment). The 4 global climate models whose data were used in this study were selected to represent a wide range of potential climate outcomes as compared to the entire range of potential climate outcomes associated with the 16 global climate models represented in the CMIP3 multimodel dataset. Future land-cover and water-use data were estimated for use in the level-2 precipitation-runoff simulations to account for development-driven changes in land cover and water use. Future land-cover characteristics were estimated for selected future years based on population projections and zoning plans for communities in the basin. Future water-use data for major water suppliers and wastewater-treatment facilities were estimated from current per capita water use, population projections for 2035, and population projections for 2090 assuming full build-out. A statistical change-factor-based approach was used to estimate future water-use characteristics by major water suppliers and wastewater-treatment facilities on the basis of reference-period historical water uses. Annual change factors that were determined for future years other than 2035 and 2090 (when the change factors could be explicitly computed) were estimated by interpolating or extrapolating linearly in time. Water uses by entities other than major water suppliers and wastewater-treatment facilities were assumed to remain unchanged because of uncertainty about if and (or) how they might change. Results from the level-1 simulations were analyzed primarily to facilitate evaluation of climate-driven temporal changes in annual, seasonal, and monthly streamflow and water-level characteristics, as well as in maximum and minimum 7-, 30-, and 180-day average streamflow and reservoir water levels. Results from the level-2 simulations were analyzed to help evaluate and contrast (relative to level-1 results) the effects of the added development-related factors on maximums and minimum 7-, 30-, and 180-day average streamflows and reservoir water levels and duration characteristics of 7- and 30-day average streamflows and reservoir water levels. Results for 12 stream locations and 5 reservoirs in the Upper Scioto River Basin are presented primarily as a series of plots. Although it is beyond the scope of this study to address results in detail for each model-output location, selected results are discussed to illustrate potential uses and interpretations of the graph products provided in this report. In addition, general trends and patterns in streamflow and water-level characteristics are identified where possible.

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USGS2014

An analysis of potential water availability from the Charles Mill, Clendening, Piedmont, Pleasant Hill, Senecaville, and Wills Creek Lakes in the Muskingum River Watershed, Ohio

This report presents the results of a study to assess potential water availability from the Charles Mill, Clendening, Piedmont, Pleasant Hill, Senecaville, and Wills Creek Lakes, located within the Muskingum River Watershed, Ohio. The assessment was based on the criterion that water withdrawals should not appreciably affect maintenance of recreation-season pool levels in current use. To facilitate and simplify the assessment, it was assumed that historical lake operations were successful in maintaining seasonal pool levels, and that any discharges from lakes constituted either water that was discharged to prevent exceeding seasonal pool levels or discharges intended to meet minimum in-stream flow targets downstream from the lakes. It further was assumed that the volume of water discharged in excess of the minimum in-stream flow target is available for use without negatively impacting seasonal pool levels or downstream water uses and that all or part of it is subject to withdrawal. Historical daily outflow data for the lakes were used to determine the quantity of water that potentially could be withdrawn and the resulting quantity of water that would flow downstream (referred to as “flow-by”) on a daily basis as a function of all combinations of three hypothetical target minimum flow-by amounts (1, 2, and 3 times current minimum in-stream flow targets) and three pumping capacities (1, 2, and 3 million gallons per day). Using both U.S. Geological Survey streamgage data (where available) and lake-outflow data provided by the U.S. Army Corps of Engineers resulted in analytical periods ranging from 51 calendar years for Charles Mill, Clendening, and Piedmont Lakes to 74 calendar years for Pleasant Hill, Senecaville, and Wills Creek Lakes. The observed outflow time series and the computed time series of daily flow-by amounts and potential withdrawals were analyzed to compute and report order statistics (95th, 75th, 50th, 25th, 10th, and 5th percentiles) and means for the analytical period, in aggregate, and broken down by calendar month. In addition, surplus-water mass curve data were tabulated for each of the lakes. Monthly order statistics of computed withdrawals indicated that, for the three pumping capacities considered, increasing the target minimum flow-by amount tended to reduce the amount of water that can be withdrawn. The reduction was greatest in the lower percentiles of withdrawal; however, increasing the flow-by amount had no impact on potential withdrawals during high flow. In addition, for a given target minimum flow-by amount, increasing the pumping rate typically increased the total amount of water that could be withdrawn; however, that increase was less than a direct multiple of the increase in pumping rate for most flow statistics. Potential monthly withdrawals were observed to be more variable and more limited in some calendar months than others. Monthly order statistics and means of computed daily mean flow-by amounts indicated that flow-by amounts generally tended to be lowest during June–October. Increasing the target minimum flow-by amount for a given pumping rate resulted in some small increases in the magnitudes of the mean and 50th percentile and lower order statistics of computed mean flow-by, but had no effect on the magnitudes of the higher percentile statistics. Increasing the pumping rate for a given target minimum flow-by amount resulted in decreases in magnitudes of higher-percentile flow-by statistics by an amount equal to the flow equivalent of the increase in pumping rate; however, some lower percentile statistics remained unchanged.

Ohio↗

USGS2013

Methods for estimating selected low-flow statistics and development of annual flow-duration statistics for Ohio

This report presents the results of a study to develop methods for estimating selected low-flow statistics and for determining annual flow-duration statistics for Ohio streams. Regression techniques were used to develop equations for estimating 10-year recurrence-interval (10-percent annual-nonexceedance probability) low-flow yields, in cubic feet per second per square mile, with averaging periods of 1, 7, 30, and 90-day(s), and for estimating the yield corresponding to the long-term 80-percent duration flow. These equations, which estimate low-flow yields as a function of a streamflow-variability index, are based on previously published low-flow statistics for 79 long-term continuous-record streamgages with at least 10 years of data collected through water year 1997. When applied to the calibration dataset, average absolute percent errors for the regression equations ranged from 15.8 to 42.0 percent. The regression results have been incorporated into the U.S. Geological Survey (USGS) StreamStats application for Ohio (http://water.usgs.gov/osw/streamstats/ohio.html) in the form of a yield grid to facilitate estimation of the corresponding streamflow statistics in cubic feet per second. Logistic-regression equations also were developed and incorporated into the USGS StreamStats application for Ohio for selected low-flow statistics to help identify occurrences of zero-valued statistics. Quantiles of daily and 7-day mean streamflows were determined for annual and annual-seasonal (September–November) periods for each complete climatic year of streamflow-gaging station record for 110 selected streamflow-gaging stations with 20 or more years of record. The quantiles determined for each climatic year were the 99-, 98-, 95-, 90-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, 2-, and 1-percent exceedance streamflows. Selected exceedance percentiles of the annual-exceedance percentiles were subsequently computed and tabulated to help facilitate consideration of the annual risk of exceedance or nonexceedance of annual and annual-seasonal-period flow-duration values. The quantiles are based on streamflow data collected through climatic year 2008.

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