United States
Environmental Protection
Agency
Region 5
Great Lakes National €PA-905/4-88-001
Program Office GL1MPO Report No. 1
230 South Dearborn Street February 1988
Chicago, Illinois 60604
Sediment, Nutrient and
Pesticide Transport in
Selected Lower
Great Lakes Tributaries
f
mr
\r
m^mmm
IF
If
' 4
A
II
II
• ^V
II
^•Bt
mm 4«BbiMu
•B*1imin
-------
EPA-905/4-88-001
GLNPO Report No. 1
February 1988
SEDIMENT, NUTRIENT AND PESTICIDE TRANSPORT
IN SELECTED LOWER GREAT LAKES TRIBUTARIES
by
David B. Baker
Water Quality Laboratory
Heidelberg College
Tiffin, Ohio 44883
Grant numbers
R005727&R005817
Sarah Pavlovic, Project Officer
Great Lakes National Program Office
U. S. Environmental Protection Agency
Chicago, Illinois 60604
U..*'. Jthvlronn^ntal Protection
jcj.*n Street, liooai 1870
. XL 60604
Great Lakes National Program Office
U. S. Environmental Protection Agency
230 South Dearborn Street
Chicago, Illinois 60604
-------
DISCLAIMER
This report has been reviewed by the Great Lakes National Program Office, U. S.
Environmental Protection Agency, and approved for publication. Approval does not signify
that the contents necessarily reflect the views and policies of the U.-S. Environmental
Protection Agency, nor does mention of trade names of commercial products constitute
endorsement or recommendation for use.
-------
FOREWORD
The Great Lakes National Program Office (GLNPO) of the United States Environmental
Protection Agency was established in Region V, Chicago, to focus attention on the significant
and complex natural resource represented by the Great Lakes.
GLNPO implements a multi-media environmental management program drawing on a wide
range of expertise represented by universities, private firms, State, Federal and Canadian
governmental agencies, and the International Joint Commission. The goal of the GLNPO
program is to develop programs, practices and technology necessary for a better
understanding of the Great Lakes Basin ecosystem and to eliminate or reduce to the maximum
extent practicable the discharge of pollutants into the Great Lakes system. GLNPO also
coordinates U.S. actions in fulfillment of the Great Lakes Water Quality Agreement of 1978
between Canada and the United States of America.
GLNPO has funded a major portion of the Lake Erie and Lake Ontario tributary studies
whose results are summarized in this report. The intensive water quality data base gathered
by Heidelberg College has contributed to our understanding of concentration and loading
patterns in the Great Lakes Basin of pollutants associated with agricultural land use.
-------
TABLE OF CONTENTS
Foreward iii
Figures vii
Tables ix
Acknowledgments xii
1. Introduction 1
2. Summary 4
2.1. Effects of Agricultural Runoff on Ambient Stream Water Quality 4
2.2. Pollutant Loading from Agricultural Nonpoint Sources 6
2.3. Hierarchical Aspects of Agricultural Pollution 8
3. Recommendations 10
3.1. Lake Erie Basin Agricultural Pollution Abatement Programs 10
3.2. Research on Agricultural Nonpoint Pollution in the Lake Erie Basin 11
4. Background of the Lake Erie Agricultural Nonpoint Pollution Research and
Demonstration Programs 13
4.1. Nonpoint Source Pollution Studies in the Great Lakes and Lake
Erie Basins 13
4.2. Agricultural Pollution Abatement Demonstration Programs 14
4.3. Possible Water Quality Trade-offs with Conservation Tillage 15
4.4. The Lake Erie Agro-ecosystem Program 16
4.5. Related Studies Underway at the Heidelberg College Water Quality
Laboratory 19
5. Study Methods 21
5.1. Sampling Locations 21
5.2. Sampling Methods 21
5.3. Analytical Program: Nutrients, Sediments, and Conductivity 26
5.4. Analytical Program: Pesticides 28
6. Results and Discussion: Sediments and Nutrients 34
6.1. Sediment and Nutrient Concentrations 34
6.1.1. Hydrograph, Sedigraph and Chemograph Patterns 34
6.1.2. Concentration-Flow Relationships 36
6.1.3. Frequency Histograms 38
6.1.4. Time Weighted and Flux Weighted Mean Concentrations 38
6.1.5. Concentration Exceedency Curves 44
6.1.6. Seasonal Variations in Flux Weighted Mean Concentrations 49
6.1.7. Effects of Watershed Size on Peak Pollutant 53
6.1.8. Nitrate Contamination of Surface Waters and Drinking Waters 54
6.1.9. Concentration Patterns for the New York Rivers 54
6.2. Sediment and Nutrient Loading in Lake Erie Tributaries 56
6.2.1. Loading Calculations 56
6.2.2. Annual Loads and Unit Area Loads for Lake Erie Tributaries 59
6.2.3. Annual Variability in Nutrient and Sediment Export 64
6.2.4. Seasonal Distribution of Material Export 64
6.2.5. Role of High Flux Periods in Total Material Export 70
-------
6.2.6. Gross Erosion Rates, Unit Area Sediment and Nutrient Yields
and Sediment Delivery Ratios 70
6.2.7. Comparisons of Agricultural Nonpoint Pollution in the Lake
Erie Basin and the Chesapeake Basin 75
7. Results and Discussion: Pesticides 76
7.1. Background on the Pesticide Monitoring Program in the Lake Erie
Basin Tributaries 76
7.2. Pesticide Concentrations in Lake Erie Tributaries 77
7.2.1. Chemograph Patterns 77
7.2.2. Time Weighted Mean Concentrations 84
7.2.3. Peak Pesticide Concentrations and Watershed Size 87
7.2.4. Concentration Exceedency Curves 87
7.2.5. Perspectives on Pesticide Concentration in Lake Erie
Tributaries 91
7.3. Pesticide Loading in Lake Erie Tributaries 97
7.3.1. Method of Calculating Pesticide Loads 97
7.3.2. Pesticide Loading Data 98
7.3.3. Significance of Pesticide Loads 103
References 104
Appendix 1: Nutrient and Sediment Transport at Lake Erie Tributary Monitoring
Stations: 1982-1985 Water Years 111
Appendix 2: Time Weighted Mean Pesticide Concentrations and Pesticide
Loadings at Lake Erie Tributary Monitoring Stations: 1983-1985
Water Years 173
VI
-------
FIGURES
Number Page
4.1 The Lake Erie Basin Agro-ecosystem Program 17
5.1 Locations of the tributary monitoring stations in the Lake Erie Basin 22
5.2 Locations of the tributary monitoring stations in the Lake Ontario Basin 23
5.3 Typical chromatographs and data reports for a mixed pesticide standard
on a DB-5 (Channel 1) and a DB-1 (Channel 2) column 30
6.1 Annual hydrograph, sedigraph and chemograph of TP, SRP, NO23-N,
conductivity at the Sandusky River transport station during the 1985
water year 35
6.2 Typical pattern of concentration changes during a runoff event,
as illustrated in June 1981 at the Honey Creek station near
Melmore, Ohio 37
6.3 Scattergrams of SS, nutrient and conductivity concentrations in
relationship to stream discharge for the 1985 water year at the
Sandusky River station 40
6.4 Scattergrams based on log transformed data of SS, nutrient and
conductivity concentrations in relationship to stream discharge 41
6.5 Histograms illustrating the percentage of time concentrations fall within
given ranges. Data from the Sandusky River, 1982-1985 water years 42
6.6 Histograms illustrating the percentage of time concentrations fall within
given ranges 43
6.7 Concentration exceedency curves for SS, TP, NO23-N, and conductivity
at the Sandusky River station during the 1985 water year 47
6.8 Concentration exceedency curves for suspended solids at the Maumee,
Sandusky River, Upper Honey Creek and Honey Creek-Melmore
stations 48
6.9 Concentration exceedency curves for NO23-N at the Honey Creek-
Melmore and Maumee River stations 48
6.10 Annual variability and seasonal distribution of rainfall, discharge and
loading of SS, TP, SRP, and NO23-N at the Maumee River
transport station 65
VII
-------
6.11 Annual variability and seasonal distribution of rainfall, discharge and
loading of SS, TP, SRP, and NO23-N at the Sandusky River
transport station 66
6.12 Annual variability and seasonal distribution of discharge and loading
of SS, TP, SRP, and NO23-N at the Honey Creek transport station 67
7.1 Pesticide concentration patterns, discharge and nitrate concentrations
in Honey Creek, 1982 78
7.2 Pesticide concentration patterns, discharge and nitrate concentrations
in Honey Creek, 1983 78
7.3 Pesticide concentration patterns, discharge and nitrate concentrations
in Honey Creek, 1984 79
7.4 Pesticide concentration patterns, discharge and nitrate concentrations
in Honey Creek, 1985 79
7.5 Pesticide concentration patterns, discharge and nitrate concentrations
in the Sandusky River, 1982 80
7.6 Pesticide concentration patterns, discharge and nitrate concentrations
in the Sandusky River, 1983 80
7.7 Pesticide concentration patterns, discharge and nitrate concentrations
in the Sandusky River, 1984 81
7.8 Pesticide concentration patterns, discharge and nitrate concentrations
in the Sandusky River, 1985 81
7.9 Pesticide concentration patterns, discharge and nitrate concentrations
in the Maumee River, 1982 82
7.10 Pesticide concentration patterns, discharge and nitrate concentrations
in the Maumee River, 1983 82
7.11 Pesticide concentration patterns, discharge and nitrate concentrations
in the Maumee River, 1984 83
7.12 Pesticide concentration patterns, discharge and nitrate concentrations
in the Maumee River, 1985 83
7.13 Lethality analysis of chemical concentration data 90
7.14 Concentration exceedency curves during the April 15-August 15
periods in 1983, 1984 and 1985 for major herbicides at Lake Erie
tributary stations 92
VIII
-------
TABLES
Number Page
5.1 Listing of tributary monitoring stations, watershed areas, mean annual
discharges, and, for the 1982-1985 water years, the discharges and
number of nutrient and pesticide samples analyzed 24
5.2 Summary of land use and gross erosion rates for Lake Erie Basin
tributary watersheds 25
5.3 Analytical methods used for nutrients and sediments 27
5.4 Pesticides identified on each channel of the gas chromatograph and
representative retention times 29
5.5 Approximate detection limits and ranges of linear response in nanograms
per liter 33
6.1 Comparisons of time weighted mean concentrations (TWMC) and flux
weighted mean concentrations (FWMC) for sediments and nutrients
at Lake Erie Basin transport stations 45
6.2 Comparison of TWMC's and FWMC's for chloride and conductivity 46
6.3 Concentrations of suspended solids (mg/L) exceeded fixed percentages
of time for Lake Erie river transport during the 1982-1985 water years 50
6.4 Concentrations of total phosphorus (mg/L) exceeded fixed percentages
of time for Lake Erie river transport during the 1982-1985 water years 51
6.5 Concentrations of nitrate plus nitrite-nitrogen (mg/L) exceeded fixed
percentages of time for Lake Erie river transport during the 1982-1985
water years 52
6.6 Seasonal and annual flux weighted mean concentrations of sediments
and nutrients for the period of record 53
6.7 Peak suspended sediment and nitrate plus nitrite-nitrogen concentrations
observed during individual storm runoff events of the 1982, 1983 and
1984 water years in northwest Ohio rivers 55
6.8 Time weighted mean concentrations (TWMC) and flux weighted mean
concentrations (FWMC) for the New York tributaries to Lake Ontario 57
6.9 Sample printout from program used to adjust monthly and annual loads
to the final USGS discharge data as published in the USGS Water
Resources Data 60
6.10 Monthly loads and discharge for the Maumee River for water year 1984 61
ix
-------
6.11 Sediment and nutrient loads (metric tons) at the Lake Erie Basin
transport stations for the 1982-1985 water years 62
6.12 Unit area yields of sediments and nutrients at the Lake Erie tributary
transport stations for the 1982-1985 water years 63
6.13 Means and coefficients of variation for annual rainfall and discharge and
for annual export of sediments and nutrients from three northwestern
Ohio watersheds of varying sizes 68
6.14 Seasonal distribution of rainfall, discharge and nutrient sediment export
from three northwest Ohio watersheds of varying sizes 69
6.15 Percentages of suspended solid loads that were exported during fluxes
which were exceeded for the indicated percentages of time . . . 1982-
1985 water years 71
6.16 Percentages of total phosphorus loads that were exported during fluxes
which were exceeded for the indicated percentages of time . . . 1982-
1985 water years 72
6.17 Percentages of nitrate plus nitrite-nitrogen loads that were exported
during fluxes which were exceeded for the indicated percentages
of time . . . 1982-1985 water years 73
6.18 Unit area yields of sediments and nutrients for the period of record, average
gross erosion rates, and average sediment delivery percentages for
three northwestern Ohio watersheds 74
6.19 Comparison of the Lake Erie Basin and Chesapeake Bay Basin with
respect to population, drainage areas and tributary pollutant loads 75
7.1 Pesticide concentrations for the Maumee River in 1985 85
7.2 Time weighted mean concentrations (jig/L) during the April 15-August 15
periods for the Michigan and Ohio tributaries to Lake Erie for 1983,
1984 and 1985 86
7.3 Maximum pesticide concentrations (|ig/L) observed at river transport
stations during the years 1982, 1983, 1984, and 1985 89
7.4 Description of data sets used for pesticide concentration exceedency
graphs 90
7.5 Comparison of atrazine concentrations in northwestern Ohio tributaries 94
7.6 Example of tabular output produced along with pesticide concentration
exceedency plots 95
7.7 Weekly maximum and annual mean concentrations of alachlor in raw
and finished surface water-for the 1985 growing season 96
-------
7.8 Means, percentiles and ranges of alachlor concentration in Lake Erie
tributaries 99
7.9 Pesticide loads for the Maumee River during the time interval 830415
to 830815 100
7.10 Observed pesticide loads, in kilograms, for the Michigan and Ohio
tributaries to Lake Erie for the years 1983, 1984 and 1985 101
7.11 Unit area pesticide loads, in grams per hectare, for the Michigan and
Ohio tributaries to Lake Erie for the years 1983, 1984 and 1985 102
XI
-------
ACKNOWLEDGMENTS
Support for these studies has come from many sources. Major support was provided by the
U.S. EPA's Great Lakes National Program Office under assistance agreements R005727 and
R005817. The help of our project officers, Mr. Clifford Risley and, upon his retirement,
Ms. Sarah White Pavlovic, is greatly appreciated. Matching funds for the EPA grants were
provided by the following companies or organizations.
American Cyanamid
Ciba-Geigy Corporation
Dow Chemical Company
Heidelberg College
E. I. DuPont de Nemours
FMC Corporation
Hoechst-Roussel Agri-Vet Company
Lilly Research Laboratories
Monsanto Agricultural Products Company
Procter and Gamble Company
Rhone-Poulenc, Inc.
Rohm and Haas Company
Shell Development Company
Soap and Detergent Association
Union Carbide Agricultural Products Company
Several organizations supported special aspects of these studies. Support for the Lost
Creek Watershed study was provided by the Defiance County Soil and Water Conservation
District through the 1984 water year and, beginning in 1985, by the U.S. Soil Conservation
Service.
The American Electric Power Service Corporation provided support for studies of the
pesticide content of rainwater. Grants from the Joyce Foundation supported pesticide analyses
of drinking water supplies in northwestern Ohio cities, as well as studies of pesticide and
nitrate occurrences in private well water in the several north central Ohio counties.
The U.S. Geological Survey district offices of Ohio, Michigan and New York provided
provisional hourly gauge height data and rating curves for the stream gauging stations. In
addition, the Ohio District Office allowed the use of their gauge houses for the operation of
sampling equipment. The staff of the Seneca County Soil and Water Conservation District
provided valuable assistance in developing techniques for the tillage surveys. Approximately
120 volunteers (mostly farmers) in Seneca, Wyandot and Crawford counties assisted in the
collection of daily rainfall samples during growing seasons. County health departments and
soil and water districts have aided in the collection of private well water samples to obtain an
overview of ground water contamination by agricultural chemicals in this region.
A major grant to the Heidelberg College Water Quality Laboratory from the State of Ohio
has allowed laboratory staff to devote time to the preparation of this report, while continuing
the operation of the basic monitoring program and launching several new directions in our
research program.
xii
-------
Above all, my thanks are extended to my colleagues in the Heidelberg College Water
Quality Laboratory, whose skills and dedication have made this research possible. The field
collections and analytical work have been directed by our Laboratory Manager, Jack Kramer,
with the able assistance of chief technician Ellen Ewing and technicians Barbara Merryfield
and Francine Turose. Most of the computer programs used for data analyses and presentation
were written by R. Peter Richards. Kenneth Krieger provided editorial assistance and
directed the tillage survey components of the study. Staff assistant Nancy Creamer and
secretary June Huss have done most of the preparation of tables and figures and the typing of
this manuscript.
XIII
-------
SECTION 1
INTRODUCTION
Much of the water pollution now affecting the Great Lakes Ecosystem, including both the
lakes themselves and the tributaries which drain into them, is derived from nonpoint
sources. Nonpoint source pollution is a consequence of the interaction of two major processes
which occur on the earth's surface -- the hydrological cycle and land use activities. As water
condenses and falls to earth, it picks up both natural and man-made chemicals from the
atmosphere. Upon striking the earth's surface, it encounters additional natural and manmade
chemical substances characteristic of that surface's land use activities, whether it be
forestry, agriculture, industry, transportation, waste disposal, or urban and suburban
living. As water either flows over the land surface into streams, rivers or lakes, or
permeates through the soil toward groundwater, it dissolves and carries with it the soluble
chemicals characteristic of that land use. Raindrops impacting the soil and water flowing over
the land surface can also suspend paniculate matter, along with chemicals associated with
these particulates, and carry them into surface water. Where the resulting dissolved or
particulate chemicals interfere with human uses of surface or groundwater, or otherwise
meet definitions of pollution, the offending substances are categorized as being derived from
nonpoint sources and as constituting nonpoint source pollution. Nonpoint sources of pollution
can yield both "conventional" pollutants, such as sediment, oxygen consuming wastes, and
forms of phosphorus and nitrogen, and toxic substances, such as industrial solvents,
pesticides and some metals.
Among the major land use activities, probably none has had, and is having, a greater
impact on the surface of the earth than the conversion of large areas of natural vegetation into
areas for agricultural production. Often this conversion and the subsequent utilization of land
for crop production has been accompanied by significant degradation of both soil and water
resources -- resources which are of fundamental importance to regional economies and
quality of life, both presently and in the future. Increased erosion often accompanying
agricultural land use not only depletes soil resources (Crosson and Stout 1983), but also
degrades water quality through increased turbidity and sedimentation (Clark et al. 1985,
Waddell 1985). As fertilizer use has increased, the transport of nutrients from soils to
surface waters has also increased, accelerating the eutrophication of surface waters
(Schaller and Bailey 1983, OECD 1985, Overcash and Davidson 1980). Increasing use of
agricultural pesticides has introduced additional toxic substances into surface waters. Soluble
nutrients and pesticides are also impacting groundwater quality in some areas (Hallberg
1986, Holden 1986). There is increasing concern about global environmental impacts that
may accompany increasing food and fiber production to meet the needs of the increasing
human population (The Conservation Foundation 1986).
In the United States, the impacts of agricultural land use on water quality are
increasingly being recognized as a major water quality problem affecting both surface and
groundwater. Numerous recent symposia (e.g., see U.S. EPA 1985a) and special reports
(e.g., see Journal of Soil and Water Conservation 1985) have addressed this topic.
Agricultural runoff is the major source of nonpoint source pollution, and nonpoint sources of
pollution are viewed as the major cause of pollution affecting most streams, rivers and lakes
in the United States (Dysart 1985).
-------
That an awareness of the magnitude of agricultural nonpoint source pollution has only
recently dawned in the United States is a consequence of several factors:
1. Most of the attention in water pollution abatement programs has focused on
point sources of pollution, which typically are much more visible, subject
to easier quantification and suitable for focused control efforts.
2. Most ambient water quality monitoring programs for streams and rivers
are designed to characterize the impact of point sources of pollution, and
they greatly underestimate the magnitude of nonpoint sources of pollution.
3. Only after significant implementation of point source control programs did
it become apparent that many water quality problems remained, and that
these could only be accounted for by nonpoint sources of pollutants.
4. The magnitude of agricultural pollution problems has probably increased
since the 1960's with the extensive industrialization of U.S. agriculture,
including its increasing reliance on fertilizers, pesticides, and intensive
row crop production.
5. Quantification of the impacts of agricultural nonpoint source pollutants on
regional water quality require detailed and long term sampling programs
that focus on runoff periods. Such studies are very rare because they
frequently are accompanied by high costs.
In the Lake Erie Basin, detailed, quantitative studies of agricultural nonpoint source
pollution have been underway since the early 1970's. These studies came about as a
consequence of the application of mass balance approaches to the development of water quality
management programs for the lakes. Such studies require accurate tributary loading data for
each lake. It soon became apparent that, for Lake Erie, intensive tributary sampling
programs during runoff events were essential to the development of accurate loading
estimates.
The major portion of monitoring programs aimed at quantifying agricultural impacts on
regional water quality in the Lake Erie Basin have been conducted by the Water Quality
Laboratory at Heidelberg College. Supported initially by the U.S. Army Corps of Engineers,
the U.S. EPA's Environmental Research Laboratory in Athens, Georgia, and manufacturers of
soaps and detergents, the laboratory developed sampling, analytical, and computational
techniques which, since 1974, have been applied in a consistent fashion to the tributaries of
Lake Erie (Baker 1984). In 1981, the U.S. EPA's Great Lakes National Program Office began
funding the intensive tributary sampling studies, and expanded them to include three major
tributaries to Lake Ontario, where accurate sediment and nutrient loading estimates were
also desired. Also in 1981, pesticide analyses were added to the analytical program and
additional support was received from pesticide manufacturers.
The study watersheds range in size from 11.3 to 16,395 sq km. As such, they are much
larger than the plot and field sized landscape units which are typically used for much of the
agricultural research aimed at evaluating both the agronomic and environmental suitability
of various cropping management practices. The wide range in watershed size allows
-------
characterization of the effects of watershed size on patterns of pollutant loadings and
concentrations. Studies of these larger landscape units have the advantage of providing direct
evidence of the cumulative impacts of agricultural practices on regional water quality, as
reflected in the streams and rivers draining the study watersheds. The disadvantage of large
watershed studies is that it is difficult to attribute the observed pollutants to particular
source areas within the watersheds. While the plot and field sized studies do facilitate
assessment of the site specific agronomic and environmental effectiveness of particular
management practices, it is difficult to predict regional water quality conditions by
extrapolating from plot and field runoff studies. Both types of studies are needed and should,
in fact, be integrated more closely.
This report describes the results of the tributary loading programs for Lake Erie and
Lake Ontario for the 1982-1985 water years. It also provides some comparisons with the
tributary loading studies in the Lake Erie Basin for the 1975-1981 water years that have
been described previously (Baker 1984). The report illustrates many of the characteristics
of agricultural nonpoint pollution from intensive corn and soybean crop productions.
-------
SECTION 2
SUMMARY
Within this summary, quantitative values will be presented for the Maumee and
Sandusky rivers since they deliver the largest loads of agricultural runoff to the Great Lakes.
Data for the other tributaries will be described relative to the Maumee and Sandusky.
2.1 EFFECTS OF AGRICULTURAL RUNOFF ON AMBIENT STREAM WATER QUALITY
Much of the emphasis in agricultural pollution studies is on the loading of agricultural
pollutants to downstream receiving waters. Loading studies require data on both pollutant
concentrations and stream flow. However, while the pollutants are in transit, their
concentrations within the streams and rivers can significantly impact ambient stream water
quality. In this region, the concentrations of sediment, phosphorus, nitrate and pesticides
that are present during storm runoff events constitute significant water quality problems. In
addition, sediment deposition to the stream bed during storm events alters the stream habitat
for extended periods following the event.
2.1.1. Sediment Concentrations
For the Maumee and Sandusky rivers during the 1982-1985 water years, the time
weighted mean suspended sediment concentrations were 87 and 72 mg/L respectively, while
the flow weighted mean concentrations were 197 and 182 mg/L. Time weighted means
generally decreased as watershed size decreased but flow weighted means were independent of
watershed size. Peak sediment concentrations increased as watershed size decreased.
High sediment concentrations degrade water quality in a variety of ways. Certainly the
turbidity associated with high sediment concentrations constitutes an aesthetic pollutant. It
also diminishes fishing success. By reducing light penetration, suspended sediments can
depauperate communities of rooted aquatic plants. This, in turn, greatly alters the habitat for
other members of aquatic communities, including fish. As sediments settle to stream or lake
beds, they also alter that habitat, affecting both benthic and fish communities. Often the
sediments settle in areas where they subsequently must be dredged, at high cost, to maintain
navigation channels or to increase channel capacity and minimize flooding. High sediment
concentrations increase the costs of water treatment at both municipal and industrial water
intake plants. While sediments are not themselves "toxic" they can serve as either a source
or a sink for toxic substances or nutrients, depending on the origin of the sediments. It has
been estimated that the offsite damages from erosion on cropland in the United States amounts
to $2.2 billion annually (Clark et al. 1985). The potential benefits of agricultural erosion
control measures, that reduce the offsite damages of sediments, should not be ignored.
2.1.2. Phosphorus concentrations
The time weighted average total phosphorus concentrations for the Maumee and Sandusky
rivers during the 1982-1985 period were 0.257 and 0.196 mg/L (as P) respectively. The
flux weighted mean concentrations for the same time period were 0.432 and 0.388 mg/L .
The time weighted mean concentrations were generally lower in smaller streams but the flux
-------
weighted means were similar.
Phosphorus is one of the plant nutrients that is primarily transported in association
with sediment particles. Consequently, its concentration also increases during runoff events.
It affects water quality when present in concentrations or amounts that stimulate an
overabundance of growth by algae or higher aquatic plants. In river systems during runoff
events, it is likely that light penetration, rather than phosphorus, is the major limiting
factor to plant growth. Phosphorus from agricultural sources, in both its soluble and
paniculate forms, begins to directly affect water quality as turbidity decreases and plant
growth begins. Sediment can serve as either a source or a sink for phosphorus, depending on
the source of the sediments, the ambient phosphorus concentrations in the water column, and
the chemical and biological environment of the sediments. Since most of the adverse water
quality effects of phosphorus are in downstream receiving waters, there is more concern
about nonpoint source phosphorus loading from rivers into lakes than there is about ambient
effects in stream systems.
2.1.3. Nitrate-nitrogen concentrations
The time weighted nitrate-nitrogen concentrations in the Maumee and Sandusky rivers
were 3.93 and 3.48 mg/L respectively. The flux weighted concentrations were 5.29 and
4.22 mg/L. These are unusually high mean nitrate concentrations and reflect the extensive
use of tile drainage systems in this region. The smaller streams had similar flux weighted
concentrations. The flux weighted mean for the Cuyahoga River, which drains urban and
forested watersheds, was only 1.85 mg/L.
Nitrate-nitrogen concentrations increase during runoff events from cropland. Although
nitrate-nitrogen is a major plant nutrient, it is generally less likely than phosphorus to be
limiting to plant growth in most aquatic systems. As is the case for phosphorus, there is
generally high turbidity present in rivers when nitrate concentrations are highest. In
contrast with phosphorus, nitrate is very soluble and is not attached to sediment. In Lake Erie
tributaries, the major ambient water quality effect of nitrate is on public drinking water
supplies. Because of its solubility, it cannot be economically removed from drinking water.
In the Sandusky River, nitrate-nitrogen concentrations have exceeded the safe drinking water
standard for 12 consecutive years during the spring period. Overall, nitrate concentrations
exceed the standard about 4% of the time in the Sandusky River. Other Ohio rivers serving as
sources for public water supplies, such as the Maumee and Scioto, are similarly affected by
high springtime nitrate concentrations.
2.1.4. Pesticide concentrations
During spring and early summer, many currently used pesticides are present in Lake
Erie tributaries. As with many nonpoint pollutants, pesticide concentrations are highest
during runoff events. In general, the concentrations of herbicides are much higher than the
concentrations of insecticides, and concentrations of both are generally proportional to their
usage. During the period from April 15 to August 15, 1985, the time weighted atrazine
concentrations in the Maumee and Sandusky rivers were 2.7 and 6.4 u,g/L respectively. The
alachlor concentrations were 0.7 and 2.9 u.g/L and the metolachlor concentrations were 2.0
and 7.2 |o.g/L in these same rivers. Cyanazine, metribuzin and linuron are also frequently
present but at lower concentrations. In smaller tributaries peak concentrations of individual
-------
compounds often exceed 100 u.g/L
The herbicide concentrations in Lake Erie tributaries appear to be higher than in many
other rivers draining cropland. The effects of these herbicides on ambient water quality
remain uncertain. Because of the low acute toxicity, the relatively low persistence and the
insignificant bioaccumulation of most herbicides, direct toxic effects on animal life in
streams and rivers appear unlikely. However, the concentrations of herbicides observed in
these streams are within the range where effects on both algal and higher aquatic plant
communities could be expected. Such effects may already be manifest in the existing algal and
rooted aquatic plant communities of this region's streams and rivers, and within their
associated wetlands and bays. Changes in these plant communities could affect the fish and
invertebrate communities in streams and rivers. Also the herbicide concentrations could
possibly induce behavioral responses in animals that could be detrimental to these
communities.
Most of the pesticides present in streams occur primarily in the dissolved state rather
than attached to sediments. Consequently, the removal of sediments at drinking water
treatment plants does not remove most pesticides. Since other aspects of conventional water
treatment, such as chlorination, also do not remove or alter these compounds, finished tap
water has very similar concentrations of these pesticides as does the raw water. At present,
the U.S. Environmental Protection Agency has not established maximum contaminant levels in
drinking water for any of the herbicides monitored in these studies, even though this set of
herbicides makes up about 85% by weight of the herbicides used in Ohio.
Drinking water standards for several of the major herbicides are scheduled to be set by
the federal government in the near future. For the present, several states are establishing
their own drinking water standards and the National Agricultural Chemicals Association has
also suggested interim health guidance levels for some compounds (NACA 1985). The
concentrations of herbicides in Lake Erie tributaries do exceed some of these guidelines, for
relatively short periods of maximum concentrations. Activated carbon can be used to remove
these compounds at water treatment plants and research is underway to evaluate other
possible treatment techniques. While the concentrations of nitrate and pesticides are
particularly high in Lake Erie tributaries, groundwater contamination by these same
chemicals in this region appears to be much less extensive than in other regions of the
country, such as portions of Iowa, Minnesota and Nebraska.
2.2. POLLUTANT LOADING FROM AGRICULTURAL NONPOINT SOURCES
While the effects of agricultural runoff on ambient water quality of streams and rivers
can be assessed in terms of pollutant concentrations, assessment of impacts on downstream
receiving waters or of losses from agricultural lands requires measurements of pollutant
loadings. This is accomplished by combining concentration data with flow data. Most of the
export from agricultural watersheds and the associated loading to receiving waters occurs
during runoff events when both stream flow and concentrations of agricultural pollutants are
high. Accurate loading data are necessary for mass balance pollutant management programs.
2.2.1. Sediment loading
The mean annual sediment loads from the Maumee and Sandusky rivers are 1,120,000
-------
and 269,000 metric tons, respectively, as measured at the transport stations closest to the
lake. This amounts to 0.68 and 0.83 metric tons per hectare per year (0.30 and 0.37 short
tons per acre per year) respectively. The sediment yields reflect about 10% of the gross
erosion which occurs within these watersheds each year. Most of the erosion which occurs
simply moves soils down slope within fields. However, some sediments are deposited in
drainage ways, in stream and river channels, and on floodplains. The Agricultural Research
Service has estimated that the off-site damages from erosion in the lakes states is about
$2.87 per year per (short) ton of gross erosion. Based on the estimates of gross erosion in
the U.S. portions of the watersheds emptying into the western and central basins of Lake Erie,
the annual off-site damages from cropland erosion would be $67 million. Most of this erosion
and these damages occur in Ohio.
2.2.2. Phosphorus loading
The mean annual export of total phosphorus from the Maumee and Sandusky rivers for
the period of record is 2460 and 503 metric tons per year. Much of the water quality
management effort in the Lake Erie Basin has been aimed at reducing phosphorus loading and
the associated problems of eutrophication. The phosphorus loads measured at the river
transport stations are used in the estimation of total phosphorus loading into Lake Erie. The
river loads include the combined output of point and nonpoint phosphorus sources within
their watersheds. Point source phosphorus inputs can account for no more than 16% and
11%, respectively, of the total phosphorus loads exported from the Maumee and Sandusky
rivers. Following separation of the point and nonpoint sources for each river, the resulting
nonpoint source unit area phosphorus loads are used to estimate nonpoint source loading from
adjacent unmonitored watersheds. Using this procedure, it has been estimated that rural
nonpoint sources contribute about 60% of the total phosphorus loads currently entering Lake
Erie. The phosphorus reduction strategies adopted by the various states to meet Lake Erie
phosphorus reduction goals are focusing on reducing rural nonpoint loading.
At approximately 1.5 kg/ha/yr, the unit area phosphorus export rates for the Maumee
and Sandusky rivers are high in relation to national averages. Even so, the phosphorus export
is equivalent to only about 10% of the annual phosphorus fertilizer application within these
watersheds. The high export rates of soluble reactive phosphorus, particularly, during
winter months, may represent a very significant portion of the bioavailable phosphorus
loading to Lake Erie. Impacts of adoption of conservation tillage on both total and soluble
phosphorus export need to be monitored very carefully, because some plot studies have shown
increased phosphorus concentrations with conservation tillage.
2.2.3. Nitrogen loading
The mean annual nitrate-nitrogen export from the Maumee and Sandusky rivers amounts
to 25,500 and 5,110 metric tons per year. Total nitrogen export, including both nitrate,
ammonium and organic nitrogen averaged 19 and 20 kg/ha/yr respectively. These losses are
also much higher than national averages, due primarily to very high exports of
nitrate-nitrogen. The extensive use of tile drainage systems in these watersheds apparently
accounts for the high nitrate export rates, as well as the high nitrate concentrations in area
rivers. Total annual nitrogen export in surface water is equivalent to about 50% of the
amount of nitrogen applied in fertilizers each year. While other sources of nitrogen exist in
these watersheds, such as nitrogen fixation and rainfall, the nitrogen export through surface
-------
runoff nevertheless does constitute a significant loss to farmers. While the concentration of
nitrate is increasing in Lake Erie, it is not currently viewed as a problem for public water
supplies utilizing the Lake or for the biological communities of the Lake.
2.2.4. Pesticide loading
In 1984 the observed export, in metric tons, of atrazine, alachlor, metolachlor,
cyanazine, and metribuzin from the Maumee River was 5.53, 4.99, 3.49, 2.90, and 3.32
respectively. In 1985, the export of these same herbicides from the Sandusky River was
1.21, 0.77, 1.52, 0.14, and 0.36 respectively. There is considerable annual variability in
pesticide export, with the data cited above representing the largest annual loads from the
1983 to 1985 period.
The loadings of most current generation pesticides into Lake Erie, while large in
comparison with other toxic substances, are not viewed as posing priority problems since
they are less persistent and have less of a tendency to bioaccumulate than the priority toxic
compounds. The major problems that may be associated with the loadings of these compounds
relate to resulting concentrations in bays and wetlands. Although these compounds are not
persistent, their continuing large volume use makes them consistent seasonal components of
the chemical environment of streams, bays and wetlands.
Surface water export of pesticides generally accounts for a small portion (<1%) of the
dissipation/degradation pathways for pesticides applied to cropland. Consequently, the losses
of these compounds by surface water runoff are seldom of consequence to farmers.
2.3. HIERARCHICAL ASPECTS OF AGRICULTURAL POLLUTION
Many of the characteristics of agricultural nonpoint pollution, as it affects both ambient
stream water quality and pollutant loading, are greatly influenced by the size of the
watershed under investigation. The importance of these "scale" or "hierarchical" effects is
readily apparent in the Lake Erie Basin studies, which include watersheds ranging in size
from 11.3 to 16,395 sq km. Many of these scale effects are a consequence of the routing of
water from various portions of the watershed through drainage networks, with the attendant
mixing of water from differing portions of storm hydrographs. Other characteristics relate
to an "averaging" effect on "inputs" that occurs within large watersheds. Still other
characteristics reflect the increasing role of in-stream processing as watershed size
increases.
Some of the important hierarchical effects observed for nonpoint source pollutants in
these studies are:
1. Peak pollutant concentrations are higher in the runoff from small
watersheds than in the runoff from large watersheds. This effect is most
pronounced for sediments and sediment associated pollutants but is also
evident in soluble pollutants, including nitrates and pesticides.
2. The duration of exposures to pollutants is much longer in streams with
large watersheds than in streams with small watersheds. Small streams
"clear up" much more quickly than large streams.
8
-------
3. As a consequence of 1 and 2 (above), the exposure patterns in small
streams tend toward "acute" episodes, while the exposures in large streams
tend toward "chronic" patterns. Whether such exposures actually have
acute or chronic effects depends on the actual concentrations of specific
pesticides and the composition of the biological community. Since the
biological communities of small streams differ from those of large streams,
assessment of ecological impacts must consider the exposure patterns likely
to be encountered by a particular community.
4. The annual variability in material export is greater in small watersheds
than in large watersheds. This effect is probably associated with less
averaging of extreme (and low recurrence) rainfall events in small
watersheds. Since annual variability in agricultural runoff is large in any
case, the larger amount of annual variability in the outputs of small
watersheds makes the task of evaluating the effectiveness of agricultural
pollution abatement demonstration projects particularly difficult. Such
projects tend to focus on small watersheds where significant changes in
management practices can more easily be achieved. The short planning
horizon for such projects generally results in inadequate baseline data for
pre-treatment conditions and inadequate follow-up studies for post project
assessment.
5. As watershed size becomes smaller, increasing proportions of the total
annual export of pollutants occurs in decreasing proportions of time.
However, the high rates of export from small watersheds are distributed
into larger numbers of individual events. Consequently, it takes more
sampling effort to accurately measure the output of a small watershed than
the output of a large watershed. Since high export rates occupy less time in
a small watershed, it is easier to "miss" them in a sampling program.
6. In small watersheds, the dominant season of sediment export corresponds to
the dominant season of erosion on the landscape, i.e., in the late
spring/early summer period, when there is a combination of high intensity
rainfall events and low amounts of ground cover. In large watersheds, the
dominant period of sediment export occurs in the late winter/early spring,
during the periods of peak discharge. During these large events in large
rivers, sediment previously deposited in the channel system is resuspended
and exported.
7. While watershed size affects seasonal export of sediments and paniculate
associated pollutants, the seasonal export of soluble pollutants, such as
soluble phosphorus, nitrate, and soluble pesticides, is not affected by
watershed size. Winter is the dominant season for the export of soluble
phosphorus, and winter and spring are the dominant seasons for nitrate
export, while pesticide export is largely confined to the late spring/early
summer periods.
-------
SECTION 3
RECOMMENDATIONS
3.1. LAKE ERIE BASIN AGRICULTURAL POLLUTION ABATEMENT PROGRAMS
3.1.1. Comprehensive Agricultural Pollution Abatement Programs Are Needed
While much of the early emphasis of agricultural pollution abatement demonstration
studies in the Lake Erie Basin focused on phosphorus load reduction, it has become clear from
the monitoring projects that agricultural runoff affects many aspects of regional water
quality. Consequently, programs which address sediment, paniculate phosphorus, soluble
phosphorus, nitrate, and pesticides are in order. Such programs, in fact, represent the trend
which has occurred within the Lake Erie demonstration projects. Because of the major
off-site damages associated with cropland erosion, conservation tillage should continue to be
an integral part of such programs. Conservation tillage represents effective means to reduce
loading of both sediment and paniculate phosphorus. More attention will need to be focused
on fertilizer and pesticide issues, as well as crop rotation patterns.
Fortunately, comprehensive programs are likely to help improve the economic condition
of area farmers, rather than cause additional economic burden. A key to the economic
recovery of farmers will be more careful management of the fuel, fertilizer, and pesticide
inputs and of the soil resource base necessary to achieve realistic and economic yields.
Reducing the overapplication of fertilizers and pesticides will also reduce their runoff into
waterways or percolation into groundwater. Given the magnitude of the off-site damages
currently associated with the essential human enterprise of food production, it is in the
public's interest to aid farmers in becoming better managers. Such aid can be channeled
through the existing infrastructure of the Extension Service, the Soil and Water Conservation
Districts, and the Soil Conservation Service. More research on "low input, sustainable"
agriculture at land grant universities would also be appropriate. Since, in the long run, the
economic recovery of the agribusiness community also hinges on the competitiveness of U.S.
farmers, it is in the best long term interests of the agribusiness community to help farmers
reduce their fertilizer and pesticide inputs to the minimum necessary for maintaining
adequate yields within the context of conservation farming systems.
3.1.2. Multi-media Aspects of Agricultural Pollution Must Be Considered
Agricultural pollution abatement programs aimed at reducing surface water
contamination should not aggravate groundwater contamination problems and vice versa.
Furthermore, the significance of volatization of agricultural chemicals, coupled with
atmospheric transport, should be considered.
3.1.3. The Concept of Targetting Needs To Be Expanded within the Context of the Multi-
pollutant. Multi-media Characteristics of Agricultural Nonpoint Pollution
The broad range of both paniculate and soluble pollutants from cropland runoff
necessitates a re-evaluation of the concept of "targetting". Targetting to areas of high gross
erosion would certainly not be appropriate for addressing the problems of nitrate and
10
-------
pesticide runoff. Nor would such targetting efficiently address the problems of wintertime
soluble phosphorus export. In fact, targetting to areas of highest gross erosion may not even
be the most effective way to reduce sediment yields at the mouths of the major rivers
emptying into Lake Erie. Targetting must also consider the potential for groundwater
contamination. More research is needed on the sources, transport, fates, and effects of
various types of pollutants as they move from the land to and through stream systems and /or
into groundwater. Such research will support more effective targetting, and thereby
increase the efficiency of agricultural nonpoint source control programs.
3.1.4. Farmer Education Programs Related to Agricultural Nonpoint Pollution
While many farmers are aware that agricultural practices can affect water quality, few
are aware of the multi-pollutant, multi-media aspects of the problem as it occurs in their
local region. The extensive local data now available for Lake Erie tributaries, and for
regional groundwater, need to be effectively relayed to the farming community and to the
local agribusinesses and government agencies which support this community. Given a
detailed awareness of the problems, as they occur "in their own backyard", they will be much
more amenable to considering modifications of their farming practices that will reduce
agricultural pollution. Just as the extension service has carried the results of agronomic
research to individual farmers, an environmental extension effort needs to be mounted to
carry the results of environmental research to individual farmers. Since nonpoint pollution
problems stem from the cumulative effects of many small sources, the related educational
efforts need to reach out to the grassroots level.
3.2. RESEARCH ON AGRICULTURAL NONPOINT POLLUTION IN THE LAKE ERIE
BASIN
3.2.1. Long Term. Large Scale Studies Are Needed for Model Verification
It is within the context of large scale, long term studies of agricultural nonpoint
pollution that the adverse impacts of food production on regional water resources become
apparent. It is within this same context that the effectiveness of measures aimed at reducing
these adverse impacts must be verified. While models based on the effects of "best
management practices", as applied within research plots and individual fields, are useful in
predicting the responses of larger systems to such practices, model predictions should not be
equated with "real world" verification. Ideally and realistically, such model predictions do
need to be validated at the scale to which they are being extrapolated.
Since the achievement of a high level of adoption of best management practices in large
watersheds will take a long time, long term studies are essential. An ecosystem approach, in
which as many of the significant input and output variables as possible are measured, will be
necessary to support assessment of system responses to management efforts and to verify the
predictions of modeling approaches to nonpoint pollution control. While the complexity and
costs of such research are high, it is essential that environmental degradation associated with
food production be minimized. A network of large scale, long term agro-ecosystem studies
should be established, including sites within major physiographic regions. The paucity of
such studies is evident from the lack of data with which to compare the results of the Lake
Erie Basin studies. The lack of data with which to assess the national scope of groundwater
contamination from agricultural activities further reflects our ignorance of fundamental
11
-------
relationships between food production and water resources.
3.2.2. Future Directions for the Lake Erie Agro-ecosvstem Program
Heretofore agricultural nonpoint pollution research in the Lake Erie Basin has consisted
of the collection of many parts, somewhat akin to collecting the pieces of a puzzle.
Considerable input and output data for the watersheds have been collected. The adequacy of
various stream sampling programs has been evaluated. Techniques for efficiently collecting
the data and analyzing the resulting volumes of information have been developed. Numerous
demonstration programs have educated the agricultural "infrastructure" (i.e., the Extension
Service, the Soil Conservation Service, Soil and Water Conservation District personnel,
Agricultural Stabilization and Conservation Service employees, and agricultural chemical
dealers) on the advantages of conservation tillage, as well as several pitfalls to avoid when
using this technology.
A major need is to advance the integration of all the data and programs underway in the
Lake Erie Basin. Such integration can be accomplished by adopting an ecosystem approach for
the agricultural watersheds draining into Lake Erie. This approach is described in Section 4
of this report, as the Lake Erie Agro-ecosystem Program. Some of the specific research
issues that need to be addressed within that program are:
1. Analyses should be initiated on the relationships between the input
variables, both management-related and weather-related, and the output
variables. An ability to separate weather induced variations in material
export from changes associated with changing management practices is a
fundamental requirement for assessing the effectiveness of various
practices in reducing agricultural pollution. Furthermore, any trends
associated with climatic changes will need to be distinguished from
responses to changing management practices.
2. Where possible, several watersheds should be selected where special BMP
implementation efforts will be coordinated with appropriate monitoring of
both weather inputs and stream outputs. Such special watershed studies can
serve as sites for model development, calibration, and verification, and for
support of more rapid assessment of the effects of control programs.
3. The "output" studies should be expanded to include assessments of changing
agricultural practices on stream communities. While we bemoan the lack of
historical data upon which to judge the impacts of current agricultural
practices on stream communities, we have probably not adequately
characterized current stream communities in such a way as to facilitate
assessment of the effects of changing or future agricultural practices.
4. The interfaces between the agricultural ecosystems and the Lake Erie
ecosystem, ie., the lower sections of rivers, and their associated wetlands
and bays, need additional study if we are to better manage the entire system.
The transport and processing of materials within the interface zones
between the lake and the land constitute a highly complex area.
12
-------
SECTION 4
BACKGROUND OF THE LAKE ERIE AGRICULTURAL NONPOINT
POLLUTION RESEARCH AND DEMONSTRATION PROGRAMS
4.1. NONPOINT SOURCE POLLUTION STUDIES IN THE GREAT LAKES AND LAKE
ERIE BASINS
In the Great Lakes Basin, and especially in the Lake Erie Basin, nonpoint sources of
pollution have received particularly detailed study. Through a series of U.S.-Canadian
investigations coordinated by the International Joint Commission's Pollution from Land Use
Activities Reference Group (PLUARG), a comprehensive overview of nonpoint source
pollution in the Great Lakes was developed in the late 1970's (International Joint
Commission 1978b, 1980, 1983). These studies revealed that land use activities do
adversely impact Great Lakes water quality. Agricultural land use was singled out as a major
source of sediments, nutrients and pesticides impacting several regions, including Green Bay,
Saginaw Bay and much of the western and central basins of Lake Erie. These studies indicated
that, although the land area draining into Lake Erie occupies only 11.5% of the total land area
in the Great Lakes Basin, Lake Erie tributaries carried 58% of the total tributary suspended
solids load entering the Great Lakes (International Joint Commission 1978b). Maps of unit
area phosphorus yields for the Great Lakes indicated that the largest aggregation of lands with
high unit area phosphorus yields occurs within the watersheds draining into the western and
central basins of Lake Erie (International Joint Commission 1978b). These high sediment
and phosphorus losses are associated with the intensive row crop agriculture which
dominates land use in large portions of the Lake Erie Basin. Consequently, agricultural
nonpoint pollution has been studied most extensively in the Lake Erie Basin.
Much of the detailed study in the Lake Erie Basin was conducted as part of the U.S. Army
Corps of Engineers' Lake Erie Wastewater Management Study (LEWMS) (U.S. Army Corps of
Engineers 1982). That study included the development of a detailed geographical information
system for the entire United States portion of the Lake Erie Basin (Adams et al. 1982) as
well as detailed water quality studies (Baker 1984, 1985 a,b). The LEWMS program was
coordinated with both the PLUARG studies and the Areawide Waste Treatment Management
planning studies conducted under Section 208 of the Federal Water Pollution Control Act
Amendments of 1972 (Public Law 92-500).
By linking together support from a series of planning and research grants, the Water
Quality Laboratory at Heidelberg College has been able to develop a combination of detailed and
long term studies of the impacts of agricultural runoff on regional water quality that are
unique. During the course of these studies, major financial support has come from: the
Army Corps of Engineers; the U.S. EPA (several offices); the State of Ohio; the Toledo
Metropolitan Area Council of Governments; the cities of Tiffin, Upper Sandusky and Bucyrus;
private foundations, including the Rockefeller Foundation, the Joyce Foundation and the Gund
Foundation; and industries, including soap and detergent manufacturers, pesticide
manufacturers and power companies.
The resulting data have been used extensively for a wide variety of purposes. The
13
-------
International Joint Commission uses these data to calculate phosphorus loading from
tributaries into Lake Erie. The data have been used extensively in major planning studies for
this region including "208" planning of the Toledo Metropolitan Area Council of Governments,
the Ohio Environmental Protection Agency and in the U.S. Army Corps of Engineers' Lake Erie
Wastewater Management Study (U.S. Army Corps of Engineers 1982). Several studies aimed
at developing nonpoint source models (Cahill et al. 1979, Zison 1980), and river transport
models (Verhoff et al. 1978), have also used these data sets. The data sets have also been used
to evaluate sampling and calculational strategies for load estimation (Richards and Holloway
1987, Watson 1985) and for developing techniques to characterize ambient water quality
impacts of agricultural runoff (Shelly 1986).
Since the data so clearly illustrate many of the charcteristics of agricultural nonpoint
pollution, the Water Quality Laboratory is increasingly called upon to participate in and /or
present workshops at the local, state and national level on the topics of agricultural pollution.
Recent presentations have been made to: the National Alliance of Independent Crop
Consultants, the American Fisheries Society, the American Association of County Agricultural
Agents, U.S. EPA-Office of Pesticide Programs, the National Federation of Soil and Water
Conservation Districts, the National Association of State Departments of Agriculture, the
National Agricultural Chemicals Association, and the National Association of Conservation
Districts.
4.2. AGRICULTURAL POLLUTION ABATEMENT DEMONSTRATION PROGRAMS
As it became evident in the above studies that agriculture was a major source of
phosphorus entering Lake Erie, ways to reduce agricultural phosphorus loading were
examined. Because most of the phosphorus delivered to Lake Erie is associated with sediment,
erosion control measures which should reduce sediment transport provide a means to reduce
phosphorus loading to the lake. A demonstration project in the Black Creek watershed of Allen
County, Indiana (Lake and Morrison 1977) suggested that erosion control through structural
measures would be an extremely costly method to reduce phosphorus loading to Lake Erie.
Instead of structural measures, conservation tillage was identified as a potentially effective
means of reducing erosion and the associated suspended sediment and paniculate phosphorus
loadings into Lake Erie. Conservation tillage consists of a variety of techniques which
increase crop resides on the soil surface thereby reducing erosion (See special issue of the
Journal of Soil and Water Conservation. Volume 38, May-June 1983 for an overview of
conservation tillage.)
The agronomic suitability of various types of conservation tillage for Lake Erie Basin
soils was then evaluated in a series of demonstration studies. The first of these
demonstrations was located in the Honey Creek Watershed of the Sandusky River Basin as part
of the LEWMS study. The success of the Honey Creek Demonstration Project (Honey Creek
Joint Board of Supervisors 1982) led to U.S. EPA-supported conservation tillage
demonstration programs in Allen and Defiance counties of Ohio and eventually to programs in
31 counties of the Lake Erie Basin (Morrison 1984). The major objectives of these
demonstration studies were to acquaint as many farmers as possible with conservation tillage
techniques, to develop local data comparing conventional tillage and conservation tillage in
terms of crop yields and production costs, and indirectly to accelerate area-wide adoption of
conservation tillage. These demonstration projects have confirmed that, for many Lake Erie
Basin soils, conservation tillage can provide either equivalent or increased profits in
14
-------
comparison with conventional tillage (Conservation Tillage Information Center 1985).
In 1983, through a Supplement to Annex 3 of the Great Lakes Water Quality Agreement of
1978, the U.S. and Canada agreed to reduce phosphorus loading to Lake Erie by an additional
2,000 metric tons per year beyond the reductions achievable by reducing major municipal
point source phosphorus loading to 1 mg/L P in the effluents. The U.S. phosphorus reduction
strategy (Great Lakes Phosphorus Task Force 1985), as well as those of the individual states
(e.g., see Ohio EPA 1985), is focusing on conservation tillage as a major tool to reduce
phosphorus loading to the lake. Implementation of agricultural phosphorus load reduction
programs should consequently consist of continuing and /or expanding programs to aid
farmers in adopting conservation tillage.
While much of the initial emphasis of the Lake Erie agricultural pollution abatement
demonstration programs focused on tillage practices to reduce sediment and paniculate
phosphorus loading, the scope of the programs has significantly broadened. The tributary
monitoring program pointed out that unexpectedly large proportions of nitrogen fertilizers
applied by farmers were not incorporated by crops but instead were being exported to Lake
Erie and were affecting public water supplies derived from tributaries. Furthermore
numerous herbicides applied to cropland are present in area rivers and pass through
conventional water treatment plants with little attenuation (Baker 1983d). At the same time
the input costs for crop production were rising and the market value of crops was decreasing,
placing many farmers in serious economic difficulties. These factors have led to the growth of
programs which link increased farm profits with reductions in agricultural pollution
through improved management of not only tillage, but also of fertilizer and pesticide inputs.
4.3. POSSIBLE WATER QUALITY TRADE-OFFS WITH CONSERVATION TILLAGE
The primary water quality benefits of conservation tillage fall in the area of reduced soil
erosion and an accompanying reduction in sediment and paniculate phosphorus export from
agricultural watersheds. The proportional reduction in watershed sediment export may differ
considerably from the proportional reduction in gross erosion rates within the watershed,
depending on the relative sediment delivery ratios from treated and untreated areas. To the
extent that the concept of stream sediment carrying capacity applies to the transport of clay
fractions in Lake Erie tributaries, reductions in gross erosion on the landscape may be
accompanied by increased stream bank and stream bed erosion rates, thereby diminishing
hoped-for reductions in sediment transport. However, the sediment derived from stream
banks would not carry the same load of agricultural nutrients or pesticides as sediment
derived from cropland. Furthermore, it is unclear how soon reduced erosion of the landscape
would become evident as reduced sediment yields since the time of transit of sediment from
fields to and through stream channels to Lake Erie is uncertain. Therefore, the magnitude of
sediment yield reductions that will actually accompany cropland erosion control measures in
the Lake Erie Basin remains to be determined.
The extent of reduction in paniculate phosphorus loading that will accompany erosion
control programs is uncertain due to all of the uncertainties noted above regarding the extent
of sediment reductions. Additional uncertainties are introduced due to probable changes in
average particle size of the exported sediment. It is likely that the average particle size will
decrease as a result of erosion control programs. It is expected that this will be accompanied
by an increase in the phosphorus to sediment ratio thereby making the proportional
15
-------
reductions in phosphorus loading less than the proportional reductions in sediment loads
(U.S. Army Corps of Engineers 1982).
While the erosion reduction benefits of conservation tillage are well documented, at least
at the level of plot and field-sized studies, much concern exists regarding the possibility that
conservation tillage could aggravate other water quality problems, especially the
contamination of surface and groundwater by nitrates and pesticides (Crosson 1981; Hinkle
1983).
Nitrate and many currently-used pesticides are primarily transported as dissolved
materials in water rather than as adsorbed materials on sediments. In addition, soluble forms
of phosphorus are much more bioavailable than paniculate phosphorus. Data from plot
studies have frequently shown that conservation tillage increased runoff amounts and /or
concentrations of nitrates and soluble phosphorus (Baker & Laflen 1983; Crosson 1981). In
a review of the effects of conservation tillage on pesticide use and runoff losses, Logan
(1981) concluded that pesticide losses would not be expected to change measurably with a
shift to conservation tillage. In part, Logan's conclusions were based on evidence that for the
soil types in northwestern Ohio, conservation tillage would do little to increase water
infiltration into soil and thus decrease surface runoff (Logan and Adams 1981). Since
herbicides move into streams as part of the surface runoff from fields, if surface runoff is
not significantly reduced, export of soluble pesticides is also unlikely to be reduced. If
application rates of soluble herbicides increase with conservation tillage, it is likely that
herbicide concentrations in surface waters will increase. However, in conservation tillage
demonstration projects in the Lake Erie Basin, soluble herbicide application rates have
shown little or no increase. The effects of conservation tillage on the movement of nitrates
and pesticides into groundwater or surface water was the subject of an EPA-sponsored
conference in Chicago in 1986. The proceedings were published in early 1987 ( Logan et al.
1987).
4.4. THE LAKE ERIE AGRO-ECOSYSTEM PROGRAM
The combination of extensive baseline data and forthcoming changes in agricultural
practices, resulting from either agricultural nonpoint pollution control programs or
economic considerations, presents important opportunities to advance the science of
agricultural nonpoint pollution control through a continuation and expansion of programs in
the Lake Erie Basin. To efficiently address the complex research issues that are involved,
current programs are being advanced within the context of a large scale, long term
agricultural ecosystem program (Figure 4.1).
Agricultural nonpoint source pollution reflects what ecologists have referred to as the
"leakiness" of agricultural ecosystems (Odum 1969). Relative to natural ecosystems,
cultivated ecosystems have a high potential for erosion and nutrient losses (Woodmansee
1984). Many of the "best management practices" aimed at reducing agricultural nonpoint
pollution attempt to "tighten up" the nutrient cycles of these agricultural ecosystems and
confer upon these systems more of the characteristics of natural ecosystems, such as
persistence and stability. Farmers are being urged to adopt a "systems approach" to
production which involves careful management of fertilizers and pesticides, as well as plant
residues (Pierce 1985). Concepts of "low input, sustainable" agriculture are receiving
increased attention.
16
-------
CONTROLLED INPUTS
AGRICULTURAL
POLLUTION
ABATEMENT
PROGRAMS
4
J
FARMFRc:
H
MANAGEMENT
PRACTICES
• rotations
• tillage
• fertilizer use
• pesticide use
• others
LAKE ERIE BASIN
AGRICULTURAL
ECOSYSTEMS
AGRICULTURAL
ECCNOMf
UNCONTROLLED INPUTS
AGRICULTURAL
WATERSHEDS
• size
• location
• soils
• topography
• geology
• drainage
• land use
• etc
METEORCLOGICAL
VARIABLES
• precipitation
• temperature
• wind
• relative humidity
• radiation
• atmospheric
deposition
OUTPUTS
AGRICULTURAL
PRODUCTS
SURFACE WATER
• quantity
• quality
- sediments
- phosphorus
- nitrates
- pesticides
GROUND WATER
• quantity
• quality
- nitrates
- pesticides
Figure 4.1. Major components and their relationships for agro-ecosystem studies
-------
While management practices reflect "controllable" inputs to agricultural ecosystems,
weather conditions reflect a major "uncontrollable" input, to which these systems are highly
sensitive. Annual variability in weather conditions causes large annual variability in
nutrient and sediment export which can easily mask the effects of improved management
practices in reducing such export. A major task in programs to assess the effectiveness of
agricultural pollution abatement practices is to account for the weather induced variability.
Consequently, it is necessary to measure both the management inputs and the weather inputs
for the study watersheds.
For the management of the Great Lakes Basin as a whole, there is strong support for
utilizing an Ecosystem Approach which addresses "the interacting components of air, land,
water and living organisms, including man" (International Joint Commission 1978a). In
fact, this approach was recommended in the 1978 Water Quality Agreement (International
Joint Commission 1978a). An important aspect of this approach is the use of mass balance in
the management of both conventional and persistent pollutants (U.S. EPA 1985b). The same
rationale that suggests an ecosystem approach for the Great Lakes Basin is also applicable to
subcomponents of the Basin, such as the agricultural ecosystems draining into the Lake Erie
Basin.
The generalized agro-ecosystem model, as shown in Figure 4.1, does facilitate efficient
approaches to the multiple objectives associated with this program. These objectives include
the provision of:
1. accurate data on pollutant loading into the Lower Great Lakes to support the
application of mass balance approaches to Great Lakes water quality
management,
2. baseline data upon which to evaluate the effectiveness of agricultural
pollution abatement measures,
3. site-specific water quality data to help garner local support among rural
and urban residents for agricultural pollution abatement programs,
4. sufficient water quality data to support the development, calibration and
verification of agricultural runoff models, as applied to large watersheds
and river basins,
5. water quality data sets to support evaluation of tributary sampling
strategies and loading calculation techniques, and
6. techniques for tracking agricultural management practices within large
tillage demonstration watersheds.
A Prospectus for the Lake Erie Agro-ecosystem Program has recently been prepared by
staff of the Water Quality Laboratory at Heidelberg College and is available upon request.
18
-------
4.5. RELATED STUDIES UNDERWAY AT THE HEIDELBERG COLLEGE WATER
QUALITY LABORATORY
In addition to the ongoing tributary loading studies, as described in this report, several
related studies are in progress. Most of these studies support the Lake Erie Agro-ecosystem
Program.
4.5.1. Tillage Tracking Program
In order to gain a more precise estimate of tillage practices actually in use by farmers in
the study watersheds, a windshield survey technique was developed and applied to the Honey
Creek and Rock Creek watersheds. The technique includes recording a set of information twice
per year on approximately 2000 individual fields. The results of the first three years of the
program have recently been reported by Krieger (1986a). Similar data are available for
each field in the Lost Creek Watershed.
4.5.2. Rural Drinking Water Studies
A program of groundwater studies, utilizing information from the analysis of water from
private wells, was initiated in 1985. The program originally focused on "critical" areas, as
judged by cooperating personnel from county health departments. While the study did result
in the location of a few "hot spots" of nitrate contamination, even these hot spots had low, if
any, pesticide contamination. Subsequently, the nitrate portion of the program was expanded
to a much larger sampling of wells with no attempt to focus on critical areas. Of the initial
3,600 samples tested in that program, the nitrate-nitrogen concentrations in 83% of the
wells were less than 0.3 mg/L. In only 2.6% of the wells was the concentration above the
drinking water standard of 10 mg/L. The nitrate studies noted above are being expanded and
an interim report on our groundwater studies will be prepared in November 1987.
4.5.3. Pesticide Studies in Rainwater
A study of the concentrations of currently used pesticides in rainwater was initiated in
1984. The study indicates that several herbicides are present in rainfall during the May,
June and July periods. The pesticide concentrations are much higher in rainwater than in
groundwater, although the rainfall concentrations are lower than in the rivers during the
spring runoff events. The sampling program includes sites at West Lafayette, Indiana, at
Potsdam, New York, at Parsons, West Virginia, and at Tiffin, Ohio. Results from the first
two years of this study have recently been published (Richards et al. 1987).
4.5.4. Rainfall Network
To augment the existing network of NOAA weather stations, a cooperative network of daily
rainfall stations was established in 1982. It involves approximately 120 local observers
(mostly farmers) in the three counties that make up most of the Sandusky River Basin.
From April through October, daily rainfall amounts are recorded and submitted at monthly
intervals to our laboratory, where the data are entered into computer storage. The main
purpose of the project is to obtain information for supporting trend analysis and modeling
efforts in these watersheds.
19
-------
In connection with this program, our laboratory operates the NOAA cooperative weather
station for Tiffin, Ohio. This station includes a continuously recording raingauge, as well as a
standard raingauge and temperature recording equipment. In 1987, an evaporation pan will
be installed at this station. The lab also operates recording raingauges at other locations in
the study watersheds.
4.5.5. Wetlands Research Programs
The laboratory is involved in research at the interface between the river systems and
Lake Erie. Currently work is in progress under a Sea Grant award through Ohio State
University to measure pesticide concentrations in wetlands adjacent to the lower portions of
the Sandusky River and at the Old Woman Creek Nature Preserve.
4.5.6. Statistical Analysis of Tributary Sampling Programs
Under a research grant from the Great Lakes National Program Office the laboratory is
evaluating various sampling strategies aimed at producing accurate loading data for Great
Lakes tributaries. Both event response and stable response streams are under investigation.
In event response streams, the concentrations of both paniculate and dissolved pollutants
from nonpoint sources increase during runoff events.
4.5.7. Pesticide Removal Research
The laboratory has a cooperative agreement with the U.S. EPA's Water Engineering
Research Laboratory in Cincinnati, Ohio to evaluate the effectiveness of various treatment
techniques for removing pesticides from drinking water. The techniques include carbon
filtration, reverse osmosis, and ozonation. Results of this research, as it applies to alachlor
removal have recently been summarized (Miltner et al. 1987).
4.5.8. Bioavailable Phosphorus Loading to Lake Erie
Beginning in 1982, additional phosphorus forms were analyzed on subsets of the
tributary samples. These additional analyses included NaOH extractable phosphorus, which
provides an estimate of the bioavailable particulate phosphorus fraction. In addition, the
soluble hydrolyzable phosphorus fraction was measured. These two measurements allow
calculation of bioavailable phosphorus loading to Lake Erie. A progress report on these
studies was submitted to the Great Lakes National Program Office in 1983 (Baker 1983b).
Data collected since that time will be included in the report summarizing the 1986 water
year program. That report is currently in preparation.
20
-------
SECTION 5
STUDY METHODS
5.1. SAMPLING LOCATIONS
The sampling locations for Lake Erie tributaries are shown in Figure 5.1 and for Lake
Ontario tributaries in Figure 5.2. All of the samples are collected either at or near U.S.
Geological Survey stream gauging stations. These stations, along with their corresponding
USGS identification numbers, are shown in Table 5.1. Except for the Maumee, Raisin and
Genesee rivers, water samples are collected in the immediate vicinity of the gauging station.
For the Maumee River, samples are collected at the water intake plant for the city of Bowling
Green. This plant is the site of a USGS water quality monitor (Number 04193490) and is
located about 3.2 km upstream from the gauging station. For the River Raisin, samples are
collected from the bridge at the Ida-Maybee Road, about 1.3 km upstream from the gauging
station. For the Genesee River samples are collected from a bridge located at the Rochester
Gas and Electric Plant near the gauging station.
Table 5.1 contains additional information for each station, including: 1) the drainage
area upstream from each stream gauging station; 2) the mean annual discharge for the period
of record through the 1985 water year, as reported in the USGS's Water Resources Data for
each state; 3) the USGS annual discharges for the 1982-1985 water years; and 4) the
numbers of nutrient and pesticide samples analyzed each year as part of these studies. Data
for Lost Creek are included in Table 5.1 and throughout this report even though this station
has been funded as a part of grants from the Defiance County Soil and Water Conservation
District (Baker 1986) and, beginning with the 1985 water year, from the U.S. Soil
Conservation Service. The Lost Creek watershed is the smallest of the study watersheds and
provides very useful information for hierarchical analysis of nonpoint source pollution.
Land use characteristics for the watersheds upstream from each sampling station in the
Lake Erie Basin are summarized in Table 5.2. The land use data were derived from the
geographical information system developed as part of the U.S. Army Corps of Engineers' Lake
Erie Wastewater Management Study (U.S. Army Corps of Engineers, 1982). With the
exception of the Cuyahoga River Basin, cropland dominates the land use within each
watershed. The geographical information system has also been used for calculations of gross
erosion for each watershed (Logan et al. 1982). Average gross erosion rates for each
watershed are also listed in Table 5.2.
5.2. SAMPLING METHODS
For all of the stations located in Ohio, automatic samplers (ISCO 1680 or equivalent) are
used to collect discrete samples at 6 hour intervals, resulting in four samples per day which
are collected at 0100, 0700, 1300 and 1900 hours. Each gauging station is equipped with an
all-weather pumping system that operates continuously. The automatic samplers are housed
in the gauging stations and the samplers pump water from sampling wells fed from the all
weather pumps. For stations on smaller watersheds, such as Lost Creek, Rock Creek, and
21
-------
MICH.
RAISIN R.
BASIN
PA.
DRTAGE R.
BASIN
'HURON R. BASIN
'SANDUSKY R. BASIN
OH.
UYAHOGA1
R. BASIN)
I
1
I
I
I
Sampling Locations:
1 . River Raisin near Monroe, Ml
2. Maumee R. at Bowling Green, OH water intake
3. Sandusky R. near Fremont, OH
4. Cuyahoga R. at Independence, OH
5. Lost Cr. tributary near Defiance, OH
6. Rock Cr. at Tiffin, OH
7. Honey Cr. at Melmore, OH
8. Upper Honey Cr. at New Washington, OH
Figure 5.1. Locations of the tributary monitoring stations in the Lake Erie Basin.
22
**»
-------
54X OF KINGSTON^
C06OURG —-i.
'ivetr
TORONTO
*Li*
9.
BEAVER I PARK
HIAGMA mve*
L NIAGARA
• FAU.S
•BUFFALO
**s^ CT
• • - - • "p
CARA ^(OSWEGO
^/^— ^^ A\
•gfccHESTER^^ ^
^^
ISLAND
0 t>
«3°50'
«s"oo'
ERIE .
METCRS
0 W U 10 40 »
JT*TOTE MILES
SOURCE NOAA(l*7l)
Sampling Locations:
1 . Genesee R. at Rochester, NY
2 . Oswego R. at Oswego, NY
3. Black R. at Watertown, NY
Figure 5.2. Locations of the tributary monitoring stations in the Lake Ontario Basin.
23
-------
Table 5.1. Listing of tributary monitoring stations, watershed areas, mean annual discharges, and, for the
1982-1985 water years, the water year discharges and the number of nutrient and pesticide samples
analyzed.
Station
USGS No
Maumee R.
01493500
Sandusky R
04198000
Cuyahoga R.
04208000
Raisin R.
04176500
Honey Cr.
04197100
Upper Honey
Creek
04197020
Rock Cr.
04197170
Lost Creek
Tnb.
04185440
Genesee R
04232000
Oswego R
04249000
Black R (NY)
04260500
Area Km2
(Mean Annual
Discharge, 106m3)
16,395km2
(4,422)
3,240 km2
(891.3)
1,831 km2
(738)
2,699 km2
(650.2)
386 km2
(124.1)
44.0 km2
(15.36)
88.0 km2
11.3km2
6,390 km2
(2,512)
13,209km2
(5,991)
4,854 km2
(3,598)
Water Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
USGS Annual
Discharge
106m3
7,107
4,748
5,878
4,365
1,390
649.6
1,940
769.8
919.8
9199
1,030
921 7
925.3
874.4
753.0
816.7
157.7
88.72
1682
91.43
16.58
11.06
21.07
12.07
43.13
19.83
6.799*
5.175*
4.956*
4.840*
3,362.3
2,431.4
3,826.4
2,201 .0
6,715.1
5,085.3
6,748.7
4,682.1
3,976
3,570
4,295
3,802
Samples Analyzed
Nutrients Pesticides
479
546
482
454
469
448
441
502
447
475
437
502
223
312
313
310
538
514
483
480
151
416
409
430
434
522
540
518
784
399
457
56
60
43
75
52
60
43
75
61
65
62
30
53
62
88
56
51
58
79
82
24
25
20
29
25
32
43
31
65
68
100
121
58
32
85
46
87
143
51
51
57
63
..
--
--
--
--
--
--
--
* Discharge records subject to revision
24
-------
Table 5.2. Summary of land use and gross erosion rates for Lake Erie Basin tributary watersheds.
Watershed
Maumee R.
Sandusky R.
Cuyahoga R.
Raisin R.
Honey Cr.
Upper Honey Cr.
Rock Cr.
Lost Cr.
Cropland
%
75.6
79.9
4.2
67.1
82.6
89.1
80.9
83.0
Pasture
%
3.2
2.3
43.1
6.8
0.6
---
2.3
—
Forest
%
8.4
8.9
29.1
9.0
10.0
7.5
11.8
10.6
Water
%
3.5
2.0
3.0
3.0
0.5
...
0.9
1.4
Other
%
9.4
6.8
20.6
14.1
6.3
3.4
4.2
5.0
Gross
Erosion Rate
kg/ha/yr
6,840
8,250
896.*
9,750
6,860
7,060
9,540
7,610."
*This gross erosion rate was calculated using the normal cover factor for forested areas. Due to unusual
combinations of soils and slopes in portions of the Cuyahoga River basin, erosion from this watershed
area is much higher than the calculated value.
**This calculation was completed in 1987 by the U.S. Soil Conservation Service and includes the
impacts of conservation tillage demonstration programs to increase residue levels on the soil.
Upper Honey Creek, a second sampler, set to collect samples at one or two hour intervals, is
also used. The second sampler is either triggered automatically when the river stage reaches
a certain level or is manually triggered during a runoff event. In either case, the time of
sample collection is recorded on a printer. During low flow periods analyses are performed
on only one sample per day. During storm events, as evidenced either by turbidity in the
samples or by high stream discharges, all available samples are analyzed (four or more per
day, depending on the station).
At the stations in Michigan and New York, grab samples are collected by local observers.
For the River Raisin five samples per week are collected on a year-around basis. For the
New York tributaries the local observers are instructed to collect at predetermined intervals
(usually 2 per week) and to collect extra samples during high flow periods. In general, the
sampling programs for the tributaries to Lake Ontario have been much less satisfactory than
for the tributaries to Lake Erie, because local observers had to decide whether a particular
storm event was a "large" event for a particular year, and because storms don't always come
at convenient times.
Pesticide samples for Lake Erie Basin sampling stations are collected with automatic
samplers at the Maumee River, Lost Creek, Sandusky River, Honey Creek, Upper Honey
Creek and Rock Creek stations. For the Maumee and Sandusky rivers, ISCO Model 2100
samplers, containing 24 400 ml glass bottles, are used. In order to obtain sufficient volume
25
-------
of samples, two bottles are filled at each sampling time. Samples are collected twice per day.
The capacity of each sampler is therefore two samples per day for six days. Since the
samplers are serviced at weekly intervals, no samples are collected on the day preceeding
sample pick-up.
Beginning in 1984 for Honey Creek and Rock Creek, in 1985 for Upper Honey Creek and
in 1986 for Lost Creek, modified ISCO Model 1840 samplers were installed which pump
directly into one-quart Mason jars. Since each sampler has 28 positions, these samplers
allow collection of 4 samples per day for 7 consecutive days. Prior to the above dates, ISCO
Model 2100 samplers were used, as described above, for sample collection at these smaller
watersheds . At the Cuyahoga and Raisin river stations, pesticide samples are collected by
grab sampling techniques. Samples for pesticide analyses are not collected from the Lake
Ontario tributaries.
5.3. ANALYTICAL PROGRAM: NUTRIENTS, SEDIMENTS, AND CONDUCTIVITY
All samples are analyzed for soluble reactive phosphorus (SRP), total phosphorus (TP),
suspended solids (SS), nitrate plus nitrite-nitrogen (NO23-N), total Kjeldahl nitrogen
(TKN), ammonia (NH3), dissolved silica (Si02), chloride (Cl), and conductivity (Cond.). In
the case of nitrate plus nitrite-nitrogen most of the nitrogen present in these rivers is in the
form of dissolved nitrate. Throughout the text the term "nitrate" is used interchangeably with
the abbreviation N023-N.
The analytical methods are identified in Table 5.3 and have been described in detail in
quality assurance materials submitted to the Quality Assurance Office, Region V, U.S. EPA.
The following documents contain information on analytical methods and related quality control
results:
1. Baker, David B. January 1981. "Quality Assurance Program for Detailed
Tributary Loading Studies in Event Response Rivers." Submitted to James
H. Adams, Chief, Quality Assurance Office, Region V, U.S. EPA.
2. Baker, David B. March 1982. "The Effects of Sample Storage for One Week
Without Preservation on Soluble Reactive Phosphorus Loading
Measurements." Submitted to David Payne, Quality Assurance Office,
Region V, U.S. EPA and Marcella Gewirth, Great Lakes National Program
Office, Region V, U.S. EPA.
3. Baker, David B. June 1982. Quality Assurance Program Update -
Responses to the April 16, 1982 Report by the Region V, EPA Quality
Assurance Office on its On-Site Evaluation of the Water Quality
Laboratory of Heidelberg College, Tiffin, Ohio. Submitted to the Quality
Assurance Office, Region V, U.S. EPA.
All of the nutrient analyses are done using Technicon Autoanalyzer II systems equipped
with digital printers. The printed outputs for each analytical tray, including the
environmental samples and the associated blanks, standards, and spikes, are transferred to
computer storage. Thus, the performance of the analytical system at the time any particular
sample was analyzed can be readily determined.
26
-------
Table 5.3. Analytical methods used for nutrients and sediments.
Parameter
Abbreviation
STORE!
Number
Method
Suspended Solids
Total Phosphorus
Soluble Reactive
Phosphorus
Nitrate + Nitrite-
Nitrogen
Ammonia
Nitrogen
Total Kjeldahl
Nitrogen
Chloride
Silica
Conductivity
S3
TP
SRP
NO23-N
TKN
Cl
SiO2
Cond.
00530
00665
00671
00631
00608
00625
00940
00955
00095
Method 160.2
Non-Filterable, Gravimetric
pp. 160.2-1 -160.2-3
Method 365.3
Colorimetric, Automated
Ascorbic Acid Reduction, Two-Reagent
(modified, EPA approved)
Sulfuric Acid - Persulfate Digestion
pp. 365.3-1 - 365.3-3
Method 365.3
Colorimetric, Automated
Ascorbic Acid Reduction, Two-Reagent
(modified, EPA approved)
pp. 365.3-1 - 365.3-3
Method 353.2
Colorimetric, Automated
Cadmium Reduction (dissolved)
pp. 353.2-1 - 353.2-7
Method 350.1
Colorimetric, Automated
Phenate
pp. 350.1-1 -350.1-6
Method 351.2
Colorimetric, Semi-Automated
Block Digester, Automated
Phenate
pp. 351.2-1 -351.2-5
Method 352.2
Colorimetric, Automated
Ferricyanide
pp. 325.2-1 - 325.2-3
Method 370.1
Colorimetric, Automated
Molybdate
pp. 370.1-1 -370.1-5
Method 120.1
Direct Reading, Temperature
Compensating. Probe
pp. 120.1-1
'All methods are taken from the following reference: Methods for Analysis of Water and Wastes,
U.S. Environmental Protection Agency, Monitoring and Support Laboratory, Cincinnati, Ohio 45268.
EPA 600/4-79-020. 1979.
27
-------
5.4. ANALYTICAL PROGRAM: PESTICIDES
Samples are analyzed for the pesticides listed in Table 5.4. The analytical procedures and
related quality control program have been described in detail by Kramer and Baker (1985).
The procedure involves methylene chloride extraction followed by Kuderna-Danish
concentration, transfer to iso-octane and analysis by capillary gas chromatography using
nitrogen-phosphorus thermionic detectors. By using a DB-1 and a DB-5 column,
simultaneous confirmation is obtained for every sample on 14 out of the 18 compounds for
which the system is routinely calibrated. Azobenzene is added to each extract to provide a
marker for calculation of relative retention times. Representative chromatographs for a
standard solution and the associated data system outputs are shown in Figure 5.3. In 1982
the analytical system consisted of a Varian Model 3700 system interfaced to a Spectra
Physics Data System. In 1984 the system was upgraded to a Varian Model 3400 Gas
Chromatograph interfaced with a Varian Vista Model 402 data system. Both systems are
equipped with autosamplers. The data systems are linked directly to the WQL's VAX 11/750
computer. The reports, as shown in Figures 5.3b and c, are transferred directly into the
laboratory computer.
The quality control program includes the analysis of spiked samples, blanks, and
replicates, as well as an interlaboratory sample exchange program with several pesticide
manufacturers. Detection limits, mean percent recoveries and linear ranges for the most
commonly observed pesticides are shown in Table 5.5. Linear ranges were determined by
analysis of a dilution series of mixed standards. The sample exchange program indicated that
correction of WQL pesticide data for recoveries less than 100%, using the mean percent
recoveries, results in values that agree closely with those of the pesticide manufacturers. In
this report data presented in summary tables have been corrected for recoveries less than
100% where indicated using the percent recoveries shown in Table 5.5. The pesticide data in
Appendix II have not been corrected for recoveries less than 100%.
28
-------
Table 5.4. Pesticides identified on each channel of the gas chromatograph and representative
retention times.
DBS
Peak#
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Column (Channel
Time
21.74
25.56
35.59
36.22
38.54
39.17
41.36
41.64
41.89
43.15
43.36
43.95
47.88
49.18
51.17
52.36
53.02
55.61
1)
Name
EPTC
Butylate
Azobenzene
Ethoprop
Trifluralin
Phorate
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Diazinon
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
DB1
Peak#
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Column (Channel
Time
20.17
24.13
33.23
33.49
36.33
36.68
37.81
37.97
38.65
40.43
44.02
46.27
48.48
49.50
52.35
2)
Name
EPTC
Butylate
Azobenzene
Ethoprop
Phorate
Trifluralin
Carbofuran
Simazine
Atrazine
Fono/Terb+
Metribuzin
Alachlor
Cyanazine
Metolachlor
Pendimethalin
+Fonofos and terbufos are not separated by this column under these operating conditions.
29
-------
p
co CHART SPEED 0.3 CM/MIN
= ATTEN: 16 ZERO: 20* 5 MIN/TICK
™ l
| -STATJ. '
a
TJ
ATTEN: 16 ZERO:
- 4
5 MIN/TICK
O
U
Z SR:OFF
p
to —
to
CJ
o>
co
•a
a.
BUTYLATl
2.556
S3 5.536
' 6.636
8.914
10.617
. 064
SR:OFF=
-EPTC
16.717
= 15.816
14.965
00
50.698
3.792
17.820
LINURON—t* ~ 42.C.88
31.682
.611
46.61 1
PROWL
CYftNAZIN
—[ 63. 161
52
' 55
59
64
52.8
.863
.788
.822
.504
57.666
— 67.047
Figure 5 3 Typical chromatographs and data reports for a mixed pesticide standard on
a DB-5 (Channel 1) and a DB-1 (Channel 2) column. Figure 5.3a. Chromato-
graphs for Channels 1 and 2;
30
-------
TITLE: DB-S PEST
0
O
»
O
bo
5"
3"
3
IB
2
0
u
~2.
O
NJ
LJ
O
oo
lu
Q.
O
r*
z
O
M
N)
vl
^
or
O
X
O
_.
O
to
0.
t/>
CHANNEL NO: 1
PEAK PEAK
NO
1
d.
3
4
5
6
7
8
9
10
1
•2.
3
4
5
6
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
3G
39
NAME
EPTC
BUTYLATE
DADK
A20BEN2EN
ETHOPROP
DI A
DEA
DK
PHORATE
S1MA2INE
CARBOFURA
ATRA2INE
TERBUFOS
DI AZINON
DA
METRIBUZE
ALACHLOR
LINURON
METOLACHL
CHLORPYRI
CYANA2INE
PROWL
TOTALS:
DETECTED PKS:
SAMPLE:
RESULT
MG/L
0.
0.
0.
0.
4.
2.
0.
0.
6.
^
4.
4.
4.
1 .
0.
4.
0.
4.
0.
1 .
0.
0.
0.
0.
2.
4.
4.
0.
4 .
0.
4 .
4 .
4.
4.
0.
0.
0.
0.
0.
78.
58
000
000
000
972
865
874
000
000
106
968
714
733
497
039
000
717
449
729
000
013
000
000
971
000
580
774
854
000
592
000
457
866
549
7B4
000
000
000
000
000
103
STANDARD
TIME
CMIN)
8.
10.
13.
13.
1 6.
22.
23.
23.
26.
27.
28.
28.
29.
30.
31 .
32.
32.
33.
33.
34.
35.
35.
35.
37.
38.
39.
40.
41 .
42.
43.
43.
44.
45.
47.
50.
52.
52.
55.
63.
914
617
0c=4
353
717
41 9
078
814
22oR
0&7
0o5
743
814
005
834
5
-------
($> TITLE: DB1701-PEST
SUPELI
i t
O
Z
O
CD
CD
5"
o1
3
o
•0
>
O
EU
Z
O
N)
N>
U
cn
03
01
a
O
0)
r*
z
o
Nl
ro
w
-J
^
CT
O
X
^
_,
o
•o
0)
a
o>
CHANNEL NO: 2
PEAK PEAK
NO
1
2
3
4
5
6
7
6
9
10
1 1
12
13
14
15
16
17
13
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
3d
39
40
4 1
42
43
NAME
EPTC
BUTYLATE
AZOBEN2EN
ETHOPROP
PHORATE
PROPOXUR
TERBUFOS
FONOFOS
DI A
CARBOFURA
ATRAZINE
SIMAZINE
ALACHLOR
CYPRAZINE
METRIBUZE
CHLORPYRI
METOLACHL
MALATHlG'i
DA
PROUL
CYANAZ 1NE
TOTALS:
DETECTED PKS:
SAMPLE
RESULT
MG/L
0.
0.
0.
0.
1 .
0.
0.
5.
0.
6.
0.
0.
1 .
e.
0.
0.
i .
0.
i .
4.
0.
4.
5.
0.
0.
0.
0.
4.
4 .
4.
4.
4 .
0.
0.
3.
5.
0.
0.
4.
0.
0.
0.
0.
71 .
55
000
000
000
000
033
000
000
121
000
385
96B
000
421
288
000
000
031
000
012
815
723
968
045
000
000
000
000
966
950
834
959
929
697
000
125
085
000
000
791
000
000
000
000
146
: STANDARD
TIME
CMIN)
7.
7.
9.
10.
14.
15.
lo.
17.
28.
23.
31 .
32.
33.
34.
34.
36.
37.
38.
38.
38.
40.
40.
40.
42.
42.
44.
44.
45.
46.
47.
47.
49.
49.
50.
51 .
52.
52.
55.
57.
59.
64 .
67.
67.
265
902
145
843
965
8 16
813
820
1 12
780R
682
218
999
190
670
718
61 1
222
614
906
49 1
712
952
216
917
362
647
870
61 1
162
925
029
825
145
254
008
6o3
788
£>oS
822
504
047
623
REJECTED PK
2:27 21 AUG 19
METHOD; DWAXPEST
TIME
OFFSET
-0.045
-0.050
-0.030
-0.038
-0.031
-0.040
-0.039
-0.036
-0.024
-0.049
-0.038
-0.028
-0.030
-0.029
-0.028
-0.025
-0.031
-0.015
-0.006
-0.042
-0.032
-0.686
12
AREA
COUNTS
777
226
4752
3099
18399
519
719
83902
856
218352
147144
845
165208
20514
2238
4297
1 10965
174
570232
85275
3878
185547
249983
404
969
374
12741
37854
165051
97976
544243
30474
3912
103
62357
81585
1259
1900
170082
1086
459
1983
725
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
RRT
.25
. 28
.32
. 38
.52
.55
.58
.62
.98
.00
. 10
. 12
. 18
. 19
.21
.28
.31
.33
.34
.35
.41
. 41
.42
. 47
. 49
. 54
. 55
.59
.62
. 64
. 66
.70
. 73
.74
.78
.81
.84
.94
.00
. 08
. 24
.33
.35
SEP
CODE
BB
BB
BB
BB
BB
BB
BB
BB
BB
BB
BV
T
BV
T
T
BB
BV
T
VV
T
T
VV
VV
T
BB
BV
VB
BB
BV
VV
VV
T
T
T
BV
VV
T
BB
BB
BB
BB
BV
VB
Wl/2
(SEC)
4.55
? 4. 40
6.20
5.25
5. 45
6. 70
8.95
5.80
7.40
6.20
7. 50
? 7.50
7.85
? 8.95
10.30
11.10
7.75
?
? 13.80
12. 15
10.15
6.35
6.75
? 7. 70
6.50
6.35
7. 30
7.00
6.55
6. 70
7.90
9.60
15.35
?
8.05
7.05
7. 30
8.55
6.90
7.65
9.75
9. 15
-? 12.30
3093440
Figure 5.3c. Data report for a DB-1 column (Channel 2).
32
-------
Table 5.5. Approximate detection limits and ranges of linear response in nanograms per liter, based
on analysis of dilution series of mixed standards, and mean percent recoveries of spikes.
Pesticide
Herbicides
Alachlor (Lasso)
Atrazine (Aatrex)
Butylate (Sutan)
Cyanazine (Bladex)
EPIC (Eradicane, Eptam)
Linuron (Lorox, Linurex)
Metolachlor (Dual)
Metribuzin (Sencor, Lexone)
Pendimethalin (Prowl)
Simazine (Princep)
Insecticides
Carbofuran (Furadan)
Fonofos (Dyfonate)
Terbufos (Counter)
Detection
Limit
100
50
50
250
50
1500
250
100
50
250
200
50
100
Linear Mean Percent Recovery
Range 1983 1984 1985
>500
>500
>200
>500
nd
>5000
>250
>2500
nd
>2500
>500
>150
nd
104
86
73
98
76
87
54
80
88
89
60
76
64
69
70
79
66
80
67
65
71
74
77
57
54
33
-------
SECTION 6
RESULTS AND DISCUSSION: SEDIMENTS AND NUTRIENTS
6.1. SEDIMENT AND NUTRIENT CONCENTRATIONS
The measurement of pollutant concentrations in streams and rivers is a fundamental
component of many water quality studies. The resulting concentration data can be used to
address a variety of water quality issues. For example, the concentration data can be:
1. compared directly with water quality standards to assess ambient water
quality at the sampling site.
2. combined with flow data to calculate pollutant transport (both watershed
export and watershed loading to downstream receiving waters).
3. analyzed to assess pollutant sources, transport pathways, and processing
within the watershed and stream system. .
Since this sampling program focuses on storm runoff events, it provides detailed information
on the effects of nonpoint pollution sources on both ambient water quality and pollutant
transport. For many pollutants, such as sediment, nitrate, pesticides, and some forms of
phosphorus, the highest pollutant concentrations occur during runoff events. Some water
quality management agencies propose the establishment of high-flow water quality standards
(Wlble 1980). If such standards are applied to agriculturally derived pollutants, they would
have to take into account several of the characteristics of pollutant runoff described below.
6.1.1. Hydrograph. Sedigraph and Chemograph Patterns
One method of presenting chemical concentration data for streams and rivers and the
relationships between chemical concentrations and stream discharge is to plot both discharge
and concentrations as a function of time. Examples of such plots are shown in Figure 6.1. This
figure contains an annual hydrograph, a sedigraph for suspended solids (SS) and chemographs
for total phosphorus (TP), soluble reactive phosphorus (SRP), nitrate + nitrite-nitrogen
(NO23-N) and conductivity (conductance) for the Sandusky River at Fremont during the
1985 water year. From the annual patterns it is evident that during periods of storm runoff
events, concentrations of SS, TP and NO23-N all increase while the concentration of total
dissolved solids, as reflected in the conductivity of the samples, decreases. Comparable plots
for each station for the 1982-1985 water years are shown in Appendix I. In comparing the
Appendix I graphs, note that the concentration and discharge scales are different on each
graph. The computer program that draws the plots arbitrarily sets full scale at 110% of the
highest concentration or discharge that occurred at that station in that year.
The changes in chemical and sediment concentrations during storm events in Lake Erie
tributaries follow typical patterns (Figure 6.2) for both small watersheds (e.g., Lost Creek,
11.3 sq. km.) and the large river basins (e.g., the Maumee River, 16,395 ). During a runoff
event, stream flow increases very rapidly on the rising limb of the hydrograph, reaches a
34
-------
se
3
-S
o
CO >
» ^
O
IQ
< Q)
0) "O
CD J
-< Q)
'CD Q-
03 o
CD
3
o
tQ
3
0.0
>o
a
ui
3) -0
TOTAL P (mq/1)
0.7 1.4
2. 1
SEDIMENT (mg/1)
854 1708
2S62 0
KLOW (cf>)
7057
21172
CONDUCTANCE (umhoi) NITRATE (mg/l) SOL. REACT. P (mg/1)
0 391 782 117+ 0.0 8.5 13.0 19.5 0.00 0.10 0.20 0.29
XI
T)
o
M
CO
o
o
CL
c
£
<'
^
CD
Q.
3
CD
10
OB
m
a
-<
-------
peak value and then decreases more slowly on the falling limb of the hydrograph. Sediment
concentration peaks early in the runoff event and usually begins to decrease before the peak
discharge occurs. Advanced peaks of sediment concentration relative to peak discharge are
much more common than simultaneous or trailing peak sediment concentrations.
Simultaneous or trailing sediment peaks are occasionally observed during "compound" storm
events with multiple hydrograph peaks or when a localized storm occurs in a small portion of
a large watershed.
Since most of the phosphorus transported during storms is attached to sediment, the TP
concentrations closely follow the concentration pattern for SS. During the falling portion of
the hydrograph, however, TP concentrations do not decline as rapidly as SS concentrations.
This can be attributed both to the presence of soluble phosphorus forms, including SRP in the
streams and to increasing ratios of paniculate phosphorus to SS, as SS concentrations
decrease. The latter effect is probably due to decreasing average particle sizes (e.g.,
increasing proportions of clays) accompanying decreasing SS concentrations (Johnson and
Baker, 1982). The clay particles are typically enriched with phosphorus.
NO23-N concentrations increase during the falling limb of the hydrograph. In the study
area, most of the NO23-N enters streams via tile drainage and interflow {Logan 1978).
Water from these sources comprises a larger proportion of the total flow during the falling
limb of the hydrograph.
The concentration patterns of soluble herbicides, such as atrazine, are distinct from both
the sediments and the nitrates. As discussed further in Section 7.2.1, atrazine apparently
moves off the fields with surface runoff water, but with different timing than for sediments.
One hypothesis for this difference is that for SS, there is apparently a "pool" of highly
erodible material on the soil surface. This material largely moves off fields with the early
portions of the surface runoff water. Subequent surface water runoff has much lower
sediment concentration. However, the surface runoff water continuously interacts with the
upper zone of the soil surface, dissolving materials, such as pesticides, which have
accumulated therein. The kinetics of dissolution may account for a relatively slow "leaching"
of pesticides out of this surface layer of soil, and the resulting broad peaks of pesticide
chemographs.
6.1.2. Concentration-Flow Relationships
Water quality data for rivers are often plotted as scattergrams showing the
concentrations of various parameters in relationship to stream flow. In Figures 6.3 and 6.4,
the data from Figure 6.1 (i.e., the Sandusky River at Fremont for the 1985 water year) are
replotted as scattergrams, using linear scales in Figure 6.3 and Iog10 scales in Figure 6.4.
Log transformations of this type of data are often used to spread the data out from the left and
bottom axes of the graphs. These data illustrate the large amount of "scatter" associated with
the concentrations of material derived from nonpoint sources in streams and rivers. Even
with this scatter, it is evident that for SS, TP and NO23-N, concentrations tend to increase
with increasing discharge, while conductivity tends to decrease with increasing discharge.
36
-------
CO
9. 10.
JUNE
14.
14.
Figure 6.2. Typical pattern of concentration changes during a runoff event, as illustrated in June 1981 at the Honey Creek
station near Melmore, Ohio. Solid line represents the hydrograph. Connected diamonds represent' A SS- B TP-
C. N023-N; D. atrazine. '
-------
Many factors contribute to the scatter in these plots. Storm discharge values less than the
peak discharge occur twice during each storm, once on the rising limb of the hydrograph and
once on the falling limb. The corresponding sediment and nutrient concentrations differ
greatly on the rising and falling limbs of the hydrograph. Furthermore, discharge values
which are near the peak discharge for small storms also occur near the beginning of the
rising limb and ending of the falling limb of the hydrograph for large storms, again yielding
large differences in concentrations for that discharge. Storms with the same peak discharge
can have very different concentrations depending on the season, on the rainfall intensities, on
the ground cover conditions and on antecedent soil moisture conditions (Baker 1984).
In order to characterize chemical water quality from the standpoint of either ambient
water quality or loading, it is necessary to adequately characterize the "cloud" of points
illustrated in Figures 6.3 and 6.4. It should be noted that, for a particular station, the
characteristics of the "cloud" change from year to year in relation to weather conditions.
Furthermore, documenting improvements in water quality requires detecting significant
trends in the characteristics of these "clouds".
6.1.3. Frequency Histograms
The distribution of pollutant concentrations in streams can also be presented in the form
of frequency histograms. Since the sampling frequency varies with stream flow, biases
associated with the stratified sampling need to be removed from the data. Thus, rather than
plot the number of samples falling within each concentration range, the percentage of time
during which concentrations fall within each concentration range is plotted. In Figure 6.5,
frequency histograms for the concentrations of SS, TP, and N023-N, are shown for the
Sandusky River at Fremont using all of the samples collected during the 1982-1985 water
years. It is evident that the frequency with which various concentrations occur in streams is
not normally distributed.
In Figure 6.6 frequency histograms for log transformed concentration data are shown.
While the histogram for SS (Figure 6.6) appears "normal" following log transformation, the
histograms for TP and NO23-N do not.
6.1.4. Time Weighted and Flux Weighted Mean Concentrations
If the concentrations of a chemical in a stream (or in a drinking water supply) were
measured continuously during some time interval, the associated average concentration
during that time interval provides one way to characterize the exposure of organisms living
in that stream (or of people drinking that water) to that chemical. For most chemicals of
interest, concentrations are not measured continuously. Instead, they are measured either at
fixed intervals (daily, weekly, monthly, annually, etc.) or according to some stratified
sampling program designed to more efficiently achieve some objective. In our studies,
sampling frequencies are increased during periods of high flows in order to more accurately
measure material loading. Since nonpoint source pollutant concentrations tend to be higher
during runoff events, this same stratified sampling program provides more detailed
information during the periods when concentrations tend to be highest.
38
-------
The procedures used to estimate the average concentration differ slightly, depending on
whether a fixed interval or a stratified sampling program was utilized. Fixed interval
concentration measurements can be directly averaged since each sample characterizes the
stream for the same length of time. The accuracy of the calculated average concentration
depends on how well the selected frequency of sampling characterizes the actual occurrence of
the chemical in the stream. For a stratified sampling program, individual samples do not
characterize the stream for equal lengths of time. Thus, to estimate the average
concentration, each sample has to be "weighted" according to the length of time it is used to
represent the stream system. The resulting "time weighted mean concentration" (TWMC)
provides an estimate of the average concentration in which biases introduced by the stratified
sampling program (in this case, more frequent sampling during periods of high
concentration) are removed. The TWMC is calculated using the following formula:
I C.t.
TWMC = —
where
Cj is the chemical concentration of the itn sample and
tj is the duration of time that the i*n sample is used to characterize
the stream concentration. It is equal to 1/2 the time interval between
the samples immediately proceeding and following the ith sample.
Often "average concentrations" in a stream are intended to characterize the export of
material from the stream system rather than the average exposures within the stream. In
this case, the desired average concentration would be the concentration observed if all of the
stream discharge were collected over the time period of interest and the resulting
concentration was measured. In practice, this average concentration is estimated by
weighting the individual samples by their associated flows. The resulting average
concentration is referred to as a flow (or flux) weighted mean concentration. Where
stratified sampling is used, it is necessary to also weight individual samples by their
associated time period. We refer to the resulting average concentration as the "flux weighted
mean concentration" (FWMC). It is calculated as follows:
^ citicli Total Load
FWMC = -
t.q. Total Discharge
where
q, is the instantaneous discharge at the time of the
itn sample.
39
-------
o
in
ID.
*.
B
+ tj * * *+
N
o
VI
oc.
o
Q.
in
* §
o Q-
4000
8000 12000
FLOW (CFS)
16000 20000
4000 8000 12000
FLOW (CFS)
16000
in
o
ui
o
CONDUCT
2o8>00
Figure 6.3. Scattergrams of SS, nutrient and conductivity concentrations in relationship to stream discharge for the 1985
water year at the Sandusky River station. A. SS; B. TP; C. NO23-N; D. Conductivity.
-------
to
0
0
«
UJ
I-
ce
O
0
o
?•
+ HH-I-
0.0 1.0 2.0 3.0
LOG FLOW (CFS)
B
-? 8
4.0 5.00.0 1.0 2.0 3.0
LOG FLOW (CFS)
4. o
o
o
-------
Sandusky R. - Concentration Histograms
40 -
4)
i= 30 -
"5
| 20-
u
o.
10 -
0 -
CO
CO
co
>' '
...
i ' ' •
CO
CM
CM
CM
CM
250
a>
u
40
20 -
10 -
CO
C-3
CM
CM
d
CO
I/)
CM
CM
0> .450
50
§
u
0)
Q.
40 -
30-
20 -
10-
in
CM
CM
CM
CM
3.0 7.0 11.0 15.0
Nitrate + Nitrite Cone. mg/L
>18.0
Figure 6.5. Histograms illustrating the percentage of time concentrations fall within
given ranges. Data from the Sandusky River, 1982-1985 water years.
A. SS; B. TP; C. NO23-N.
42
-------
Sandusky R. - Log Concentration Histograms
Percent of T
S
30-
20-
10 -
Q -
£
r— i
o
I
in
CM
at
CM
at
o
0>
^—
CM
0
Cfl
' V
* : ..
CM
*—
CM
• •" 1 '-
in
en
o
— — — ,- . o
1 — I ° °
0.17 0.84 1.50 2.17 2.84
Suspended Solids log cone., mg/L
>3.33
ou -
40-
30-
20 -
10-
0 -
T
CM
CO
CO
o>
CM
CM
"*" °* m
o d I 1
* ;
•^
v:
v' \
' • ^ *•
en
u>
O)
^~
CM
...'. * "
' I 1
I I
< -t.6 -1.3 -0.9 -0.5
Total Phosphorus log cone., mg/L
> -0.2
o>
u
30 -
20 -
10-
.
0 -
,*_
•
f5
on"
CO
CO
,
1.4
Nitrate + Nitrite log cone., mg/L
Figure 6.6. Histograms illustrating the percentage of time concentrations (log
transformed data) fall within given ranges. A. SS; B. TP; C. NO23-N.
43
-------
It should be noted that the FWMC is equivalent to the total load divided by the total
discharge for the period of interest.
The TWMC's and the FWMC's for nutrients and sediments at each of the transport stations
for the 1982-1985 water years are shown in Table 6.1. It is evident from Table 6.1 that
there is considerable difference between the TWMC's and the FWMC's. For sediments and TP
the annual FWMC is often 2 or more times the TWMC. Ratios of FWMC to TWMC (i.e.,
FWMC/TWMC) greater than 1 indicate that, for the overall data set, the concentrations tend
to increase with increasing discharge. Increasing concentrations with increasing discharge
are characteristic of materials derived from the surface runoff component (and the tile
drainage component) of nonpoint source pollution.
Where there are significant point sources of a pollutant, the concentrations of that
pollutant tend to decrease with increasing stream flow and the accompanying increase in
dilution of the point source input. This results in FWMC to TWMC ratios <1.0. For the
Cuyahoga River the TWMC's of SRP are greater than the FWMC's of SRP suggesting that point
sources are a significant part of the SRP input into that river.
The FWMC/TWMC ratios also reflect the relative contributions of surface runoff water to
groundwater for major rivers. For chloride and conductivity, TWMC's are greater than
FWMC's (Table 6.2). Runoff water from land surfaces generally has much lower chloride
levels and conductivity than does water derived from interflow or groundwater. The latter
sources contribute most of the water present in streams during low flow conditions.
The differences between TWMC's and FWMC's are large and important. Unfortunately, in
many studies, the distinction between TWMC's and FWMC's are ignored. For example, in the
modelling studies conducted by Resources for the Future (RFF) (Gianessi et al 1986) as a
basis for establishing national pollution control policies for governmental agencies, sediment
and nutrient concentrations are estimated from loading and discharge estimates (i.e., they are
FWMC's) but the same concentration values are interpreted as reflecting average ambient
water quality concentrations (i.e., as TWMC's). While the RFF model attempts to include the
effects of in-stream material processing, the failure to distinguish between TWMC's and
FWMC's should raise significant questions regarding the adequacy of the model as a basis for
even "broad brush" policy development.
6.1.5. Concentration Exceedency Curves
With respect to ambient water quality, information regarding peak pollutant
concentrations may be more important than TWMC's. Also it may be especially important to
know the duration of time a pollutant exceeds some critical value. While chemographs such as
those in Figure 6.1 and Appendix I do indicate peak concentrations, concentration exceedency
curves and tables are more useful in assessing the duration of various concentration ranges.
In Figure 6.7, the same data contained in Figure 6.1 are plotted in the form of concentration
exceedency curves. Again, the individual samples are time weighted to remove bias associated
with stratified sampling.
One use of concentration exceedency curves is to illustrate the duration of time
particular concentrations (such as water quality standard) are exceeded. For example, in
44
-------
Table 6.1. Comparisons of time weighted mean concentrations (TWMC) and flux weighted mean concentrations (FWMC) for sediments and nutrients
at Lake Erie Basin transport stations.
01
Station
Maumee
Sandusky
Cuyahoga
Raisin
Honey Cr.
Upper
Honey Cr.
Rock Cr.
Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1983
1984
1985
SS, mg/L
TWMC FWMC
99.5
85.6
78.5
—
96.7
48.6
72.6
72.4
141.6
78.4
71.1
85.4
40.7
44.2
37.6
33.1
82.2
45.4
48.0
37.6
25.8
41.1
48.6
29.4
44.6
44.3
39.9
180
199
183
205
283
164
144
178
256
178
158
269
49
91
77
86
252
133
127
125
...
175
212
190
271
249
183
TP, mg/L
TWMC FWMC
0.280
0.261
0.262
...
0.221
0.144
0.233
0.190
0.433
0.392
0.396
0.391
0.183
0.176
0.172
0.166
0.211
0.174
0.212
0.169
0.100
0.114
0.157
0.092
0.132
0.147
0.123
0.396
0.438
0.452
0.434
0.460
0.362
0.399
0.351
0.486
0.419
0.407
0.527
0.149
0.256
0.229
0.248
0.441
0.355
0.375
0.348
0.337
0.447
0.388
0.436
0.466
0.341
SRP, mg/L*
TWMC FWMC
0.075
0.058
0.059
...
0.049
0.035
0.048
...
0.156
0.167
0.171
...
0.051
0.050
0.043
...
0.056
0.058
0.066
...
0.028
0.028
0.043
...
0.026
0.032
—
0.081
0.060
0.066
...
0.065
0.055
0.084
...
0.103
0.111
0.102
...
0.036
0.045
0.039
...
0.059
0.056
0.075
...
0.058
0.085
...
0.036
0.045
—
NO23-N, mg/L
TWMC FWMC
3.49
3.68
4.11
4.42
3.02
2.99
3.54
4.30
2.52
2.65
2.41
2.59
1.94
2.83
2.61
2.81
3.83
4.10
4.49
5.22
2.52
3.12
2.60
3.04
2.65
2.13
2.37
3.99
5.52
6.03
5.52
3.59
5.57
3.74
5.74
1.83
1.89
1.74
1.99
1.54
4.07
4.22
4.23
3.77
5.72
4.20
6.35
5.64
3.96
5.77
6.07
2.61
3.86
TKN,
TWMC
1.33
1.35
1.37
1.46
1.13
0.87
1.13
1.03
1.33
1.13
1.36
1.28
0.93
0.95
0.98
0.95
1.15
0.95
1.05
0.99
0.72
0.75
0.79
0.59
0.75
0.80
0.73
mg/L
FWMC
1.62
1.89
1.86
1.73
1.84
1.52
1.60
1.45
1.46
1.21
1.41
1.60
0.77
1.26
1.27
1.30
1.87
1.67
1.54
1.64
1.81
1.76
1.51
2.15
1.91
1.53
* No SRP data were obtained for the 1985 water year.
-------
Table 6.2. Comparison of TWMC's and FWMC's for chloride and conductivity.
Station
Maumee R.
Sandusky R.
Cuyahoga R.
Raisin R.
Honey Cr.
Upper Honey Cr.
Rock Cr.
Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1983
1984
1985
Chloride
TWMC
35.0
40.5
41.5
44.9
36.1
42.2
29.3
40.4
103.3
94.0
107.6
117.5
37.5
37.7
43.1
44.7
24.9
28.0
23.2
30.2
28.8
29.0
23.9
31.6
32.2
27.4
36.7
mg/L
FWMC
24.8
27.4
24.8
28.4
21.7
30.1
20.3
33.6
94.5
84.5
96.0
92.0
21.8
30.9
31.8
31.3
17.1
21.6
15.0
20.8
24.0
26.4
16.0
20.6
19.5
14.0
23.9
Conductivity
TWMC
573.3
611.6
604.1
630.0
640.9
736.6
555.0
685.7
752.8
760.8
793.8
816.2
638.6
668.5
697.0
707.0
557.2
607.2
533.5
616.2
657.6
658.7
581.1
691.9
743.4
659.7
769.6
(j. mhos/cm
FWMC
456.1
523.2
464.7
496.0
426.2
588.6
417.3
600.1
655.6
674.4
684.8
709.7
432.7
588.3
573.9
542.5
341.8
447.7
331.5
388.9
452.7
509.3
353.0
390.1
462.4
312.6
452.8
46
-------
o.'
T>. 00
K-
N03 data
14. Jt 28.97 42.81 97.14 71.43 89.71
Percent of time concentration li exceeded
100.00
42.88 97.14
concent rat ton
71.43 89.71
le exceeded
100.00
g TP data
14.2* 28.97 42.88 97.14 71.43 89.71
Percent of time concentration It exceeded
eg
o
o
Cond data
14.39 28.37 43 86 37.14 71.43 83 71
Percent of time concentration It exceeded
Figure 6.7. Concentration exceedency curves for SS(A), TP(B), NO23-N(C), and Conductivity(D) at the Sandusky River
station during the 1985 water year.
-------
laeee.
1000...
01
O
M
8
UJ
a
UJ
a.
108...
MAUMEE RIVER
SANDUSKY RIVER
UPPER HONEY CREEK
HONEY CREEK
I .
49. 58. 60.
DURATION 00
96. iee.
Figure 6.8. Concentration exceedency curves for suspended solids at the Maumee,
Sandusky River, Upper Honey Creek and Honey Creek-Melmore stations. Data for
the period of record at each station.
8. 18. 28. 38. -48. 58. 68. 78. 88. 98. 100.
DURATION CO
Figure 6.9. Concentration exceedency curves for N023-N at the Honey Creek-
Melmore and Maumee River stations. Data for the period of record at each station.
48
-------
1985 the NO23-N standard of 10 mg/L was exceeded in the Sandusky River for about 11% of
the time. Concentration exceedency graphs can also be used to compare the concentration
patterns for different rivers. In Figure 6.8 concentration exceedency curves for the
suspended solids concentrations (log scale) are shown for four of the river transport
stations. It is clearly evident in Figure 6.8 that as the watershed size decreases,
(Maumee>Sandusky>Honey Creek), the suspended solids concentrations are significantly
lower for much of the time. The curves in Figure 6.8 do not reflect the fact that the peak
sediment concentrations are higher for small watersheds than for large watersheds.
In Figure 6.9, NO23-N concentration exceedency curves are shown for the Maumee River
and for Honey Creek. Honey Creek, the smaller watershed, has higher peak concentrations,
but slightly lower ambient concentrations for much of the rest of the time.
Concentration exceedency data can also be presented in the form of exceedency tables. In
such tables the values listed can show either concentrations exceeded for fixed percentages of
time or the percentages of time particular concentrations are exceeded. In Tables 6.3-6.5,
the concentrations of SS, TP and N023-N that are exceeded fixed percentages of time are
shown for seven of the transport stations for the 1982-1985 water years. The stations are
listed in the sequence of decreasing watershed size. The TWMC and the FWMC for the combined
1982-1985 period are also shown for each parameter and period.
The data in Tables 6.3-6.5 provide an interesting example of the effects of watershed size
on pollutant concentration patterns. The FWMC's of SS and TP are rather similar for all of
the agricultural watersheds except for the River Raisin, which has lower concentrations. The
TWMC's decrease as watershed size decreases. The concentrations exceeded 50% of the time
correspond to the median concentrations. Note that the median values are lower than the
TWMC's. Furthermore, these medians decrease even more than the TWMC's as watershed size
decreases. The concentration patterns become skewed more and more to the left as watershed
size decreases.
6.1.6. Seasonal Variations in Flux Weighted Mean Concentrations
The long term records (7-11 years) for the Maumee, Sandusky and Honey Creek
watersheds, allow analyses of the seasonal aspects of pollutant concentrations in river
systems. The FWMC's for SS, TP, SRP and NO23-N during the fall (Oct-Dec), winter
(Jan-March), spring (April-June), and summer (July-Sept) periods are shown in Table
6.6. For SS, the highest concentrations occur in the spring period. The differences between
the spring and the fall/winter concentrations are much larger for Honey Creek than for the
Maumee River. Again, these differences are probably associated with watershed size. As
watershed size decreases the peak sediment concentrations more closely coincide with the
peak periods of soil erosion by high intensity spring storms which occur when crop cover is
minimal. As watershed size increases, sediment transport is more closely associated with the
movement of large storm runoff events through the river systems that wash out sediment
previously deposited in the channel system. Many of the large runoff events occur in the
winter.
While watershed size seems to have a significant effect on seasonal concentration patterns
of SS and sediment-associated pollutants such as TP, watershed size has much less of an
49
-------
en
o
Table 6.3. Concentrations of suspended solids (mg/L) exceeded fixed percentages of time for Lake Erie river transport
during the 1982-1985 water years.
% of time listed
cone, were equaled Maumee
or exceeded 16,395
0.2
0.5
1 .0
2.0
5.0
10.0
25.0
50.0
TWMC
FWMC
1045
798
634
462
286
184
85
53
87.0
197.0
Sampling station
Sandusky Raisin
3,240 2,699
1542
1146
744
504
253
1 46
68
33
72.2
181.9
ouopo i
532
41 4
305
203
1 18
70
39
26
38.7
82.1
i and associated
Cuyahoga
1,831
ded solids, mg
2716
1289
954
665
329
176
67
30
91.9
209.3
drainage area
Honey Cr.
386
/i
/!_ -------
1 196
81 1
538
367
197
1 10
45
22
53.0
159.8
(Km2)
Rock Cr.
88.0
892
680
481
370
1 73
79
31
1 8
42.7
240.8
Upper
Honey Cr.
44.0
945
592
385
258
125
71
34
1 6
38.0
176.4
Total Monitored
time (hrs.) 33,349
31,145
26,527
31 ,705
33,998
23,419
25,591
-------
Table 6.4. Concentrations of total phosphorus (mg/L) exceeded fixed percentages of time for Lake Erie river transport
during the 1982-1985 water years.
% of time listed
cone, were equaled Maumee
or exceeded 16,395
0.2
0.5
1.0
2.0
5.0
10.0
25.0
50.0
TWMC
FWMC
1.194
1.090
0.971
0.812
0.577
0.449
0.282
0.201
0.257
0.432
Sa
Sandusky
3,240
1 .712
1.382
0.912
0.725
0.529
0.376
0.226
0.134
0.196
0.388
mpling station and associated drainage area
Raisin Cuyahoga Honey Cr.
2,699 1,831 386
- total phosphorus concentrations, mg/L -
0.905
0.798
0.596
0.457
0.321
0.255
0.198
0.158
0.173
0.241
2.571
1 .625
1.260
1.086
0.722
0.577
0.452
0.348
0.402
0.452
1.557
1.176
0.873
0.654
0.485
0.376
0.218
0.142
0.191
0.381
(Km2)
Rock Cr.
88.0
1.324
0.949
0.780
0.622
0.434
0.271
0.140
0.090
0.134
0.433
Upper
Honey Cr.
44.0
1.578
1.014
0.819
0.598
0.382
0.252
0.116
0.070
0.118
0.395
Total Monitored
time (hrs.) 33,349
31,145
26,527
31 ,705
33,998
23,419
25,591
-------
en
Table 6.5. Concentrations of nitrate plus nitrite-nitrogen (mg/L) exceeded fixed percentages of time for Lake Erie
river transport during the 1982-1985 water years.
% of time listed
cone, were equaled Maumee
or exceeded 16,395
0.2
0.5
1.0
2.0
5.0
10.0
25.0
50.0
TWMC
FWMC
17.3
15.9
14.0
11.0
8.4
7.1
6.0
4.1
3.93
5.29
Sampling station £
Sandusky Raisin
3,240 2,699
17.7
14.9
13.6
12.2
9.5
7.0
5.0
3.2
3.48
4.22
i ii LI CILG p
12.0
10.3
8.4
7.2
6.2
5.4
3.7
2.1
2.61
3.66
md associated
Cuyahoga
1 ,831
lus nitrite-nitre
7.2
6.3
6.1
5.5
4.8
4.3
3.2
2.3
2.54
1.85
drainage area (Km2)
Honey Cr. Rock Cr.
386 88.0
\fiQn mn/l
)y CM, i ily/L - -
25.4
20.5
17.8
14,4
9.5
7.0
5.2
3.8
4.42
4.57
16.0
14.9
12.7
9.4
6.5
5.1
3.1
1.8
2.35
3.28
Upper
Honey Cr.
44.0
21.0
19.4
16.2
9.7
7.4
5.8
4.1
2.4
2.87
4.55
Total Monitored
time (hrs.) 33,349
31,145
26,527
31,705
33,998
23,419
25,591
-------
Table 6.6. Seasonal and annual flux weighted mean concentrations of sediments and nutrients for
the period of record at long-term transport stations.
Watershed
Flux weighted mean concentrations (mg/L)
Oct-Dec Jan-Mar Apr-Jun Jul-Sep
Overall
Honey Creek
Sandusky River
Maumee River
Honey Creek
Sandusky River
Maumee River
Honey Creek
Sandusky River
Maumee River
72
125
179
0.294
0.332
0.445
0.088
0.083
0.092
Suspended Solids
133 381 221
206 409 226
205 272 140
Total Phosphorus
0.346 0.598 0.407
0.444 0.603 0.402
0.473 0.531 0.360
Soluble Reactive Phosphorus
0.074 0.060 0.098
0.093 0.062 0.085
0.095 0.071 0.092
Nitrate + Nitrite-Nitrogen
203
249
216
0.417
0.464
0.479
0.074
0.082
0.087
Honey Creek
Sandusky River
Maumee River
4.84
4.87
5.25
3.85
3.73
3.76
6.16
6.19
5.87
4.67
3.35
4.39
4.82
4.57
4.82
interaction with the seasonal concentrations of soluble constituents. For all of the
watersheds, NO23-N concentrations are highest in the spring but the ratio of spring
concentrations to the concentrations in other seasons is similar. Whether the high spring
concentrations of N023-N are associated with the spring application of nitrogen fertilizers
or the warming of the soil and subsequent increased nitrification by soil bacteria is
uncertain.
For all three watersheds, SRP concentrations were lowest in the spring. The seasonal
variation in SRP may reflect differences in the amounts of SRP processing within the stream
system, due to biological activity and/or sediment adsorption.
6.1.7. Effects of Watershed Size on Peak Pollutant Concentrations
Plots of concentration exceedency curves allow convenient comparisons of pollutant
concentrations over much of the concentration and duration range. However, comparison of
peak concentrations on concentration exceedency graphs is more difficult (see Figure 6.8).
In Table 6.7 the peak concentration of SS and NO23-N for individual storm events are shown
for four watersheds, ranging in size from 11.3 km2 (Lost Creek) to 16,400 km2 (Maumee
53
-------
River). It is evident that the peak sediment concentrations in Lost Creek are much higher
than the peak concentrations in the Maumee River. Peak concentrations for the other
watersheds are intermediate in size. In comparing the peak sediment concentrations in Lost
Creek with those observed in runoff from individual fields, the Lost Creek values are low. In
the Four Mile Creek Watershed study in Iowa (Johnson and Baker 1982), peak sediment
concentrations in storm runoff from a 5 ha and a 6 ha plot were an order of magnitude higher
than those observed in Lost Creek.
It is likely that both sediment deposition and water routing contribute to the decreasing
peak sediment concentrations with increasing watershed size. Comparison of the sedigraphs
with the hydrographs (Figures 6.1 and 6.2) indicates that the distribution of high sediment
concentrations within the hydrograph is largely confined to the front portion of the storm. As
storm waters converge from various tributaries into a larger stream, they will be in
different phases of their own hydrographs, thereby providing considerable water with low
sediment concentration to mix with and dilute the water with high sediment concentrations.
In the case of nitrates, the peak concentrations are also higher in smaller watersheds
than in larger watersheds. However, for nitrates, the ratios of peak concentrations for small
to large watersheds are not nearly so large as similar ratios for sediments. This may be due
to the fact that nitrates are distributed more broadly within the hydrograph than are
sediments (Figures 6.1 and 6.2). Consequently, water routing through the channel system is
accompanied by less dilution of nitrates.
6.1.8. Nitrate Contamination of Surface Waters and Drinking Waters
In northwestern Ohio, as elsewhere in the Midwest, several municipalities withdraw
water for public water supplies directly from rivers. Since conventional water treatment
procedures do not remove nitrates, the nitrate concentrations present in the rivers are also
present in the finished water supplies. The nitrate concentrations in Lake Erie tributaries
frequently exceed the drinking water standard of 10 mg/L nitrate-nitrogen, usually during
the May-July period. In the case of the Sandusky River, which supplies drinking water for
both Fremont and Tiffin, Ohio, the nitrate standard has been exceeded every year since the
onset of our monitoring program in 1974. In 1985, the standard was exceeded continuously
for 30 days.
For the period of record in the Sandusky River, nitrates exceeded the standard 4.1% of
the time, but since these occurrences were always in the months of May, June or July, the
standard was exceeded 16% of the time during these months. For the Sandusky, nitrates were
in the range of 7-10 mg/L for about 12% of the time. If conservation tillage increases
infiltration and, consequently, the proportion of stream water derived from tile effluents, it
is likely that the percentage of time nitrates exceed the drinking water standard will
increase.
6.1.9. Concentration Patterns for the New York Rivers
As was mentioned in Section 5.2, the sampling program for the New York tributaries is
less dense than that for the Ohio rivers, and probably characterizes the important high-flow
periods less adequately, for reasons discussed in that section. The average number of samples
taken yearly on these rivers is about 50, as compared with 300 to 500 on the Ohio
54
-------
Table 6.7. Peak suspended sediment and nitrate + nitrite-N concentrations observed
during individual storm runoff events of the 1982,1983 and 1984 water years in
northwest Ohio rivers.
Watershed
Lost Creek
1 1 .3 km2
Honey Creek
386 km2
Sandusky River
3,240 km2
Maumee River
16,395km2
Suspended Solids
Date mg/L
820330
830610
820527
830615
840422
830710
820710
820715
840414
820719
820703
820528
820629
820703
820331
820523
820312
840422
820528
840423
820401
820317
830703
840626
820105
840427
820529
13,744
6,500
4,992
4,376
4,148
3,935
3,825
3,690
3,625
3,316
3,078
5,238
4,507
2,161
1,681
1,600
1,241
1,196
2,037
1,566
1,437
1,417
1,171
1,146
1,694
1,067
1,045
Nitrate + Nitrite-N
Date mg/L
830607
820523
830629
840915
820528
830702
820618
830703
840708
840713
820529
820525
820619
830629
820529
840710
820706
820528
830702
831113
840525
820607
23.6
22.6
19.0
19.0
16.2
15.5
28.1
20.1
19.3
18.1
15.8
14.8
15.7
12.9
12.2
12.1
11.5
12.3
11.4
10.8
10.6
10.3
55
-------
tributaries. While these data are less dense than we would wish, they still provide some
indication of the concentrations which are characteristic of the rivers. Table 6.8 compares
the TWMC's and the FWMC's for the New York tributaries. Flow data can be found in Table
5.1.
A comparison of data for the New York rivers with data (Tables 6.1 and 6.2) for the
Sandusky and Maumee Rivers, which are comparable in size, suggests that:
1. the Genesee has comparable SS and Cond, high Cl, lower TP and SRP, and
much lower N023-N and TKN. The difference in comparability of Cond and
Cl suggests that the major ion composition of these two waters is
significantly different.
2. The Oswego has higher Cond, much higher Cl, and much lower SS, TP, SRP,
NO23-N, and TKN concentrations.
3. The Black has consistently much lower concentrations of all parameters.
Comparison of the TWMC's with the FWMC's suggests that the New York tributaries as a
group respond less to runoff events with changes in concentration than do the Ohio tributaries
to Lake Erie. Of the three, the Genesee seems most event-responsive, the Black is
intermediate, showing responses only in SS and TP, and the Oswego is the most stable, with
only SS concentrations suggesting event responsiveness. These relationships between the
three are consistent with their relative sizes and with the relatively low level of agriculture
in the Black River watershed.
6.2. SEDIMENT AND NUTRIENT LOADING IN LAKE ERIE TRIBUTARIES
6.2.1. Loading Calculations
Sampling programs of the type underway in these studies allow a direct calculation of
nutrient and sediment loading. These calculations are similar to the mid-interval technique
that the U.S. Geological Survey uses to calculate sediment loads at daily sediment stations
(Porterfield 1972). The automatic samplers are set to collect "on the hour," i.e., at 0100,
0700, 1300, and 1900 hours. Where more frequent samples are collected during storm
events, the times of sample collection are listed by a printer interfaced to the sampler. The
USGS provides hourly gauge height data in the form of provisional reports for each station.
The gauge height at the time of sample collection is added to our data file for each sample. A
rating table, relating gauge height to discharge, is also provided by the USGS and stored on
our computer for each station. The rating table is used, together with the gauge height
information, to determine the instantaneous stream discharge at the time of sample
collection. On occasions when the stage recording equipment fails, the USGS estimates mean
daily flows based on relationships to adjacent stream gauges. These estimated mean daily
flows appear in the U.S.G.S. Water Resources Data for each state and water year are used in
our calculations when gauge height data are unavailable.
56
-------
Table 6.8. Time weighted mean concentrations (TWMC) and flux weighted mean concentrations (FWMC) for
the New York tributaries to Lake Ontario. In the calculations, each sample was allowed to represent up to
200 hours of time. See text for a discussion of the way we determine how much time each sample represents.
Parameter
SS, mg/L
TP, mg/L
SRP, mg/L
NO23-N, mg/L
TKN, mg/L
Cl, mg/L
Conductivity,
|imhos/cm
Year
1982
1983
1984
1985
Overall
1982
1983
1984
1985
Overall
1982
1983
1984
1985
Overall
1982
1983
1984
1985
Overall
1982
1983
1984
1985
Overall
1982
1983
1984
1985
Overall
1982
1983
1984
1985
Overall
Genesee
TWMC FWMC
125.1
49.3
196.4
68.6
123.3
0.141
0.064
0.193
0.094
0.136
0.016
0.007
0.005
<0.000>
0.008
1.08
1.07
1.38
1.10
1.14
0.610
0.402
0.707
0.642
0.620
57.5
70.0
48.0
86.1
63.1
544.4
610.8
483.9
718.4
579.1
230.7
62.8
254.5
162.6
215.1
0.227
0.073
0.248
0.175
0.214
0.016
0.007
0.006
<0.000>
0.008
1.16
1.05
1.35
1.19
1.21
0.763
0.425
0.801
0.822
0.758
42.7
64.4
41.0
65.4
47.5
447.1
571.8
434.7
594.6
474.9
Oswego
TWMC FWMC
9.84
13.75
15.44
12.28
13.00
0.074
0.077
0.071
0.077
0.075
0.027
0.017
0.004
0.004
0.014
0.768
0.636
0.752
0.463
0.649
0.774
0.727
0.626
0.841
0.740
141.1
197.7
148.6
357.6
207.4
864
1141
894
1480
1091
9.52
20.06
17.42
12.06
15.70
0.072
0.074
0.071
0.074
0.072
0.026
0.011
0.003
0.005
0.013
0.787
0.744
0.794
0.487
0.754
0.781
0.751
0.635
0.827
0.731
128.4
136.6
125.7
335.1
141.6
801
877
798
1423
859
Black
TWMC FWMC
6.79
10.60
11.83
6.62
8.75
0.032
0.036
0.040
0.018
0.032
0.004
0.004
0.001
<0.000>
0.002
0.482
0.389
0.422
0.476
0.421
0.468
0.420
0.340
0.310
0.392
2.41
2.88
2.44
2.67
2.55
94.6
108.9
94.9
76.9
97.2
15.22
16.97
17.00
8.86
14.05
0.040
0.050
0.051
0.021
0.040
0.003
0.005
0.003
<0.000>
0.002
0.528
0.438
0.484
0.509
0.464
0.477
0.509
0.380
0.350
0.424
1.95
2.81
2.45
2.53
2.33
88.8
109.1
93.9
73.3
93.0
57
-------
The instantaneous flux of each nutrient or sediment is calculated as the product of the
sample concentration times the instantaneous discharge. This instantaneous flux is assumed to
characterize the river transport for a specific time interval associated with that sample.
This time interval (or time multiplier) is equivalent to one-half the time interval between
that sample and the preceeding sample plus one-half the time interval between that sample
and the following sample. The time interval that any sample can be used to characterize the
loading rate can be limited to a particular value. For our nutrient and sediment loading
calculations we usually limit the maximum time interval to 24 hours. Multiplying the
instantaneous flux for each sample by the time interval for each sample gives a total load for
the time period associated with that sample. Summing the total loads for all the individual
samples yields the total load for the time period covered by the sampling program. The
formula for the load calculation is:
Total Load = £ c.t.q
i i M
where
Cj = concentration of the itn sample
qj = instantaneous discharge at the time of collection of the itn sample
tj = is the time interval associated with the ith sample
It corresponds to 1/2 the time interval between the samples
immediately preceeding and following the itn sample.
Since the loading calculations described above are based on provisional hourly stage data
supplied by the USGS rather than on final USGS discharge data, the loading values obtained by
the above techniques are adjusted to the final USGS discharge data as described below. These
adjustments are done for the reporting of monthly and annual loads (See Table 6.10 and
Appendix I). The adjustments also allow corrections for time intervals not characterized by
instantaneous discharge data or the chemical sampling program, due to breakdown in the
pumping system, automatic samplers, or analytical systems.
Table 6.9 consists of a computer printout from the program used for adjusting monthly
and annual loads to final USGS discharge data. In this case the printout is for total phosphorus
loading from the Maumee River during the 1984 water year. The program is run separately
for each parameter, each water year and each station. The program calculates an observed
total load for each month using the sampling program for that month, and the instantaneous
discharges as described above. For each month the number of samples (N), the flux weighted
mean concentration (FWMC), sum of the time multipliers, (cumulative time) the total
observed discharge (observed flow), and the total load (observed flux) is listed. Water year
totals for the number of samples analyzed, the cumulative time, the observed flow and the
observed flux are also shown. An observed flux weighted mean for the water year, obtained by
dividing the total observed load by the total observed flow, is also listed.
58
-------
Final USGS monthly discharges, as presented in the Water Resources Data series for each
state and water year, are stored in data files accessed by the program. These USGS flows for
each month, along with the ratio of the USGS flow to the observed flow for that month are also
listed in the program printouts. The program then multiplies the observed flux by the flow
ratio yielding a calculated (or adjusted) flux for each month. For months where the flow ratio
is >1.5 and the USGS monthly flow is 10% or more of the USGS annual discharge, the
suitability of the observed FWMC for that month is subjectively assessed. The assessment
involves comparison with the FWMC for that particular month over the entire period of
record. Depending on the extent of missing flow data (and associated samples), the observed
FWMC is either replaced by or averaged with the FWMC for that month from the period of
record. The revised FWMC is manually multiplied by the USGS flow for that month to produce
a revised calculated monthly flux. The calculated monthly fluxes, including any manual
revisions, are added to provide a calculated flux for the water year. This calculated value
represents the annual load for that station as presented in this report (e.g. Table 6.11 and
Figures 6.10-6.12). The calculated flux for the water year is divided by the total USGS
water year discharge to determine an adjusted FWMC which is also shown on the computer
generated tables. The FWMC's reported in Table 6.1 are the adjusted FWMC's generated by
this computer program, as modified by any manual corrections.
After the above program has been run for each parameter for a given station and water
year, the monthly and annual loads for major nutrients and sediments are summarized as
illustrated in Table 6.10. Note that the last column of the loading worksheet (Table 6.9)
showing monthly calculated fluxes of total phosphorus is the same as the column for TP in
Table 6.10. The summary includes the USGS discharge for each month, the ratio of the USGS
discharge to the discharge calculated from the sampling program, the number of samples
analyzed each month, and the calculated monthly loads of SS, TP, SRP, N023-N, TKN, and
chloride (Cl). Water year totals for each of the above are also shown. A table similar to Table
6.10 is included in Appendix I for each station and each water year from 1982-1985.
6.2.2. Annual Loads and Unit Area Loads for Lake Erie Tributaries
The annual loads for the major parameters for each station and water year are shown in
Table 6.11. The Maumee River, which has the largest watershed, has the largest sediment and
nutrient loads. The Sandusky and Cuyahoga rivers also have substantial loads of sediments and
nutrients. Annual variability in loads is evident for all parameters and stations.
In Table 6.12, unit area yields of sediments and nutrients are shown for each station and
water year. These unit area yields are all calculated by dividing the annual yields (Table
6.11) by the total watershed area upstream from each sampling station. The Cuyahoga River
has the highest unit area yields of sediments, total phosphorus, soluble reactive phosphorus,
and chlorides. In fact, the unit area chloride export from the Cuyahoga River is four to five
times higher than that of any other of the Lake Erie tributaries currently monitored.
Whether these high chloride export rates are associated with industrial or municipal point
sources, with geological features or with some other source is uncertain. The high unit area
export of soluble reactive phosphorus is likely to be derived from municipal point sources.
As noted earlier, the concentrations of soluble reactive phosphorus at this station are higher
under low flow conditions than under high flows, suggesting point source origins. The unit
area nitrate export for the Cuyahoga River is much lower than for the watersheds dominated
by row crop agriculture.
59
-------
WATER QUALITY LAB
HEIDELBERG COLLEGE
03-Dec-86
Flux Comparison for MAUMEE
Parameter: TP
Water year: 1984
Month
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Aug.
Sept.
N
36
53
37
35
34
40
66
37
34
36
40
34
482
FWMC
mg/L
.212885
.556125
.44282
.196659
.318432
.376246
.648432
.429087
.263132
.159178
.207369
.199739
.454981
Cum. Time
hours
751
711
753
738
660
696
720
738
720
744
738
708
8677
Obs. Flow
m**3
.797967E+08
.6784E+09
.111943E+10
.748888E+08
.960514E+09
.109575E+10
.141911E+10
.596606E+09
.161358E+09
.381856E+08
.43935E+08
.190265E+08
.628699E+10
USGS Flow
m**3
.844068E+08
.616688E+09
.101232E+10
.760283E+08
.789769E+09
.113695E+10
.13089E+10
.541692E+09
.165067E+09
. 55201 9E+08
.589678E+08
.325475E+08
.587854E+10
Flow Ratio
1.05777
.909033
.904324
1.01522
.822236
1.0376
.922341
.907957
1.02299
1.44562
1.34216
1.71064
Obs. Flux
Metric Tons
16.9875
377.275
495.704
14.7275
305.858
412.272
920.194
255.996
42.4584
6.07829
9.11075
3.80033
2860.46
Calc. Flux
Metric Tons
17.9689
342.956
448.277
14.9516
251.487
427.773
848.733
232.433
43.4344
8.78691
12.2281
6.501
2655.53
Adjusted FWMC:
.451733
Table 6.9. Sample printout from program used to adjust monthly and annual loads to the final USGS discharge data as
published in the U.S.G.S. Water Resources Data for each state and water year.
-------
Table 6.10. Monthly loads and discharge for the Maumee River for water year 1984. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
84.41
616.69
1012.32
76.03
789.77
1136.95
1308.90
541.69
165.07
55.20
59.00
32.55
Flow
Ratio
1.058
0.909
0.904
1.015
0.822
1.038
0.939
0.908
1.023
1.446
1.342
1.711
Not
Samples
36
53
37
35
34
40
66
37
34
36
40
34
SS
3786
137804
128897
286
60073
183798
432218
103840
17607
2741
3328
1930
TP
18.0
343.0
448.3
15.0
251.5
427.8
848.7
232.4
43.4
8.8
12.2
6.5
SRP
5.42
48.26
66.96
10.93
86.68
64.15
53.89
38.88
9.90
1.14
2.06
0.95
NO23-N
273
4837
6118
335
3374
7336
7874
4160
982
76
78
7
TKN
101.8
1386.9
1806.6
104.0
1504.4
1935.6
2850.1
863.7
189.6
59.1
76.1
42.4
CL
5401.7
17371.3
20496.0
4350.3
26552.7
22843.8
24007.1
13064.8
4412.6
2820.9
3168.3
2021.0
Totals
5878.54
482
1076310
2655.5
389.22
35449
10920.1
146510.0
-------
Table 6.11. Sediment and nutrient loads (metric tons) at the Lake Erie Basin transport stations for the 1982-1985 water years.
O)
Station
Maumee
Sandusky
Cuyahoga
Raisin
Honey Cr.
Upper
Honey Cr.
Rock Cr.
Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1983
1984
1985
1984
1985
SS
1,280,000
947,000
1,080,000
897,000
393,000
106,800
280,000
137,000
235,500
164,150
163,100
247,600
45,000
79,500
57,600
69,900
39,720
11,800
21,420
11,440
1,940
4,470
2,300
10,700
3,620
TP
2,820
2,080
2,660
1,900
639
235
773
270
447
386
419
486
138
224
173
202
69.6
31.5
63.0
31.8
4.17
9.42
4.68
20.1
6.76
SRP
576
286
389
90.0
35.7
162
94.8
102
105
32.9
39.6
29.4
9.30
5.01
12.7
.645
1.79
1.95
NO23-N
28,400
26,200
35,450
24,100
4,900
3,620
7,250
4,420
1,680
1,740
1,790
1,830
1,430
3,560
3,180
3,450
595
508
707
580
62.4
83.4
69.7
113
76.6
TKN
11,500
8,900
10,920
7,560
2,560
988
3,100
1,100
1,340
1,120
1,460
1,470
708
1,100
960
1,060
295
148
259
150
20.0
37.0
18.2
82.3
30.3
SiO2
40,100
32,300
38,300
40,200
7,580
4,110
11,200
7,060
5,950
5,940
6,950
8,800
3,060
5,890
5,050
7,920
856
626
1,074
806
88.5
147
116
236
169
Cl
168,000
131,000
146,500
128,000
30,500
19,800
37,900
25,500
86,800
76,300
99,100
97,600
13,900
27,100
24,300
26,500
2,770
1,920
2,570
1,950
276
340
271
621
486
-------
Table 6.12. Unit area yields of sediments and nutrients at the Lake Erie tributary transport stations for the 1982-1985 water years.
03
03
Station
Maumee
Sandusky
Cuyahoga
Raisin
Honey Cr.
Upper
Honey Cr.
Rock Cr.
Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1983
1984
1985
1984
1985
SS
kg/ha
781
577
656
547
1213
330
864
422
1286
896
891
1352
167
295
214
259
1029
307
555
296
441
1016
522
1218
411
TP
kg/ha
1.72
1.27
1.62
1.16
1.97
.727
2.39
.833
2.44
2.11
2.29
2.65
.511
.829
.640
.750
1.80
.817
1.63
.824
.948
2.14
1.06
2.28
.768
SRP
kg/ha
.351
.114
.237
.278
.110
.501
.518
.559
.575
.122
.147
.109
.241
.130
.328
.147
.407
.221
NO23-N
kg/ha
17.3
16.0
21.6
14.7
15.4
11.2
22.4
13.6
9.18
9.49
9.77
9.99
5.30
13.2
11.8
12.8
15.4
13.2
18.3
15.0
14.2
19.0
15.8
12.8
8.71
TKN
kg/ha
7.01
5.48
6.66
4.61
7.90
3.05
9.57
3.43
7.32
6.09
7.95
8.04
2.62
4.08
3.56
3.94
7.64
3.84
6.70
3.88
4.55
8.41
4.14
9.35
3.44
SiO2
kg/ha
24.5
19.7
23.3
24.5
23.4
12.7
34.7
21.8
32.5
32.4
38.0
48.1
11.3
21.8
18.7
29.3
22.2
16.2
27.8
20.9
20.1
33.3
26.3
26.8
19.2
Cl
kg/ha
102.5
79.8
89.4
77.9
94.1
61.1
117
78.7
474
417
541
533
51.5
100
89.9
98.0
71.8
49.8
66.5
50.4
62.7
77.3
61.5
70.6
55.2
-------
The River Raisin has the lowest sediment, total phosphorus and nitrate export rates of
the watersheds dominated by agricultural land uses. It is noteworthy that the average gross
erosion rate for the River Raisin (Table 5.2) is higher than that of any of the Ohio
tributaries to Lake Erie. The low sediment and nutrient yields from the River Raisin
illustrate a lack of correlation between high gross erosion rates and high unit area yields of
sediments and nutrients {Baker et al. 1985b).
6.2.3. Annual Variability in Nutrient and Sediment Export
Agricultural nonpoint source pollution is characterized by a large amount of annual
variability. This annual variability is illustrated in Figures 6.10, 6.11 and 6.12 which
depict the seasonal and annual rainfall, discharge and loads of SS, TP, SRP and N023-N for
the period of chemical transport studies at the Maumee, Sandusky and Honey Creek stations.
Each bar in the graphs of Figures 6.10 - 6.12 is composed of four segments representing the
four seasons. The fall period (Oct.-Dec.) is at the base of each bar, followed by the winter
period (Jan.-Mar.), and the spring period (April-June), with the summer period
(July-Sept.) at the top of each bar. The rainfall data for the Maumee are based on the average
from 17 NOAA weather stations located in northwest Ohio and the Maumee River Basin. For
the Sandusky River, the rainfall data are based on the average of the 11 NOAA weather
stations in north central Ohio, four of which are in the Sandusky Basin and five adjacent to
the basin.
In Table 6.13 the means and coefficients of variation for annual rainfalls, discharges and
loads of SS, TP, SRP, and NO23-N are listed, based on data collected through the 1985 water
year. Using data from Table 6.13 together with the bar graphs of Figures 6.10-6.12 the
following generalizations regarding variability in annual export can be made.
1. Total annual rainfall is the least variable of the factors monitored.
2. Total stream discharge is much more variable than is total rainfall.
Rainfall intensities and timing, relative to soil moisture content, are
apparently more important in influencing seasonal and annual discharge
than is the total amount of rainfall.
3. As watershed size decreases, the annual variability in sediment and total
phosphorus load increases, and for smaller watersheds is much greater than
the annual variability in discharge.
4. The variability in the export of soluble nutrients such as SRP and NO23-N
is similar to the variability in discharge.
6.2.4. Seasonal Distribution of Material Export
In Table 6.14 the percentage of material export occurring during each season for the
entire period of record is shown for the three watersheds with the longest records. With
64
-------
\&J -
•y 100 -
| 80-
a 60 -
1 40 -
c
'c5
cc 20 -
0 -
P»:
..'..o
'%•
I
•*-
~
"
\
' X
\
•"-
•^
I
' X
n
|
/
s
—
fTl
35;
$
1
X
—
T
i-
I
X
n
-'•:
i
X
"n
m
1
. S
X
. V
— •
«5
:=;
\
ft?
[JIH
v,-
1
\
T
i '•
1
X *
s
F***"l
!•-•"
1
V
\
— -
1975 1977 1979 1981 1983 1985 ave
water year
^ H-UUU
C
o
u
S 3000 -
!
5 2000 -
o
.c
Q.
CO
.i 1000-
o.
'(5
X
X
'
"*"
\
++•
y
s
I
X
N
X
X
_*,
1
"* ™"
1
—
rr
1
X
X
X
X
""*"
1
N
X ,
X ,
X
1-
1
C—
1975 1977 1979 1981 1983 1985 ave
water year
-£* OUUU -
3
"3
o 6000 -
J 4000 -
1
§> 2000 -
01
^
u
en
^ n -
•s
N
\
s'
\'
i^~
i
^
s
ra
!
N.
rp»
i
X
X
^
s
v •
\
\
±.
1
s •
£
w*
1
X
X
X
X
x^
X
X
X
X
™~*
i
i \.
1
X
*x
1
1
s
\'
X ,
X ,
w—
1975 1977 1979 1981 1983 1985 ave
water year
ouu -
CO
c
^ 600 -
7 400-
o
a
^ 200 -
o
DC
"o
U) n -
„,
v
/
',
^
n
1
V.
X
N
X
gw^
p!
X -
X ,
X .
I_
1
1
s
1
X
X
N '
—
n
N
I
, \
X
A
1975 1977 1979 1981 1983 1985 ave
water year
o
•o
c
-------
120
•
Rainfall (centimeters;
8 S S 8 ?
SF
'A
I
X
I
s
x •
/
X
1
I
s
%
I
f
s
1
s
I
X
\
w*
1
X
^ .
X
s
f ,
X
X ,
X
f .
\
H?fi
I
•w
3
1
• X
• ^
\
s
— . ouu -
M
c
o
tal Phosphorus (metric t
8 § §
o o o
1.1,1
£
^
S
s
f
s
s
_
s
. X
s
, X
f
•, X
/
_— .
12
Vs"
1
•x?
%
X
x'
FH
\
X
X y
X
^ t
X
x /
X
x
x-"V
:»
v/
•ft
!
1
1
X
' ^
X
' X
x
' ^
X
• ^
X
X
x'
—
1
~~
'//
1
X
s
X
s
x
s
X
f
\
s
X
X
™
C"*"
/
X '
s
!
s
1975 1977 1979 1981 1983 1985 ave 1975 1977 1979 1981 1983 1985 ave
water year water year
o
0
E
u
harge (million cub
o
o
a
. \
u
(A
?; n -
X
' /•
\.
• f
X
' ^
x
X
X
^
X
X
zz
x •
s
1
I
s
s
/
I
s
* s
* s
i
\
* s
1
f .
s .
X
X
X
X
X
1
psa
^
^
-^
70S
tf
x'
X
1
• f
s
' /•
s
•jr
c
o
^J
•^
1.
| 100-
Q.
O
a>
GC
o
W 0-
X
• ^
X
' ^
~*
1 X
x •
1 X
• x
x •
X
s
X
s
x •
f
i
s
i
s
f
f
f
V
i X
/
\ X
f
\
/
s
X
X
X
X
X
f
X
J~"
n
x'xT
•^
X i
X
X *
X
X ,
X .
X ;
X
X .
s
X
X
x
1
X
1975 1977 1979 1981 1983 1985 ave
water year
1975 1977 1979 1981 1983 1985
water year
c
o
o
10
•o
01
•a
c
0)
a
u)
U)
ouu -
500 -
400 -
300 -
200 -
100 -
n -
S
f
s
s
'
F
k
L.
n
/
\ X
f
—
7-
/^
I
S
s
X
s
i.
*;
!
J#;
j
x
E§]
i " I
1
N
—
Fl
t— I
1
s
x
.--I-
*5T
c
0
|o 6000 -
JL
o 4000 -
Z
o 2000 -
ra
w
•z.
n -
™
^
f
^
/
s
=53
f
' s
*-^-
-;
' '^/
' ^
' /
' s
s .
s ,
s .
X
x
_L.
i
/
X
s
s
L-
I
I
s ,
x
x -
X
x /
,V-
^
!
ss
"T"
/ x
•V
|
• X
• X
X
_
p
ty
•^"f
f
psa
1
X '
X
X '
s
X
s
X
s
X
s
I
"** j
s
s
~
I
s
^ ^
s
—
1975 1977 1979 1981 1983 1985 ave
water year
1975 1977 1979 1981 1983 1985 ave
water year
Figure 6.11. Annual variability and seasonal distribution of rainfall, discharge and
loading of SS, TP, SRP and NO23-N at the Sandusky River transport station.
66
-------
Legend for bar graphs of
figures 6.10 -6.12.
D fall amount
Q winter amount
^3 spring amount
H summer amount
o
•o
•S 20000 -
o
a.
(A
3
01 n -
„
I
i
pa
1
•*•*
1
s-
s
s
m I
^
1975 1977 1979 1981 1983 1985
water year
ave
C
2 800-
u
1 600 -
£
1 400 -
— 200 -
z
n -i
X
, \
s
s
\
I
X
X
X
1
X
X ,
X
X
ffi*
I
X
x
X '
x
n>m
j
-"-
n
4**U
p
i
X
x
X
=ss
1
x
X
x
~
~
1
X
X •
s
I
s
—
\
s
s
1975 1977 1979 1981 1983 1985 ave
water year
Figure 6.12. Annual variability and seasonal distribution of discharge and loading of
SS, TP, SRP and N023-N at the Honey Creek transport station. Rainfall patterns at
Honey Creek would be similar to those at the Sandusky River transport station.
67
-------
Table 6.13. Means and coefficients of variation for annual rainfall and discharge and for annual export of
sediments and nutrients from three northwestern Ohio watersheds of varying sizes.
Watershed
(Years of data)
Honey Creek
(10 years)
Rainfall Discharge
cm
106m3
122
±27.%
Suspended
Solids
103 metric
tons
24.0
±73.%
Total
Phosphorus
metric
tons
50.2
±43.%
Soluble
Reactive
Phosphorus
metric
tons
8.67
±37.%
Nitrate +
Nitrite-
Nitrogen
metric
tons
600
±23.%
Sandusky R.
(11 years)
93.7
±7.%
1100
±36.%
269
±55.%
503
±41.%
93.3
±40.%
5110
±30.%
Maumee R.
(7 years)
90.2
±7.%
5030
±24.%
1120
±25.%
2460
±19.%
417
±46.%
25500
±24.%
respect to rainfall, the spring and summer have the largest amounts, with about 50% more
rainfall during these seasons than during the fall and winter period. Discharges are,
however, much greater during the winter than for spring and fall, with the least amount in
the summer. Watershed size seems to have little effect on the seasonal distribution of
discharge.
For suspended sediments in Honey Creek, the spring accounted for 57% of the total
export with the winter accounting for only 27%. In contrast, in winter the Maumee River
transported 42% of the sediment, while the spring accounted for 37%. The Sandusky River
was intermediate in terms of the seasonality of sediment export. As noted by McGuinness et al.
(1971) in smaller watersheds sediment export is more closely tied to the timing of soil
erosion events on the landscape while for larger rivers, sediment export coincides more
closely with the timing of stream discharge. The seasonal patterns of total phosphorus export
for the three watersheds are similar to those for suspended solids.
The seasonal distribution of soluble phosphorus export is similar to the seasonal
distribution of discharge, except that winter is even more important for soluble phosphorus
export. The sources of the soluble phosphorus exported during winter are uncertain. It is
possible that the freezing of vegetation releases soluble phosphorus that is subsequently
exported. As noted in Section 6.1.7 it is also possible that there is less processing of SRP
during winter, resulting in greater SRP concentrations and export.
For N023-N the winter and spring periods are large and equally important, followed in
importance by the fall season. There is very little nitrate export during the summer period.
The lower spring discharges are accompanied by higher nitrate concentrations (Section
6.1.7), resulting in loads similar to those exported in the winter time with its higher
discharges and lower nitrate concentrations.
68
-------
Table 6.14. Seasonal distribution of rainfall, discharge and nutrient sediment export from three north-
west Ohio watersheds of varying sizes.
Oct-Dec
Percent of mean annual load
Jan-Mar April-June July-Sept
Honey Creek
[see Sandusky R.]
Sandusky R.
Maumee R.
Honey Creek
Sandusky R.
Maumee R.
Honey Creek
Sandusky R.
Maumee R.
Honey Creek
Sandusky R.
Maumee R.
21.5
22.3
19.8
17.4
17.2
7.5
9.0
15.5
14.3
12.6
17.7
20.4
18.8
42.8
46.8
42.3
28.3
38.7
44.3
35.7
44.5
46.3
Rainfall
28.7
30.4
Discharge
29.8
27.4
33.0
Suspended Sediment
55.8
45.0
36.8
Total Phosphorus
42.6
35.4
32.2
29.3
28.7
7.4
8.5
7.6
8.2
7.7
3.1
7.3
7.3
3.6
Soluble Reactive Phosphorus
Honey Creek
Sandusky R.
Maumee R.
24.1
17.9
21.6
41.8
52.5
49.2
24.2
20.7
23.7
10.0
8.9
5.4
Nitrate + Nitrite-Nitrogen
Honey Creek
Sandusky R.
Maumee R.
20.0
18.3
22.8
34.7
38.4
38.0
38.3
37.4
34.8
7.0
6.0
4.4
69
-------
Watershed size seems to have little effect on the seasonal aspects of the export of soluble
constituents including both SRP and N023-N.
6.2.5. Role of High Flux Periods in Total Material Export
Since the transport of materials derived from nonpoint sources occurs primarily during
storm runoff periods, it is not surprising that large proportions of material export occur
during small proportions of time. In Tables 6.15-6.17, the roles of periods of high fluxes in
the export of SS, TP and N023-N are presented for watersheds of various sizes. For SS, the
0.5% of the time with the highest fluxes accounted for 17% of the total export for the
Maumee and 48% of the total export for Upper Honey Creek. In general, as watershed size
decreases, small percentages of time with the highest flux rates account for increasing
proportions of the SS and TP export. It should be noted that the 0.5% of the time (or any
other of the percentages listed) does not represent a continuous time interval during a single
storm event, but rather the periods of peak flux rates during several different storm events.
The program that produces the values presented in Table 6.15-6.17 ranks the instantaneous
flux rates, thereby picking out short time intervals with high flux rates from all of the
runoff events of that station.
The data as presented in Tables 6.15-6.17 underscore the importance of obtaining
samples during the relatively small proportion of time with high flux rates even though these
periods may constitute short periods of many individual storms. As watershed sizes become
smaller, the time windows which must be carefully sampled to produce accurate loading data
also become smaller. Monte Carlo analyses of data sets for the Maumee, Sandusky and Honey
Creek stations indicated that more samples are required in small watersheds than in large
watersheds to achieve a given level of precision and accuracy in load estimation (Richards and
Holloway 1985a,b).
N023-N, with 0.5% of the time accounting for 5% of the NO23-N export from the
Maumee and 16% from Upper Honey Creek. The export of particulate phosphorus probably
corresponds more closely to SS export while the export of SRP, which is also included in the
TP measurements, probably is more like the export of nitrates. It should be noted that the
effects of watershed size on the durations of material export are important for both
particulate and soluble constituents.
6.2.6. Gross Erosion Rates. Unit Area Sediment and Nutrient Yields and Sediment Delivery
Ratios for Long Term Transport Stations
In Table 6.18 the average unit area yields of SS, TP, SRP, N023-N, and TKN are listed
for each of the long term transport stations. The average yields of total phosphorus and total
nitrogen (N023-N + TKN) for croplands in the United States, as used to estimate lake
loadings (Rast and Lee 1983), are also shown in Table 6.18. The monitored yields for Lake
Erie tributaries are much higher than the average yields from agricultural land. In the case
of total nitrogen, the unit area yields for northwestern Ohio are equivalent to approximately
50% of the nitrogen fertilizer added to those watersheds each year. Thus the nitrogen losses
via surface water (and associated tile systems) represent significant losses to farmers.
70
-------
Table 6.15. Percentages of suspended solid loads that were exported during fluxes which were exceeded for the
indicated percentages of time (e.g. for the Maumee River fluxes exceeded 1% of the time accounted for 27.1% of the
total suspended solids export during the period encompassing the 1982-1985 water years).
Percent of time
fluxes were Maumee
exceeded 16,395
0.5
1.0
2.0
5.0
10.0
20.0
50.0
17.3
27.1
41.3
64.3
81.6
93.9
98.9
Sampling station
Sandusky Raisin
3,240 2,699
_ _ _ °A nf tr,
24.3
36.4
50.9
73.1
87.7
95.4
99.3
17.8
26.9
41.3
64.2
79.6
91.2
97.7
and associated
Cuyahoga
1 ,831
tal load export
28.3
38.1
51.0
69.4
81.5
90.9
98.3
drainage area
Honey Cr.
386
pH
32.9
45.7
60.6
78.8
89.9
97.0
99.7
(Km2)
Rock Cr.
88.0
42.7
59.5
76.6
93.2
97.6
99.0
99.8
Upper
Honey Cr.
44.0
48.2
63.5
77.9
92.0
96.6
98.8
99.7
-------
Table 6.16. Percentages of total phosphorus loads that were exported during fluxes which were exceeded for the
indicated percentages of time (e.g. for the Maumee River fluxes exceeded 1% of the time accounted for 17.2% of the
total phosphorus export during the period encompassing the 1982-1985 water years).
Percent of time
fluxes were Maumee
exceeded 16,395
0.5
1.0
2.0
5.0
10.0
20.0
50.0
9.8
17.2
28.7
48.9
67.5
85.6
97.6
Sampling station
Sandusky Raisin
3,240 2,699
O/ nf +n
14.8
22.8
35.2
58.3
77.3
90.2
98.5
14.8
23.9
33.4
51.5
67.9
81.3
92.9
and associated
Cuyahoga
1,831
ital load export
13.2
18.0
26.0
39.4
51.3
64.8
85.1
drainage area
Honey Cr.
386
oH
18.1
27.4
40.4
63.0
80.8
92.8
99.1
(Km2)
Rock Cr.
88.0
30.9
47.2
64.0
86.4
93.9
97.2
99.3
Upper
Honey Cr.
44.0
32.8
46.7
62.2
82.7
93.0
97.4
99.5
-------
-vl
CO
Table 6.17. Percentages of nitrate plus nitrite-nitrogen loads that were exported during fluxes which were exceeded
for the indicated percentages of time (e.g. for the Maumee River fluxes exceeded 1% of the time accounted for 8.6%
of the local nitrate plus nitrite nitrogen export during the period encompassing the 1982-1985 water years).
Percent of time
fluxes were Maumee
exceeded 16,395
0.5
1.0
2.0
5.0
10.0
20.0
50.0
5.0
8.7
15.3
31.9
52.2
75.4
97.0
Sampling station
Sandusky Raisin
3,240 2,699
_______ <>/- nf t/i
6.9
12.3
20.4
37.8
56.7
77.2
97.2
5.3
9.5
17.3
34.1
54.2
76.4
95.4
and associated
Cuyahoga
1,831
ital load export
3.0
5.2
8.7
16.3
25.9
40.5
71.2
drainage area
Honey Cr.
386
O/H
9.1
15.1
24.3
43.1
61.7
81.0
97.5
(Km2)
Rock Cr.
88.0
17.9
28.8
44.9
67.8
81.0
91.4
98.9
Upper
Honey Cr.
44.0
16.3
26.2
39.6
64.3
79.8
90.7
99.0
-------
Table 6.18. Unit area yields of sediments and nutrients for the period of record, average gross erosion rates, and average sediment
delivery percentages for three northwestern Ohio watersheds. Data through the 1985 water year.
Average Gross Average Soluble Total
Erosion Rate Sediment Sediment Total Reactive Nitrate + Kjeldahl
metric metric Delivery Ratio Phosphorus Phosphorus Nitrite-N Nitrogen
tons/ha/yr tons/ha/yr As Percent kg/ha/yr kg/ha/yr kg/ha/yr kg/ha/yr
Honey Creek
Sandusky R.
Maumee R.
6.86 0.62 9.0 1.30 0.22 15.5 5.8
8.25 0.83 10.0 1.55 0.29 15.8 5.6
6.84 0.68 10.0 1.50 0.25 15.6 5.5
Average for
agricultural lands
0.50
- - 5.0 - -
-------
Average gross erosion rates, as calculated during the Lake Erie Wastewater Management
Study (Logan et al. 1982) are also listed in Table 6.18. The average gross erosion rates in
these watersheds are lower than average gross erosion rates for U.S. cropland. These gross
erosion rates listed in Table 6.18 probably slightly overestimate current erosion rates, due
to the adoption of various types of conservation tillage practices in the Lake Erie Basin.
Unfortunately, no new estimates of gross erosion rates for these watersheds are available.
Using the LEWMS gross erosion rates, the delivery ratios for sediments average about 10%.
Sediment delivery ratio estimates for other Lake Erie Basin watersheds have been described
by Baker (1984) and Baker et al. (1985b).
6.2.7. Comparisons of Agricultural Nonpoint Pollution in the Lake Erie Basin and the
Chesapeake Basin
The large magnitude of agricultural pollution in the Lake Erie Basin is evident when
compared to data from the Chesapeake Bay Region (Macknis 1985, Smullen et al. 1982).
While the populations of both areas are the same, the drainage area of Chesapeake Bay is
approximately three times larger than that of Lake Erie (Table 6.19). River loadings of
sediment, total phosphorus and total nitrogen are, however, much larger for Lake Erie
tributaries. Consequently, the unit area loads of sediment, total phosphorus and total nitrogen
are 6.4, 5.2 and 4.2 times higher, respectively, than those for Chesapeake Bay watersheds.
These higher unit area loads for Lake Erie watersheds are associated with the larger
propotions of intensive row crop agriculture in the Lake Erie watershed than in the
Chesapeake Basin. The higher population densities coupled with intensive agricultural land
use put particularly heavy pressure on the water and soil resources of the Lake Erie Basin.
Table 6.19. Comparison of the Lake Erie Basin and Chesapeake Bay Basin with respect to
population, drainage areas and tributary pollutant loads.
Parameter Lake Erie Basin Chesapeake Bay Basin
Population 14,000,000 14,000,000
Land Area, km2 56,980 165,800
River Sediment Loads
metric tons/yr 6,531,000 3,005,800
kg/ha/yr 1,150 181
River Phosphorus Loads
metric tons/yr 8,400 4,659
kg/ha/yr 1.47 0.28
River Nitrogen Loads
metric tons/yr 111,670 77,584
kg/ha/yr 19.6 4.67
75
-------
SECTION 7
RESULTS AND DISCUSSION: PESTICIDES
7.1. BACKGROUND ON THE PESTICIDE MONITORING PROGRAM IN THE LAKE
ERIE BASIN TRIBUTARIES
The pesticide monitoring program in Lake Erie tributaries was initiated in 1980 in
response to concerns that conservation tillage could aggravate the pesticide problems in
surface waters. An obvious question arose as to the nature of the "pesticide problems" that
might be aggravated. Most pesticide monitoring programs in surface waters were directed
toward confirming the disappearance of organochlorine insecticides, such as DDT, that had
been banned because of their persistence and their tendency to bioaccumulate. Since the
pesticides that were replacing them were generally less persistent and often had less of a
tendency to bioaccumulate, little priority was given to monitoring their occurrence in
surface water and groundwater. Yet it was these newer generation pesticides whose use
might be increased with increasing adoption of conservation tillage. Furthermore, the use of
many of these compounds, especially the herbicides, had already increased dramatically in
association with conventional tillage. According to Hileman (1982) herbicide use in the
United States increased 280% between 1966 and 1981.
As our pesticide monitoring program developed, we decided to focus on as many of the
"large use" and "local use" compounds as possible, subject to their suitability for inclusion
within a multi-residue scanning method using capillary gas chromatography and
nitrogen-phosphorus detectors. Considerable analytical method development has accompanied
this program and the methods are still undergoing annual modifications. The methods as
applied in 1985 included analyses for 19 compounds representing, by weight, about 90% of
the herbicides used in Ohio and also 90% of the insecticides.
A second important aspect of the program is that it focuses the sampling effort on runoff
events following pesticide application in the spring and summer period (April 15 through
August 15). The sampling program outside of the above dates is reduced to about one or two
samples per month.
Pesticide monitoring programs for streams and rivers have seldom been focused as
described above (General Accounting Office 1981). In the short period of five years, the
pesticide monitoring data set for Lake Erie tributaries has become the largest data set of its
kind available in the United States. Because studies of comparable detail and duration are
virtually nonexistent, data with which to directly compare the Lake Erie Basin data are
generally not available. Recent studies of exposure patterns for alachlor (U.S. EPA 1986)
and atrazine (Ciba-Geigy 1986) do provide some basis for comparisons with other regions.
Most of the discussion and analyses will involve comparisons from within the data set rather
than with other regions.
76
-------
7.2. PESTICIDE CONCENTRATIONS IN LAKE ERIE TRIBUTARIES
7.2.1. Chemograph Patterns
In Figures 7.1-7.12 the runoff patterns for 1982-1985 of four major herbicides
(atrazine, alachlor, metolachlor and cyanazine) are illustrated for Honey Creek, the
Sandusky River and the Maumee River. The corresponding hydrographs and nitrate
chemographs are also shown for each year and station. The graphs are restricted to the April
15 through August 15 period since that time interval encompasses the major periods of
pesticide runoff. With few exceptions (e.g., atrazine and metolachlor), the concentrations of
pesticides outside of this time interval are near or below the detection limits. Atrazine and, to
a lesser extent metolachlor, is present in concentrations well above detection limits for much
of the year, particularly during runoff events. In Figure 7.1-7.12 the concentration scales
for pesticides and nitrates are uniform for all years and stations, so that the concentration
curves for a given parameter are directly comparable in all of the plots. None of the data in
the graphs have been corrected for recoveries less than 100%.
The data presented in Figures 7.1-7.12 suggest that pesticide runoff in these tributaries
has the following characteristics:
1. Pesticide concentrations during late April and early May are below or near
detection limits.
2. Pesticide concentrations increase in association with runoff events.
3. The peak pesticide concentrations can occur in late May, June, or July.
Some of the highest pesticide concentrations observed occurred in July,
suggesting that hydrological factors have a greater influence on pesticide
concentrations than pesticide breakdown in the soil (see Honey Creek 1984,
Figure 7.3). A rainfall event of a particular intensity and duration can
yield high stream concentrations even though the pesticides have been on the
fields for some time.
4. By mid August, pesticide concentrations, even in association with runoff
events, are low and approach detection limits.
5. Peak pesticide concentrations decrease with increasing watershed size.
6. Multiple storms with high pesticide concentrations can occur in the same
watershed in the same year. (See Honey Creek 1985, Figure 7.4). This
may contrast with results from field runoff studies, where high pesticide
concentrations are generally confined to the first runoff event following
pesticide application (Wauchope 1978).
7. The shapes of the pesticide chemograph are rather broad, corresponding
more closely to chemographs for nitrates than for sediments. The pesticide
chemographs are, however, shifted to the left relative to nitrate
chemographs (i.e., they occur earlier in the runoff event). As noted in
Section 6.1.2, pesticides probably are exported from fields throughout the
77
-------
03
Z o
l-t
M O
ATRA2.
ALACH.
o
,o
.0 I
- o
05/01
06/01 07/01
SUMMER 1982
08/01
.-1
V.
o>
cc
o
1
X
0
<
3
1—
Id
3
n
0
0.
CM
O
ci.
0
(D™
Q : METOL.
f *: CYANA.
1
L
•
» •
• -1
rf^»i ** * "/
R
.IV
oUT
• 1 1 «•
A 1 JmL M
U'ffV ,:,....
01
O
"(O
o
"ri
0
'o
^
<;
o>
3
Ul
Z
M
M
<
Z
<
>-
o
05/01
06/01 07/01
SUMMER 1983
08/01
Figure 7.1. Pesticide concentration patterns, discharge
and nitrate concentrations in Honey Creek, 1982.
Figure 7.2. Pesticide concentration patterns, discharge
and nitrate concentrations in Honey Creek, 1983.
-------
co
05/01
06/01 07/01
SUMMER 1984
08/01
05/01
06/01 07/01
SUMMER 1985
08/01
Figure 7.3. Pesticide concentration patterns, discharge
and nitrate concentrations in Honey Creek, 1984.
Figure 7.4. Pesticide concentration patterns, discharge
and nitrate concentrations in Honey Creek, 1985.
-------
SANDUSKY RIVER
05/01
06/01
O> O.
3 N
z o
M
M O
<£.
00
O
ATRAZ.
ALACH.
V
'«-J°
o
.o
ce
o o
.o x
•- o
UJ
Z o
I-H
M O
tc.
1-
<
ATRAZ.
ALACH.
-I-T*
a:
o
_
-o x
— o
KL
O
O
_J
O
METOL.
CYAN A.
05/01
06/01 07/01
SUMMER 1982
08/01
05/01
06/01 07/01
SUMMER 1983
08/01
Figure 7.5. Pesticide concentration patterns, discharge
and nitrate concentrations in the Sandusky River, 1982.
Figure 7.6. Pesticide concentration patterns, discharge
and nitrate concentrations in the Sandusky River, 1983.
-------
05/01
06/01
07/01
08/01
00
o> o
3 CM
M O
< -
cc
ATRAZ.
ALACH.
,,f\\
* yjfl1.. °
o
_O
a:
o o
-O X
•- (J
SANDUSKY RIVER
n
•^
^01 0
= 6.
**"' CM
g
I °
3 2-
o
i—
i. 1
3 0
' Ifc ^
- . -" . . A^^» 4-f » 1 *"
s
I.
*^» 4
Q-I---I---I- 1 1 1 1
05/01 06/01 07/01
^j: METOL.
^ : CYAN A.
B
. » J 8 J^E
en
o
'(D
0
"ri
0
08/01
3
LJ
(£.
O
METOL.
CYANA.
M
" " ^
" Z
>-
05/01
SUMMER 1984
06/01 07/01
SUMMER 1985
08/01
Figure 7.7. Pesticide concentration patterns, discharge
and nitrate concentrations in the Sandusky River, 1984.
Figure 7.8. Pesticide concentration patterns, discharge
and nitrate concentrations in the Sandusky River, 1985.
-------
00
ro
05/01
06/01
07/01
08/01
m
< °
u* o.
3 ex
UJ
Z o
l-t
M o.
(C
K
<
ATRAZ.
ALACH.
.o o>
3
O g
-d x
- o
o:
o
I
o
METC,
CYANA.
•*tjfcAv~~~,
"" i
o
05/01
06/01 07/01
SUMMER 1982
08/01
-
3 o
' W
ce
o
_i _
I °
4 O_
^
1—
= 0
d~
Q: METOL.
^ : CYAN A.
JJrf^ a £ s £ '•! W^"'* 4
/ ' / ' / i • • 1 • 1
at
°. ^°-
"«> ^
1. 1
Z
° K
"" 1
o
o
6
SUMMER 1983
Figure 7.9. Pesticide concentration patterns, discharge
and nitrate concentrations in the Maumee River, 1982.
Figure 7.10. Pesticide concentration patterns, discharge
and nitrate concentrations in the Maumee River, 1983.
-------
05/01
06/01
07/01
08/01
05/01
06/01
07/01
08/01
co
co
ATRAZ.
ALACH.
.o x
•- o
<
V O.
3 CM
Z o
M d.
ATRAZ.
ALACH.
.o x
- O
ro
1^
^CT 0
•^ s-
o:
o
i
X °
< 2-
_l
O
t—
» o
o"
ft
J
H: METOL.
A : CYANA.
M
• ^^w • »» .
* i I /_ .
s~+
-
u
o
'd
05/01
06/01
SUMMER 1984
ca
o
METOL.
CYANA.
UJ
M
M
05/01
06/01 07/01
SUMMER 1985
08/01
Figure 7.11. Pesticide concentration patterns, discharge
and nitrate concentrations in the Maumee River, 1984.
Figure 7.12. Pesticide concentration patterns, discharge
and nitrate concentrations in the Maumee River, 1985.
-------
period of surface water runoff, whereas sediment export from fields is
focused within the early portions of the surface water runoff and nitrate
enters streams via tile drainage and interflow.
7.2.2. Time Weighted Mean Concentrations
The TWMC's for pesticides can be calculated in the same way as for nutrients and
sediment (see Section 6.1.5). The output of a program which computes TWMC's for the major
pesticides is illustrated in Table 7.1 The program does not incorporate corrections for
recoveries less than 100%. In running the program the maximum duration for which any
single sample may be used to characterize the stream can be selected. Likewise, the beginning
and ending dates for inclusion in the calculation may be selected.
For this report the maximum duration was set at 14 days so that biweekly samples prior
to and following the period of maximum concentration would be weighted to a greater extent
than the more frequent samples during periods of high concentrations. The time interval was
set from April 15 through August 15. These dates cover the same time interval as plotted in
Figures 7.1-7.12. The program lists the total number of pesticide samples included in the
selected period, as well as the total time interval within the period that was characterized by
the sampling program, subject to the limitation set by the maximum duration any single
sample was used to characterize the concentration. Tables similar to Table 7.1 are included in
Appendix II for each station and year. The pesticide data for 1982 (and 1986) have not yet
been transferred into files accessible by the program and are not included in Appendix II.
The program automatically extrapolates the observed TWMC for the selected period to an
annual TWMC for that year, using the assumption that the pesticide has zero concentration
during the period outside the selected period. Since for several pesticides, the concentrations
in the late summer/early fall, while low, are still above detection limits, the above
extrapolation to an annual TWMC underestimates the actual values. Techniques for improving
the estimated annual TWMC to better reflect actual values are described and utilized in
Section 7.2.5.
In Table 7.2 the TWMC's for the major pesticides for the time intervals between April
15 and August 15 are shown for each station for the 1983, 1984 and 1985 water years. The
1984 and 1985 values have been corrected for recoveries less than 100% using the values
listed in Table 5.5. It is evident from Table 7.2 that:
1. atrazine, alachlor, metolachlor and cyanazine have the highest TWMC's;
2. there is considerable annual variability in TWMC's;
3. some of the highest TWMC's occur in the smaller watersheds;
4. of the agricultural watersheds, the River Raisin has the lowest pesticide
concentrations;
5. the Cuyahoga River, draining primarily forested suburban and industrial
areas, has far lower concentrations of the major herbicides than do the
agricultural watersheds.
84
-------
Table7.1.Pesticide concentrations for the Maumee River in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.503
Results based on 38 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1653
0.0461
1.9017
0.0009
0.0004
0.2536
0.4723
0.0126
1.3159
0.3216
Adjusted to
whole year
0.0553
0.0154
0.6356
0.0003
0.0001
0.0848
0.1578
0.0042
0.4398
0.1075
Observed
flux
ppb-days
19.9206
5.55576
229.164
.108242
.503646E-01
30.561
56.908
1.5225
158.574
38.7578
85
-------
Table 7.2. Time weighted mean concentrations (|o.g/L) during the April 15 - August 15 periods for the
Michigan and Ohio tributaries to Lake Erie for the years 1983, 1984 and 1985. Data of 1984 and
1985 corrected for recoveries less than 100%.
Year
Atrazine
1983
1984
1985
Alachlor
1983
1984
1985
Metolachlor
1983
1984
1985
Cyanazine
1983
1984
1985
Metribuzin
1983
1984
1985
Linuron
1983
1984
1985
Simazine
1983
1984
1985
Carbofuran
1983
1984
1985
Terbufos
1983
1984
1985
Fonofos
1983
1984
1985
Maumee
River
1.751
3.464
2.756
1.046
1.688
0.738
1.308
1.819
1.964
0.622
1.166
0.407
0.443
0.830
0.390
0.036
0.040
0.016
0.0
0.210
0.223
0.175
0.211
0.060
0.001
<0.001
0.002
0.0
0.004
0.001
Sandusky
River
1.805
2.940
6.406
0.508
1.206
2.933
2.252
3.151
7.200
0.447
0.494
0.782
0.296
0.687
1.410
0.088
0.003
0.407
0.0
0.121
0.266
0.154
0.154
0.241
0.0
0.0
0.002
0.004
0.0
0.008
Honey
Creek
3.029
5.194
7.673
1.381
2.042
3.324
2.989
3.468
6.577
0.660
0.664
1.466
0.353
0.502
1.020
0.332
0.052
0.836
0.0
0.059
0.235
0.105
0.299
0.338
0.001
0.0
0.005
0.0
0.0
0.002
Rock
Creek
2.516
1.084
5.200
0.525
0.240
0.882
2.917
2.513
9.960
0.221
0.038
0.252
0.304
0.075
0.882
0.645
0.0
0.860
0.0
0.079
0.079
0.061
0.143
0.297
0.0
0.0
0.002
0.0
0.0
<0.001
U. Honey
Creek
0.636
0.969
5.366
0.287
0.274
0.399
0.618
0.361
2.136
0.202
0.152
3.056
0.159
0.163
0.402
0.027
0.0
0.059
0.001
0.010
0.076
0.083
0.063
0.154
0.001
0.0
<0.001
0.002
0.0
0.0
Lost
Creek
3.768
6.583
0.938
2.369
1.657
0.104
1.483
0.694
0.613
0.826
1.569
0.567
0.586
0.457
0.077
0.367
0.0
0.005
0.002
0.050
0.014
0.066
0.130
0.031
0.036
0.0
<0.001
0.002
0.003
0.0
River
Raisin
1.067
1.128
2.618
0.540
0.754
1.603
0.317
0.514
1.175
0.341
0.492
0.580
0.135
0.086
0.232
0.079
0.013
0.540
0.001
0.048
0.254
0.172
0.032
0.052
0.028
0.0
0.0
0.003
0.034
0.012
Cuyahoga
River
0.358
0.254
0.640
0.090
0.092
0.021
0.516
0.001
0.160
0.292
0.006
0.120
0.174
0.088
0.0
0.090
0.380
0.132
0.034
0.842
0.597
0.596
0.205
0.056
0.096
0.007
0.0
0.167
0.014
0.026
86
-------
7.2.3. Peak Pesticide Concentrations and Watershed Size
In Table 7.3 the peak pesticide concentrations observed at each station for the
1982-1985 water years are listed. Atrazine has been observed in the highest
concentrations, reaching 245 u,g/L in Lost Creek in 1984 and 226 u,g/L in Upper Honey
Creek in 1985. Metolachlor was observed to reach 154 u,g/L in Rock Creek in 1985.
Cyanazine was found at 86 u,g/L in Upper Honey Creek in 1985 in the same samples that had
atrazine at 226. Linuron was observed in Lost Creek at 160 (ig/L in 1982. Since this value
for linuron is more than an order of magnitude higher than any other observations of
linuron, it may be a consequence of a spill or other "point source" introduction of linuron
rather than runoff from normal field operations.
The data on peak concentrations indicate that higher concentrations are found in the
streams having smaller watersheds. It should be noted that the sampling program for
pesticides is more likely to hit peak concentrations for large streams, having two collections
per day, than it is to hit peak concentrations in small watersheds where a maximum of four
samples per day are collected. Thus, as the title to Table 7.3 indicates the peak observed
concentrations are listed. It is likely that the values listed in Table 7.3 actually
underestimate the real peak values, due to the limitations of the sampling program, and that
the underestimates are larger for the smaller watersheds.
Additional scrutiny of the values for peak concentrations presented in Table 7.3 is
warranted. As noted for linuron, some of the peak values may be a consequence of spills or
improper pesticide handling (e.g., rinsing spray tanks into streams) rather than from field
runoff. Examination of adjacent samples and other parameters would help to distinguish
spills from field runoff. Since the peak values represent the extremes, the performance of
the analytical systems and confirming columns also needs close scrutiny.
It is evident from these studies that the peak concentrations for several of the herbicides
are sufficiently high that biological effects would be expected. Krieger (1986b) recently
reviewed literature on the biological effects of pesticides and noted the overlap between
pesticide concentrations which occur in Lake Erie tributaries and wetlands and
concentrations which have been noted to affect biological communities.
7.2.4. Concentration Exceedency Curves
In assessing potential effects of pesticide concentrations on either human or on aquatic
ecosystems neither peak concentrations nor TWMC are totally adequate. Information on the
duration of exposures to various concentrations allows a better assessment of potential
human health or ecosystem level effects. Consequently, the modeling efforts supported by the
U.S. EPA's Environmental Research Laboratory at Athens, Georgia attempt to first generate
chemographs of the type shown in Figures 7.1-7.12 and then to generate concentration
exceedency curves that can be compared with toxicity curves as shown in Figure 7.13
(Donigian et al. 1983). The duration of times a particular pollutant falls within the acute,
chronic and subchronic (below maximum acceptable toxicant concentration) ranges can then
be assessed.
In Figure 7.14 concentration exceedency curves for the six major herbicides are plotted
for each of the eight Lake Erie tributary monitoring stations. The data used for the exceedency
87
-------
plots include the April 15-August 15 periods for 1983, 1984 and 1985. The total number
of samples and the total number of days monitored for each station, using a maximum
duration for each sample of either 14 days or four days, are listed in Table 7.4. For the
exceedency curves, a 14-day maximum was chosen so that the 100% duration would
represent approximately the same total number of days for all of the stations. All of the
herbicide concentrations are plotted on the same scale (20 jj,g/L maximum) so that the
concentrations of various herbicides can be directly compared and so that different stations
can also be directly compared. It should be noted that these duration curves only apply to the
April 15-August 15 period and hence cover only about one third of the time (see Table 7.4
for the total days covered out of the three-year period). Since most of these herbicides are
virtually absent at time periods outside the selected time intervals, the duration curves for
the entire period would compress the curves of Figure 7.14 into the left 33% with
essentially no exposures during the added 67% of the time.
From viewing exposure duration curves, the following aspects of pesticide concentrations
in Lake Erie tributaries are evident.
1. For all of the tributaries atrazine residues are present for the longest
duration of time.
2. For Sandusky Basin stations, metolachlor concentrations are higher than
atrazine for the short durations with highest pesticide concentrations.
3. For the Maumee River and Lost Creek, alachlor concentrations are higher
than atrazine for the short durations with highest pesticide concentrations.
4. In general, as watershed size decreases, herbicide concentrations are higher
for the brief, high concentration periods, but drop off more quickly to low
concentrations and, except for atrazine, disappear more quickly.
5. The River Raisin, although also dominated by agricultural land use, has, in
general, much lower pesticide concentrations than northwestern Ohio
tributaries. This may be associated with the more permeable soils in the
River Raisin watershed.
6. The Cuyahoga River has very low pesticide concentrations, particularly for
the typical corn and soybean herbicides. Only a small proportion of the
Cuyahoga Basin is devoted to row crop agriculture.
7. The data suggest that the ratios of alachlor to metolachlor use in Lost Creek
and Rock Creek are very different, with Rock Creek having relatively more
metolachlor use than Lost Creek.
The differences in concentration duration curves, both in respect to individual compounds
and between stations, should provide useful information upon which to evaluate the
performance of pesticide runoff models. The shapes of curves reflect combinations of use
patterns, decay rates, solubility, soil type, and watershed size.
88
-------
Table 7.3. Maximum pesticide concentrations (ng/L) observed at river transport stations during the
years 1982, 1983, 1984, and 1985. Data of 1984 and 1985 corrected for recoveries less than
100%.
Year Maumee
River
Atrazine
1982
1983
1984
1985
Alachlor
1982
1983
1984
1985
Metolachlor
1982
1983
1984
1985
Cyanazine
1982
1983
1984
1985
Metribuzin
1982
1983
1984
1985
Linuron
1982
1983
1984
1985
Simazine
1982
1983
1984
1985
Carbofuran
1982
1983
1984
1985
Terbufos
1982
1983
1984
1985
Fonofos
1982
1983
1984
1985
Pendimethalin
1982
1983
1984
1985
14.04
5.415
1362
9.000
9.266
7.485
1764
5640
10.06
7033
1373
8.520
4.260
1.942
10.16
1.580
3.356
4200
1069
2530
2324
0390
1.379
0420
6926
00
0781
0840
—
0478
2.717
0.760
2250
0.030
0.021
0019
0.215
00
0.057
0024
—
0.269
0666
0.0
Sandusky
River
18.76
7.971
10 15
28.42
18.20
4.924
8.754
26.31
40.64
1670
1945
42.40
6.993
1.392
3.401
3.440
8208
2447
8085
4.750
3513
1.029
0.421
3860
3355
0005
1.424
1 320
—
0 500
1.588
1.610
0 104
0.0
0.0
0081
0050
0033
0.0
0086
0.371
0570
0.130
Honey
Creek
48.41
17.48
3746
29.23
74.99
8871
2201
27.06
90.80
2342
35.42
35.00
14.88
2.231
4.984
8.500
8241
3.423
6.319
7.350
13.12
4.300
1.930
5.910
3603
00
1.197
0.650
—
0425
5.747
3120
1 338
0.016
0.0
0075
0024
0.0
0.0
0.018
0.623
1 248
0.230
Rock
Creek
—
16.36
15.55
48.09
11.88
7137
20.19
—
6650
5715
1540
—
1 495
1.179
2.830
—
4.885
0.713
24.53
—
7.655
0.0
14 16
0.0
0.830
0590
—
0.226
6036
4.770
0.012
0.0
0.044
00
00
0.0
—
0.470
0.276
00
U. Honey
Creek
—
8492
5.743
225.9
—
8.688
0.817
2.250
—
29.02
2.145
25.10
—
1 336
0.857
86.10
—
6.937
0.730
3.020
—
1.220
00
3.890
—
0.015
0.102
1 180
—
0.569
1 634
2440
0047
00
0.022
0030
0.0
00
—
3.660
0055
0.0
Lost
Creek
3891
31.44
245.4
6.110
1846
34.44
31 84
1.610
12.71
13.28
7.894
6.260
10.08
10.25
23.09
2.510
5418
6.940
5.731
2.030
159.9
4.122
0.0
0.360
3.278
0.078
0.407
0.061
—
0.545
4054
0.640
0090
0.483
0.0
0.048
0.082
0052
0.060
00
—
3.455
0.346
0.310
River
Raisin
9.263
9.608
5.893
10.00
8.163
8.522
4.837
8.760
3.317
4.586
4.313
7.120
4288
2.667
3823
2.270
1.726
2.456
0761
1 690
2.788
0973
0.448
2.410
4952
0.022
0244
0730
—
0582
0.565
0.390
0.127
0341
00
00
0.205
0.027
0945
0091
—
0333
0080
00
Cuyahoga
River
0.742
1.436
1.031
3.010
0.603
1.164
0336
0.380
0733
5.683
0.0
0.850
6.618
1.357
0.085
0.540
0.526
1.050
0.204
0.038
7.683
10.93
2.692
6.310
10.77
0.429
2.875
1.810
—
1.976
1 454
0.880
0058
1 057
0.042
00
00
0.810
0.067
0056
—
1.057
0.139
0.0
89
-------
Table 7.4. Description of data sets used for pesticide concentration exceedency graphs. The
data include all samples collected between the April 15 and August 15 periods for the 1983,
1984 and 1985 water years.
River
N
Total Days with
14 day max/sample
Total Days with
4 day max/sample
Maumee R.
Sandusky R.
Honey Cr., Melmore
Rock Cr.
Honey Cr., N. W.
Lost Cr.
Raisin R.
Cuyahoga R.
165
179
233
207
121
127
69
53
387
389
391
381
390
385
366
346
312
325
340
297
272
264
217
171
z
o
O
Z
o
o
SUBCHRONIC REGION
DURATION
Figure 7.13. Lethality analysis of chemical concentration data. MATC = maximum
acceptable toxicant concentration. (After Donigian et al. 1983).
90
-------
7.2.5. Perspectives on Pesticide Concentration in Lake Erie Tributaries
Two recent studies suggest that the pesticide concentrations in northwestern Ohio
tributaries to Lake Erie are particularly high. Ciba-Geiby Corporation recently examined
existing data on atrazine concentrations in surface and groundwater (Ciba-Geigy 1986).
They utilized data from many sources including internal company monitoring programs and
state and federal studies. Only data from areas of significant atrazine use were included in the
analysis. Also, only data from fixed interval sampling programs were included, so as to avoid
any biases that might be introduced from seasonally stratified sampling programs. This latter
restriction excluded data from the Lake Erie tributary monitoring program. The pooled data
included 4,000 samples from which the average, the median, the 90th percentile, the 95th
percentile and the range were determined. Values below the detection limit were arbitrarily
assigned a value of 0.25 u,g/L when used to determine average values. These values are shown
in Table 7.5.
In order to compare the Lake Erie tributary data with the Ciba-Geigy summaries, we
modified the computer program we use to plot the concentration exceedency curves so that the
TWMC, the median (50% exceedency), the 90th percentile, the 95th percentile and the
range are reported. A sample output from the program is shown in Table 7.6. The program
has several options. The maximum time any single sample can be used to represent stream
concentrations is selectable. The time interval for data inclusion in the calculation can be
selected. Missing time within the selected time can be assigned arbitrary values such as zero
or the detection limit or can be ignored.
In Table 7.5, data from Lake Erie tributaries is listed for comparison with the
Ciba-Geigy summaries. The programs were run using the selection parameters listed in
Table 7.6 (i.e., maximum duration of 14 days, all data from the 1983, 1984 and 1985
water years, and 0.2 u.g/L for the unmonitored time period). The data in Table 7.5 have not
been corrected for recoveries less than 100%. The data differ from those in Table 7.2 in that
in Table 7.5 the values represent annual values whereas in Table 7.2 the values are for the
April 15-August 15 period.
The TWMC's for all of the Lake Erie tributaries were slightly higher than the Ciba-Geigy
average values. For the larger Lake Erie watersheds, the medians were also higher than the
Ciba-Geigy median. The 90th percentiles were higher in four out of six of the northwest
rivers, while the 95th percentiles in all of the Lake Erie tributaries were higher than the
Ciba-Geigy values. Maximum values for four of the tributaries exceeded the maximum values
from the pooled data set. While the Lake Erie values were generally higher than the national
averages, the similarity in the values is also very apparent.
In the second recent study, Monsanto Corporation monitored alachlor concentrations in
1985 in raw and finished tap water for 24 municipal water supplies in areas of high
alachlor use. The study involved analyses of weekly samples, each of which consisted of
weekly composites of seven daily samples. In Table 7.7, the maximum values of the weekly
composites are listed for each of the water supplies. The data were also used to estimate an
"annualized" mean concentration. Two values are listed for the annualized mean
concentration, the lower of which assigns zero concentrations to values less than the detection
limits and the higher of which assigns the detection limit (0.20 ng/L) to values lower than
the detection limit. The Monsanto study did not include any of the municipal water supplies
91
-------
WAUMEE RIVER
1 - atrazine
2 - alachlor
3 - metolaohlor
4 - metnbuzin
5 - cyanazina
6 - linuron
co
ro
3t J7 42 It 57 14
ol I i me concentration
71 4} «S 71
11 exceeded
D SANOUSKY RIVER
1 - alrazina
2 • alachlor
3 • metdachlor
4 • metnbuzin
5 • cyanazina
6 • linuron
HOtY CREEK
1 -atrazine
2 - alachlor
3 - metolachkx
4 • melribuzln
5 • cyanazlna
6 • linuron
100 oo
14 21 3t 57 42 (t S7 14 7') 4J
Parctnl ol tim« conctntration n
ij 71
100 04
D
ROCK CREEK
1 • etrazina
2 - alachlor
3 - metolachlor
4 • metnbuzin
5 • cyanazina
6 - linuron
o oo 14 29
Percent
21 17 42 It 57 14 71 43 85 71
ol time concintrotion 11 «xce«d«d
too oo
oo
14.21 21 57 42 It S7 14 71.43 IS 71
Percent of time concentration it exceeded
100.0
Figure 7.14. Concentration exceedency curves during the April 15-August 15 periods in 1983, 1984 and 1985 for major
herbicides at Lake Erie tributary stations. A. Maumee R.; B. Sandusky R.; C. Honey Cr.; D. Rock Cr.; E. Upper
Honey Cr.; F. Lost Cr.; G. River Raisin; H. Cuyahoga R.
-------
LOST CREEK
1 - atrazlne
2 - alachlor
3 • metolachlor
4 - metribuzin
5 - cyanazina
6 - llnuron
<8
G
RIVER RAISIN
1 • Btrazlne
2 • •lachlor
3 • melolacMof
4 - metribuzln
5 • cyanazln*
6 • llnuron
42 It 37. 14
concent rot Ion
7\.4J IS. 71
le exceeded
100 o
00
14 It
Pe rcen t
It S7 4J II 57 14
of time concent rot Ion
71. 4S IS 1\
le exceeded
(00 0
CO
CO
UPPER HONEY CREEK
1 • atrazln*
2 - alachlor
3 - melolachtor
4 • metrtbuzln
5 - cyanazln*
6 - llnuron
°0 »0
U'J'M Jl
Percent
of
»7
time
4J.M »7. U
concentration
It
. »J »»J»
exceeded
c
o
r§
cS
8*
100.1
H
CUYAHOGA RIVER
1 • auazln*
2 - alacHor
3 • melolachlor
4 - mstrlbuzln
5 - cyanazin*
6 • linuron
14,71
Percent
II 57 41.11 17. 14
of tine concent rot ion
71.43 19 71
(• exceeded
100
Figure 7.14. Continued.
-------
CD
Table 7.5. Comparison of atrazine concentrations in northwestern Ohio tributaries with preliminary data supplied by the Ciba-Geigy
Corporation on atrazine concentrations in surface and ground water for areas of atrazine use. The WQL data are not corrected for
recovery.
River
Maumee River
Sandusky River
Honey Creek
Rock Creek
Upper Honey Creek
Lost Creek
Ciba-Geigy Preliminary
Surface Water
Ground Water
(Sensitive Areas)
N
206
219
289
272
174
1 71
Data1
4000
987
Elapsed
Time
Days
895
902
894
895
895
902
Percent
Monitored
69%
71%
70%
69%
70%
70%
TWMC
1.70
2.00
3.05
1.49
1.25
2.43
1.04
0.49
50th
(median)
0.36
0.37
0.52
<0.25
<0.25
<0.25
<0.25
<0.25
Percentile
90th
2.97
3.87
5.51
2.48
2.02
2.15
2.25
0.25
95th
4.54
6.22
11.14
5.62
3.45
4.03
3.75
1.25
Range
0-1 1 .7
0-19.46
0-32.2
0-33.2
0-56.9
0-21 1
<0. 25-25
<0. 25-19. 7
1Data supplied via personal communications with Dr. Darryl Sumner, Ciba-Geigy Corporation, Greensboro, N.C. on February 11, 1987.
-------
Figure 7.6. Example of tabular output produced along with pesticide concentration
exceedency plots.
River: MAUMEE
Pesticide: Alachlor
Total number of samples:
Initial sample used: 8304041455
Final sample used: 8509161500
Elapsed time between initial and final samples:
Total time represented by samples:
Time not represented by samples:
Maximum time a sample represents:
206
896.004 days
631.032 days
264.972 days
14.000 days
DISTRIBUTION CHARACTERISTICS OF TIME-WEIGHTED CONCENTRATIONS
All concentrations are given in micrograms per liter
Time-weighted mean concentration:
0.742
Median concentration (50% percentile): 0.200 (at 48.81th percentile)
90th percentile concentration:
95th percentile concentration:
Minimum concentration:
Maximum concentration:
1.085 (at 89.45th percentile)
2.859 (at 94.70th percentile)
0.000
18.350
Conditions imposed on this run:
Data used: data between 8304041455 and 8509161500
Handling of missing time: missing time assigned a concentration of .2
95
-------
Table 7.7. Weekly maximum and annual mean concentrations of alachlor in raw and finished surface water
for the 1985 growing season.1
Location
State
Alachlor Concentration
Weekly Maximum
Raw Finished
Columbus OH 10.7
Davenport IA 0.68
Decatur IL <0.20
Greenville NC 0.26
Kankakee IL 0.85
Lexington MO 0.84
Marion IL <0.20
Michigan City IN <0.20
Monroe Ml <0.20
Mount Vernon IN 1.1
Muncie IN 2.5
Piqua OH 0.89
Quincy IL 0.54
Richmond IN 3.5
Roanoke Rapids NC <0.20
Toledo OH <0.20
University of Iowa IA 1.6
Wyaconda MO 0.24
Ypsilanti Ml <0.20
Overall 10.7
10.9
0.32
0.29
0.27
0.77
0.59
<0.20
<0.20
<0.20
1.0
2.8
0.63
0.70
3.6
<0.20
<0.20
1.8
<0.20
<0.20
10.9
Annualized Mean
Raw Finished
Bethany
Blanchester
Breese
Charleston
Clarinda
MO
OH
IL
IL
IA
<0.20
1.3
4.6
<0.20
<0.20
<0.20
1.1
4.4
<0.20
<0.20
0-0.20
0.16-0.32
0.29-0.44
0-0.20
0-0.20
0-0.20
0.15-0.31
0.29-0.42
0-0.20
0-0.20
1.3 -1.5
0.02-0.21
0-0.20
0.01-0.20
0.09-0.24
0.05-0.23
0-0.20
0-0.20
0-0.20
0.06-0.24
0.26-0.40
0.05-0.23
0.04-0.21
0.57-0.68
0-0.20
0-0.20
0.10-0.28
0.02-0.20
0-0.20
0.13-0.31
1.3 -1.4
0.01-0.20
0.03-0.20
0.01-0.20
0.08-0.24
0.03-0.21
0-0.20
0-0.20
0-0.20
0.05-0.23
0.25-0.38
0.04-0.22
0.06-0.23
0.57-0.69
0-0.20
0-0.20
0.11-0.29
0-0.20
0-0.20
0.12-0.30
1 Reference: Monsanto, 1986 as cited by U.S. EPA, 1986 (Alachlor Special Review Technical Support
Document Sept. 1986, Office of Pesticide Programs. U.S. EPA).
96
-------
located along the Sandusky or Maumee rivers.
In the Monsanto study, the highest weekly maximum and the highest annualized mean
concentrations of alachlor were observed in Columbus, Ohio. The Scioto River watershed,
which supplies much of the water for the city of Columbus, is very similar to the Maumee
and Sandusky watersheds with respect to both land use and soil types. The Monsanto study also
clearly shows that conventional water treatment does not remove alachlor to any appreciable
extent, since raw water and finished water had essentially the same concentrations. Similar
results have been observed for water treatment plants along the Sandusky and Maumee rivers
(Baker 1983d).
In Table 7.8 alachlor concentration data for the Lake Erie tributaries are summarized in
the same format as the atrazine data of Table 7.5. For these calculations a value of 0.20 u,g/l_
was assigned to all missing time for the calculation period. Samples with values less than
0.20 u,g/L were still allowed to represent their associated time intervals. The data in Table
7.8 have not been corrected for recoveries less than 100%. The above calculational
procedures for Lake Erie tributaries would tend to yield concentrations biased low relative to
the Monsanto values listed in Table 7.7. Nevertheless, the TWMC's for Lake Erie tributaries,
which would correspond to the annualized mean concentrations of the Monsanto data, are high
in comparison to the locations included in the Monsanto study. Only the Columbus, Ohio and
the Richmond, Indiana locations had mean concentrations in the same range as those of the
larger Lake Erie tributaries. The weekly maximum values of the Monsanto study would
correspond approximately to the 98th percentile. For the major Lake Erie tributaries the
95th percentile concentrations of alachlor are higher than the weekly maximum values in the
Monsanto study.
The above comparisons do suggest that the pesticide concentrations observed in Lake Erie
tributaries are higher than average for rivers draining agricultural watersheds. The
relatively fine textured soils of this region tend to seal rather quickly, resulting in large
amounts of surface runoff. These conditions may result in particularly severe runoff of
pesticides.
7.3. PESTICIDE LOADING IN LAKE ERIE TRIBUTARIES
7.3.1. Method of Calculating Pesticide Loads
Pesticide loads can be calculated in a manner similar to that used for nutrient and
sediments (see Section 6.2.1). Pesticide concentration data are often far more widely spaced
in time than nutrient data. Consequently, the flow data associated with the nutrient samples
are much more complete than would be flow data associated with pesticide samples.
Furthermore, pesticide samples are not necessarily collected at the same time as nutrient
samples. For these reasons, a new approach and associated computer programs were developed
for estimating pesticide loads from these data.
In developing the pesticide load calculation technique, the general concept of the
mid-interval summation approach was retained, but the characterization of a given time
interval by pesticide concentration and flow had to be decoupled. The process involves the
following steps:
97
-------
1. Choose a maximum interval of time that pesticide samples will be allowed to
represent. This value is used to set up a time window symmetrically about
the sample - the time it represents.
2. If the windows of two adjacent samples overlap, the window boundary for
both samples is reset to half-way between the two.
3. The resulting time window for a given pesticide sample is imposed on the
flow data stored in the nutrient file. Flows corresponding to the edges of the
window are calculated by linear interpolation. The total discharge for the
time window is calculated by the mid-interval technique, applied to all of
the individual flow measurements available within the time window. The
load associated with that pesticide sample is then calculated as the product of
the pesticide concentration and the total discharge. The sample loads
calculated in this way are summed to produce the load estimate for the
period of interest.
This approach does not change the basic approach to calculating the load, but allows the
more detailed flow data from the nutrient files to be completely utilized, producing a more
accurate load estimate.
When concentration data are infrequent in time, the measured load may represent a
smaller interval of time than the elapsed time, because many of the individual time windows
fail to overlap. For this reason, both the elapsed time and the monitored (i.e. "windowed")
time are reported, and discharges are calculated for each, subject to the limitation that no
flow observation may count for more than one day. When flow data are adequate but pesticide
data are inadequate, it is useful to extrapolate the loads to the total elapsed time by
multiplying the observed load by the ratio of the total discharge during that time to the
monitored discharge. This adjusted load estimate is reported along with the original estimate,
and is also expressed on a unit area basis. All of the above calculations are accomplished by a
computer program which generates tabular outputs (e.g., Table 7.9 and Appendix II).
Occasionally the flow data in the nutrient files are too infrequent, and the discharge from the
nutrient files is less than the discharge from the pesticide files. The latter is calculated with
a 14 day time limit instead of the one day time limit. For these cases, the extrapolated loads
are less than the observed loads. When the discharge record from the nutrient file covers
many fewer days than the elapsed number of days between the selected dates, the extrapolated
load may significantly underestimate the actual loads (e.g., Lost Creek in 1984 and 1985). In
these cases, the total loads should be adjusted to the USGS discharge for the elapsed time
interval. This option has not yet been added to the pesticide load calculation program.
There is little firm basis for the choice of an interval of time for a pesticide sample to
represent. Experimentation indicates that, if flow data are adequate and the pesticide
sampling program emphasizes high-flow sampling, the adjusted load estimates are not
strongly sensitive to the choice of this time interval.
7.3.2. Pesticide Loading Data
The observed pesticide loads for 1983-1985, as calculated by the above procedure, are
summarized in Table 7.10. The associated unit area loads are shown in Table 7.11. The
98
-------
Table 7.8. Means, percentiles and ranges of alachlor concentration in Lake Erie tributaries.
River
Maumee River
Sandusky River
Honey Creek
Rock Creek
Upper Honey Creek
co
00 Lost Creek
Raisin River
N
206
219
289
272
174
171
1 06
Elapsed
Time
Days
895
902
895
895
895
902
902
Percent
Monitored
69%
71%
70%
69%
70%
70%
68%
TWMC
M/L
0.77
0.78
1.18
0.35
0.25
0.97
0.51
50th
(median)
M/L
<0.20
<0.20
<0.20
0.00
0.14
0.04
0.20
Percentile
90th
H9/L
1.09
1 .03
1.76
0.26
0.40
0.28
0.54
95th
H9/L
2.86
3.45
4.73
0.66
0.66
1.04
1.39
Range
M/L
0.00-18.4
0.00-17.0
0.00-22.9
0.00-12.9
0.00-8.69
0.00-34.5
0.00-7.52
-------
Table 7.9: Pesticide loads for the Maumee River, USGS04193500,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 52 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated In this manner are as follows:
Extrapolated Unit area
Load Load
kg g/ha
0 0
249.423 .152134
2517.61 1.53559
2.35958 .143921E-02
0 0
704.763 .429865
2066.14 1.26023
47.1244 .287431E-01
1780.04 1.08572
1170.52 .713948
60.2476 .367475E-01
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metrlbuzin
Alachlor
Linuron
Metolachlor
Cyanazlne
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trlfluralin
Phorate
Propoxur
Aid! car b
Observed
Load
kg
0
235.161
2373.65
2.22466
0
664.465
1948
44.4298
1678.25
1103.59
56.8027
The monitored time is 116.434 days.
The monitored discharge is 681260 cfs-days, or 1667.04 million cubic meters.
The total discharge during this time is 722577 cfs-days,
or 1768.14 million cubic meters, and Is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.875 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 161 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
Is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
100
-------
Table 7.10. Observed pesticide loads, in kilograms, for the Michigan and Ohio tributaries to Lake Erie
for the years 1983, 1984 and 1985. See Appendix II Tables.
Year Maumee
River
Atrazine
1983
1984
1985
Alachlor
1983
1984
1985
Metolachlor
1983
1984
1985
Cyanazine
1983
1984
1985
Metribuzin
1983
1984
1985
Linuron
1983
1984
1985
Simazine
1983
1984
1985
Carbofuran
1983
1984
1985
Terbufos
1983
1984
1985
Fonofos
1983
1984
1985
Pendimethalin
1983
1984
1985
2347.6
5529.5
1035.0
1946.8
4989.1
404.9
1671.6
3491.3
906.0
1100.6
2903.5
170.5
663.7
3323.2
189.7
44.43
54.30
24.30
0.0
327.02
89.26
233.19
564.17
34.93
2.225
0.693
0.613
0.0
10.67
0.908
56.80
117.1
0.0
Sandusky
River
563.2
764.2
1208.3
179.9
432.0
767.5
635.1
603.8
1521.9
98.68
163.9
137.1
84.24
200.5
364.5
26.66
1.345
101.2
0.0
45.93
55.61
34.79
73.83
48.15
0.0
0.0
0.658
0.141
0.0
1.729
4.154
5.345
0.285
Honey
Creek
76.61
93.94
101.2
31.41
45.53
62.29
59.58
53.42
97.19
12.88
13.80
17.13
8.088
14.11
20.80
6.434
0.665
13.74
0.0
2.653
1.439
2.991
7.559
6.504
0.007
0.0
0.057
0.0
0.0
0.009
0.338
2.455
0.115
Rock
Creek
19.20
30.67
14.24
5.474
10.51
2.781
24.56
24.38
27.20
1.385
2.055
0.658
2.894
1.669
3.346
5.453
0.0
2.219
0.0
2.972
0.215
0.266
6.921
1.262
0.0
0.0
0.005
0.0
0.0
0.001
0.090
0.065
0.0
U. Honey
Creek
6.052
1.296
6.809
3.203
0.729
0.709
2.968
1.433
3.464
0.517
0.269
2.713
0.741
0.589
0.664
0.273
0.0
0.165
0.001
0.535
0.130
0.184
0.513
0.363
0.005
0.0
0.001
0.001
0.0
0.0
0.036
0.005
0.0
Lost
Creek
7.766
27.67
0.116
5.887
3.785
0.024
3.113
0.985
0.035
1.935
3.273
0.291
1.586
1.182
0.013
0.595
0.0
0.001
0.005
0.093
0.001
0.083
0.315
0.014
0.052
0.0
0.353
0.003
0.007
0.0
0.579
0.033
0.001
River
Raisin
412.3
373.3
220.0
257.3
260.5
136.0
154.6
110.1
103.0
107.6
202.7
45.04
73.58
45.95
21.11
31.39
0.458
32.40
0.131
11.74
17.05
40.16
3.342
4.023
6.738
0.0
0.0
0.764
5.515
1.027
8.129
2.782
0.0
Cuyahoga
River
73.80
63.24
145.7
13.23
22.12
3.79
85.21
9.075
35.11
56.31
4.397
21.53
21.81
32.79
0.466
12.42
83.94
57.26
4.982
150.3
114.5
161.1
75.02
21.60
14.29
2.746
0.0
13.86
4.553
3.310
12.01
0.542
0.0
101
-------
Table 7.11. Unit area pesticide loads, in grams per hectare, for the Michigan and Ohio tributaries to
Lake Erie for the years 1983, 1984 and 1985. Based on observed loads as presented in Table 7.10.
Year
Atrazine
1983
1984
1985
Alachlor
1983
1984
1985
Metolachlor
1983
1984
1985
Cyanazine
1983
1984
1985
Metribuzin
1983
1984
1985
Linuron
1983
1984
1985
Simazine
1983
1984
1985
Carbofuran
1983
1984
1985
Terbufos
1983
1984
1985
Fonofos
1983
1984
1985
Maumee
River
1.432
3.373
0.631
1.187
3.043
0.247
1.020
2.129
0.553
0.671
1.771
0.104
0.405
2.027
0.116
0.027
0.033
0.015
0.000
0.199
0.054
0.142
0.344
0.021
0.001
0.000
0.000
0.000
0.007
0.000
Sandusky
River
1.738
2.359
3.729
0.555
1.333
2.369
1.960
1.864
4.697
0.305
0.506
0.423
0.260
0.619
1.125
0.082
0.004
0.312
0.000
0.142
0.172
0.107
0.228
0.149
0.000
0.000
0.002
0.000
0.000
0.000
Honey
Creek
1.985
2.434
2.622
0.814
1.180
1.614
1.544
1.384
2.518
0.334
0.358
0.444
0.210
0.366
0.539
0.167
0.017
0.356
0.000
0.069
0.037
0.077
0.196
0.168
0.000
0.000
0.001
0.000
0.000
0.000
Rock
Creek
2.182
3.485
1.618
0.622
1.194
0.316
2.791
2.770
3.091
0.157
0.234
0.075
0.329
0.190
0.380
0.620
0.000
0.252
0.000
0.338
0.024
0.030
0.786
0.143
0.000
0.000
0.000
0.000
0.000
0.000
U. Honey
Creek
1.375
0.295
1.547
0.728
0.166
0.161
0.675
0.326
0.787
0.117
0.061
0.617
0.168
0.134
0.151
0.062
0.000
0.038
0.000
0.122
0.030
0.042
0.117
0.082
0.001
0.000
0.000
0.000
0.000
0.000
Lost
Creek
8.825
31 .443
0.132
6.690
4.301
0.027
3.537
1.119
0.040
2.199
3.719
0.331
1.802
1.343
0.015
0.676
0.000
0.001
0.006
0.106
0.001
0.094
0.358
0.016
0.059
0.000
0.401
0.003
0.008
0.000
River
Raisin
1.528
1.383
0.815
0.953
0.965
0.504
0.573
0.408
0.382
0.399
0.751
0.167
0.273
0.170
0.078
0.116
0.002
0.120
0.000
0.043
0.063
0.149
0.012
0.015
0.025
0.000
0.000
0.003
0.020
0.004
Cuyahoga
River
0.403
0.345
0.796
0.072
0.121
0.021
0.465
0.050
0.192
0.308
0.024
0.118
0.119
0.179
0.003
0.068
0.458
0.313
0.027
0.821
0.625
0.880
0.410
0.118
0.078
0.015
0.000
0.076
0.025
0.018
Pendimethalin
1983
1984
1985
0.035
0.071
0.000
0.013
0.016
0.000
0.009
0.064
0.003
0.010
0.007
0.000
0.008
0.001
0.000
0.658
0.037
0.001
0.030
0.010
0.000
0.066
0.003
0.000
102
-------
pesticide loads have considerable annual variability as expected for agricultural chemicals.
An important use of data such as these will be to compare export rates with use rates in the
study watersheds. A survey of 1986 pesticide usage is currently in progress by Dr. A. C.
Waldron of the Ohio State University Extension Service under a grant from the Great Lakes
National Program Office. When those data become available, they will be combined with data
from a similar survey conducted in 1982. This will allow calculation of the percent of
applied pesticide that is exported from large watersheds. The resulting export percentages
can be compared with similar data from plot and field size studies and the possible role of
instream pesticide processing can be assessed.
7.3.3. Significance of Pesticide Loads
The loadings of most current generation pesticides into Lake Erie, while large in
comparison with other toxic substances, also are not viewed as posing priority problems
since they are less persistent and have less of a tendency to bioaccumulate than the priority
toxic compounds. The major problems that may be associated with the loadings of these
compounds relate to resulting concentrations in the bays and wetlands. Although these
compounds are not persistent, their continuing large volume use makes them consistent
seasonal components of the chemical environment of streams, bays and wetlands.
Surface water export of pesticides generally accounts for a small portion (<1%) of the
dissipation/degradation pathways for pesticides applied to cropland. Consequently, the losses
of these compounds by surface water runoff are seldom of consequence to farmers.
103
-------
REFERENCES
Adams, J. R., T. J. Logan, T. H. Cahill, D. R. Urban, and S. M. Yaksich. 1982. A land resource
information system (LRIS) for water quality management in the Lake Erie Basin. J.
Soil and Water Cons. 37:45-50.
Baker, D. B. 1983a. Tributary loading of bioavailable phosphorus into lakes Erie and
Ontario. U.S. EPA, Region V, Chicago.
Baker, D. B. 1983b. Studies of sediment, nutrient, and pesticide loading in selected Lake
Erie and Lake Ontario tributaries, Part IV: Pesticide concentrations and loading in
selected Lake Erie tributaries. U.S. EPA, Region V, Chicago.
Baker, D. B. 1983c. Studies of sediment, nutrient, and pesticide loading in selected Lake
Erie and Lake Ontario tributaries, Part V: Sediment and nutrient loading summary.
U.S. EPA, Region V, Chicago.
Baker, D. B. 1983d. Herbicide contamination in municipal water supplies of northwestern
Ohio. Draft final report to the Joyce Foundation, Chicago, III. Heidelberg College,
Tiffin, Ohio. 33 p. + appendix.
Baker, D. B. 1984. Fluvial transport and processing of sediments and nutrients in large
agricultural river basins. U.S. Environ. Protection Agency, ERL, Athens, Georgia.
EPA-600/3-83-054.
Baker, D. B. 1985a. Regional water quality impacts of intensive row-crop agriculture: a
Lake Erie Basin case study. J. Soil and Water Conserv. 40:125-132.
Baker, D. B. 1985b. Impacts of cropland runoff on nutrient and pesticide concentrations in
river systems. Proceedings of a symposium, May 1985. The Conservation
Foundation, Washington, D.C. pp. 63-80.
Baker, D. B. 1986. Nutrient, sediment and pesticide runoff from the Lost Creek watershed,
Defiance County, Ohio. Defiance Soil and Water Conservation District, Defiance,
Ohio. 41 p.
Baker, D. B. 1987. Rural nonpoint pollution in the Lake Erie Basin: Overview. IN: Effects
of Conservation Tillage on Groundwater Quality - Nitrates and Pesticides. Lewis
Pub., Chelsea, Ml. pp. 65-91.
Baker, D. B., K. A. Krieger, R. P. Richards, and J. W. Kramer. 1985a. Effects of intensive
agricultural land use on regional water quality in northwestern Ohio. pp.
201-207. IN: U.S. EPA, Perspective on nonpoint source pollution. EPA
440/5-85-001.
Baker, D. B., K. A. Krieger, R. P. Richards, and J. W. Kramer. 1985b. Gross erosion rates,
sediment yields, and nutrient yields. IN: Perspective on nonpoint source pollution.
EPA 440/5-85-001.
104
-------
Baker, J. L. and J. M. Laflen. 1983. Water quality consequences of conservation tillage. J.
Soil and Water Cons. 38(3) :186-193.
Cahill, T. H., R. W. Pierson, Jr., and B. R. Cohen. 1979. Nonpoint source model calibration
in Honey Creek watershed. U.S. Environ. Protection Agency, ERL, Athens, Georgia.
EPA-600/3-79-054. 134 p.
Ciba-Geigy Corporation. 1986. Briefing paper on atrazine. Analysis of chronic rat feeding
study results. Greensboro, NC. 12 p.
Clark, E. H. II, J. A. Haverkamp, and William Chapman. 1985. Eroding soils: The off-farm
impacts. Washington, D.C., The Conservation Foundation. 252 p.
Conservation Tillage Information Center. 1985. Lake Erie conservation tillage
demonstration projects: evaluating management of pesticides, fertilizer, residue to
improve water quality. Conservation Tillage Information Center, Fort Wayne,
Indiana. 20 p.
Conservation Foundation. 1986. Agriculture and the environment in a changing world
economy, an issue report. Washington, D.C. 66 p.
Crosson, P. 1981. Conservation tillage and conventional tillage: a comparative assessment.
Soil Cons. Soc. Am., Ankeny, Iowa.
Crosson, P. and A. T. Stout. 1983. Productivity effects of cropland erosion in the United
States. Washington, D.C., Resources for the Future. 103 p.
Donigian, A. S., J. C. Imhoff, and B. R. Bicknell. 1983. Predicting water quality resulting
from agricultural nonpoint source pollution via simulation - HSPF. pp.
200-249. IN: Schaller, F.W., and G.W. Bailey (eds.). Agricultural management
and water quality. Iowa State Univ. Press, Ames, Iowa.
Dysart, B. C. III. 1985. Perspectives on nonpoint source pollution control: a conservation
view. pp. 16-18. IN: U.S. Environ. Protection Agency. Perspectives on nonpoint
source pollution. Proc. national conference, Kansas City, Missouri, May 19-22,
1985. EPA-440/5-85-001. Washington, D.C. 514 p.
General Accounting Office. 1981. Better monitoring techniques are needed to assess the
quality of rivers and streams. Washington, D.C. 121 p.
Gianessi, L.P., H.M. Peskin, P. Crosson, and C. Putter. 1986. Nonpoint-source pollution:
Are cropland controls the answer? J. Soil and Water Cons. 41(4):215-218.
Great Lakes Phosphorus Task Force. 1985. United States task force plan for phosphorus load
reductions for non-point, and point sources on Lake Erie, Lake Ontario, and Saginaw
Bay. U.S. Environ. Protection Agency, Chicago, Illinois. 176 p.
Hallberg, G. R. 1986. From hoes to herbicides: Agriculture and groundwater quality. J.
Soil and Water Cons. 41(6):357-364.
105
-------
Hileman, B. 1982. Herbicides in agriculture. Environ. Sci. and Technol.
16(12):645A-650A.
Hinkle, M. K. 1983. Problems with conservation tillage. J. Soil and Water Conserv.
38:201-206.
Holden, P. W. 1986. Pesticides and groundwater quality: Issues and problems in four states.
Washington, D.C., National Academy Press, 124 p.
Honey Creek Joint Board of Supervisors. 1982. Honey Creek watershed project,
1979-1981. U.S. Army Corps of Engineers, Buffalo District, Buffalo, New York.
International Joint Commission. 1978a. Great Lakes Water Quality Agreement of 1978. IJC
Canada and the U.S., Ottawa. 52 p.
International Joint Commission. 1978b. Environmental management strategy for the Great
Lakes system. Final report from PLUARG. Windsor, Ontario. 115 p.
International Joint Commission. 1980. Pollution in the Great Lakes Basin from land use
activities. Rep. to the governments of the United States and Canada. Windsor,
Ontario. 141 p.
International Joint Commission. 1983. Nonpoint source pollution abatement in the Great
Lakes Basin: an overview of post-PLUARG developments. Windsor, Ontario. 129 p.
Johnson, H. P., and J. L. Baker. 1982. Field-to-stream transport of agricultural chemicals
and sediment in an Iowa watershed: Part I. Data base for model testing
(1976-1978). Project Summary. U.S. Environ. Protection Agency, Athens,
Georgia. EPA-600/S3-82-032.
Journal of Soil and Water Conservation. 1985. Nonpoint Water Pollution: A Special Issue.
J. Soil and Water Conserv. 40(1). 176 p.
Journal of Soil and Water Conservation. 1983. Conservation Tillage: A Special Issue. J.
Soil and Water Conserv. 38 (3). 319 p.
Kramer, J. W., and D. B. Baker. 1985. An analytical method and quality control program for
studies of currently used pesticides in surface waters, pp. 116-132. IN: J. K.
Taylor and T. W. Stanley, Eds. Quality assurance for environmental measurements,
ASTM STP 867, Amer. Soc. Testing and Materials, Philadelphia, PA.
Krieger, K. A. 1986a. Conservation tillage adoption in two north central Ohio watersheds.
U.S. EPA, Region V, Chicago.
Krieger, K. A. 1986b. App. II. A primer on agricultural herbicides and insecticides and
their effects on aquatic biota, pp. 82-113. IN: Baker, D.B. Pesticide loading into the
St. Clair River and Lake St. Clair in 1985. U.S. Environ. Protection Agency,
Chicago, Illinois.
106
-------
Lake, J., and J. Morrison. 1977. Environmental impact of land use on water quality. Final
Rep. on the Black Creek Project (Tech. Rep.). U.S. Environ. Protection Agency,
Chicago, Illinois. EPA-905/9-77-007-B. 280 p.
Logan, T. J. 1978. Maumee River Basin pilot watershed study. Int. Ref. Group on Great
Lakes pollution from land use activities. IJC, Windsor, Ontario. 96 p.
Logan, T. J. 1981. Pesticide use in the Lake Erie basin and the impact of accelerated
conservation tillage on pesticide use and runoff losses. U.S. Army Corps of
Engineers, Buffalo District, Buffalo, New York. 30 p.
Logan, T. J. and J. R. Adams. 1981. The effects of reduced tillage on phosphate transport
from agricultural land. U.S. Army Corps of Engineers, Buffalo District, Buffalo,
NY. 25 p.
Logan, T. J., D. R. Urban, J. R. Adams, and S. M. Yaksich. 1982. Erosion control potential
with conservation tillage in the Lake Erie Basin: estimates using the universal soil
loss equation and the Land Resource Information System (LRIS). J. Soil and Water
Cons. 37:50-55.
Logan, T. J., J. M. Davidson, J. L Baker and M. R. Overcash. 1987. Effects of Conservation
Tillage on Groundwater Quality-Nitrates and Pesticides. Lewis Pub., Chelsea, Ml.
292 p.
McGuinness, J. L., L. L. Arnold, and W. M. Edwards. 1971. Relation of rainfall, energy and
streamflow to sediment yield from small and large watersheds. J. Soil and Water
Cons. 26:233-235.
Macknis, J. 1985. Chesapeake Bay nonpoint source pollution. Proceed, of a national
conference, May 19-22, 1985, Kansas City, MO. EPA 440/5-85-001, pp.
165-171 .
Miltner, Richard J., C. A. Fronk, T. F. Speth. 1987. Removal of alachlor from drinking
water. Proceedings Nat'l. Conf. on Env. Eng. American Soc. of Civil Engineers,
Orlando, FLA. Drinking Water Research Div., U.S. EPA, Cincinnati, OH.
Morrison, J. B. 1984. Lake Erie demonstration projects evaluating impacts of conservation
tillage on yield, cost, environment. Nat. Assoc. Conserv. Districts. 17 p.
National Agricultural Chemicals Association. 1985. Health guidance levels for agricultural
chemicals in groundwater. Washington, D.C., 6 p.
Odum, Eugene P. 1969. The strategy of ecosystem development. Science, v. 164:262-269.
Ohio Environ. Protection Agency. 1985. State of Ohio phosphorus reduction strategy for Lake
Erie. Columbus, Ohio. 89 p. + app.
OECD. 1985. The state of the environment. Organization for Economic Co-Operation and
Development, Paris, France. 271 p.
107
-------
Overcash, M. R. and J. M. Davidson, eds. 1980. Environmental impact of nonpoint source
pollution. Ann Arbor, Ann Arbor Science pub. 449 p.
Pierce, Francis J. 1985. A systems approach to conservation tillage: Introduction. IN: A
systems approach to conservation tillage, edited by Frank M. D'ltri. Chelsea, Ml.,
Lewis pub. pp. 3-14.
Porterfield, G. 1972. Techniques of water-resouces investigations of the United States
Geological Survey. Book 3, Ch. C3. Computation of fluvial-sediment discharge. U.S.
Gov. Printing Office, Washington, D.C. 66 p.
Rast, W., and G. F. Lee. 1983. Nutrient loading estimates for lakes. J. Environ. Eng.
109(2):502-517.
Richards, R. P. 1983. Monte Carlo investigation of strategies for sampling event-response
rivers for loading calculations. U.S. EPA, Region V, Chicago.
Richards, R. P. and Jim Holloway. 1987. Monte Carlo studies of sampling strategies for
estimating tributary loads. Water Resources Research. In press.
Richards, R. P. 1985b. Monte Carlo studies of sampling strategies for estimating tributary
loads: II. Effects on bias and precision due to differences among watershed sizes and
the transported materials being monitored. U.S. EPA, Region V, Chicago.
Richards, R. P. 1985. Estimating the extent of reduction needed to satistically demonstrate
reduced nonpoint phosphorus loading to Lake Erie. J. Great Lakes Res.
11(2):110-116.
Richards, R. P., J. W. Kramer, D. B. Baker, and K. A. Krieger. 1987. Pesticides in
rainwater in the northeastern United States. Nature. Vol. 327, No. 6118, 14 May
1987.
Schaller, F. W. and G. W. Bailey, eds. 1983. Agricultural management and water quality.
Iowa State University Press, Ames, Iowa.
Shelly, P. E. 1986. Description and summary of new rainfall and agricultural nonpoint
source data bases. U.S. EPA, Washington, D.C. 28 p. and Appendices.
Shindel, H. L., J. H. Klingler, J. P. Mangus, and L E. Trimble. 1986. Water resources data
Ohio, Water Year 1985. Vol. 2. St. Lawrence River Basin statewide project data.
U.S. Geological Survey, Columbus, Ohio. 281 p.
Smullen, J. T., J. L. Taft, and J. Macknis. 1982. Nutrient and sediment loads to the tidal
Chesapeake Bay system. Chesapeake Bay program technical studies: A synthesis.
U.S. EPA, Washington, D.C. pp. 150-265.
U.S. Army Corps of Engineers, Buffalo District. 1979. Lake Erie wastewater management
study methodology report. Buffalo, New York. 146 p.
108
-------
U.S. Army Corps of Engineers, Buffalo District. 1982. Lake Erie wastewater management
study. Final report. Buffalo, New York. 225 p.
U.S. Environmental Protection Agency. 1985a. Perspectives on nonpoint source pollution.
Proc. national conference, Kansas City, Missouri, May 19-22, 1985.
EPA-440/5-85-001. Washington, D.C. 514 p.
U.S. Environmental Protection Agency. 1985b. Five year program strategy for Great Lakes
National Program Office, 1986-1990. EPA-905/9-85-002. Chicago, U.S. EPA.
49 p.
U.S. Environmental Protection Agency. 1986. Technical supplement to Alachlor Position
Document 2/3. Office of Pesticide Programs, Washington, D.C.
Verhoff, F. H., D. A. Melfi, S. M. Yaksich, and D. B. Baker. 1978. Phosphorus transport in
rivers. Tech. Rep. Series. U.S. Army Corps of Engineers, Buffalo District, Buffalo,
New York. 88 p.
Waddell, T. E., ed. 1985. The off-site costs of soil erosion. Proc. symposium held in May
1985. The Conservation Foundation, Washington, D.C. 284 p.
Watson, . 1985. Methods for estimating phosphorus loading from rivers entering
the Great Lakes. (Draft report submitted to IJC-GLNPO).
Wauchope, R. D. 1978. The pesticide content of surface water draining from agricultural
fields-a review. J. Environ. Quality 7(4):459-472.
Woodmansee, Robert. 1984. Comparative nutrient cycles of natural and agricultural
ecosystems: A step toward principles. IN: Agricultural ecosystems unifying
concepts, edited by Richard Lowrance et al. pp. 145-156.
Wible, Lyman F. 1980. High flow water quality standards. IN. : Seminar on Waste Quality
Management Trade-Offs : Point Source vs. Diffuse Source Pollution.
EPA-905/9-80-009. pp. 329-333.
Zison, S. W. 1980. Sediment-pollutant relationships in runoff from selected agricultural,
suburban, and urban watersheds, a statistical correlation study. U.S. Environ.
Protection Agency, ERL, Athens, Georgia. EPA-600/3-80-022. 136 p.
109
-------
APPENDIX 1
NUTRIENT AND SEDIMENT TRANSPORT
AT
LAKE ERIE TRIBUTARY MONITORING STATIONS:
1982 -1985 WATER YEARS
111
-------
APPENDIX 1 - NOTES
Contents
This Appendix provides a summary of nutrient and sediment transport data at eight
tributary stations in the Lake Erie Basin for the 1982-1985 water years. For each station
and water year, the summary consists of an annual hydrograph, a sedigraph and chemographs
for total phosphorus, soluble reactive phosphorus, nitrate plus nitrite-nitrogen and specific
conductance. Also, on the facing page of each set of graphs, a summary of monthly discharge
and monthly sediment and nutrient loads is presented.
Additional Parameters
In addition to the parameters shown in this Appendix, all of the samples have also been
analyzed for ammonia nitrogen, total Kjeldahl nitrogen and silica. Chemographs and monthly
loading data for these parameters can be obtained from the Water Quality Laboratory,
Heidelberg College.
Data Availability
Data containing the concentrations of nutrients and sediments in individual samples are
available in the U.S. EPA's STORET data system. The data are stored under the corresponding
U.S. Geological Survey station number. Data can also be supplied directly on magnetic tape
from the Water Quality Laboratory, Heidelberg College, Tiffin, Ohio 44883.
Pesticide Data (see Appendix 2)
Data on spring runoff of major, currently used herbicides and insecticides are also
available for the transport stations, beginning with the 1982 water year. The pesticide data
are available in the STORET system or directly from the Water Quality Laboratory.
Sampling and Analytical Methods and Calculational Procedures
The sampling methods, analytical procedures and calculational methods are described in
the accompanying main report. They have also been described in more detail in the following
report.
Baker, D.B. 1984. Fluvial Transport and Processing of Sediment
and Nutrients in Large Agricultural River Basins. U.S. Environmental
Protection Agency, Environmental Research Laboratory, Athens, Georgia.
EPA-600/3-83-054. January 1984.
112
-------
Sampling Locations
Locations of Lake Erie Tributary monitoring stations operated by the Water Quality
Laboratory at Heidelberg College for the 1982-1985 water years are shown below:
MICH.
RAISIN R
BASIN
INO. I
/HURON ft. BASIN
'SANDUSKY R. BASIN
OH.
UYAHOGA'
'ft. BASIN)
i
i
i
PA.
Sampling Locations:
River Raisin near Monroe, Ml
Maumee R at Bowling Green, OH water intake
Sandusky H near Fremont, OH
Cuyahoga R. at Independence, OH
Lost Cr. tributary near Defiance, OH
Rock Cr. at Tiffin, OH
Honey Cr. at Melmore, OH
Upper Honey Cr. at New Washington, OH
Historical Nutrient and Sediment Data
Sampling programs of the type illustrated in this Appendix were initiated by the Water
Quality Laboratory in 1974. The following table lists the stations and years for which
nutrient and sediment data are available.
Transport Stations
Sandusky River Stations
1 Fremont
2 Mexico
3 Upper Sandusky
4 Bucyrus
Sandusky River Tributaries
5. Wolf Creek, East
6. Wolf Creek, -West
7. Honey Cr , Melmore
8. Honey Cr., New Wash
9. Tymochtee Creek
1 0 Broken Sword Cr.
1 1 . Rock Creek
Other Lake Erie Tributaries
12. Maumee River
Raisin
"ahoga
-.
U S Geological
Survey
Station Number
04198000
04197000
04196500
04196000
04192450
04197300
04197100
04197020
04196800
04196200
04197170
04193500
04176500
04208000
04195500
04199000
04185440
Drainage
Area
Km2
3,240
2,005
722
230
213
171.5
386
440
593
217
88.0
16,395
2,699
1,831
1,109
961
11.3
Mean Annual Discharge
Years of
Record
57
55
57
40
5
5
7
3.908
19
5
3
58
43
52
51
31
4
m3/s
27 75
16.62
6.967
2.461
1.82
1 34
3.908
(0.445)a
4.956
2 45
---
139.5
19.85
23.14
9.091
8.496
cm
270
262
28.5
33 8
27.0
24.6
32.0
(32.0)a
263
35.5
---
26.8
23.2
39.8
25.9
27.9
---
Chemical
Sampling
Period
1974-85
1974-81
1974-81
1974-81
1976-81
1976-81
1976-85
1979-81,
1983-85
1974-81
1976-81
1983-85
1975-80,
1982-85
1982-85
1981-85
1974-78
1974-79
1982-85
Number of
Samples
Analyzed
5092b
2178
2973
2998
2425
2419
5075b
2701
2471
2512
1496b
3608b
1115b
1882b
1856
2027
2158b
/ Creek at Melmore
jrthe
1 986 water year.
113
-------
List of Tables
The following tables for the indicated stations and water years include:
1. USGS discharge for each month and the entire water year.
2. The ratios of the monthly USGS discharge to the discharge observed in the monitoring program.
3. The number of samples analyzed each month.
4. The monthly and water year loads of suspended solids (SS), total phosphorus (TP), soluble
reactive phosphorus (SRP), nitrate plus nitrite-nitrogen (NO23-N), total Kjeldahl nitrogen (TKN),
and Chloride (Cl).
Table
1
2
3
4
5
6
7
8
9
10
1 1
12
13
14
15
16
17
18
19
20
22
23
24
25
26
Station
Maumee
Maumee
Maumee
Maumee
Sandusky
Sandusky
Sandusky
Sandusky
Cuyahoga
Cuyahoga
Cuyahoga
Cuyahoga
Raisin
Raisin
Raisin
Raisin
Honey Creek
Honey Creek
Honey Creek
Honey Creek
Rock Creek
Rock Creek
Upper Honey Creek
Upper Honey Creek
Upper Honey Creek
Water Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1984
1985
1983
1984
1985
Page
117
119
121
123
125
127
129
131
133
135
137
139
141
143
145
147
149
151
153
155
159
161
163
165
167
114
-------
List of Figures
The following figures for the indicated stations and water years include annual hydrographs,
sedigraphs and chemographs for total phosphorus, soluble reactive phosphorus, nitrate plus nitrite-
nitrogen, and conductivity.
Figure
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Station
Maumee
Maumee
Maumee
Maumee
Sandusky
Sandusky
Sandusky
Sandusky
Cuyahoga
Cuyahoga
Cuyahoga
Cuyahoga
Raisin
Raisin
Raisin
Raisin
Honey Creek
Honey Creek
Honey Creek
Honey Creek
Rock Creek
Rock Creek
Rock Creek
Upper Honey Creek
Upper Honey Creek
Upper Honey Creek
Lost Creek
Lost Creek
Lost Creek
Lost Creek
Water Year
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1982
1983
1984
1985
1983
1984
1985
1983
1984
1985
1982
1983
1984
1985
Page
116
118
120
122
124
126
128
130
132
134
136
138
140
142
144
146
148
150
152
154
156
158
160
162
164
166
168
169
170
171
115
-------
9LI.
CO
NJ
fl) 3
rt d
(0 (1)
CD ^<
Qj O.
ra
(D
a.
H-
f
SU
rt
h(
H-
(D
3
rt
n
g"
i-i
I
S1
rt
CD
01
n>
(D
en
o
en
Ul
o
H-
0. 0
TOTAL P
0. 6
(mg/1)
1. 2
1. 8
SEDIMENT (mg/1)
621 1243
5 =°
fn >
M "Q
71
-<
m
>
S.
1864 0
FLOW (cfs)
31775 63551 95326
CONDUCTANCE (umhos)
0 299 598 898
NITRATE (mg/1)
0.0 4.5 9.0
SOL. REACT.
13.5 0.00 0.07
P (mg/1)
0.14 0.21
09
10
> 5
3 -<
-------
Table 1. Monthly loads and discharge for the Maumee River for water year 1982. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
uses
Discharge
312.67
207.92
329.96
632.33
872.23
2898.23
807.53
380.83
341.43
269.69
31.21
23.43
Flow
Ratio
1.371
1.387
1.043
0.801
0.964
1.403
1.008
1.040
1.053
1.108
1.212
1.511
Nof
Samples
33
21
39
30
29
54
58
46
37
60
36
36
SS
41485
7127
29714
162744
47908
519923
191453
165879
51629
61042
2005
962
TP
116.4
42.0
83.3
360.7
223.7
1153.5
346.7
239.7
117.6
121.7
6.6
5.0
SRP
33.16
17.11
29.46
67.53
97.07
182.75
55.84
29.19
33.40
28.50
0.82
1.60
NO23-N
1728
878
1948
3289
2006
7769
3563
2824
2828
1523
4
<1
TKN
523.6
242.9
382.4
1027.5
1213.2
4825.6
1437.9
868.2
458.1
454.2
43.7
25.9
CL
8723.4
8860.8
13425.9
23659.8
23109.4
42624.7
17554.9
11557.4
10159.3
5444.4
1285.4
1405.4
Totals
7107.47
479
1281870
2816.9
576.42
28361
11503.0
167811.0
-------
rt d
3- fi
n> n>
LJ
* &
fa 3
rf C
0> Pi
•< s-
fl> *<
m a.
H H
• o
tQ
l-i
I
tn
tD
QJ
H-
ua
^
I
g
rt-
»-!
H-
tl)
ft
O
(O
I
t-j
rl-
SC
TOTAL P
0.0 0.4
(mg/1)
0. 8
1. 1
SEDIMENT (mg/1)
0 266 532
798
FLOW (cfs)
16382 32764
49146
c
in
en
C/3
ID
UJ
Ln
O
O
CL
C
l-i
H-
CONDUCTANCE (umhos)
0 278 557
835
NITRATE (mg/1)
0.0 3.8 7.6
SOL. REACT. P (mg/1)
11.4 0.00 0. 05 0. 10 0. 15
-------
CD
Table 2. Monthly loads and discharge for the Maumee River for water year 1983. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
23.19
384.74
976.38
224.68
291.81
336.54
1069.93
959.05
209.68
217.50
37.47
17.34
Flow
Ratio
1.617
1.042
1.024
1.044
1.048
1.045
1.021
1.065
1.026
1.120
1.263
1.310
Nof
Samples
35
88
55
38
35
44
63
45
34
36
38
35
SS
950
34635
278021
9174
13220
32941
243090
274559
25045
30689
2570
1756
TP
5.0
123.0
562.7
54.1
67.7
80.1
517.7
531.6
53.1
71.7
8.0
5.2
SRP
1.28
32.31
61.61
15.65
20.96
8.27
62.83
49.86
13.17
17.00
1.63
1.11
NO23-N
<1
1723
5266
1102
1528
1893
6971
4769
1088
1861
29
3
TKN
25.9
589.7
2311.9
309.0
351.6
442.3
2162.6
2041.8
316.4
363.9
49.2
21.9
CL
1820.6
16508.2
25741.6
7378.4
11557.5
12470.7
22632.2
18416.8
6797.0
4888.5
1610.7
1017.4
Totals
4748.30
546
946649
2079.9
285.70
26233
8986.0
130840.0
-------
021-
ft
Cu
3
rt
h
H-
n>
n-
o
(D
§
I
31
rt
3"
gf
g
VD
LO
O
O
a
c
H-
io _
00 m
*. o>
Si
' 5
SEDIMENT (mg/1)
0 356 712
1067 0
FLOW (cfs)
16583 33165
49748
CONDUCTANCE (umhos)
0 354 708
NITRATE (mg/1)
1062 0.0 3.6 7.2
SOL. REACT. P (mg/1)
10.8 0.00 0.07 0,14 0.21
8~
U>
CD
37
X
m
>
-------
Table 3. Monthly loads and discharge for the Maumee River for water year 1984. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
84.41
616.69
1012.32
76.03
789.77
1136.95
1308.90
541.69
165.07
55.20
59.00
32.55
Flow
Ratio
1.058
0.909
0.904
1.015
0.822
1.038
0.939
0.908
1.023
1.446
1.342
1.711
Not
Samples
36
53
37
35
34
40
66
37
34
36
40
34
SS
3786
137804
128897
286
60073
183798
432218
103840
17607
2741
3328
1930
TP
18.0
343.0
448.3
15.0
251.5
427.8
848.7
232.4
43.4
8.8
12.2
6.5
SRP
5.42
48.26
66.96
10.93
86.68
64.15
53.89
38.88
9.90
1.14
2.06
0.95
N023-N
273
4837
6118
335
3374
7336
7874
4160
982
76
78
7
TKN
101.8
1386.9
1806.6
104.0
1504.4
1935.6
2850.1
863.7
189.6
59.1
76.1
42.4
CL
5401.7
17371.3
20496.0
4350.3
26552.7
22843.8
24007.1
13064.8
4412.6
2820.9
3168.3
2021.0
Totals
5878.54
482
1076310
2655.5
389.22
35449
10920.1
146510.0
-------
n- c
m a>
S3
Oi
I
in
m
iQ
t-i
PJ
P)
R
I
CD
rt
o>
01
0. 0
TOTAL P
4. 1
(mg/l)
8. 3
12.4 0
SEDIMENT (mg/l)
2989 5978
8967 0
o
FLOW (cfs)
34051 68102 102153
f
ff
(D
B)
(D
n>
G
W
n
en
Ol
O
O
^
H-
CONDUCTANCE (umhos) NITRATE (mg/l) SOL. REACT. P (mg/1)
0 366 732 1098 0. 0 6.5 13.1 19.6 0.00 0.06 0.11 0.17
R
3 -<
-------
ro
co
Table 4. Monthly loads and discharge for the Maumee River for water year 1985. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
80.04
183.49
307.00
564.38
990.55
1027.50
788.55
94.28
156.85
55.51
51.35
66.48
Flow
Ratio
1.302
1.065
0.946
0.847
0.843
0.946
0.936
1.200
1.011
1.494
1.418
1.385
Not
Samples
36
34
34
31
42
54
49
37
33
35
35
35
SS
6802
13460
29498
103556
245853
185258
278980
6323
16174
4330
2480
4347
TP
22.4
46.3
81.6
280.7
498.7
440.0
445.2
16.3
36.5
9.8
7.6
10.8
SRP NO23-N
151
957
2054
3746
3892
6438
4644
190
1579
405
11
49
TKN
103.1
253.5
391.1
1159.7
1613.6
1798.1
1684.5
112.0
209.4
79.4
70.7
86.6
CL
4646.1
8468.2
13586.7
15164.1
26412.3
23304.2
14551.8
4798.3
7226.7
2473.2
3016.5
4012.5
Totals
4365.94
455
897064
1895.8
24116
7561.6
127661.0
-------
ua
c
to
el-
s' >
a
M C
IX) fil
00 M
n> o
p<; fa
(D t3
D>
(D
I
ill
o>
3
ri-
tC
o>
TOTAL P (mg/1)
. 0 0. 6 1.2 1.
S.
SEDIMENT (mg/1)
8 0 621 1243 1864
FLOW (cfs)
31775 63551
95326
i-i
I
51
3-
(D
c
en
03
O
O
O
-------
ro
en
Table 5. Monthly loads and discharge for the Sandusky River for water year 1982. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
40.22
45.25
130.95
171.34
235.33
408.89
158.13
80.44
49.70
62.49
3.98
3.52
Flow
Ratio
1.008
1.000
1.072
1.850
1.043
1.020
1.651
1.137
1.133
1.053
1.042
1.012
Nof
Samples
36
35
35
28
39
63
37
35
45
46
34
36
SS
1592
933
12084
7615
17626
170720
74595
83410
10012
14657
142
89
TP
6.4
5.8
33.7
45.5
59.8
241.4
110.8
91.9
16.6
26.2
0.5
0.4
SRP
2.77
2.20
10.09
16.48
20.48
18.57
6.77
5.57
3.69
3.16
0.09
0.07
N023-N
127
132
544
519
388
1132
526
747
484
391
<1
<1
TKN
40.9
40.7
138.9
201.2
293.6
932.2
404.4
319.7
69.1
110.6
3.7
3.0
CL
1149.2
1797.1
4232.4
4415.9
3587.7
6833.6
3468.7
1745.3
1571.0
1311.2
195.6
213.6
Totals
1390.24
469
393473
639.0
89.95
4990
2557.9
30521.1
-------
921-
TOTAL P (mg/1)
0.0 0.4 0.9
1.3
SEDIMENT (mg/1)
0 391 7B1
o
y
to
3o
1172 0
R"
FLOW (cfs)
36B6 7371
11057
CONDUCTANCE (umhos)
0 347 693
NITRATE (mg/1)
1040 0. 0 4. 3 8. 6
SOL. REACT. P
12. 9 0. 00 0. 07
o
(mg/1)
0. 13
0.20
-------
Table 6. Monthly loads and discharge for the Sandusky River for water year 1983. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
3.41
48.97
145.76
30.93
40.56
24.45
113.60
166.96
19.09
43.29
3.90
8.68
Flow
Ratio
0.976
1.021
5.000
0.993
1.029
1.061
1.165
1.142
0.915
1.062
1.164
1.212
Not
Samples
35
63
21
28
32
35
40
44
38
45
36
29
SS
38
4595
19824
330
996
423
19611
40587
1372
18562
137
311
TP
0.2
14.9
51.1
2.1
5.8
2.2
41.1
82.4
3.1
24.9
0.5
1.1
SRP
0.03
3.55
11.08
1.08
1.69
0.39
5.33
8.15
0.78
3.22
0.14
0.22
NO23-N
<1
239
772
125
192
69
746
996
74
402
1
5
TKN
2.1
62.0
217.3
17.6
32.2
17.6
188.8
327.5
18.9
94.3
3.1
7.0
CL
192.1
1845.9
4963.4
1289.2
1526.2
1170.0
3052.5
3549.7
707.6
935.6
199.8
370.0
Totals
649.60
446
106787
235.4
35.66
3621
988.5
19802.0
-------
821-
U3
Q, C
C »-!
^ CD
rt
y >
a a
M C
kO £U
CD *->
B) QJ
rt hj
(D 0
hj iQ
f
Oi
rt
*-!
H-
(D
ft
O
V
(I
I
BJ
*O
S1
rt
(D
CL
tn
C
cn
w
ID
OD
O
O
O
TOTAL P (mg/1)
0. 0 0. 6 1.2
1. 8
SEDIMENT (mg/1)
0 522 1044
1SE6 0
FLOW (cfs)
9061 18121
27182
CONDUCTANCE (umhos)
0 341 683 1024 0
8~
NITRATE (mg/1)
0 4.0 8.1
SOL. REACT. P (mg/1)
12.1 0.00 0.12 0.24
0.36
<° -.
OJ m
*. o
O
C
00
m
-------
to
Table 7. Monthly loads and discharge for the Sandusky River for water year 1984. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
75.10
254.35
220.37
76.32
532.52
356.06
243.73
118.19
25.59
17.99
12.08
8.18
Flow
Ratio
0.991
0.981
1.101
0.500
0.951
1.119
1.008
0.977
0.941
1.066
1.082
1.129
Not
Samples
41
49
24
14
32
34
39
40
45
36
51
37
SS
12952
31375
15570
7319
40443
54651
91369
19018
4796
1529
642
279
TP
31.8
107.5
71.9
29.4
214.2
114.8
145.8
43.5
8.1
3.5
1.9
0.9
SRP
6.27
18.31
12.11
7.20
80.30
18.39
10.32
7.76
0.73
0.63
0.24
0.06
NO23-N
412
1191
823
337
1125
1663
947
520
91
122
16
2
TKN
127.3
403.5
252.4
78.3
1019.9
470.5
512.8
160.6
33.3
20.8
11.1
8.0
CL
1798.6
5487.6
4077.5
2942.8
9444.9
5873.4
3671.7
2507.4
739.7
579.1
453.0
351.0
Totals
1940.47
442
279943
773.3
162.31
7251
3102.0
37926.6
-------
oei
"d
H*
-------
co
Table 8. Monthly loads and discharge for the Sandusky River for water year 1985. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
uses
Discharge
4.78
24.62
74.80
81.54
206.66
118.08
114.20
37.05
63.00
20.86
13.89
10.29
Flow
Ratio
1.200
1.446
1.083
0.471
0.693
1.063
0.965
1.036
1.018
1.022
1.015
1.184
Not
Samples
36
25
33
28
40
49
44
38
61
40
35
35
SS
58
1010
12582
7826
28350
20658
23880
3112
34194
3003
1300
794
TP
0.4
4.3
27.8
24.0
64.8
41.3
46.1
7.4
43.4
5.8
2.6
2.0
SRP NO23-N
<1
110
466
360
880
681
722
313
779
86
10
14
TKN
3.8
24.3
110.7
83.7
290.6
169.9
191.6
42.1
143.8
27.4
14.3
10.1
CL
222.5
1024.8
3104.6
3210.4
6757.6
3508.8
2854.2
1538.1
1758.3
659.5
534.2
333.7
Totals
769.78
464
136767
269.9
4422
1112.2
25506.6
-------
361.
"d
(->•
"a
a c
P VD
VD P)
CO M
ro
(D O
H iO
3-8
PJ J3*
en
n>
CL
p.
U3
t-i
I
0>
3
&
g
rt
H
H.
ro
rt
O
n>
I
H)
O
I
I
H-
rl
i-f
a
en
n
en
o
CD
O
O
O
0.0
TOTAL P
2.5
(mg/1)
5.0
7.5
SEDIMENT (mg/1)
4464 8928
00
to
APR MAY
ER YEAR
13392 0
FLOW (cfs)
2542 5084
7626
CONDUCTANCE (umhos)
0 555 1110 1664
0.0
<£>
00
SO
|
m
»
m
a
NITRATE
2.3
(mg/1)
4.6
6.9
SOL.
0.00
REACT.
0.21
P (mg/1)
0.41 0.62
-------
co
CO
Table 9. Monthly loads and discharge for the Cuyahoga River for water year 1982. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
45.26
57.58
102.84
106.77
144.96
173.36
90.91
46.34
63.11
45.39
17.60
25.67
Flow
Ratio
1.660
1.103
2.562
1.443
1.072
1.072
1.063
1.061
0.983
4.166
1.141
Nof
Samples
0
21
37
17
58
64
36
44
45
47
44
34
SS
3168
2488
28830
50266
56619
48749
4704
11704
18284
4374
2527
3825
TP
22.6
16.1
51.3
77.5
81.7
64.7
22.3
26.3
38.9
17.6
11.8
16.5
SRP
14.03
3.75
6.72
8.48
8.65
8.60
7.50
7.71
10.69
6.82
4.92
6.97
NO23-N
158
101
194
190
175
196
138
136
141
100
61
90
TKN
58.8
69.7
135.8
128.3
265.6
296.3
117.3
66.1
95.9
46.5
24.5
37.0
CL
4278.2
5460.2
11566.1
8935.1
15002.9
14836.9
8336.3
4903.5
5194.1
3913.6
1795.3
2570.4
Totals
919.79
447
235538
447.3
94.84
1682
1341.7
86792.6
-------
TOTAL P (mg/1)
0.0 0.7 1.4
2. 1
SEDIMENT (mg/1)
0 630 1261
1891
FLOW (cfs)
3440 6880
o. c
C if
f-( (D
P-
3 I-1
iQ O
rt
(D >
I-1 3
0> C
CD P)
U) M
« 3-
fl) t<
rt CL
(D n
(n
(D
a.
H-
I
H
H-
(B
rt
(D
§
'a
3-
B1
rt
(D
o
50
H-
(D
a
w
o
to
o
CD
O
O
O
CONDUCTANCE (umhos)
0 530 1061
10320
NITRATE (mg/1)
1591 0.0 2.5 4.9
0.51
-------
co
en
Table 10. Monthly loads and discharge for the Cuyahoga River for water year 1983. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
17.25
78.21
139.03
71.16
75.80
109.87
128.04
129.24
53.67
64.56
23 47
29.70
Flow
Ratio
0.622
1.095
1.084
1.139
1.057
1.039
1.081
1.215
1.093
1.322
0.837
0.948
Not
Samples
37
62
49
34
37
50
53
31
37
29
40
43
SS
466
9709
19418
3604
8625
18585
21756
13033
22458
36476
2669
7347
TP
7.6
37.1
55.2
23.9
27.8
47.9
47.6
45.0
29.5
31.5
13.7
19.0
SRP
5.68
11.22
16.45
9.63
8.46
10.08
6.62
8.99
5.90
5.26
7.28
6.84
NO23-N
86
164
264
159
143
168
156
158
132
121
86
99
TKN
26.5
108.0
128.6
58.2
83.2
163.0
157.4
115.1
88.4
123.8
24.9
38.6
CL
1856.6
6125.1
13073.4
7512.8
7994.0
10864.8
8197.7
7953.3
3904.7
3424.5
2510.6
2845.9
Totals
920.00
502
164145
385.6
102.41
1737
1115.6
76263.4
-------
961-
•n
a c
c n
>i d>
H-
3 t-1
03 1-1
rt
fl> >
l-i 3
(O C
00 W
p, t<
ft a
(D t-i
K o
en
n>
p.
s-
(D
I
I
rt
S"
o
P)
?
(D
o
en
O
CD
O
O
O
TOTAL P (mg/1)
0.0 0.5 1.0
a> m
*. a>
l\
SEDIMENT (mg/1)
1.5 0 454 907
o
1361 0
FLOW (cfs)
2985 5976
8964
CONDUCTANCE (umhos)
0 830 1660
NITRATE (mg/1)
2490 0.0 2.5 5.0
SOL. REACT. P (mg/1)
7.5 0. 00 0. 18 0.36
0.54
-------
co
-vl
Table 11. Monthly loads and discharge for the Cuyahoga River for water year 1984. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
uses
Discharge
24.13
107.72
111.89
35.57
139.48
169.65
104.95
181.77
48.07
37.13
37.58
32.06
Flow
Ratio
1.078
1.011
0.994
1.032
1.263
0.988
1.037
1.045
1.839
1.008
1.044
0.995
Not
Samples
36
41
35
33
32
44
35
37
21
42
42
37
SS
952
18929
12762
835
15923
46210
5489
41885
6641
6662
5431
1406
TP
12.9
53.6
38.3
17.3
52.6
65.8
25.1
76.6
21.3
19.3
21.9
14.4
SRP
7.41
12.92
11.13
7.20
9.73
10.39
6.11
9.00
6.71
5.00
10.37
9.35
NO23-N
84
193
203
67
188
221
140
222
122
107
135
107
TKN
23.0
138.3
119.9
115.7
252.1
285.7
136.4
214.9
51.5
43.0
42.6
32.6
CL
2371.3
7659.9
10957.3
7366.5
18285.4
18814.7
8800.6
10652.9
3785.5
3478.3
3716.3
3207.0
Totals
1030.01
435
163123
419.1
105.31
1789
1455.7
99095.7
-------
8CI-
H-
3
rt
fl> >
I-1 3
us c:
CD (11
Ul M
n- a
(D H
M o
ID (U
tn
tD
I
c
rt
i-i
O
(D
I
n
c
H-
I
c?
O
CD
O
O
O
0. 0
TOTAL P (mg/1)
2.6 5. 1
7.7
f> ~
m
X
SEDIMENT (mg/1)
2540 5081
7621 0
o
FLOW (cfs)
3316 6632
9948
CONDUCTANCE (umhos)
NITRATE (mg/1)
847
1694
<*> ~
t» •
Ul
a
?
2541 0.0
SOL. REACT. P (mg/1)
0.00 0.41 0.82 1.23
-------
CD
Table-12. Monthly loads and discharge for the Cuyahoga River for water year 1985. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jut
Aug
Sep
USGS
Discharge
37.96
84.91
95.80
73.73
132.76
171.70
126.07
51.14
55.51
33.08
37.64
21.41
Flow
Ratio
0.980
1.054
1.495
1.012
1.104
1.071
1.001
1.030
1.034
0.998
1.068
1.044
Not
Samples
38
36
32
34
43
51
34
42
45
42
43
35
SS
3901
6711
7005
5338
113541
63134
19666
8228
5816
3524
10050
710
TP
20.9
33.2
37.3
25.2
166.2
76.3
34.8
26.0
23.5
16.0
19.4
7.0
SRP N023-N
116
149
203
150
258
248
169
121
123
104
111
78
TKN
44.9
97.1
286.6
77.0
283.7
278.8
126.5
65.3
55.7
66.5
69.9
20.2
CL
3433.5
6119.0
8938.1
10624.1
24814.2
14432.3
9622.7
5391.4
4944.9
3301.9
3639.0
2312.0
Totals
921.70
475
247625
485.7
1830
1472.3
97573.0
-------
a c
c if
if n>
i-1-
lQ 00
rt
(D >
M 3
ID C
00 B>
SI 3"
&» ^<
rt £L
0) if
i< t-i
(t> 01
£U W
ff iT
If
flj
9)
s.
rt
if
p-
a>
TOTAL P Img/l)
3.0 0.4 0.8 1.3
to
CD
11
SEDIMENT (mg/l)
0 165 329 494
FLOW (cfs)
8484 16968
25452
Hi
O
If
n>
o
en
cn
o
o
(D
CD
(O
f
>
TO
CONDUCTANCE (umhos) NITRATE (mg/l) SOL. REACT. P (mg/l)
0 345 690 1035 0.0 5.1 10.2 15.3 0.00 0.06 0.13 0.19
-------
Table 13. Monthly loads and discharge for the River Raisin for water year 1982. Discharge is given in million cubic meters, and loads are given
in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
127.27
65.30
42.51
42.24
31.88
336.81
127.00
55.99
41.51
31.85
12.18
10.73
Flow
Ratio
...
—
...
...
—
0.853
0.961
1.074
1.084
1.049
1.061
1.177
Nof
Samples
0
0
0
0
0
41
35
32
35
27
27
26
SS
—
...
...
—
28662
6330
6296
1673
1470
332
285
TP
—
...
86.4
18.5
15.0
7.3
6.0
2.7
2.2
SRP
—
...
18.84
4.19
3.56
2.74
2.23
0.59
0.75
N023-N
---
547
299
311
155
100
8
9
TKN
—
---
428.0
116.8
82.1
35.3
25.2
10.5
10.2
CL
—
...
4737.9
3500.4
1949.0
1483.6
1107.9
571.2
597.0
Totals
925.26
223
45047
138.2
32.89
1428
708.0
13946.9
-------
a c
c i
t-j (D
H'
3 I-1
rt
ID »
M 3
10 C
00 0)
CO M
£ 3-
(1) ><
rt- &
(D i-(
tl O
ro
Cb
H-
I
0)
Cb
c
rt
^i
H-
n>
3
o
HI
o
rt
(D
PJ
H-
cn
a
w
O
O
*.
I-1
-J
o
o
TOTAL P
0.0 0.3
(mg/1)
0.6
0. 9
SEDIMENT (mg/1)
0 220 441
661
CD n
OJ CD
FLOW (cfs)
2986 5972
8959
CONDUCTANCE (umhos) NITRATE (mg/1)
0 299 599 898 0.0 4.0 8.0
-------
Table 14. Monthly loads and discharge for the River Raisin for water year 1983. Discharge is given in million cubic meters, and loads are given
in metric tons.
GO
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
13.42
60.42
132.68
46.84
53.06
72.84
173.86
184.69
52.87
52.69
20.72
10.35
Flow
Ratio
1.138
1.381
1.210
1.317
1.245
1.159
1.235
1.310
1.372
1.524
1.407
1.229
Nof
Samples
27
24
27
27
24
27
26
26
26
26
27
25
SS
331
2144
12098
600
1195
5281
15399
34169
3954
3240
742
393
TP
2.5
11.6
31.1
5.0
8.0
14.7
42.7
80.1
11.2
11.0
3.8
2.0
SRP
1.32
4.26
5.39
2.19
3.14
1.99
5.23
8.53
2.63
3.07
1.39
0.45
NO23-N
16
222
743
158
203
308
755
565
274
284
23
8
TKN
8.1
58.0
177.0
38.0
54.3
82.0
216.0
315.4
59.9
64.4
18.6
9.3
CL
615.0
2546.2
5044.4
1857.8
2052.8
2485.7
4487.4
3552.4
1610.5
1470.9
815.2
536.5
Totals
874.44
312
79547
223.8
39.59
3560
1101.0
27074.8
-------
a H-
c *
H C
H- I-!
3 o
rt
(D
a>
-
s;
fu
rt
a>
Qj to
H 00
O •*
(D
01 hj
H 0)
in
I
(D
rt
o
(D
TOTAL P (mg/1)
0.0 0.4 0.7
? 5
3 '
5
m "
& - 5
SEDIMENT (mg/1)
1.10 251 502
o
FLOW (cfs)
1787 3574
5361
CONDUCTANCE (umhos)
0 354 709
NITRATE (mg/1)
1053 0.0 2.8 5.6
8~
SOL. REACT. P (mg/1)
8.4 0. 00 0. 06 0. 11 0. 17
o
B>
H-
Ul
a -<
en m
O >
CO TO
01
(Tv
O
O
-------
Table 15. Monthly loads and discharge for the River Raisin for water year 1984. Discharge is given in million cubic meters, and loads are given
in metric tons.
01
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
14.98
54.45
130.92
28.02
110.48
122.11
119.19
92.11
45.12
12.27
12.34
11.05
Flow
Ratio
1.206
1.427
1.153
0.956
1.033
1.243
1.175
1.286
1.335
1.386
1.356
1.239
Nof
Samples
27
26
25
27
24
27
27
25
26
27
26
26
SS
371
4201
6808
46
6779
12894
11895
10440
3332
365
247
260
TP
2.8
14.0
28.1
2.7
21.7
34.9
27.3
25.7
9.2
1.9
2.3
2.2
SRP
1.26
3.80
5.42
1.31
4.79
4.44
2.70
2.67
1.40
0.20
0.63
0.75
NO23-N
21
255
659
50
413
500
580
485
170
7
25
13
TKN
9.6
71.0
149.8
27.4
129.1
203.6
166.8
124.7
47.6
11.4
10.8
8.2
CL
703.7
2247.0
4066.7
1176.5
2794.4
3472.3
3583.2
2685.4
1416.8
713.3
721.7
678.7
Totals
753.04
313
57636
172.8
29.37
3177
959.9
24259.7
-------
CONDUCTANCE (umhos) NITRATE (mg/1)
0 364 728 1092 0.0 3.3 6.5
i
o
I
rt
tt>
(D
i-i
H-
U>
H-
a
CO
o
o
,£>
O
O
SOL. REACT. P (mg/1)
9.8 0. 00 0. 05 0. 11 0. 16
8"
TOTAL P (mg/1) SEDIMENT (mg/1)
0.0 0.3 0.6 0.9 0 195 390 585
FLOW (cfs)
4459 8917
z
o
o
m
o
1
o
PI
o
00
Ol
m
>
»
VI
ni
•n
U)
PI
-o
13376
-------
Table 16. Monthly loads and discharge for the River Raisin for water year 1985. Discharge is given in million cubic meters, and loads are given
in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
18.42
34.90
48.76
112.93
140.34
201.38
156.95
29.98
27.20
17.65
14.08
14.14
Flow
Ratio
1.400
1.434
1.178
1.441
0.968
1.209
1.362
1.652
1.475
1.515
1.373
1.430
Nof
Samples
26
25
29
26
24
28
23
26
26
24
28
25
SS
436
791
3881
10060
16342
16486
18940
748
1053
429
375
356
TP
3.8
5.1
10.4
32.8
50.9
37.7
44.6
4.5
5.4
2.7
2.5
2.0
SRP NO23-N
36
151
279
617
393
1024
696
71
117
45
15
11
TKN
13.3
31.5
56.0
162.7
228.5
261.3
216.9
29.7
23.0
16.5
13.1
10.4
CL
904.3
1581.7
2235.4
3910.0
3384.1
5703.6
3954.1
1325.1
1182.8
818.3
744.3
715.5
Totals
816.73
310
69898
202.5
3454
1062.9
26459.2
-------
;?. TOTAL P (mg/1) SEDIMENT (mg/O FLOW (cfs)
rt "§ 0
y HI
(5 (C 0
o
(—>»-» ~*
ro • z
to o
% £
B) 5 o
rt 3 "
(DC °
h[ Eu
M c.
*ro 3- z
{U *•<
• h$ (0 1*1
O CD *
iQ ro
S * 5
s- ! ".
> r*i ^
33 "D
W »
CD -<
?- i >
U3 3D -<
« fe"
D- z
3 c
a r-
1 1
S" s
3 -D
rt
§•
(H
0 1.6 3. 3 4
S
f
r^~
r
£
i
E
r
rnMniirTAkirr ^,,~i,~-\
.9 0
0
o
z
o
.
D
m
o
z
m
D
.
£
C_
i
C
l-
I
u>
m
•o
1921 3841 5762 0
»
H>
^—
?-
h
o
0
-4
z
o
<
o
m
o
c_
i
-n
m
CD
X
>
T>
y>
|"
t_
I
c.
c
r-
>
c
0
U)
m
•o
900 1800 2700
;»
,?
^— ~~m
^-
f
s*~
r
I
S1
o
ff co
3 ^
W m
O
M
10
o
o
0 334 668 1002 0.0 10.3 20.6 30.9 0.00 0.11 0.22 0.33
8
-------
CD
Table 17. Monthly loads and discharge for Honey Creek at Melmore for water year 1982. Discharge is given in million cubic meters, and loads
are given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
1.89
4.15
13.44
18.93
30.69
48.98
19.45
4.44
6.02
9.35
0.19
0.16
Flow
Ratio
1.012
1.012
0.878
0.703
0.826
1.045
1.502
1.030
1.105
1.033
1.424
0.518
Not
Samples
35
35
43
41
39
64
42
60
61
56
28
34
SS
49
47
554
944
1295
18023
5786
5272
4240
3502
5
3
TP
0.2
0.6
2.4
5.0
6.8
28.5
11.2
5.3
4.7
4.8
<1.0
<1.0
SRP
0.07
0.24
0.97
1.26
2.36
2.37
0.72
0.28
0.37
0.63
0.01
0.02
NO23-N
6
19
79
68
55
129
72
41
62
63
<1
<1
TKN
1.7
4.4
14.5
26.1
34.8
115.4
42.1
19.6
15.9
19.9
0.1
0.2
CL
41.2
143.7
424.9
373.5
388.2
673.9
383.2
93.0
114.7
118.5
5.7
5.3
Totals
157.70
538
39719
69.6
9.30
595
294.6
2765.9
-------
091-
rt C
rr M
CD CD
ID CD
OD •
£ >
DJ 3
rt 3
CD e
hj JD
m :r
[U *<
S
I
ut
n>
f
H.
c
rt
fB
rt
&
CD
O
iQ
t-i
I
Hi
O
O
CD
(D
a
r/i
to
o
.c.
o
o
Qi
$
H-
TOTAL P (mg/1)
0.0 0.3 0.7
1.0
SEDIMENT (mg/1)
0 312 623
935
L
FLOW (cfs)
647 7293
1940
CONDUCTANCE (umhos)
0 289 579
Jg -n
Oo m
CJ OD
868
NITRATE (mg/1)
0.0 6.7 13.4
SOL. REACT. P (mg/1)
20. 1 0.00 0. 13 0.26 0.38
-------
Table 18. Monthly loads and discharge for Honey Creek at Melmore for water year 1983. Discharge is given in million cubic meters, and loads
are given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Totals
USGS
Discharge
0.13
7.99
21.98
2.94
7.11
3.66
15.39
23.81
1.74
3.23
0.18
0.56
88.73
Flow
Ratio
0.615
1.010
1.040
1.050
1.079
1.229
1.167
1.021
1.119
1.105
1.246
0.993
Nof
Samples
35
62
55
38
36
33
41
52
40
45
36
39
512
SS
1
779
2132
28
249
63
2190
5134
152
1029
4
76
11838
TP
<0.1
2.8
7.5
0.3
1.3
0.4
5.2
12.0
0.3
1.5
0^2
31.5
SRP
0.01
0.77
1.30
0.13
0.28
0.14
0.75
1.22
0.10
0.24
0.01
0.04
5.01
NO23-N
<1
49
112
12
41
14
95
130
8
44
2
508
TKN
0.1
12.4
35.3
1.9
7.2
2.9
25.2
53.9
1.8
6.8
0.1
0.7
148.3
CL
4.8
236.1
478.0
87.5
181.2
117.0
300.8
388.4
42.8
67.6
4.6
15.0
1923.9
-------
(mg/1)
I
31
g
o
M
CD
in
a
s
en
o
i-"
ID
O
O
H-
1. 6
» •*
CE m
*. a
m "
> E
SEDIMENT (mg/1)
0 399 797
1196 0
FLOW (cfs)
1006 2011
3017
CONDUCTANCE (umhos)
0 284 569 853
NITRATE (mg/1)
3.0 6.4 12.9
SOL. REACT. P (mg/1)
19.3 0.00 0.21 0.41 0.62
-------
Ol
co
Table 19. Monthly loads and discharge for Honey Creek at Melmore for water year 1984. Discharge is given in million cubic meters, and loads
are given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
7.57
30.46
23.01
4.72
17.09
44.33
24.98
12.53
1.25
1.54
0.52
0.20
Flow
Ratio
1.096
1.035
1.023
0.617
0.621
0.998
0.906
1.046
1.369
1.251
1.773
0.659
Nof
Samples
40
48
27
34
38
46
41
40
34
39
59
35
SS
783
2980
1148
146
1999
6044
6154
1863
28
236
35
4
TP
2.8
12.1
6.4
2.3
6.1
14.1
13.3
5.1
0.2
0.5
0.1
<0.1
SRP
0.89
2.91
1.35
1.28
1.38
2.24
0.97
1.38
0.05
0.13
0.04
0.02
NO23-N
50
144
90
12
49
195
90
50
4
19
2
<1
TKN
12.3
47.6
27.1
9.1
28.5
63.8
46.5
19.5
1.0
2.4
0.5
0.2
CL
155.8
585.1
372.0
92.4
213.3
542.6
293.6
216.5
27.4
45.5
13.2
8.0
Totals
168.21
481
21419
63.0
12.65
707
258.6
2565.5
-------
fSI-
ft C
y H
(T> fD
00 •
Ul
* "S
B) 5
rt 3
CD C
H PJ
&l
•§•
I
a.
H-
(B
rt
O
I
>S
f-j
I
Hi
O
I
(D
n>
n>
G
cn
cn
O
O
a
c
0.0
TOTAL P (mg/l)
0.5 1.0
1.5
SEDIMENT (mg/l)
388 776
1164 0
oo
01
m
TO
C
FLOW (cfs)
1392 2783
4175
CONDUCTANCE (umhos) NITRATE (mg/l) SOL. REACT. P (mg/l)
0 321 642 963 0.0 10.6 21.2 31.8 0.00 0.12 0.24 0.37
TO -o
3>
-<
i I
-------
en
en
Table 20. Monthly loads and discharge for Honey Creek at Melmore for water year 1985. Discharge is given in million cubic meters, and loads
are given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
0.68
2.16
10.92
9.47
29.82
15.15
13.77
3.41
2.28
1.00
2.00
0.77
Flow
Ratio
1.163
1.212
1.148
1.398
0.949
1.020
0.995
1.051
1.284
1.291
1.319
1.390
Not
Samples
36
34
36
33
41
46
46
43
45
41
41
40
SS
5
55
1739
515
3227
1957
2657
595
224
136
276
53
TP
0.1
0.4
4.6
3.1
8.6
5.1
6.6
1.5
0.5
0.3
0.7
0.2
SRP NO23-N
1
15
85
60
136
86
89
62
35
4
6
2
TKN
0.6
2.5
20.0
14.1
46.1
23.3
28.9
6.4
2.7
1.4
2.8
0.9
CL
23.8
75.3
326.8
222.9
452.2
320.8
257.3
118.7
74.8
23.8
35.8
14.9
Totals
91.43
482
11439
31.8
580
149.7
1947.2
-------
991
£! TOTAL P (mg/1) SEDIMENT (mg/1) FLOW (cfs)
ft£ °
ro 2 °
I-" K)
ID M "
CD • g
<•» <
£S "
^ B>
"§ * *
0) ^< ~*
g W D
l-j 5 E"
(U > >
*O ~ •"
3* 5
s g 5.
&5 5
LQ ^
1 l
S «-"
3 c
Oj *~
§ 5
rt o
4
S" S
3 -D
ft
fr .
0 0. 5 1.0 1
.
—
_
^
r
1
t^—
\
1
>•
5 0
o
o
z
o
<
o
n
o
-
>
z
-n
0)
i
>
T)
3)
E
>
•<
c.
C
Z
c.
F
>
c
a
v>
•o
457 914 1371 0
k
^_
*z-
"-
c=~
o
n
z
0
<
o
m
o
>
z
•n
CD
£
3)
>
-D
•x
|
c_
L.
F
>
c
n
i/>
•o
192 385 577
^
?
:=-
^
h
NITRATE (mg/1)
0 340 679 1019 0.0 8.5 16.9
f
B1
a
8
en
o
.c.
10
-j
m
"i
m
"° >
-<
SOL. REACT. P (mg/1)
25.4 0.00
R"
0. 19
-------
8SI
^ TOTAL P (mg/1) SEDIMENT (mg/1) FLOW (cfs)
ft C 0
ro n> o
o
P> KJ -<
<£> NJ
00 • Z
5] •>
£1) 3 O
rt 3 m
ro d °
>•! B)
H1 c_
(D 3* z
fl) *-
01 -< 3
fD "^
a > •
P- 5° 5
"§• i
3 5=
5. £
3
& i
H-
ro
3 m
ft •"
. 0 1.4 2.9 4
'>
^^^
>
/
^3
f
^
^*
^
~S-
^
^
S
7-
v»— —
<
i
r
r
•
.3 0
0
o
^
Z
o
m
o
c.
Z
m
03
1
30
T)
5
c.
C
Z
e_
F
_
C
O
.
(/)
m
571 1142 1713 0
>
^»*^™-^
»
'
S-"
*
^_
—
V
^-
w
o
n
-4
r
o
o
o
z
"**
n
l"
,
>
•o
I
c.
C
Z
•
c
r-
C
C)
™
Pi
•o
522 1043 1565
^^
j""
^~
g=a«=
3
B____^^^^
.r
>
^.
r^
»—
I
Ml
O
ro
ro _
*
G
U)
tn
m
O >
*. 33
QJ
CONDUCTANCE (umhos)
0 547 1094
n
NITRATE (mg/1)
1641 0.0 2.2 4.4
SOL. REACT. P (mg/1)
6. 7 0. 00 0. 07 0. 14 0. 22
-------
Table 22. Monthly loads and discharge for Rock Creek for water year 1984. Discharge is given in million cubic meters, and loads are given in
metric tons.
en
CO
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
0.91
7.30
5.62
0.88
5.49
10.46
6.48
4.72
0.53
0.29
0.27
0.18
Flow
Ratio
1.199
0.948
1.076
1.290
0.722
0.769
0.851
0.722
0.845
3.017
0.895
0.644
Nof
Samples
39
51
33
35
33
65
69
54
34
36
40
34
SS
141
1184
454
17
1703
2377
3276
1538
13
6
10
2
TP
0.35
3.90
1.80
0.24
2.53
3.75
4.80
2.60
0.04
0.03
0.04
0.02
SRP
0.062
0.601
0.318
0.109
0.213
0.330
0.064
0.214
0.008
0.005
0.017
0.007
NO23-N
4.5
20.1
12.8
1.6
10.1
33.9
14.6
13.2
0.9
0.2
0.4
0.1
TKN
1.50
15.55
6.27
1.34
12.86
16.34
15.73
11.93
0.27
0.15
0.24
0.09
CL
22.8
116.6
81.4
31.2
65.3
127.0
66.5
72.8
12.7
8.2
10.8
6.1
Totals
43.13
523
10721
20.10
1.949
112.6
82.26
621.3
-------
091
"fl TOTAL P (mg/1)
rt 1 00 °; 4 0; 9 1
OCT ' NOV ' DEC ' JAN ' FEB ' MAR ' APR ' MAY ' JUN ' JUL ' AUO SEP
1985 WATER YEAR
re 23. Annual hydrograph, sedigraph and nutrient
he 1985 water year.
5~
r^
£~~
^
f
<^
f
3 0
8
z
o
O
m
O
c_
2
^1
W
70
TJ
£
C.
i
C
r~
^
u>
•o
SEDIMENT (mg/1)
331 663 994 0
•
—
]r_
»
E.
/~"~
f
f
8
z
o
<
o
fn
0
W
>
Z
-n
m
D
^"
a
E
>
<
^
i
C_
F
l"
M
Fl
•D
FLOW (cfs)
611 1222 1833
•^ •
CONDUCTANCE (umhos)
NITRATE (mg/1)
SOL. REACT. P (mg/1)
420
I
51
o
to
(D
a
w
o
en
"> ~
00 •
Ul
f I
^
3 ?
3J
§»
-J
O
a
fi
H-
B40
i _
1261 0.0
5.6
11.3
16.9 0.00
0.03
0.06
0.09
-------
Table 23. Monthly loads and discharge for Rock Creek for water year 1985. Discharge is given in million cubic meters, and loads are given in
metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
0.29
0.37
1.86
1.55
7.57
3.00
2.06
0.94
0.64
0.27
0.56
0.73
Flow
Ratio
0.613
0.620
0.865
2.155
0.889
0.887
0.761
0.942
0.982
0.565
0.720
0.822
Nof
Samples
36
34
47
33
81
53
51
38
42
42
44
40
SS
3
3
296
21
1556
803
471
29
53
23
120
243
TP
0.02
0.02
0.75
0.14
2.85
1.37
0.85
0.10
0.12
0.04
0.20
0.30
SRP NO23-N
<0.1
0.2
10.7
5.2
26.6
12.9
10.3
4.1
4.1
0.5
0.8
1.3
TKN
0.10
0.16
3.69
0.93
11.75
5.83
3.99
0.75
0.56
0.23
0.80
1.50
CL
9.4
16.3
70.3
59.5
125.0
69.9
40.2
35.9
25.9
8.7
12.7
11.9
Totals
19.83
541
3621
6.76
76.6
30.28
485.6
-------
291.
£' °
OCT ' NOV ' DEC ' JAN ' FEB ' WAR ' APR ' MAY ' JUN ' JUL ' AUG ' SEP
19B3 WATER YEAR
jre 24. Annual hydrograph, sedigraph and nutrient
luring the 1983 water year.
TOTAL P (mg/1)
0 0. 6 1.2 1
t_
$-
r~
V
k
I
s~~
r^e~
8 0
o
o
-4
z
o
<
D
m
O
c.
Z
•n
m
m
i
-
>
TJ
70
.
>
c_
C
Z
c_
C
f-
n
t/>
m
T3
SEDIMENT (mg/1)
712 1424 2136 0
^^^^— •—
-^••IMK.
"~
O
o
— 4
Z
O
<
o
m
o
c_
Z
-n
m
CD
C
>
3)
>
TJ
3)
c
>
-<
c_
C
Z
c_
F
>
c
n
i/>
m
•o
FLOW (cfs)
137 274 4
I
5
r
—
o
ro
i
•o
ro
§
ro
ro
ro
-J
O
K)
O
CONDUCTANCE (umhos)
0 302 604 906
NITRATE (tng/1)
0.0 6.7 13.3
SOL. REACT. P (mg/1)
20. 0 0. 00 0. 12 0. 25
0.37
-------
O)
CO
Table 24. Monthly loads and discharge for Upper Honey Creek for water year 1983. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Jar
Apr
May
Jun
Jul
Aug
Sep
Totals
USGS
Discharge
0.03
1.41
2.58
0.28
0.85
0.56
1.77
2.71
0.21
0.45
0.01
0.20
11.07
Flow
Ratio
1.235
1.154
0.528
1.480
1.292
1.777
1.481
1.381
1.670
1.338
0.678
1.532
Nof
Samples
14
54
29
2C
37
35
51
32
29
36
26
46
415
SS
<1
171
154
9
93
8
288
859
7
299
1
50
1939
TP
<0.01
0.51
0.58
0.03
0.20
0.03
0.60
1.81
0.02
0.32
<0.01
0.09
4.17
SRP
0.001
0.108
0.130
0.006
0.025
0.004
0.077
0.237
0.004
0.036
<0.001
0.018
0.645
NO23-N
<0.1
8.6
14.4
0.9
4.7
2.1
10.9
13.4
0.5
5.9
1.1
62.4
TKN
0.02
2.58
3.31
0.15
0.95
0.30
3.50
7.35
0.14
1.38
0.01
0.31
20.00
CL
0.7
41.3
78.3
9.6
22.0
18.5
40.1
45.2
6.1
9.4
0.3
4.3
276.0
-------
1791.
TOTAL P (mg/1)
0.0 0.6 -1.2
SEDIMENT (mg/1)
FLOW (cfs)
1.8
pure 25. Annual hydrograph, sedigraph and nutrient ch
during the 1984 water year.
(D
O
•ft
f
m
TO
•<
m
£
o
n
-4
Z
O
<
o
m
o
c_
>
Z
•n
m
D
»
>
-o
3!
|"
e_
C
Z
e_
C
r-
o
tn
m
'
t i
^T
^~
^
^^
t
t
t
o
o
z
o
<
o
m
o
c.
Tl
m
CD
E
X
E
>
-<
c_
C
z
c.
c
r—
n
m
•o
I
s-
•0
(D
l-i
O
3
CD
(D
X
o
w
ID
-~J
O
M
O
0
o
i"
o
o
c.
-n
m
CD
E
31
|
_
c_
C
Z
c.
c
r~
e>
i/>
•o
790 1580 2
1 i
^^—>
^r—
r
»
-^-
L
* —
•
i
i
r
r
371 0
0
n
— i
z
o
o
o
c_
Z
m
CD
i
T>
a
c.
C
Z
t-
o
in
•o
229 458 6E
^^••.^
j^*"""-
>i
^_
p— —
r~~
f
*• •
^
CONDUCTANCE (umhos)
0 279 558 837 0
"~~ 8~
NITRATE (mg/1)
0 11.4 22.7
SOL. REACT. P (mg/1)
34.1 0.00 0.49 0.98 1.48
R"
i
o
3D
m
m
-------
05
tn
Table 25. Monthly loads and discharge for Upper Honey Creek for water year 1984. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
USGS
Discharge
2.72
4.13
2.13
0.35
2.03
4.83
2.43
1.88
0.19
0.30
0.04
0.03
Flow
Ratio
1.200
1.317
1.260
0.792
0.840
1.355
1.376
2.838
2.722
2.046
0.420
0.196
Not
Samples
43
47
27
29
38
24
41
28
34
42
32
24
SS
569
614
139
9
353
1874
550
151
6
205
1
<1
TP
1.34
1.81
0.52
0.26
0.90
2.70
1.17
0.48
0.01
0.21
<0.01
<0.01
SRP
0.323
0.362
0.128
0.187
0.228
0.385
0.083
0.074
0.002
0.017
<0.001
<0.001
NO23-N
14.0
16.1
7.1
0.5
4.3
20.0
9.1
7.0
0.2
5.1
<0.1
<0.1
TKN
5.43
7.54
2.06
0.78
3.95
9.66
4.23
2.55
0.08
0.70
0.02
0.01
CL
45.3
72.9
39.7
8.0
28.5
59.8
33.0
38.0
4.8
8.2
1.0
0.9
Totals
21.07
409
4472
9.42
1.790
83.4
36.99
340.0
-------
991-
2. TOTAL P (mg/1) SEDIMENT (mg/1) FLOW (cfs)
a c o.
H ro 0
H- 8
3 10 -i
tQ Cft
" z
£i o
3- <
n> >
!_. 3 °
M 3 m
kO C o
CD (11
Ul 1-
* 51 ^
si •<
rt Qj '
ro n — ^
^ 8 m I"
iO w
t^ 7^ t'1
0) (D _. 5
S"§- 1 »
. Z~ — H
«, 3 %
"> »
o -<
£ > 5"
i-i •° •*
PJ
! l
13 «-
p, C
d >
rt- g
M-
§ 8
rt '
0 0.7 1.3 2.0 0
\
1
I
^^^-«
-S1"
2
^~
<=r —
1^—
1
|
/
^^-^
^
r*=
r
|
r
o
o
-^
_
z
0
o
m
0
._"
z
"
jj
ID
.
C
>"
•x
,
E
•<
•
C
Z
C
>"
C
o
in
m
433 866 V
\
"^~
^
-
^3—
x *
-
__^^^^
~7^~~~
"
•
f
y
r
7
P
r
r
Z99 0
0
o
^
•
z
o
D
f»I
O
c_
Z
"
Pi
O)
.
C
3)
T)
30
.
5
~*
*
i
C.
C
^~
o
I/I
PI
354 707 1
*"
f —
^
-
361
§•
tD
§
I
l-h
O
C?
o
ft
m
>
7)
-J
O
to
O
CONDUCTANCE (umhos) NITRATE (mg/1) SOL. REACT. P
331 662 993 0.0 9.4 18.8 28.2 0.00 0.05 0
8
(mg/l)
.09
0.14
o
z
m
•<
o
a
m
m
-------
Table 26. Monthly loads and discharge for Upper Honey Creek for water year 1985. Discharge is given in million cubic meters, and loads are
given in metric tons.
Month
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
uses
Discharge
0.04
0.37
1.72
0.85
4.50
2.09
1.42
0.42
0.46
0.15
0.04
0.02
Flow
Ratio
0.844
2.145
1.419
2.893
0.957
1.380
1.629
2.374
2.258
1.044
0.916
0.109
Nof
Samples
36
35
41
33
44
50
39
34
14
34
35
34
SS
1
15
923
76
816
391
59
4
6
4
1
TP
<0.01
0.07
1.47
0.20
1.69
0.97
0.22
0.02
0.03
0.01
<0.01
<0.01
SRP NO23-N
<0.1
2^4
11.7
4.2
19.1
12.7
7.3
4.3
7.7
0.3
'."
-------
991-
"fl
H-
rr C 0
3- S j
OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUO SEP
1982 WATER YEAR
e 27. Annual hydrograph, sedigraph and nutrient
e 1982 water year.
o
n>
vQ 0
"H- 3
o i"
n <
rt °_
o i
"> _ -*i"
CD
S s 5"
Tl J »
o " 3
o m c"
i " 5-
3 Z-
\ I
H- >
3 C
iQ °
V)
TOTAL P (mg/l)
0 5.5 11.0 16.5 0
-
F —
o
o
z
o
D
n
z
•n
pi
o
30
•D
30
|"
c.
Z
c
r-
C
O
u>
m
•n
CONDUCTANCE (umhos)
253 505 758 0
fc .
~^
^
-^~
:=S=L
R
1
o
PI
0
c.
z
IB
>
TO
TJ
3)
E
C
Z
c.
C
i
CA
PI
•o
SEDIMENT (mg/l)
5039 10079 151 18 0
r —
o
r>
z
0
o
m
o
c.
Pi
ID
|"
T)
l"
C_
I
c
r-
c
o
pi
•0
NITRATE (mg/l)
.0 8.3 16.6 24.8 0
r
^
8
z
o
o
PI
0
c.
z
-n
pi
BI
E
C
Z
C
r-
c
o
to
PI
FLOW (cfs)
103 207 310
^
h
C
SOL. REACT. P (mg/l)
.00 0.08 0.15 0
^
t
^ o
=._ CO
m
m
23
-------
691
?t o
(D fl> o
M hJ 3
v^ oo
(jj ^
< a- s
S- 3 °
% 5 m
• g °
3? s
' 1 i 5.
1 Jl_
m >
tn » 3
(D j
* > 5"
vQ aj K
9>
•5 £
e
UL AUG SEP
id nutrient
o
1 0
| §
Hi Z
0 o
F °"
0 rn
CD °
ft
n >
n z
(D
S- - s
^ 5 •
o ^ 5
w -<
m >
O m
ib > >
M aj -<
00
Ul f_
o
*-^ c.
a r
c
H- C
D 0
m
T)
TOTAL P (mg/1)
0 2.0 4.1 6
f^
r
•
r
^
^~
X"
CONDUCTANCE (umhos)
255 510 7
"^-s_
^
^"
^^r
a=~—
-
—
. 1 0
g
-H
1
o
0
z
m
0
3
c_
C
O
s"
•o
66 0
g
P
o
PI
0
-»l
PI
o>
i
•x
I
c
z
c
o
I/)
PI
•o
SEDIMENT (mg/1)
2384 4767 7
h-
^*
-
B=
NITRATE (mg/1)
.0 8.7 17.3 2
f
N
^
C-
-=^—
151 0
o
o
z
o
o
p>
o
c_
-n
a
I
>
a
u>
PI
•D
6.0 0
S
P
o
PI
o
c.
PI
m
X
.
3>
C
5
*
c
r~
o
in
•o
FLOW (efs)
178 355 5
r-
P—
£=
-
CL
SOL. REACT. P (mg/1)
.00 0.15 0.29 0
^~
\
^
k
^^
f
~* 0
5=r— c/)
_ —i
- 0
m
m
33
4
-------
QLl
«d
p-
iQ n
rt C °
OCT NOV DEC JAN FEB MAR APR MAY JUN JUL AUO SEP
1984 WATER YEAR
ce 29. Annual hydrograph, sedigraph and nutrient
le 1984 water year.
n
o>
I o
I §
$ \
t-1 °
S 5
rt
0 I
H _
1 5 S"
•* £ •
Ih"
w m >•
«, 30 TJ
? -< ».
2 > 5
£ » 5
s -•
S S
O
•*-* c-
a ^
c
P- 5
5 °
VQ
U)
m
•o
TOTAL P (mg/1)
0 1.6 3.2 4
r
r
$—
r
f
7 0
o
o
-4
1
0
m
o
t,
>
z
•n
m
0)
7)
?"
a
5"
C.
i
c.
?
o
i/>
Tn
•o
CONDUCTANCE (umhos)
296 591 887 0
S'
-
O
o
H
Z
0
<
o
m
o
c_
>
Z
•n
m
m
31
*"
3)
£
>
-<
c.
C
Z
^
?
O
c/l
m
•D
SEDIMENT (mg/1)
1521 3042 4564 0
»
•
•
R
-H
1
o
m
0
c.
>
Z
•n
m
o
31
>
TJ
31
>
b.
C
z
c.
F
>
c
o
U)
m
•o
NITRATE (mg/1)
- 0 6.9 13.9 20.8 0
^?
~>
— _
o
o
-4
Z
o
<
o
PI
0
c.
£
^l
m
a
3>
s"
a
5"
e_
C
Z
c.
F
l"
(/)
m
T)
FLOW (cfs)
66 132 196
/^
f
"P
-
SOL. REACT. P (mg/1)
.00 0.12 0.23 0
2-
* r~
: O
_ (/)
: -H
— o
- ^0
m
- m
_— — ?s
.35
-------
ILl
1 TOTAL P (mg/J)
H-
>0 0.0 1.0 1.9 2.
' OCT ' NOV ' DEC ' JAN ' FEB ' MAR ' APR ' MAY ' JUN ' JUL ' AUO SEP
1985 WATER YEAR
ire 30. Annual hydrograph, sedigraph and nutrien
he 1985 water year.
cr -1
§•
(D
§ 0
^ 0
HI O
v ->
z
Hi 0
0 <
l-i
O
t-l ni
5 0
!fl
ft c.
f? *.
(D ^. -*\
(D ia •*!
Wo0
Ul
H * >
en 5 »
O -H
to m >
3) 5
2 3>
o-< J
. PI _
o > >
£> 3> -<
h->
00 c.
Ul C
*. z
*>
&
n 5
H- 0
5 „-
m
•D
f—
r
r
r^
r
9 0
o
o
-i
l"
O
n
c_
z
•n
PI
O>
5
20
>
-D
3)
|"
«_
C
Z
«_
P
j'
0
u>
m
•D
CONDUCTANCE (umhos)
293 585 878 0
-^
"^
§
\
O
m
0
c.
>
Z
•n
m
CD
3D
5
3
|"
^
C
z
«_
P
>
c
0
VI
m
•0
SEDIMENT (mg/1)
997 1993 2990 0(
^•^^•^
(^•••a—
•
1
^B
J""™"
o
o
—i
z
o
<
.
o
m
o
c.
Z.
^
m
OJ
%"
3D
5
c_
C
Z
c_
F
5"
0
(A
m
•D
NITRATE (mg/1)
0 6.4 12.8 19.2 0^
?
^
7
t
•?
^^
8
-4
§
.
O
s
^
>
z
^1
m
ID
£
£
J
>
T)
7
|"
e_
C
Z
c.
F
0
w
m
•o
FLOW (cfs)
109 218 326
^^^^••w
^1
•
>•—
c: !
SOL. REACT. P (mg/1)
00 0.06 0.11 0
»
*~"
^•••^^^^iv
, '
^^••••H^H^
(—
O
to
-H
s~ ^o
[ m
^__ m
"} ^
i
17
-------
APPENDIX 2
TIME WEIGHTED MEAN PESTICIDE CONCENTRATIONS
AND PESTICIDE LOADINGS AT
LAKE ERIE TRIBUTARY MONITORING STATIONS:
1983 -1985 WATER YEARS
173
-------
APPENDIX 2 -- NOTES
Contents
This Appendix contains a summary of the time weighted mean pesticide concentrations,
the pesticide loads, and the unit area pesticide loads for Lake Erie tributary monitoring
stations during the 1983, 1984 and 1985 water years. The Appendix is organized such that
the time weighted mean concentrations and the loading data for a particular station and year
are presented on facing pages. The methods of calculation for time weighted mean
concentrations and pesticide loads are presented in the accompanying report.
Additional Parameters
In addition to the pesticides for which calculations are included in this Appendix, samples
were also analyzed for several other pesticides. These are listed in the TWMC tables. Since
they were rarely detected, calculation of concentrations and loads are not included in the
Appendix.
Data Availability
Data containing the concentrations of pesticides in individual samples are available in the
U.S. EPA's STORET data system. The data are stored under the corresponding U.S. Geological
Survey station number. Data can also be supplied directly on magnetic tape from the Water
Quality Laboratory, Heidelberg College, Tiffin, Ohio 44883.
Sampling and Analytical Methods and Calculational Procedures
The sampling methods, analytical procedures and calculational methods are described in
the accompanying main report. The analytical procedure has also been described in detail in
the following paper:
Kramer, Jack W. and David B. Baker. 1985. An analytical method
and quality control program for studies of currently used pesticides
in surface waters. IN: Taylor, J.K. and T.W. Stanley, eds. Quality
assurance for environmental measurements, ASTM STP 867.
Amer. Soc. Testing & Materials, Philadelphia, pp. 116-132.
174
-------
Sampling Locations
Locations of Lake Erie Tributary monitoring stations operated by the Water Quality
Laboratory at Heidelberg College for the 1982-1985 water years are shown below:
MICH.
RAISIN R
HAS
PA.
IND. I
'HURON R. BASIN
'SANDUSKV R. BASIN
OH.
UYAHOGA'
R. BASIN!
i
i
Sampling Locations:
River Raisin near Monroe, Ml
Maumee R. at Bowling Green, OH water intake
Sandusky R. near Fremont, OH
Cuyahoga R. at Independence, OH
Lost Cr. tributary near Defiance, OH
Rock Cr. at Tiffin, OH
Honey Cr. at Melmore, OH
Upper Honey Cr. at New Washington, OH
175
-------
List of Tables
Appendix II contains two types of tables. The first type presents the time weighted mean
concentration (TWMC's) of pesticides for a particular station and water year. The second type presents
the pesticide loads and unit area loads for each station and water year.
Table
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Station
Maumee
Maumee
Maumee
Maumee
Maumee
Maumee
Sandusky
Sandusky
Sandusky
Sandusky
Sandusky
Sandusky
Honey Creek
Honey Creek
Honey Creek
Honey Creek
Honey Creek
Honey Creek
Upper Honey Creek
Upper Honey Creek
Upper Honey Creek
Upper Honey Creek
Upper Honey Creek
Upper Honey Creek
Rock Creek
Rock Creek
Rock Creek
Rock Creek
Rock Creek
Rock Creek
Type
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
Water Year
1983
1983
1984
1984
1985
1985
1983
1983
1984
1984
1985
1985
1983
1983
1984
1984
1985
1985
1983
1983
1984
1984
1985
1985
1983
1983
1984
1984
1985
1985
Page
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
176
-------
Table
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Station
Lost Creek
Lost Creek
Lost Creek
Lost Creek
Lost Creek
Lost Creek
Raisin
Raisin
Raisin
Raisin
Raisin
Raisin
Cuyahoga
Cuyahoga
Cuyahoga
Cuyahoga
Cuyahoga
Cuyahoga
Type
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
TWMC
Loads
Water Year
1983
1983
1984
1984
1985
1985
1983
1983
1984
1984
1985
1985
1983
1983
1984
1984
1985
1985
Page
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
177
-------
Table 1: Pesticide concentrations for the Maumee River in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 116
Results based on 43 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0000
0.1749
1.7507
0.0008
0.0000
0.4429
1.0461
0.0355
1.3080
0.6616
Adjusted to
whole year
0.0000
0.0585
0.5852
0.0003
0.0000
0.1481
0.3496
0.0119
0.4372
0.2211
Observed
flux
ppb-days
0
20.2903
203.076
.09375
0
51.3816
121.344
4.1217
151.73
76.7448
178
-------
Table 2: Pesticide loads for the Maumee River, USGS04193500,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 52 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DBA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
0
235.161
2373.65
2.22466
0
664.465
1948
44.4298
1678.25
1103.59
56.8027
Extrapolated
Load
kg
0
249.423
2517.61
2.35958
0
704.763
2066.14
47.1244
1780.04
1170.52
60.2476
Unit area
Load
g/ha
0
.152134
1.53559
.143921E-02
0
.429865
1.26023
.287431E-01
1.08572
.713948
.367475E-01
The monitored time is 116.434 days.
The monitored discharge is 681260 cfs-days, or 1667.04 million cubic meters.
The total discharge during this time is 722577 cfs-days,
or 1768.14 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.875 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 161 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
179
-------
Table 3: Pesticide concentrations for the Maumee River in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.488
Results based on 58 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1849
0.1878
2.9754
0.0003
0.0022
0.4484
1.7556
0.0396
1.5738
1.1463
Adjusted to
whole year
0.0618
0.0628
0.9945
0.0001
0.0007
0.1499
0.5868
0.0132
0.5260
0.3831
Observed
flux
ppb-days
22.2798
22.6228
358.494
.032
.266094
54.0253
211.524
4.76666
189.622
138.114
180
-------
Table 4: Pesticide loads for the Maumee River, USGS04193500,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 67 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
287.449
503.242
4749.82
.523548
6.37051
1794.54
5188.71
54.3
3019.99
2854.17
117.083
Extrapolated
Load
kg
290.954
509.379
4807.74
.529933
6.44821
1816.42
5251.98
54.9622
3056.82
2888.98
118.511
Unit area
Load
g/ha
.177465
.310692
2.93245
.323228E-03
.393303E-02
1.10791
3.20341
.335238E-01
1.86448
1.76211
.722849E-01
The monitored time is 119.009 days.
The monitored discharge is 729089 cfs-days, or 1784.08 million cubic meters.
The total discharge during this time is 737980 cfs-days,
or 1805.84 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 122 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 173 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
181
-------
Table 5: Pesticide concentrations for the Maumee River in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.503
Results based on 38 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1653
0.0461
1.9017
0.0009
0.0004
0.2536
0.4723
0.0126
1.3159
0.3216
Adjusted to
whole year
0.0553
0.0154
0.6356
0.0003
0.0001
0.0848
0.1578
0.0042
0.4398
0.1075
Observed
flux
ppb-days
19.9206
5.55576
229.164
.108242
.503646E-01
30.561
56.908
1.5225
158.574
38.7578
182
-------
Table 6: Pesticide loads for the Maumee River, USGS04193500,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 42 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
66.0537
26.8966
714.135
.33093
.517415
123.306
259.141
19.4406
607.037
134.686
0
Extrapolated
Load
kg
67.3255
27.4145
727.885
.337302
.527378
125.68
264.131
19.8149
618.725
137.28
0
Unit area
Load
g/ha
.410647E-01
.167213E-01
.443968
.205735E-03
.32167E-03
.766574E-01
.161104
.120859E-01
.377387
.837327E-01
0
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
r\T A « w -•• _^«»
ULA — ——
Ethoprop
Trifluralin
Phorate
Aldicarb
The monitored time is 115.816 days.
The monitored discharge is 149661 cfs-days, or 366.222 million cubic meters.
The total discharge during this time is 152543 cfs-days,
or 373.273 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.75 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 139 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
183
-------
Table 7: Pesticide concentrations for the Sandusky River in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 122.198
Results based on 45 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0000
0.1542
1.8049
0.0000
0.0035
0.2955
0.5077
0.0880
2.2521
0.4470
Adjusted to
whole year
0.0000
0.0515
0.6033
0.0000
0.0012
0.0988
0.1697
0.0294
0.7528
0.1494
Observed
flux
ppb-days
0
18.8382
220.557
0
.43177
36.112
62.0349
10.7554
275.199
54.6176
184
-------
Table 8: Pesticide loads for the Sandusky River, USGS04198000,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 49 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
0
34.7943
563.198
0
.141157
84.2416
179.872
26.6641
635.118
98.6846
4.15412
Extrapolated
Load
kg
0
30.2541
489.709
0
.122738
73.2494
156.402
23.1848
552.245
85.8078
3.61207
Unit area
Load
g/ha
0
.093377
1.51145
0
.378822E-03
.226078
.482721
.715582E-01
1.70446
.264839
.111484E-01
The monitored time is 117.453 days.
The monitored discharge is 123364 cfs-days, or 301.871 million cubic meters.
The total discharge during this time is 107267 cfs-days,
or 262.481 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 115.25 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 162 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
185
-------
Table 9: Pesticide concentrations for the Sandusky River in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.49
Results based on 53 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1503
0.1370
2.5254
0.0000
0.0000
0.3709
1.2546
0.0033
2.7255
0.4858
Adjusted to
whole year
0.0502
0.0458
0.8441
0.0000
0.0000
0.1240
0.4193
0.0011
0.9110
0.1624
Observed
flux
ppb-days
18.1118
16.5041
304.279
0
0
44.69
151.166
.393226
328.394
58.5347
186
-------
Table 10: Pesticide loads for the Sandusky River, USGS04198000,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 60 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
40.3723
65.8552
656.49
0
0
108.259
439.937
1.34463
522.266
161.119
5.34462
Extrapolated
Load
kg
40.6242
66.2662
660.587
0
0
108.935
442.683
1.35302
525.525
162.125
5.37798
Unit area
Load
g/ha
.125383
.204525
2.03885
0
0
.336218
1.3663
.004176
1.62199
.500386
.165987E-01
The monitored time is 119.76 days.
The monitored discharge is 144723 cfs-days, or 354.138 million cubic meters.
The total discharge during this time is 145626 cfs-days,
or 356.348 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.75 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 177 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
187
-------
Table 11: Pesticide concentrations for the Sandusky River in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.505
Results based on 62 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1970
0.1858
4.4201
0.0011
0.0044
0.9166
1.8770
0.3254
4.8239
0.6176
Adjusted to
whole year
0.0659
0.0621
1.4774
0.0004
0.0015
0.3064
0.6274
0.1088
1.6124
0.2064
Observed
flux
ppb-days
23.741
22.3859
532.646
.13625
.530953
110.456
226.186
39.2176
581.301
74.4226
188
-------
Table 12: Pesticide loads for the Sandusky River, USGS04198000,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 66 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
41.1518
37.0776
833.711
.355286
.985262
236.898
491.222
80.9559
1019.64
108.339
.285062
Extrapolated
Load
kg
41.5872
37.4699
842.532
.359045
.995686
239.404
496.42
81.8124
1030.43
109.485
.288078
Unit area
Load
g/ha
.128356
.115648
2.60041
.110816E-02
.307311E-02
.738901
1.53216
.252508
3.18033
.337917
.889128E-03
The monitored time is 115.845 days.
The monitored discharge is 54637.1 cfs-days, or 133.697 million cubic meters.
The total discharge during this time is 55215.2 cfs-days,
or 135.112 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.875 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 174 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
189
-------
Table 13: Pesticide concentrations for Honey Creek in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 122.168
Results based on 57 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0000
0.1052
3.0290
0.0005
0.0000
0.3532
1.3811
0.3323
2.9892
0.6600
Adjusted to
whole year
0.0000
0.0352
1.0124
0.0002
0.0000
0.1180
0.4616
0.1111
0.9991
0.2206
Observed
flux
ppb-days
0
12.8497
370.049
.640278E-01
0
43.1452
168.725
40.5968
365.186
80.6281
190
-------
Table 1A: Pesticide loads for Honey Creek, USGS04197100,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 59 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
Ethoprop
Aldicarb
0
2.99224
76.749
.657169E-02
0
8.09728
31.489
6.49241
59.8298
12.9188
.338332
0
3.02351
77.5509
.664036E-02
0
8.18188
31.818
6.56024
60.455
13.0538
.341867
0
.783292E-01
2.00909
.17203E-03
0
.211966
.824301
.169954
1.56619
.338182
.885666E-02
—————
The monitored time is 114.939 days.
The monitored discharge is 13501.1 cfs-days, or 33.0373 million cubic meters.
The total discharge during this time is 13642.2 cfs-days,
or 33.3825 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.75 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 176 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
191
-------
Table 15: Pesticide concentrations for Honey Creek in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 117.003
Results based on 72 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0519
0.2668
4.4613
0.0000
0.0000
0.2709
2.1238
0.0522
3.0001
0.6525
Adjusted to
whole year
0.0174
0.0892
1.4912
0.0000
0.0000
0.0905
0.7099
0.0174
1.0028
0.2181
Observed
flux
ppb-days
6.07593
31.2206
521.984
0
0
31.6909
248.492
6.10662
351.028
76.3419
192
-------
Table 16: Pesticide loads for Honey Creek, USGS04197100,
during the time Interval 8404150000 to 8408150000, a span of 122 days,
during which 75 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated In this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DBA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
2.33222
6.74291
80.6978
0
0
7.6174
47.3483
.664561
46.2513
13.5665
2.45533
Extrapolated
Load
kg
2.32553
6.72359
80.4665
0
0
7.59557
47.2126
.662657
46.1188
13.5276
2.44829
Unit area
Load
g/ha
.060247
.174186
2.08463
0
0
.196776
1.22313
.171673E-01
1.19479
.350456
.634273E-01
The monitored time is 119.262 days.
The monitored discharge is 14785 cfs-days, or 36.179 million cubic meters.
The total discharge during this time is 14742.7 cfs-days,
or 36.0753 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 120.875 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 171 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
193
-------
Table 17: Pesticide concentrations for Honey Creek in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 122.203
Results based on 88 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1737
0.2601
5.2946
0.0028
0.0011
0.6630
2.1271
0.6690
4.4065
1.1582
Adjusted to
whole year
0.0581
0.0869
1.7697
0.0009
0.0004
0.2216
0.7110
0.2236
1.4729
0.3871
Observed
flux
ppb-days
21.2316
31.7883
647.017
.347003
.136146
81.0252
259.939
81.7535
538.49
141.536
194
-------
Table 18: Pesticide loads for Honey Creek, USGS04197100,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 91 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DEA
ryi_J f -I ..—,, 1 4 n
•Q
Aldicarb
1.06503
5.00794
69.8392
.307577E-01
.507882E-02
13.5167
39.8674
10.9928
65.12
13.5346
.115428
1.05741
4.97211
69.3395
.305377E-01
.504248E-02
13.42
39.5822
10.9141
64.6541
13.4378
.114602
.273942E-01
.128811
1.79636
.791132E-03
.130634E-03
.347667
1.02545
.282749
1.67498
.348129
.296896E-02
The monitored time is 120.391 days.
The monitored discharge is 2948.33 cfs-days, or 7.21457 million cubic meters.
The total discharge during this time is 2927.24 cfs-days,
or 7.16295 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 120.25 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 165 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
195
-------
Table 19: Pesticide concentrations for Upper Honey Creek in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.75
Results based on 35 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0011
0.0825
0.6361
0.0008
0.0021
0.1586
0.2867
0.0274
0.6179
0.2016
Adjusted to
whole year
0.0004
0.0276
0.2126
0.0003
0.0007
0.0530
0.0958
0.0092
0.2065
0.0674
Observed
flux
ppb-days
.128672
9.96368
76.8143
.979583E-01
.257344
19.1481
34.62
3.30898
74.6056
24.3435
196
-------
Table 20: Pesticide loads for Upper Honey Creek, USGS04197020,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 38 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbuf os
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
FPTP
Iji J. V>
OTA
.979229E-04
.183825
6.06971
.476676E-02
.195846E-03
.748462
3.21361
.272666
2.98445
.5167
.358543E-01
.855643E-04
.160625
5.30367
.416516E-02
.171129E-03
.654
2.80803
.238254
2.60779
.451488
.313292E-01
.194464E-04
.365057E-01
1.20538
.946627E-03
.388929E-04
.148636
.638188
.541485E-01
.59268
.102611
.712028E-02
Ethoprop
Trifluralin
Propoxur
Aldicarb
The monitored time is 117.941 days.
The monitored discharge is 1380.63 cfs-days, or 3.37839 million cubic meters,
The total discharge during this time is 1206.38 cfs-days,
or 2.95201 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 94.75 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 127 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
197
-------
Table 21: Pesticide concentrations for Upper Honey Creek in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 121.181
Results based on 18 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0092
0.0564
0.8327
0.0000
0.0000
0.0880
0.2852
0.0000
0.3121
0.1492
Adjusted to
whole year
0.0031
0.0189
0.2783
0.0000
0.0000
0.0294
0.0953
0.0000
0.1043
0.0499
Observed
flux
ppb-days
1.12048
6.83808
100.906
0
0
10.6607
34.5576
0
37.8249
18.0765
198
-------
Table 22: Pesticide loads for Upper Honey Creek, USGS04197020,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 19 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
wprr
.470106E-01
.45771
1.1129
0
0
.317983
.758534
0
1.23958
.2647
.483292E-02
.437803E-01
.426259
1.03643
0
0
.296133
.706413
0
1.1544
.246512
.450084E-02
Unit area
Load
g/ha
.995008E-02
.096877
.235552
0
0
.067303
.160548
0
.262364
.560254E-01
.102292E-02
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
The monitored time is 117.885 days.
The monitored discharge is 1058.82 cfs-days, or 2.59093 million cubic meters.
The total discharge during this time is 986.063 cfs-days,
or 2.4129 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 116.005 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 145 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
199
-------
Table 23: Pesticide concentrations for Upper Honey Creek in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 121.698
Results based on 54 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0564
0.1183
3.7028
0.0001
0.0000
0.2611
0.2552
0.0474
1.4310
2.4145
Adjusted to
whole year
0.0189
0.0395
1.2377
0.0000
0.0000
0.0873
0.0853
0.0159
0.4783
0.8070
Observed
flux
ppb-days
6.8688
14.3992
450.627
.01075
0
31.7717
31.0578
5.77333
174.147
293.835
200
-------
Table 24: Pesticide loads for Upper Honey Creek, USGS04197020,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 59 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DBA
17*. T-
CiCnOprop
Trifluralin
Phorate
•Q
IT r opoxur
Aldicarb
.963748E-01
.279561
4.69832
.284121E-03
0
.431541
.453975
.131815
2.32101
2.14332
0
.564224E-01
.163668
2.75062
.166338E-03
0
.252645
.265779
.077171
1.35883
1.2548
0
.128233E-01
.371973E-01
.62514
.378041E-04
0
.574192E-01
.604042E-01
.175389E-01
.308825
.285182
0
The monitored time is 114.391 days.
The monitored discharge is 435.665 cfs-days, or 1.06607 million cubic meters.
The total discharge during this time is 255.059 cfs-days,
or .624129 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 103.625 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 117 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
201
-------
Table 25: Pesticide concentrations for Rock Creek in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 117.024
Results based on 37 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0000
0.0609
2.5161
0.0000
0.0000
0.3038
0.5253
0.6445
2.9165
0.2207
Adjusted to
whole year
0.0000
0.0203
0.8410
0.0000
0.0000
0.1015
0.1756
0.2154
0.9748
0.0738
Observed
flux
ppb-days
0
7.12338
294.449
0
0
35.5525
61.4676
75.4237
341.296
25.8273
202
-------
Table 26: Pesticide loads for Rock Creek, USGS04197170,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 36 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
0
.210944
16.943
0
0
2.69211
4.62516
5.29239
23.1922
.908147
.895597E-01
0
.234893
18.8666
0
0
2.99775
5.15026
5.89324
25.8252
1.01125
.997275E-01
0
.262157E-01
2.10564
0
0
.33457
.574806
.657728
2.88228
.112863
.111303E-01
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
The monitored time is 110.75 days.
The monitored discharge is 2029.93 cfs-days, or 4.96724 million cubic meters.
The total discharge during this time is 2260.39 cfs-days,
or 5.53118 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 111.5 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 274 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
203
-------
Table 27: Pesticide concentrations for Rock Creek in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.493
Results based on 59 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0691
0.1278
0.9312
0.0000
0.0000
0.0407
0.2491
0.0000
2.1740
0.0371
Adjusted to
whole year
0.0231
0.0427
0.3112
0.0000
0.0000
0.0136
0.0833
0.0000
0.7267
0.0124
Observed
flux
ppb-days
8.32152
15.3977
112.198
0
0
4.90295
30.013
0
261.956
4.47312
204
-------
Table 28: Pesticide loads for Rock Creek, USGS04197170,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 61 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonof os
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
Ethoprop
irlrluralin
Phorate
Propoxur
A1 ^-tnat-k
2.62026
6.17311
26.3585
0
0
.904893
10.9323
0
21.0935
2.01961
.646228E-01
2.63461
6.20692
26.5029
0
0
.909849
10.9922
0
21.209
2.03067
.649767E-01
.294041
.692736
2.95791
0
0
.101546
1.22681
0
2.36708
.226638
.725187E-02
—————
The monitored time is 119.764 days.
The monitored discharge is 4855.33 cfs-days, or 11.881 million cubic meters.
The total discharge during this time is 4881.92 cfs-days,
or 11.9461 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.875 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 198 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
205
-------
Table 29: Pesticide concentrations for Rock Creek in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 121.674
Results based on 101 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0582
0.2286
3.5877
0.0010
0.0001
0.5736
0.5646
0.6879
6.6734
0.1993
Adjusted to
whole year
0.0194
0.0764
1.1992
0.0003
0.0000
1917
1887
0.2299
2.2306
0.0666
0.
0.
Observed
flux
ppb-days
7.07836
27.8185
436.523
.122806
.0155
69.7899
68.6994
83.704
811.979
24.2469
206
-------
Table 30: Pesticide loads for Rock Creek, USGS04197170,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 105 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonof os
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
DIA
Ethoprop
Phorate
Propoxur
AT rM/^ar-K
.159376
.972099
9.82585
. 26681 9E-02
.438666E-03
2.23313
1.78
1.77497
18.223
.519935
0
.159949
.975597
9.86121
.267779E-02
.440244E-03
2.24117
1.7864
1.78136
18.2886
.521806
0
.178515E-01
.108884
1.10058
.298861E-03
.491344E-04
.250131
.199376
.198812
2.04114
.582373E-01
0
The monitored time is 119.799 days.
The monitored discharge is 1083.67 cfs-days, or 2.65173 million cubic meters.
The total discharge during this time is 1087.57 cfs-days,
or 2.66127 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 121.875 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 156 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
207
-------
Table 31: Pesticide concentrations for Lost Creek in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 118.981
Results based on 39 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0022
0.0657
3.7682
0.0355
0.0016
0.5862
2.3692
0.3666
1.4825
0.8258
Adjusted to
whole year
0.0007
0.0220
1.2595
0.0119
0.0005
0.1959
0.7919
0.1225
0.4955
0.2760
Observed
flux
ppb-days
.265
7.81519
448.347
4.22753
.18617
69.7411
281.885
43.6163
176.394
98.25
208
-------
Table 32: Pesticide loads for Lost Creek, USGS04185440,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 40 pesticide samples were taken. (Values subject to revision.)
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
.512874E-02
.831541E-01
7.76558
.516162E-01
.347704E-02
1.58573
5.88742
.594775
3.11311
1.93489
.578629
.457867E-02
.742357E-01
6.93271
.460803E-01
.310412E-02
1.41565
5.25598
.530984
2.77922
1.72737
.51657
.538668E-02
.873361E-01
8.15613
.542121E-01
.365191E-02
1.66548
6.18351
.624687
3.26967
2.03221
.60773
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
The monitored time is 109.753 days.
The monitored discharge is 569.545 cfs-days, or 1.39368 million cubic meters.
The total discharge during this time is 508.46 cfs-days,
or 1.2442 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 63.0163 days out of 122
with each flow measurement characterizing one day or less. 6 flow values
out of 234 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
209
-------
Table 33: Pesticide concentrations for Lost Creek in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 117.491
Results based on 36 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0440
0.1160
5.6544
0.0000
0.0016
0.2470
1.7234
0.0000
0.6007
1.5428
Adjusted to
whole year
0.0147
0.0388
1.8900
0.0000
0.0005
0.0826
0.5760
0.0000
0.2008
0.5157
Observed
flux
ppb-days
5.17228
13.6343
664.346
0
.184479
29.0201
202.486
0
70.5752
181.269
210
-------
Table 34: Pesticide loads for Lost Creek, USGS04185440,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 38 pesticide samples were taken. (Values subject to revision.)
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
DIA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Extrapolated
Load
kg
Unit area
Load
g/ha
.817506E-01
.280967
23.7721
0
.400351E-02
.638174
3.93656
0
.852234
3.21759
.331997E-01
.462343E-01
.158902
13.4444
0
.22642E-02
.360921
2.22634
0
.481984
1.81972
.187762E-01
.543933E-01
.186944
15.8169
0
.266376E-02
.424613
2.61922
0
.56704
2.14085
.220897E-01
The monitored time is 116.745 days.
The monitored discharge is 548.96 cfs-days, or 1.34331 million cubic meters.
The total discharge during this time is 310.466 cfs-days,
or .75971 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 45.9684 days out of 122
with each flow measurement characterizing one day or less. 48 flow values
out of 139 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
211
-------
Table 35: Pesticide concentrations for Lost Creek in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 122.017
Results based on 37 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0101
0.0236
0.6471
0.0001
0.0000
0.0503
0.0666
0.0039
0.4110
0.4479
Adjusted to
whole year
0.0034
0.0079
0.2163
0.0000
0.0000
0.0168
0.0223
0.0013
0.1374
0.1497
Observed
flux
ppb-days
1.23285
2.87943
78.9536
.013
0
6.14306
8.13094
.47225
50.1449
54.6473
212
-------
Table 36: Pesticide loads for Lost Creek, USGS04185440,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 44 pesticide samples were taken. (Values subject to revision.)
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Observed
Load
kg
Extrapolated
Load
kg
Unit area
Load
g/ha
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
LJtA
Ethoprop
in riuraiin
Phorate
Propoxur
A1 A1 ^>o — K
.100654E-02
.109786E-01
.079732
.190866E-05
0
.843038E-02
.154783E-01
.143002E-03
.235787E-01
.229641E-01
.995599E-03
______
.397579E-03
.43365E-02
.314939E-01
. 75391 5E-06
0
.332997E-02
.611389E-02
.564853E-04
.931353E-02
.907076E-02
.393259E-03
.46774E-03
.510176E-02
. 37051 6E-01
.886959E-06
0
.391762E-02
.719281E-02
.664533E-04
.109571E-01
.106715E-01
.462657E-03
— — — —
The monitored time is 118.017 days.
The monitored discharge is 38.0826 cfs-days, or .931882E-01 million cubic meters.
The total discharge during this time is 15.0425 cfs-days,
or .368091E-01 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 76.75 days out of 122
with each flow measurement characterizing one day cr less. 2 flow values
out of 92 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
213
-------
Table 37: Pesticide concentrations for the River Raisin in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 117.599
Results based on 18 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0008
0.1715
1.0671
0.0280
0.0026
0.1352
0.5399
0.0792
0.3166
0.3409
Adjusted to
whole year
0.0003
0.0573
0.3567
0.0093
0.0009
0.0452
0.1804
0.0265
0.1058
0.1139
Observed
flux
ppb-days
.0895
20.164
125.486
3.28691
.305234
15.8997
63.4869
9.31544
37.2295
40.0871
214
-------
Table 38: Pesticide loads for the River Raisin, USGS04176500,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 19 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
.131227
40.1594
412.29
6.73803
.764416
73.576
257.318
31.386
154.639
107.582
8.12934
Extrapolated
Load
kg
.113987
34.8834
358.126
5.85283
.663991
63.9099
223.513
27.2627
134.323
93.4487
7.06135
Unit area
Load
g/ha
.422332E-03
.129246
1.32688
.216852E-01
.246014E-02
.236791
.828133
.10101
.497677
.346235
.261628E-01
The monitored time is 109.87 days.
The monitored discharge is 141563 cfs-days, or 346.404 million cubic meters.
The total discharge during this time is 122965 cfs-days,
or 300.896 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 103.141 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 104 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
215
-------
Table 39: Pesticide concentrations for the River Raisin in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 120.5
Results based on 29 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0421
0.0288
0.9688
0.0000
0.0202
0.0467
0.7842
0.0126
0.4446
0.4834
Adjusted to
whole year
0.0141
0.0096
0.3238
0.0000
0.0068
0.0156
0.2621
0.0042
0.1486
0.1616
Observed
flux
ppb-days
5.06772
3.47321
116.737
0
2.43408
5.63188
94.4923
1.51433
53.5796
58.2546
216
-------
Table 40: Pesticide loads for the River Raisin, USGS04176500,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 30 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DBA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
10.315
2.98087
320.642
0
3.29257
24.8124
270.88
.458378
95.2372
199.298
2.78217
Extrapolated
Load
kg
9.18442
2.65415
285.499
0
2.93169
22.0928
241.19
.408138
84.7988
177.454
2.47723
Unit area
Load
g/ha
.034029
.983382E-02
1.05779
0
.108621E-01
.818556E-01
.893627
.151218E-02
.314186
.65748
.917833E-02
The monitored time is 116.944 days.
The monitored discharge is 86900.8 cfs-days, or 212.646 million cubic meters.
The total discharge during this time is 77376.1 cfs-days,
or 189.339 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 102.937 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 103 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates Is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
217
-------
Table 41: Pesticide concentrations for the River Raisin in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 110
Results based on 15 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.1880
0.0401
1.8062
0.0000
0.0067
0.1508
1.0260
0.4316
0.7873
0.4583
Adjusted to
whole year
0.0628
0.0134
0.6037
0.0000
0.0022
0.0504
0.3429
0.1443
0.2632
0.1532
Observed
flux
ppb-days
20.6759
4.40915
198.681
0
.732958
16.591
112.859
47.4775
86.6053
50.4184
218
-------
Table 42: Pesticide loads for the River Raisin, USGS04176500,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 16 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
12.6168
3.09756
151.834
0
.585477
13.7212
87.0336
25.9203
68.9871
35.5808
0
Extrapolated
Load
12.5889
3.09073
151.499
0
.584185
13.6909
86.8415
25.8631
68.8349
35.5022
0
Unit area
Load
g/ha
.466429E-01
.114514E-01
.561314
0
.216445E-02
.507258E-01
.321754
.958246E-01
.255038
.131538
0
The monitored time is 103.427 days.
The monitored discharge is 30744.3 cfs-days, or 75.2313 million cubic meters.
The total discharge during this time is 30676.5 cfs-days,
or 75.0653 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 99.6041 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 99 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
219
-------
Table 43: Pesticide concentrations for the Cuyahoga River in 1983.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 113.298
Results based on 15 samples in the period 830415 to 830815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.0343
0.5960
0.3583
0.0963
0.1673
0.1742
0.0904
0.0903
0.5159
0.2924
Adjusted to
whole year
0
0.0114
0.1992
1197
0.0322
0.0559
0.0582
0.0302
0.0302
0.1725
0.0977
Observed
flux
ppb-days
3.88052
67.5232
40.5894
10.9056
18.9564
19.737
10.2468
10.2356
58.4559
33.1333
220
-------
Table 44: Pesticide loads for the Cuyahoga River, USGS04208000,
during the time interval 8304150000 to 8308150000, a span of 122 days,
during which 15 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DBA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
4.98199
161.081
73.7977
14.291
13.8592
21.8147
13.2275
12.4207
85.2091
56.3098
12.0116
Extrapolated
Load
kg
5.37344
173.737
79.5963
15.4139
14.9481
23.5288
14.2668
13.3966
91.9043
60.7342
12.9553
Unit area
Load
g/ha
.029347
.948866
.434715
.841829E-01
.816392E-01
.128502
.779182E-01
.731654E-01
.501935
.3317
.707556E-01
The monitored time is 100.865 days.
The monitored discharge is 109643 cfs-days, or 268.297 million cubic meters.
The total discharge during this time is 118258 cfs-days,
or 289.378 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 107.5 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 141 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
221
-------
Table 45: Pesticide concentrations for the Cuyahoga River in 1984.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 83.8663
Results based on 12 samples in the period 840415 to 840815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.7405
0.1833
0.2179
0.0053
0.0082
0.0475
0.0958
0.3799
0.0010
0.0063
Adjusted to
whole year
0.2475
0.0613
0.0728
0.0018
0.0028
0.0159
0.0320
0.1270
0.0003
0.0021
Observed
flux
ppb-days
62.105
15.3751
18.2751
.448
.691121
3.98034
8.03184
31.8616
.859372E-01
.532122
222
-------
Table 46: Pesticide loads for the Cuyahoga River, USGS04208000,
during the time interval 8404150000 to 8408150000, a span of 122 days,
during which 14 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalln
EPTC
DIA
DEA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
132.075
66.9182
54.3214
2.07351
2.71794
17.7068
23.0053
83.9372
7.8496
4.32179
.541895
Extrapolated
Load
kg
148.643
75.3128
61.1358
2.33362
3.0589
19.9281
25.8912
94.4668
8.83431
4.86394
.609873
Unit area
Load
g/ha
.811813
.411321
.333893
.127451E-01
.167062E-01
.108837
.141405
.51593
.482485E-01
.265644E-01
.333082E-02
The monitored time is 85.9549 days.
The monitored discharge is 113783 cfs-days, or 278.428 million cubic meters.
The total discharge during this time is 128057 cfs-days,
or 313.355 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 108.375 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 134 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
223
-------
Table 47: Pesticide concentrations for the Cuyahoga River in 1985.
In the results below, the time any sample can represent was
limited to 14 days.
Adjustments to the whole year were made assuming the time-weighted
mean concentration characterized the monitored interval, and a
concentration of 0.000 characterized the rest of the year.
Total monitored time (days) is 121.552
Results based on 16 samples in the period 850415 to 850815
Parameter
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Time-weighted
mean concentration
(ug/L or ppb)
0.4415
0.0431
0.4417
0.0000
0.0151
0.0000
0.0135
0.1054
0.1070
0.0949
Adjusted to
whole year
0.1476
0.0144
0.1477
0.0000
0.0050
0.0000
0.0045
0.0352
0.0358
0.0317
Observed
flux
ppb-days
53.6694
5.23406
53.6945
0
1.8352
0
1.645
12.8075
13.005
11.5295
224
-------
Table 48: Pesticide loads for the Cuyahoga River, USGS04208000,
during the time interval 8504150000 to 8508150000, a span of 122 days,
during which 19 pesticide samples were taken.
The time characterized by any pesticide sample was limited to 14 days.
The loads calculated in this manner are as follows:
Pesticide
Simazine
Carbofuran
Atrazine
Terbufos
Fonofos
Metribuzin
Alachlor
Linuron
Metolachlor
Cyanazine
Pendimethalin
EPTC
DIA
DBA
Ethoprop
Trifluralin
Phorate
Propoxur
Aldicarb
Observed
Load
kg
84.7051
16.6353
100.551
0
1.88642
.303122
2.42571
45.8115
23.5251
17.0119
0
Extrapolated
Load
kg
82.7257
16.2465
98.2013
0
1.84233
.296038
2.36903
44.741
22.9753
16.6144
0
Unit area
Load
g/ha
.451806
.887303E-01
.536326
0
.100619E-01
.161681E-02
.129384E-01
.244353
.12548
.907394E-01
0
The monitored time is 121.052 days.
The monitored discharge is 75005.8 cfs-days, or 183.539 million cubic meters.
The total discharge during this time is 73253 cfs-days,
or 179.25 million cubic meters, and is based on the most complete
discharge record available in the computer. Due to differences in data and
calculation approach, this discharge may differ from the USGS discharge for
the same time period. The discharge record covers 120 days out of 122
with each flow measurement characterizing one day or less. 0 flow values
out of 166 were missing.
The observed loads correspond to the time and discharge monitored.
The extrapolated loads are calculated by multiplying the observed load
by the ratio of the total discharge to the monitored discharge.
The unit area load is the extrapolated load divided by the watershed
area and re-expressed as grams per hectare.
The accuracy of the load estimates is dependent on the frequency and
representativeness of the pesticide samples and the flow data.
Infrequent pesticide samples are more often the limiting factor than
is inadequate flow data.
Pesticide concentrations below detection limit are taken as 0.000 ug/L.
* U S GOVERNMENT PRINTING OFFICE.1988- 543-860 I 62141
225
-------
TECHNICAL REPORT DATA
't'^sc read Inductions on the ret i.nc hi fore cortpU ting)
1 RErORT NO
EPA-905/4-88-001
3 RECIPIENT'S ACCESSIO.VNO.
4. TITLE AND SUBTITLE
Sediment, Nutrient and Pesticide Transport in
Selected Lower Great Lakes Tributaries
5. REPORT DATE
February 1988
6. PERFORMING ORGANIZATION CODE
5GL
7 AUTHOH(S)
8. PERFORMING ORGANIZATION REPORT NC.
David B. Baker
GLNPO Report No. 1
9 PERFORMING ORGANIZATION NAME AND ADDRESS
Heidelberg College
Uater Quality Laboratory
310 E. Market Street
Tiffin, Ohio 44883
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
R005817-01
R005727-01
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Great Lakes National Program Office
230 South Dearborn Street
Chicago, Illinois 60604
13. TYPE OF REPORT AND PERIOD COVtF-ED
Final 1982-85
14. SPONSORING AGENCY CODE
Great Lakes National Program
Office, U.S. EPA, Region V
15. SUPPLEMENTARY NOTES
Sarah Pavlovic, Project Officer
16. ABSTRACT
Event sampling -programs were conducted at 11 tributary monitoring stations in the
Lake Erie and Lake Ontario watersheds during the 1982 - 1985 water years. Samples
were analyzed for suspended sediments, nutrients and pesticides at 8 stations in
the Lake Erie watershed and for suspended sediments and nutrients at 3 stations
in the Lake Ontario watershed. The resulting data illustrate and quantify the
effects of agricultural nonpoint pollution on regional surface waters. The data
are analyzed with respect to both the concentration patterns of pollutants at the
transport stations and the loadings of pollutants at the stations. Time weighted
and flux weighted mean concentrations are presented, as are percentile distributions
and concentration exceedency curves. Total loads, unit area loads and loading
exceedency tables are also presented. Relative to tributaries in other agricultural
regions, the concentrations of nitrates and pesticides in northwestern Ohio
tributaries to Lake Erie are particularly high.
These data,in combination with similar studies dating back to the 1975 water year,
are used to illustrate the annual and seasonal variability in agricultural runoff.
Since the study watersheds range in size from 11.3 to 16,395 sq.km. the data also
illustrate the effects of watershed size on concentration patterns and on seasonal
loading characteristics.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
h.lOI'N 1 IFILRS/CPEN ENDED TtRVIS C. i.-OSATI
Nonpoint pollution Maumee River
Tributary loading Cuyahoga River
Agricultural runoff Raisin River
Pesticide runoff Lake Erie
Pesticide exposure assessment
Agricultural escosystems Lake Ontario
Sandusky River
19 Olb m;BU PON ST A fEMGNT
Document is available to the public through
the National Technical Information Service
(NTIS), Springfield, VA 22161
19 'jt CUfilTY C'.^SS |';V,
NO. U!
244
20. &ECURI 1 Y C'-AfiS /T-Vr p-'i
-------
|