Search USGS⌕ Search

Geology topics

Robert A. Darner

Publications and source records attributed to Robert A. Darner.

16 recordsLinked to original sources
USGS2018

Hydrologic performance of retrofit rain gardens in a residential neighborhood (Cleveland Ohio USA) with a focus on monitoring methods

Green infrastructure refers to a range of urban stormwater management tools that can be flexibly implemented. These practices can aid in mitigating the negative impacts of runoff by increasing catchment detention capacity. We studied two engineered rain gardens (Cleveland OH) that were designed to infiltrate and detain direct runoff volume generated from an adjacent roadway, and sheet flow from pervious areas of each catchment area. We also accounted for hydrologic interactions between the engineered and upslope basic (non-engineered) rain gardens. A whole water-cycle monitoring approach was employed to fully assess the role of green infrastructure interventions on performance as inflows captured, duration of outflow drainage (i.e., excess moisture), hydrologic losses (e.g., evapotranspiration), and groundwater table dynamics. We found that these tandem rain gardens had good capacity for runoff inflow volumes over the course of over 100 storm events.The integration of green infrastructure in urban landscapes and long-term monitoring for effectiveness and its key functions produces novel data that can be used by researchers and other interested parties to conduct assessments of urban ecosystem functions and leverage these unique datasets by integrating with other datasets as per good scientific practice. We role model good monitoring practice, discuss unique ways to interpret challenging hydraulic circumstances, and conclude with a discussion of monitoring techniques that scale between the simple, passive and elegant; to full-blown research-grade monitoring infrastructure such as that employed in this study.

Ohio↗
USGS2015

Hydrologic characteristics of low-impact stormwater control measures at two sites in northeastern Ohio, 2008-13

This report updates and examines hydrologic data gathered to characterize the performance of two stormwater-control measure (SCM) sites in the Chagrin River watershed, Ohio. At the Sterncrest Drive site, roadside bioswales and rain gardens were used to alleviate drainage problems in this residential neighborhood area. At the Washington Street site, a treatment train (including a pervious-paver system, rain garden, and bioswales) was used to reduce and delay stormwater runoff at a small business development. Selected metrics were used to demonstrate SCM system performance with regard to stormwater-management objectives at each site. Rain-garden overflow-frequency data collected at the Sterncrest Drive site during 2008–13 were used to characterize system sensitivity to rainfall characteristics. Approximately 70 percent of storms exceeding 0.75 inches during 3 hours or more resulted in overflows. Drainage-design features that may restrict flow through the system were identified. Overall, the data and local observations confirmed the continued success of the SCM at the Sterncrest Drive site in preventing roadway closure due to flooding. The additional years of data collected at the Washington Street site indicated that a previous analysis of increased runoff removal, based on only the first 2 years (2009–10) of data, provided premature conclusions. With 5 years of data (2009–13) and adjusting for changes in rainfall characteristics, it appears that the percentage of runoff removed by the system is decreasing; however, the lag time (time from onset of rainfall to runoff) has remained nearly constant. The annual mean percent removal for 2010–13 ranged from 55 to 37 percent with an overall mean of 45 percent, and this does meet the project objective of reducing runoff from the business complex. One possible explanation for the combination of increased volume of runoff and no change in the timing of runoff is the preferential flow paths developed in the SCM, increasing the capacity for internal drainage. Data indicated that the SCM system at the Washington Street site had reduced functionality over time.

Ohio↗
USGS2014

Visualization of soil-moisture change in response to precipitation within two rain gardens in Ohio

Stormwater runoff in urban areas is increasingly being managed by means of a variety of treaments that reduce or delay runoff and promote more natural infiltration. One such treatment is a rain garden, which is built to detain runoff and allow for water infiltration and uptake by plants.Water flow into or out of a rain garden can be readily monitored with a variety of tools; however, observing the movement of water within the rain garden is less straightforward. Soil-moisture probes in combination with an automated interpolation procedure were used to document the infiltration of water into two rain gardens in Ohio. Animations show changes in soil moisture in the rain gardens during two precipitation events. At both sites, the animations demonstrate underutilization of the rain gardens.

Ohio↗
USGS2011

Using existing data to estimate aquifer properties, Great Lakes Region, USA

To determine specific storage and porosity, areally limited and time-consuming aquifer tests are frequently done. Hydrogeologic studies often do not have the resources to collect such data and rely on existing data sources for aquifer properties. An alternative tool for determining these aquifer properties is the analysis of earth tides. The objective of this study was to determine whether existing water-level and barometric-pressure data could be used to determine aquifer properties, such as porosity and specific storage, on a regional scale. In this study, national databases from the Great Lakes Region were queried for continuous records of groundwater-level and barometric-pressure data. Records from 37 selected wells were then analyzed for barometric efficiency and earth-tide responses. Specific-storage (S s ) and porosity values were determined, and the quality of the results were assessed with a measure of the "goodness of fit" (percent variance) of reconstruction of the response. Records from wells completed in several aquifer systems were analyzed with varying degrees of success. Aquifer S s values ranging from 5.9 x 10 -8 to 3.8 x 10 -6 /m were derived, with percent variance of reconstruction ranging from 1% to 78%. Comparisons with aquifer and laboratory testing of S s and porosity are favorable if the percent variance of reconstruction is above about 30%. Although the earth-tide-analysis method is not suitable for every situation, the S s and porosity of aquifers can, in many places, be estimated with existing water-level and barometric-pressure data or with data that are relatively inexpensive to collect.

Great Lakes↗
USGS2011

Hydraulic characteristics of low-impact development practices in northeastern Ohio, 2008–2010

Low-impact development (LID) is an approach to managing stormwater as near to its source as possible; this is accomplished by minimizing impervious surfaces and promoting more natural infiltration and evapotranspiration than is typically associated with developed areas. Two newly constructed LID sites in northeastern Ohio were studied to document their hydraulic characteristics. A roadside best-management practice (BMP) was constructed by replacing about 1,400 linear feet of existing ditches with a bioswale/rain garden BMP consisting of a grassed swale interspersed with rain-garden/overflow structures. The site was monitored in 2008, 2009, and 2010. Although some overflows occurred, numerous precipitation events exceeding the 0.75-inch design storm did not result in overflows. A second study site consists of an 8,200-square-foot parking lot made of a pervious pavers and a rain garden that receives runoff from the roof of a nearby commercial building. A comparison of data from 2009 and 2010 indicates that the median runoff volume in 2010 decreased relative to 2009. The centroid lag times (time difference between centroid of precipitation and centroid of flow) decreased in 2010, most likely due to more intense, shorter duration precipitation events and maturation of the rain garden. Additional data could help quantify the relation between meteorological variables and BMP efficiency.

Ohio↗
USGS2009

Testing and refining the Ohio Nowcast at two Lake Erie beaches— 2008

The Ohio Nowcast has been providing real-time beach advisories to the public on the basis of predictive models since 2006. In support of the nowcast, data were collected during the recreational season of 2008 to validate and refine predictive models at two Lake Erie beaches. Predictive models yield data on the probability that the single-sample bathing-water standard for E. coli will be exceeded. Field personnel collected or compiled data on Escherichia coli (E. coli) concentrations as well as variables expected to affect these concentrations, including manual and automated measurements of turbidity, wave height, and water temperature; lake level; and radar and airport rainfall amounts. Two new variables were measured during 2008 - photosynthetically-active radiation at Huntington (Bay Village) and foreshore head at Edgewater (Cleveland). (The foreshore is a strip of land along a body of water between low and high water marks.) The performance of the nowcast was monitored during 2008. The Huntington nowcast yielded a greater percentage of correct responses (84.9 percent) than did the previous day's E. coli concentration (75.2 percent). In contrast, at Edgewater, the nowcast yielded a slightly higher percentage of correct responses (61.0 percent) as compared to the previous day's E. coli concentration (56.5 percent), but both percentages were relatively low. Lake levels in 2008 were significantly higher than levels in the data used to develop the Edgewater models (2004-7), confounding their abilities to provide correct responses. At Edgewater during 2008, the strongest relation (as measured by Pearson's correlation) was between E. coli concentrations and the difference in foreshore head over the past 24 hours (r=0.48), a variable not included in the models. At Huntington, photosynthetically-active radiation on the previous day showed a significant negative relation to E. coli concentrations (r=-0.33) during 2008. Refined models were developed for Huntington and Edgewater using data collected from 2005-8. The refined models included the variables wave height, log turbidity, radar or airport rainfall, and day of the year in various combinations for different dated segments of the recreational season. Water-resource managers will determine which models to apply to the Ohio Nowcast for issuing water-quality advisories in 2009.

Ohio↗
USGS2007

Nowcasting Beach Advisories at Ohio Lake Erie Beaches

Data were collected during the recreational season of 2007 to test and refine predictive models at three Lake Erie beaches. In addition to E. coli concentrations, field personnel collected or compiled data for environmental and water-quality variables expected to affect E. coli concentrations including turbidity, wave height, water temperature, lake level, rainfall, and antecedent dry days and wet days. At Huntington (Bay Village) and Edgewater (Cleveland) during 2007, the models provided correct responses 82.7 and 82.1 percent of the time; these percentages were greater than percentages obtained using the previous day?s E. coli concentrations (current method). In contrast, at Villa Angela during 2007, the model provided correct responses only 61.3 percent of the days monitored. The data from 2007 were added to existing datasets and the larger datasets were split into two (Huntington) or three (Edgewater) segments by date based on the occurrence of false negatives and positives (named ?season 1, season 2, season 3?). Models were developed for dated segments and for combined datasets. At Huntington, the summed responses for separate best models for seasons 1 and 2 provided a greater percentage of correct responses (85.6 percent) than the one combined best model (83.1 percent). Similar results were found for Edgewater. Water resource managers will determine how to apply these models to the Internet-based ?nowcast? system for issuing water-quality advisories during 2008.

Open-File Report↗
USGS2006

Models for predicting recreational water quality at Lake Erie beaches

Data collected from four Lake Erie beaches during the recreational seasons of 2004-05 and from one Lake Erie beach during 2000-2005 were used to develop predictive models for recreational water quality by means of multiple linear regression. The best model for each beach was based on a unique combination of environmental and water-quality explanatory variables including turbidity, rainfall, wave height, water temperature, day of the year, wind direction, and lake level. Two types of outputs were produced from the models: the predicted Escherichia coli concentration and the probability that the bathing-water standard will be exceeded. The model for one of beaches, Huntington Reservation (Huntington), was validated in 2005. For 2005, the Huntington model yielded more correct responses and better predicted exceedance of the standard than did current methods for assessing recreational water quality, which are based on the previous day's E. coli concentration. Predictions based on the Huntington model have been available to the public through an Internet-based 'nowcasting' system since May 30, 2006. The other beach models are being validated for the first time in 2006. The methods used in this study to develop and test predictive models can be applied at other similar coastal beaches.

Scientific Investigations Report↗
USGS2003

Escherichia coli at Ohio bathing beaches—Distribution, sources, wastewater indicators, and predictive modeling

Results of studies during the recreational seasons of 2000 and 2001 strengthen the science that supports monitoring of our Nation's beaches. Water and sediment samples were collected and analyzed for concentrations of Escherichia coli ( E. coli ). Ancillary water-quality and environmental data were collected or compiled to determine their relation to E. coli concentrations. Data were collected at three Lake Erie urban beaches (Edgewater, Villa Angela, and Huntington), two Lake Erie beaches in a less populated area (Mentor Headlands and Fairport Harbor), and one inland-lake beach (Mosquito Lake). The distribution of E. coli in water and sediments within the bathing area, outside the bathing area, and near the swash zone was investigated at the three Lake Erie urban beaches and at Mosquito Lake. (The swash zone is the zone that is alternately covered and exposed by waves.) Lake-bottom sediments from outside the bathing area were not significant deposition areas for E. coli . In contrast, interstitial water and subsurface sediments from near the swash zone were enriched with E. coli . For example, E. coli concentrations were as high as 100,000 colonies per 100 milliliters in some interstitial waters. Although there are no standards for E. coli in swash-zone materials, the high concentrations found at some locations warrant concern for public health. Studies were done at Mosquito Lake to identify sources of fecal contamination to the lake and bathing beach. Escherichia coli concentrations decreased with distance from a suspected source of fecal contamination that is north of the beach but increased at the bathing beach. This evidence indicated that elevated E. coli concentrations at the bathing beach are of local origin rather than from transport of bacteria from sites to the north. Samples collected from the three Lake Erie urban beaches and Mosquito Lake were analyzed to determine whether wastewater indicators could be used as surrogates for E. coli at bathing beaches. None of the concentrations of wastewater indicators of fecal contamination, including 3b-coprostanol and cholesterol, were significantly correlated (a=0.05) to concentrations of E. coli . Concentrations of the two compounds that were significantly correlated to E. coli were components of coal tar and asphalt, which are not necessarily indicative of fecal contamination. Data were collected to build on an earlier 1997 study to develop and test multiple-linear-regression models to predict E. coli concentrations using water-quality and environmental variables as explanatory variables. The probability of exceeding the single-sample bathing-water standard for E. coli (235 colonies per 100 milliliters) was used as the model output variable. Threshold probabilities for each model were established. Computed probabilities that are less than a threshold probability indicate that bacterial water quality is most likely acceptable. Computed probabilities equal to or above the threshold probability indicate that the water quality is most likely not acceptable and that a water-quality advisory may be needed. Models were developed at each beach, whenever possible, using combinations of 1997, 2000, and (or) 2001 data. The models developed and tested in this study were shown to be beach specific; that is, different explanatory variables were used to predict the probability of exceeding the standard at each beach. At Mentor Headlands and Fairport Harbor, models were not developed because water quality was generally good. At the three Lake Erie urban beaches, models were developed with variable lists that included the number of birds on the beach at the time of sampling, lake-current direction, wave height, turbidity, streamflow of a nearby river, and rainfall. The models for Huntington explained a larger percentage of the variability in E. coli concentrations than the models for Edgewater and Villa Angela. At Mosquito Lake, a model based on 2000 and 2001 data contained the explanatory variables rainfall, number of dry days preceding a rainfall, date, wind direction, wind speed, and turbidity. Additional research could include testing the threshold probabilities assigned for these models in subsequent years and comparing the models’ ability to predict recreational water quality to results from the current method—using antecedent E. coli concentrations. Each year the model is tested, new data can be added and model variables can be recalculated to determine whether the predictive ability improves with additional data.

Ohio↗
USGS2002

Forecasting bacteria levels at bathing beaches in Ohio

The U.S. Geological Survey developed models for predicting exceedance of the bathing-water standard for Escherichia coli ( E. coli ) at three Lake Erie beaches and one inland lake in Ohio. The statistical models were specific to each beach, and the best model for each beach was based on a unique combination of environmental and water-quality variables as explanatory factors. For the Lake Erie beaches, these factors included wave height, number of birds on the beach at the time of sampling, lake-current direction, rainfall, turbidity, and streamflow of a nearby river. For the inland lake, these factors included date, wind direction and speed, number of birds, and rainfall. The prediction error in the models was too large to accurately estimate concentrations of E. coli ; however, the models can be used like weather forecasts to predict the probability, given a set of input variables, that the Ohio bathing-water standard used to judge swimming safety will be exceeded.

Ohio↗
USGS2002

Water and bed-sediment quality in the vicinity of Berlin Lake, Ohio, 2001

Berlin Lake, in northeast Ohio, was created by the U.S. Army Corps of Engineers in 1943 and is used primarily for flood control for the upper reaches of the Mahoning River. The area surrounding and under the lake has been tapped for oil and natural gas production. One of the by-products of oil and gas production is concentrated salt water or brine, which might have an effect on the chemical quality of area potable-water sources. This report presents the results of a U.S. Geological Survey baseline study to collect current (2001) water and sediment-quality data and to characterize water quality in the Berlin Lake watershed. Chloride-to-bromide ratios were used to detect the presence of brine in water samples and to indicate possible adverse effects on water quality. Analyses of ground-water samples from domestic wells in the area indicate a source of chloride and bromide, but defining the source would require more data collection. Analyses of specific conductance and dissolved solids indicate that 78 percent (14 of 18) of the ground-water samples exceeded the Secondary Maximum Contaminant Level for dissolved solids in public water supplies of 500 milligrams per liter (mg/L), compared to 6 percent of samples exceeding 500 mg/L in two nearby studies. Surface water was analyzed twice, once each during low-flow and surface runoff conditions. A comparison of the 2001 data to historical chloride concentrations, accounting for seasonal changes, does not indicate an increase in chloride loads for surface water in the area of Berlin Lake. Polycyclic aromatic hydrocarbons were found in bed-sediment samples collected from the mouths of major tributaries to Berlin Lake. Polycyclic aromatic hydrocarbons are produced during the incomplete combustion of organic carbon materials such as wood and fossil fuels, and they are components of petroleum products.

Water-Resources Investigations Report↗
USGS2001

Ground-water quality in Geauga County, Ohio — Review of previous studies, status in 1999, and comparison of 1986 and 1999 data

Most residents in Geauga County, Ohio, rely on ground water as their primary source of drinking water. With population growing at a steady rate, the possibility that human activity will affect ground-water quality becomes considerable. This report presents the results of a study by the U.S. Geological Survey (USGS), in cooperation with the Geauga County Planning Commission and Board of County Commissioners, to provide a brief synopsis of work previously done within the county, to assess the present (1999) ground-water quality, and to determine any changes in groundwater quality between 1986 and 1999. Previous studies of ground-water quality in the county have consistently reported that manganese and iron concentrations in ground water in Geauga County often exceed the U.S. Environmental Protection Agency (USEPA) Secondary Maximum Contaminant Level (SMCL). Road salt and, less commonly, oil-field brines and volatile organic compounds (VOCs) have been found in ground water at isolated locations. Nitrate has not been detected above the USEPA Maximum Contaminant Level (MCL) of 10 milligrams per liter as N; however, nitrate has been found in some locations at levels that may indicate the effects of fertilizer application or effluent from septic systems. Between June 7 and July 1, 1999, USGS personnel collected a total of 31 water-quality samples from wells completed in glacial deposits, the Pottsville Formation, the Cuyahoga Group, and the Berea Sandstone. All samples were analyzed for VOCs, sulfide, dissolved organic carbon, major ions, trace elements, alkalinity, total coliforms, and Escherichia coli bacteria. Fourteen of the samples also were analyzed for tritium. Water-quality data were used to determine (1) suitability of water for drinking, (2) age of ground water, (3) stratigraphic variation in water quality, (4) controls on water quality, and (5) temporal variation in water quality. Water from 16 of the 31 samples exceeded the Geauga County General Health District’s standard of 0 colonies of total coliform bacteria per 100 milliliters of water. Esthetically based SMCLs were exceeded in the indicated number of wells for pH (8), sulfate (1), dissolved solids (3), iron (19), and manganese (18). Hydrogen sulfide was detected at or above the detection limit of 0.01 milligram per liter in 17 of the 31 water samples. A range of water types was found among and within the four principal stratigraphic units. The waters can be categorized in three groups based on predominant anion type: bicarbonatetype waters, chloride-type waters, and sulfatetype waters. Chloride-to-bromide ratio analyses indicate that water from 8 of the 31 wells is in some way affected by human activity. Five other samples were in a chloride-to-bromide ratio range that could indicate possible effects of human activity. Ground-water-quality data from the current study were compared to data collected in 1986. Statistical analyses of data from the 16 wells that were sampled in both years did not indicate any significant changes that could be attributed to human activity.

Ohio↗
USGS1998

How do we determine when the beaches are safe for swimming?

The use of Lake Erie and other public waters for swimming is a valuable recreational resource for the people of Ohio and elsewhere in the United States. Water-resource managers and the scientific commu­nity have recognized the need for rapid methods to determine the quality of these recreational waters to adequately protect public health. Fecal-indicator bacteria, such as Escherichia coli ( E. coli ) and fecal coliforms, are used to determine the risk of contracting waterborne disease from fecal-contaminated recreational waters. Fecal-indicator bacteria are not necessarily pathogens ( disease-causing organisms), but their presence can indicate the possible presence of pathogens. Although improvements to existing sewage treatment systems are continuously being made in many areas, fecal contamination is still a possibility. Therefore, findings from carefully designed monitoring programs are needed to inform the public on the risk of swimming in fecal-contaminated waters. Current methods to assess the concentrations of fecal indicators-that is, the number of bacteria in a certain volume of water-take at least 24 hours to complete. Due to the long time frame, some scientists have suggested using other water-quality or environ­mental surrogates (substitutes) to determine these concentrations. The U.S. Geological Survey (USGS) is working to address this concern in a study con­ducted at three Lake Erie beaches in the Cleveland, Ohio, area. The study has shown that turbidity (the amount of light scattered or absorbed by suspended materials in a water sample), rainfall, and wave height could be used in a statistical model to predict E. coli concentrations.

Ohio↗
USGS1998

Factors affecting Escherichia coli concentrations at Lake Erie public bathing beaches

The environmental and water-quality factors that affect concentrations of Escherichia coli (E. coli) in water and sediment were investigated at three public bathing beachesEdgewater Park, Villa Angela, and Sims Parkin the Cleveland, Ohio metropolitan area. This study was done to aid in the determination of safe recreational use and to help water- resource managers assess more quickly and accurately the degradation of recreational water quality. Water and lake-bottom sediments were collected and ancillary environmental data were compiled for 41 days from May through September 1997. Water samples were analyzed for E. coli concentrations, suspended sediment concentrations, and turbidity. Lake- bottom sediment samples from the beach area were analyzed for E. coli concentrations and percent dry weight. Concentrations of E. coli were higher and more variable at Sims Park than at Villa Angela or Edgewater Park; concentrations were lowest at Edgewater Park. Time-series plots showed that short-term storage (less than one week) of E. coli in lake-bottom sediments may have occurred, although no evidence for long-term storage was found during the sampling period. E. coli concentrations in water were found to increase with increasing wave height, but the resuspension of E. coli from lake-bottom sediments by wave action could not be adequately assessed; higherwave heights were often associated with the discharge of sewage containing E. coli during or after a rainfall and wastewater-treatment plant overflow. Multiple linear regression (MLR) was used to develop models to predict recreational water quality at the in water. The related variables included turbidity, antecedent rainfall, antecedent weighted rainfall, volumes of wastewater-treatment plant overflows and metered outfalls (composed of storm-water runoff and combined-sewer overflows), a resuspension index, and wave heights. For the beaches in this study, wind speed, wind direction, water temperature, and the prswimmers were not included in the model because they were shown to be statistically unrelated to E. coli concentrations. From the several models developed, one model was chosen that accounted for 58 percent of the variability in E. coli concentrations. The chosen MLR model contained weighted categorical rainfall, beach-specific turbidity, wave height, and terms to correct for the different magnitudes of E. coli concentrations among the three beaches. For 1997, the MLR model predicted the recreational water quality as well as, and in some cases better than, antecedent E. coli concentrations (the current method). The MLR model improved the sensitivity of the prediction and the percentage of correct predictions over the current method; however, the MLR model predictions still erred to a similar degree as the current method with regard to false negatives. A false negative would allow swimming when, in fact, the bathing water standard was exceeded. More work needs to be done to validate the MLR model with data collected during other recreational seasons, especially during a season with a greater frequency and intensity of summer rains. Studies could focus on adding to the MLR model other environmental and water-quality variables that improve the predictive ability of the model. These variables might include concentrations of E. coli in deeper sediments outside the bathing area, the direction of lake currents, site-specific-rainfall amounts, time-of-day information on overflows and metered outfalls, concentrations of E. coli in treated wastewater-treatment plant effluents, and occurrences of sewage-line breaks. Rapid biological or chemical methods for determination of recreational water quality could also be used as variables in model refinements. Possible methods include the use of experimental rapid assay methods for determination of E. coli concentrations or other fecal indicators and the use of chemical tracers for fecal contamination, such as coprostanol (a degradation

Water-Resources Investigations Report↗