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i„· l
A LIMNOLOGICAL INVESTIGATION OF LAKE MANASSAS, VIRGINIA
byBrent Frederic Harvey
Thesis submitted to the Faculty of the
Virginia Polytechnic Institute and State University
in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE
inENVIRONMENTAL ENGINEERING
APPROVED:
Dr. Thomas G izz rd, Chairman _
Dr. Adil N. Godrej Mr. Harold Post
October 1989
Blacksburg, Virginia
LIMNOLOGICAL PROFILE OF LAKE MANASSAS (VIRGINIA)
byBrent Frederic Harvey
Committee Chairman: Thomas J. Grizzard
(ABSTRACT)
Lake Manassas is a man—made impoundment in the Northern
Virginia suburbs of Washington, D.C. The lake currently
supplies drinking water at a rate of 6.7 million gallons per
day to the City of Manassas, Virginia. The lake discharges,
via the stream Broad Run, to the Occoquan Reservoir. The
Occoquan Reservoir supplies potable water to over 750,000
people in the Northern Virginia area.
As the population of Washington, D.C., continues to
increase, the development of the surrounding suburbschangesthe
quality of surface runoff water into existing
reservoirs. These reservoirs can become enriched with
bothtoxicand biomass inducing nutrient pollutants. The result
can be less desirable and less dependable supplies of
drinking water.
A State of Virginia mandated Environmental Monitoring
Program is in force in this area to ensure the Occoquan
Watershed remains a dependable supply of potable water. A
computerized database, containing the results of the
environmental monitoring program, allows for a quantitative
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estimate of the overall water quality of the reservoirs to
be made.
This thesis presents the results of a limnological
analysis of Lake Manassas. The analysis techniques used are
established limnological techniques to arrive at a profile
which can be compared to accepted scales of ranking.
One conclusion from the analysis is that Lake Manassas
is eutrophic, which means that the production of biomass in
the lake is at a higher than desired rate. The result of
this eutrophic condition is that the water quality of the
lake will decline rather rapidly. Another conclusion is
that Broad Run is the major supplier of nutrients into Lake
Manassas, but that conditions are also affected by a point
source discharge from a sewage treatment plant. These
conclusions are consistent with previous studies done on
Lake Manassas.
In summary, Lake Manassas is an important water
resource in the Northern Virginia area, and it is importantV to continue to closely monitor and manage runoff practices
in the watershed to ensure the lake does not degrade to
unacceptable conditions.
TABLE OF CONTENTS
I I I I I I I I I I I I I I I I I I I I I I I I i i
ACKNOWLEDGEMENTS .................... iv
LIST OF FIGURES .................... vii
LIST OF TABLES ..................... xi
CHAPTER
I. INTRODUCTION ................. 1
II. LITERATURE REVIEW .............. 6
History of Lake Manassas ...... 6
Lake History ............ 6Water Treatment .......... 7Watershed Management ........lOCurrent Watershed Development . . .11
Limnological Principles ......15
The Lake as an Ecosystem ......15Morphology .............15Energy Input to Lakes .......17Lake Productivity .........21Nutrients for Biomass Production . .24Quantification and Prediction ofLake Productivity .........32
III. METHODS AND MATERIALS ............39
Sampling Program ..........39Sample Analysis ..........42Data Analysis ...........43
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IV. RESULTS ................... 55
Lake Manassas Morphology ...... 55Lake Manassas Thermal Stratification 55Lake Manassas Dissolved OxygenProfiles ............. 67Lake Manassas Chlorophyll Q .... 89Lake Manassas Nitrogen andPhosphorus .............102Lake Manassas Watershed Properties .113Lake Manassas Watershed EnvironmentalMonitoring Data ..........117Prediction of the Eutrophic Status ofLake Manassas ...........130
V. DISCUSSION ..................142
Discussion of Monitoring ProgramResults for Lake Manassas . . 142Discussion of Monitoring ProgramResults for the Lake ManassasWatershed .......... 149Discussion of the ModelingResults Predicting the EutrophicStatus of Lake Manassas ....152
VI. CONCLUSIONS .................154
VII. RECOMMENDATIONS ...............156
REFERENCES ..................158
VITA .....................161
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LIST OF FIGURES
Figure 1 - Geographic Location of Lake Manassas ......3
Figure 2 — Development of Lake Manassas Watershed .... 14
Figure 3 - Density versus Temperature Curve for Water . . 19
Figure 4 - The Vollenweider Model Relationship ..... 34
Figure 5 - Lake Manassas Sampling Stations ....... 40
Figure 6 - Hypsographic Curve for Lake Manassas ..... 57
Figure 7 - Temperature Profile at Monitoring Station —
LMO1 ..................... 59
Figure 8 - Temperature Profile at Monitoring Station
LM02 ..................... 60
Figure 9 - Temperature Profile at Monitoring Station
LM03 ..................... 61
Figure 10 — Temperature Profile at Monitoring Station
LM04 .....................62Figure11 - Temperature Profile at Monitoring Station
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LM05 ..................... 63
Figure 12 — Temperature Profile at Monitoring Station
LM06 ..................... 64
Figure 13 - Temperature Profile at Monitoring Station
LM07 ..................... 65
Figure 14 - Temperature Profile at Monitoring Station
LM08 ..................... 66
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Lee............................................_....____________________
Figure 15 - Dissolved Oxygen Profile at Station LMO1 . . .68
Figure 16 — Dissolved Oxygen Profile at Station LMO2 . . .69
Figure 17 - Dissolved Oxygen Profile at Station LM03 . . .70
Figure 18 — Dissolved Oxygen Profile at Station LMO4 . . .71
Figure 19 — Dissolved Oxygen Profile at Station LM05 . . .72
Figure 20 - Dissolved Oxygen Profile at Station LMO6 . . .73
Figure 21 — Dissolved Oxygen Profile at Station LM07 . . .74
Figure 22 — Dissolved Oxygen Profile at Station LM08 . . .75
Figure 23 — % Saturation DO Profile at Station LM01 . . .77
Figure 24 - % Saturation DO Profile at Station LMO2 . . .77
Figure 25 - % Saturation DO Profile at Station LM03 . . .78
Figure 27 - % Saturation DO Profile at Station LMO4 . . .79
Figure 27 — % Saturation DO Profile at Station LM05 . . .80
Figure 28 - % Saturation DO Profile at Station LM07 . . .81
Figure 29 - % Saturation DO Profile at Station LM07 . . .82
Figure 30 - % Saturation DO Profile at Station LM08 . . .83l
Figure 31 - Top and Bottom DO Profiles at Station LM01 . .85
Figure 32 - Top and Bottom % Saturation DO Profiles
at Station LMO1 ...............86
Figure 33 - Top and Bottom DO Profiles at Station LM08 . .87
Figure 34 — Top and Bottom % Saturation DO Profiles
at Station LM08 ...............88
Figure 35 — Chlorophyll Q Profile at LMO1 ........90
Figure 36 — Chlorophyll Q Profile at LMO2 ........91
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tFigure 37 — Chlorophyll Q Profile at LMO3 ........92
Figure 38 - Chlorophyll Q Profile at LM06 ........93
Figure 39 - Chlorophyll Q Profile at LMO7 ........94
Figure 40 - Chlorophyll Q Profile at LMO1 & LM02 .....95
Figure 41 - Chlorophyll Q Profile at LMO3 & LM07 .....96
Figure 42 - Chlorophyll Q Profile at LMO3 & LMO7 .....97
Figure 43 — Surface Chlorophyll Q at LMO1 and LM03 ....99
Figure 44 — Surface Chlorophyll Q at LMO1 and LM07 . . . 100
Figure 45 — Surface Chlorophyll Q at LMO7 and LM07 . . . 101
Figure 46 — Nitrogen in the Bottom Waters of LMO1 . . . 103
Figure 47 — Nitrogen in the Bottom Waters of LMO7 . . . 104l
Figure 48 - Nitrogen in the Bottom Waters of LM07 . . . 105
Figure 49 — Oxidized Nitrogen at the Top and Bottom
of LMO1 ...................106
Figure 50 — Nitrogen and Phosphorus at the Bottom
of LMO1 ...................108
Figure 51 - Nitrogen and Phosphorus at the Bottom
of LMO7 ...................109
Figure 52 - Phosphorus in the Bottom Waters at LMO1. . . 110
Figure 53 — Phosphorus in the Bottom Waters at LMO7. . . 111
Figure 54 - Total Phosphorus in the Surface at LMO1, LMO3
and LMO7 .................. 112
Figure 55 — Rainfall in Lake Manassas watershed .... 115
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IFigure 56 - % Runoff into Broad Run versus Yearly
Rainfall .................. 116
Figure 57 - ST70 Loading of Orthophosphorus ...... 123
Figure 58 - ST70 Loading of Total Soluble Phosphorus . . 124
Figure 59 - ST70 Loading of Total Phosphorus ...... 125
Figure 60 - ST70 Loading of Ammonia Nitrogen ...... 126
Figure 61 — ST70 Loading of Oxidized Nitrogen ..... 127
Figure 62 — ST70 Loading of TKN ............ 128
Figure 63 - ST70 Loading of SKN ............ 129
Figure 64 - Spreadsheet Statistical Model for
Lake Manassas ............... 131
Figure 65 - Current Average Phosphorus Loading ..... 132
Figure 66 - Current Median Phosphorus Loading ..... 133
Figure 67 - CURAVGLOAD Output Distribution Graph .... 134
Figure 68 - CURMEDLOAD Output Distribution Graph .... 135
Figure 69 - Vollenweider Plot of Current Conditions in Lake
Manassas .................. 136i
Figure 70 — Vollenweider Plot of Lake Manassas after
eliminating the Vint Hill point source
discharge ................. 139
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WLIST OF TABLES
Table 1 - Nutritional Requirements ...........26
Table 2 - Carlson's Trophic State Index ........36
Table 3 - Trophic State Indices based on Chlorophyll Q .37
Table 4 - EPA Trophic State Index System ........38
Table 5 - Distribution Functions for Spreadsheet Model .47
Table 6 — Database Structure and Contents .......51
Table 7 - Morphological Characteristics of Lake
Manassas ...................56
Table 8 — Properties of Lake Manassas Watershed Basins 114
Table 9 · Summary of Environmental Monitoring Data for
Drainages into Lake Manassas ........ 118
Table 10 — Summary of Metal Content of Drainages to Lake
Manassas .................. 120
Table 11 — Summary of Results from Spreadsheet Model of
Lake Manassas ............... 138
Table 12 - Summary of Other Trophic State Indices for Lake
Manassas .................. 141
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IChapter I
INTRODUCTION
Groundwater became an undependable supply of potable
water in the area around the City of Manassas, Virginia, in
the mid—1960·s. The expanding population increased the
demand for water to the point where the aquifer experienced
an overdraft condition. Because the population was expected
to continue to increase at a relatively rapid rate, the
overdraft condition would continue to worsen.
In response to this problem, the City of Manassas began
a study for alternative supplies of water. The result of
this study was the recommended development of a man·made
impoundment, Lake Manassas, by constructing a dam on Broad
Run, approximately 10 miles west of the City of Manassas.
In 1968 the construction process began and by 1971 the lake
and a new water treatment plant were supplying water to the
City of Manassas.
The lake was designed for a capacity of 5.8 billion
gallons and a surface area of approximately 780 acres.
However, more recent studies indicate these design figures
may be ten to twenty percent higher than the actual size of
the lake. The issue of lake size, will be discussed in
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subsequent sections of this report. The water treatment
plant was initially designed for a capacity of 4 million
gallons per day (MGD), but the continued expansion of the
surrounding population necessitated a doubling of the output
capacity to 8 MGD in 1987. Figure 1 shows the location of
Lake Manassas in the north-eastern corner of Virginia,
approximately 30 miles due west of Washington, D.C.
Lake Manassas lies in the upper reaches of a major
watershed for Northern Virginia: the Occoquan River
watershed. The Occoquan River is impounded by a dam near
its discharge into the Potomac River, south of Washington,
DC. The Occoquan Reservoir is one of the largest potable
water reservoirs in the northern Virginia area. Because of
this, the Occoquan Reservoir and its watershed have been
monitored and studied extensively.
Lake Manassas has grown in popularity as a recreational
facility since its construction. The lake is stocked with
fish, and the State Game Commission allows access to the
lake for fishing on a permitted basis. No gasoline engines
are allowed on the lake, and no swimming is permitted. A
further example of the popularity of the lake is the recent
acquisition of a significant portion of the land on the
north—western shoreline for construction of a large golf
resort and convention center. Current plans include the
El
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construction of three 18 hole golf courses, and an
accompanying hotel and convention facility.
Limnological principles show that as the development of
a watershed proceeds, the increased input of nutrients and
other pollutants results in the gradual decline of the
quality of the receiving water body. This decline is
typified by an increase in algal growth, known as lake
productivity. Typically, taste and odor problems and
filtration overloading, all caused by these microorganisms,
make it difficult and uneconomical to treat the water. Asl
the lake productivity continues to increase, the water body
can no longer be a useful supply of potable water. However,
there are land management practices that can be implemented
to minimize or control this undesirable environmental
process.
It can be expected that as the population of this
geographic region continues to increase, there will be an
accompanying increased demand for potable water. Therefore,
it is important that all existing water supply resources
continue to be protected from any decline in quality.
The objectives of this study are to present a
comprehensive analysis of the existing conditions in Lake
Manassas. These existing, or baseline, conditions can be
used in a comparative fashion to track the changes in the
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lake as the watershed development continues. These
comparisons can be a useful way to monitor land management
practices in the watershed so that their maximum
effectiveness is achieved.
Specific objectives of this study were (1) to
investigate the limnological characteristics of Lake
Manassas including the morphology, stratification due to
thermal effects, nutrient input and distribution, and lake
productivity; (2) to use existing models to predict the
magnitude of eutrophication in the lake; and (3) to
characterize the major input streams to the lake.
1Chapter II
LITERATURE REVIEW
History of Lake Manassas
Lake History
In 1962, the Town Council of Manassas requested that
I the Northern Virginia Soil Conservation District make a
survey of possible sites for a water reservoir that would
replace the increasingly unreliable groundwater supply. The
community was undergoing rapid development, and the
overdraft condition in the aquifer would only worsen with
time. The survey proposed the development of an impoundment
on Broad Run by placing a dam just south of the confluence
of Broad Run and the North Fork tributary to Broad Run. The
land in this area was purchased, and a bond referendum
provided the funds to construct the dam. (1) Construction
began in November of 1968, and the dam was completed in
1970. Parallel with construction of the dam, a water
treatment plant at the base of the dam was designed and
constructed. The treatment plant began supplying water in
1971 to the City of Manassas through a seven mile long, 24-
inch diameter water main (2).
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Water Treatment
The water treatment plant was initially designed to
operate at a capacity of 4 MGD, and did so until 1987 when a
plant expansion doubled its capacity to 8 MGD. Currently,
the plant is operating at a nominal capacity of 6.7 MGD
supplying water to the City of Manassas, and to the Prince
William County Service Authority for other areas of Prince
William County, Virginia. In addition to this withdrawal of
water from Lake Manassas, a small hydroelectric plant at the
base of the spillway was completed in 1987. This
hydroelectric plant is designed to supplement local peak
electricity demand. The hydroelectric plant is therefore
only operated intermittently. Current plans are to operate
the hydroelectric plant 3 to 7 hours per day, 5 to 10 days
per year. (2)
Raw water is withdrawn from the lake by an intake
system at depths of 5, 15, 25, 35, 45, and 55 feet below the
lake surface. The spillway elevation of the lake is 285
feet above sea level. Typically, all water is drawn from
the 5-foot level except during summer when some water is
drawn from the 15—foot level and mixed with the shallower
water to achieve an acceptable temperature. Deeper water is
rarely withdrawn because experience has shown that the
higher level of dissolved iron and manganese of the deeper
8
waters causes processing problems. The water is then
conveyed via an underground pipeline to the treatment plant.
Pumps are available to pump water from the lake, but normal
lake levels provide sufficient head for gravity flow. The
raw water enters the plant in a rapid mix chamber where
typically, the following chemicals are added; potassium
permanganate for oxidizing iron and manganese, liquid alum
to enhance flocculation, caustic soda for pH control,
hydrofluorous salaic acid for fluoridation purposes,
hexametaphosphate for corrosion protection, and some gaseous
chlorine for preliminary disinfection. After the mix
chamber, the water is sent to one of the two identical
processing systems to complete treatment. (The plant
expansion of 1987 essentially built an identical processing
system parallel to the existing system.) The water flows
through a series of settling basins which contain rotating
flocculators to enhance flocculation and settling. The
water then flows into dual media filters consisting of a bed
of granular activated carbon (GAC) overlying sand. GAC is
used because of problems with taste and odor control. The
water from Lake Manassas has had taste and odor problems
since the opening of the reservoir. As a historical note,
this water treatment plant was the second facility in the
State of Virginia to use GAC for taste and odor control. (2)
9
Finished water is held in one of two 205,000 gallon
clearwells, which form the structural foundation of the
water treatment plant buildings. The water is then
withdrawn from the clearwells, and pumped into a 24-inch
main which carries the water to water tanks nearer the city.
To complete the disinfection process, and to provide the
necessary chlorine residual for the distribution system,
gaseous chlorine is added just before the water enters the
main.l
Treatment plant operators have been experimenting by
varying chemical addition rates to reduce the level of
trihalomethanes (THM's) produced by the chlorination
process. In general, the THM production level is controlled
by the amount of pretreatment chlorination. Some
experiments have shown that with minimal pretreatment
chlorination, the level of THM's leaving the plant can be
maintained below 30 parts per billion. (2) Current drinking
water regulations require THM's to be held to less than 100
parts per billion.Algae from Lake Manassas have historically caused
significant processing problems. Filter clogging was very
predominant, as were taste and odor problems. In order to
control these problems, Lake Manassas is treated with copper
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sulfate, an algicide. The copper sulfate is applied from a
moving boat in powder form and is typically applied four
times per year, twice in the spring and twice in the fall.
The application of copper sulfate to Lake Manassas has been
practiced for approximately 14 years. (2)
The water from Lake Manassas is rather soft, with an
average total hardness of less that 40 milligrams per liter
(mg/L) as calcium carbonate (CaCOg. Therefore, the
treatment plant does not perform any processing for hardness
reduction.
Watershed Management
As previously stated, Lake Manassas and its watershed
are part of the larger Occoquan River watershed. The
Occoquan River is impounded by a dam near its outlet into
the Potomac River. The Occoquan Reservoir is a very
important water resource in the Northern Virginia area
because it supplies potable water to over 750,000 people and
regional businesses (3).
In 1971, the Commonwealth of Virginia State Water
Control Board issued a policy statement titled "waste
Treatment and Water Quality Management in the Occoquan
Watershed" (3). This policy statement was the result of
research into the increasing pollution content of the
——9e———————————-—------.....................,.___________________________
11
Occoquan Reservoir. In the early 1970's, the major sources
of pollution into the watershed were point source discharges
from sewage treatment plants. The new policy statement
instituted the following major programs:
1. New high-performance wastewater treatment
facilities in the watershed were to be constructed
to replace some of the existing low efficiency
plants.
2. The Occoquan watershed Monitoring Program was
established to continue to monitor the water
quality of the reservoir and its watershed.
3. Erosion and sediment control standards were
invoked.
The State Water Control Board revised the Occoquan watershed
Policy in 1980 to include more detailed requirements for the
performance of new treatment plants and the expansion of
existing treatment plants in the watershed (3). Most of the
analytical data used in this document were obtained from the
Occoquan watershed Monitoring Program.
Current Watershed Development
In November, 1985, a golf resort development company
requested permission from the Prince William County,
Virginia, Planning Commission to build a golf resort on the
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northern shores of Lake Manassas. The golf resort plans
include golf courses, 800,000 square feet of office space, a
500 unit full service hotel, and a residential community of
400 detached single family homes, 200 condominium homes, and
200 townhouse homes. (4) The placement of this resort is
shown in Figure 2, with the golf courses nearest to the lake
areas.
The land that the resort would be placed on is
essentially undeveloped forest and pasture land with minimal
population currently present. In order to obtain a
preliminary understanding of the potential impact this
resort community may have on Lake Manassas, the Prince
William County Planning Commission contracted with the
Northern Virginia Planning District Commission for a
technical analysis. In April of 1986, the Planning District
Commission published the results of their analysis (5). The
following statements summarize the qualitative results of
the analysis;
"Results of the Watershed Model simulations showedthat, due to the very small size of the site [theproposed resort] compared to the total area thatdrains to Lake Manassas, the proposed developmentwould have only a slight effect on the lake. Thefact that the model showed any effect at all,however, indicates that additional developmentwithin the watershed without adequate controlscould result in significant adverse impacts onwater quality in the lake." (5)
That report also recommended that runoff control measures
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and structures be built around the proposed resort to
minimize nutrient and pollutant loadings into Lake
Manassas (5).
K
14
‘ oAan 4 , ’I
.„-·i==E==EE===E==E===E==§:=¤zi -4nz!••§••l•••:§••=••:i¤•§••:=y'
I-!j··=·-=l·‘---···-=¢-=|-=-lg
;•¢-nl,••·•¤=•••!••:•¤l••:••*'
jl glljl I=l°
wir
„ @3
Ruvi
Figure 2 - Development of the Lake Manassas Watershed
15
Limnological Principles
The Lake as an Ecosystem
The study of fresh water bodies, their ecosystems, and
their response to environmental changes is termed limnology.
Limnology is a complex discipline because of the dynamic and
extreme diversity of conditions that exist in the freshwater
bodies of the world. Lakes are ecosystems with the
metabolism of the resident species (herein termed a lake's
metabolism) dependent on and responsive to the inputs of the
entire drainage basin of the lake, the atmosphere, and the
sun(6). As with any scientific discipline, there are
"yardsticks" which have been developed to measure parameters
and thereby enable comparisons between different lakes.
These parameters will be presented along with a discussion
of their effects on a lake.
Morphology
The size and shape of a lake is highly dependent on the
mechanism by which the lake was created (6). Examples of
the processes which create freshwater lakes include:
tectonic movement resulting in the creation of huge basins,
volcanic activity which produce lava flows that can distort
1A——A—-—-—-e---—.-..................................._._„___________Q
Ä
16Ä
as they cool to form cavities and dams, landslides which
create natural dams in existing drainage pathways, glacial
activities which carve out earthen soil and bedrock and
subsequently deposit these materials as dams when the
glaciers recede, meandering rivers which can have entire
sections cut off by sedimentation processes, solution lakes
caused by the dissolution of certain bedrock, shoreline
lakes which result from the cyclic erosion and deposition
actions of wave activity, and manmade lakes which are often
formed by damming existing drainage ways. (7)
Examples of parameters which are used to describe the
morphological characteristics of a lake include lake area:
lake volume, maximum, mean, and relative depths, lake
length, shoreline length, and shoreline development. The
final term, shoreline development, is defined as the ratio
of a lake's shoreline length to the radius of a circle whose
area is that of the lake. Therefore, a perfectly circular
lake would have a shoreline development of 1.00. Typically,
natural lakes have a shoreline development of around 2.00
with some manmade impoundments approaching a value of
5.0 (6). Shoreline development is of interest because it
reflects the potential for greater development of littoral
communities (shallow shoreline areas with a higher
preponderance of life forms) in proportion to the volume of
Ä
17
the lake (8).
The volume of a lake is an important parameter because
it controls the concentration of constituents within the
lake and therefore the lake's metabolism. These data are
often presented in the form of a hypsographic curve which
plots the depth of a lake versus the percent of the total
lake area for a particular depth. The shape of this curve
can help indicate whether a lake has a substantial portion
of its volume at a depth where light could penetrate and
provide energy for photosynthetic organisms (9).
Hydraulic retention time, or the average time an
individual water molecule spends in a lake, is a useful
parameter to relate a lake to its surrounding drainage
basin. Long retention times indicate a stable lake
metabolism, and short retention times indicate a propensity
for quick changes in lake metabolism due to rapid changes in
lake inputs. (6)
Energy Input to Lakes
A lake's metabolism is highly dependent on the input
and distribution of energy within the lake. The food chain,
be it terrestrial or aquatic, starts with the conversion of
solar energy into chemical energy via the process of
photosynthesis. Furthermore, most life forms need some form
18
of thermal energy to keep their temperature in the range
necessary for biochemical processes to proceed. Therefore,
the amount of light impinging on a lake, the depth to which
it penetrates, and the overall distribution of the resulting
thermal energy is very important to a lake's metabolism.
(6,9)There is an array of physical, chemical, and biological
properties which controls the absorption of solar energy.
However, it is the distribution of this energy that is of
most interest to limnological studies. As water becomes
warmer, it also becomes less dense and therefore rises to
the surface of the lake. The cooler, more dense water sinks
and remains in the deeper portions of the lake. Figure 3
represents the change in the density of water with
temperature. Other forces on the lake, such as wind, tend
to promote mixing. However, during the spring and summer
months, the heat input from solar radiation, and the often
less windy conditions associated with the warmer seasons,
create conditions where the heat induced density gradient
remains quite evident, a condition known as stratification.
The layer of warmer water on the top of the lake is termed
the epilimnion, the layer with a relatively rapid
temperature change with depth is termed the metalimnion, and
the lower layer of colder water the hypolimnion. It is
19
‘ , - · — — _ _ 0.01‘ ~ X 0.006
0.999 ‘ X x \ O;\ \V0 xE ¤ OU \ — .005Ö \E 0.998 ‘ 2.\ ‘
X -0.01 g\/\ Cs. \ °°
2 x *0.015 glO x; 0.997 X g‘X -0.02 Rlv; xC \Q \C! -0.025
\\\
-0.03
0.995010 zu 30_ _ Temperature In degree: CDWWHY “' % Change in Density
Figure 3 — Density of Water versus Water Temperature
1
20
easily seen that this set of conditions also acts as a
barrier to mixing of dissolved materials between the layers
of different density (6,9). The effects of this
stratification will be developed further in later
discussion.
With a change in seasons (summer to autumn), the
epilimnion cools to a point where it's density is no longer
significantly different from the rest of the lake. At that
time, the action of wind can induce sufficient mixing action
to create a condition known as turnover. The hypolimnion
and its dissolved materials then mix with the rest of the
lake to create essentially uniform chemical conditions
throughout the lake. (10)
Depending on the climate of the lake's location, ice
can form in winter. The ice cover then creates a small
thermal gradient near the surface of the lake. However,
this stratification condition is much less severe than the
summer stratification. (6, 9)
With the onset of spring, the uniform temperature
gradient develops again and spring turnover occurs. As the
heat input of solar radiation increases in the spring, the
entire stratification cycle is then repeated. A lake which
experiences this type of repeated cycle is termed a dimictic
21
lake, and is typical for the temperate zones of the planet
(6, 9).
Other stratification cycles are also seen for other
sets of environmental conditions, such as: polymictic lakes
which experience frequent circulation cycles (typically
found in equatorial regions with little seasonal weather
changes), cold monomictic lakes which have water
temperatures at or below 4FC most of the year and therefore
little to no thermal stratification (typically found in
Arctic and mountain areas), warm monomictic lakes which have
temperatures always above 4%Zand thus only stratify in the
summer (typically found in temperate climates near oceans),
and oligomictic lakes which are always above ¢© which have
rare recirculation periods at irregular intervals (typically
found in tropical areas). (6,9) The difference between
oligomictic and warm monomictic lakes is that warm
monomictic lakes undergo regular recirculation at the end of
summer, but oligomictic lakes do not undergo a regular
interval recirculation.
Lake Productivity
It is the metabolism of a lake, or more accurately the
metabolism of the organisms living in the lake, that is the
overriding concern of limnological studies (11). All lakes
22
will go through a gradual process of building up sedimentary
material, ultimately turning the lake into a soil column
with surface water flowing over it (6, 9, 11). This process
is called eutrophication. Some sedimentary material is
always being added from the entrained sediment in the supply
waters to the lake. However, depending on the propensity
for organic life forms to exist in the lake, the buildup of
the sediment may be much more rapid due to the addition of
detritus from dead organisms. The usefulness and aesthetic
qualities of the lake may also be severely impacted if too
much organic life is present. For example, excessive algae
growth makes the water difficult to treat for domestic use,
and can inhibit recreational use of the lake (12).
Therefore, it is the productivity of new biomass within the
lake (its metabolism) that can drastically affect the useful
lifetime of a lake (13). It is important at this point to
ensure a useful terminology and technical approach is
developed for this study. The underlined text in the
following quote was added by the author of this thesis to
emphasize key concepts.
"Much of the confusion ...[of limnology]... emanatesfrom early concepts that considered productivity as themaximum growth and development of organisms underoptimal conditions. While the potential of organismsto produce and increase towards infinity may be auseful conceptual framework, in the real worldenvironmental constraints regulate these increases.Optimal conditions for an organism, population,community, or ecosystem can, at best, only be
23i
approximated after extensive investigation. ... It ismuch more meaningful to define the terms production andproductivity in relation to realized or actualproduction of organisms. Changes in production arerelated ...[to the]... dynamics of environmental ...parameters." (6)
It is the environmental parameters such as oxygen content
and nutrient availability, and their affects on lake
organisms that will be discussed further in this study.
This author does not intend that the above noted quotation
over simplify limnology. Instead this author intends that
the quotation help focus the scope of this study because
limnology can involve so many complex interactive variables.
A lake that is low in biomass productivity is termed
oligotrophic, and this condition most often corresponds to a
low supply of nutrients for organic life. As the nutrient
supply slowly increases, so does the biomass productivity
and the lake becomes mesotrophic. Finally, a lake which is
enriched in nutrients to a point where other parameters,
such as the length of the warm season, control the biomass
production is termed eutrophic (14).
Typically, the algal population in a eutrophic lake is
high during the spring and summer seasons because there is
adequate sunlight and because of the slower metabolism rate
during the cooler seasons (9). Algae produce oxygen during
photosynthesis, and it is quite common for the epilimnion
uu
2 4 *waters to be supersaturated with oxygen (15). However, the
thermal stratification prevents the oxygen from diffusing
into the hypolimnion. The aerobic life forms in the
hypolimnion rapidly decrease the oxygen content of the
hypolimnion water to a point below which aerobic life can
not be supported. Often, even fish can not survive at these
locations (9). Anaerobic and anoxic bacteria then flourish
as they decompose organic matter that settles from higher
points in the lake. These hypolimnion conditions set up a
reducing redox potential, which enables the sediment toV
release reduced forms of some metals such as iron (Fe”) and
manganese (Mn”). These materials will remain in the
hypolimnion waters until the lake experiences a turnover
condition with the normal change of seasons (6).
Nutrients Necessary for Biomass Production
All living organisms require a diverse combination of
chemical materials, or nutrients, in order to survive and
flourish. All organisms have different nutritional
requirements, but similar organisms have similar nutritional
requirements (9, 11). The organisms of most interest to
limnologists, with regard to a lake's productivity, are the
phytoplankton communities referred to as algae (8, 11).
These communities are actually a combination of many
N
N25
individual microbiological algae species, including the
blue—green, green, yellow-green, red, brown, and golden-
brown algae, as well as the diatoms and euglenoids. These
organisms are photosynthetic, converting sunlight into
chemical energy for their entire biochemical metabolism.
Table 1 lists their basic nutritional needs and the sources
of the nutrients (1, 6).
Studies have shown that the average stoichiometric
cellular makeup of freshwater algae organisms is given by
C„H„5%J%P (16). From this molecular formula, and the
biological data of Table 1, some conclusions can be made
regarding the nutritional requirements of freshwater algae.
First, carbon, hydrogen, and oxygen are needed in relatively
large amounts for production of cellular biomass. Second,
nitrogen and phosphorus are also needed but in lesser
amounts.
A parallel concept concerning nutritional requirements
and organism productivity is Leibig's "Law of the Minimum"
(9). In 1840, Justus Leibig, while studying inorganic
chemical fertilizers, found that crop growth was limited by
whatever essential element was in shortest supply,
regardless of whether the total amount required was large or
small (1). Therefore, whatever nutrient is the
l
l
26
Table 1 - Nutritional Requirements(6)
Function Source
Energy Source Organic and inorganic compoundsSunlight via photosynthesis
Electron Acceptor O2from Respiration Organic compounds
NO; , NO2” , so}Material for CO2,.HCO;, NOg, NO;, PO;2Cellular Biomass Organic compounds
Trace elements such as vitamins
27 lleast abundant, relative to an organism's need, is the
controlling nutrient for organism productivity.
This concept is a useful and well proven predictive
tool for limnologists and many other biological scientists
(6, 9, 10, 14). However, it should be emphasized that it is
a "relative law", subject to the level of detail of the
. analysis. For example, certain vitamins may be essential to
an organism‘s biochemical pathways such that its absence,
regardless of the supply of energy sources and electron
receptors, could prevent that organism from flourishing.
Also, as stated previously, the dynamic change in the
characteristics of environmental parameters, including
nutrients, also affect the productivity of lake ecosystems.
In lakes, the most necessary chemical elements are also
the most prolific. Carbon is readily available from organic
matter present, CO2, and the dissolved forms of CO2 HCO2 and
cofx Hydrogen is readily available from organic matter
present and water itself. Oxygen is reasonably available in
the epilimnion from both dissolved atmospheric O2, and O2
produced from the photosynthesis process (6). For aerobic
life forms, oxygen is the terminal electron acceptor in
biochemical oxidation - the energy producing process. In
anaerobic and anoxic life forms, other compounds can be the
terminal electron acceptors. Since carbon, hydrogen, and
I28
oxygen are available in relatively large amounts, the
availability of nitrogen and phosphorus controls the
production of algae.
In summary, nutrients can be kinetically or
stoichiometrically limiting. Although the assumptions for
deriving limiting nutrients under either of these categories
can be different, both should be considered when performing
such analyses (10).
The above analysis stresses the production of algae and
other similar biomass. This does not mean that in other
areas of the lake different biochemical processes (or
metabolic pathways) result in a prolific collection of
different life forms, such as anoxic and anaerobic bacteria
in lake sediment (6, 9). However, these other metabolic
pathways are not as efficient in the production of biomass
material (17).
Nitrogen is a common element in the environment, and
its availability to freshwater lakes is the result of
numerous sources. Limnological studies have yielded the
following information regarding some of the pathways in a
lake's nitrogen budget (6, 8, 9, 10, 14).
1. Aerobic decomposition processes are not present in
an anaerobic hypolimnion.
Z29
2. The metabolism of epilimnion organisms can be a
major source of organic nitrogen in lakes.
3. Many components of nitrogen input to lakes are
either seasonal or intermittent in application and
variable in magnitude. Examples of these sources
include organic and ammonia nitrogen from water fowl
excretions, and both organic and oxidized nitrogen from
sewage treatment plant discharges.
4. Nitrogen uptake and release from sediments is a
complex and not well understood process. One study
showed that although there is a significant source of
nitrogen present in lake sediments, it is not readily
available for metabolism in a lake system. Therefore,
I the influent sources of nitrogen usually determine the
quantity of nitrogen available in the water column of a
lake.
In summary, for most lakes, nitrogen is available in
sufficient quantities to not be the limiting nutrient for
algae growth. However, because nitrogen is critical for
biomass production, the amount of nitrogen present can have
w
30
an affect upon the total amount of biomass produced.
Therefore, minimizing the nitrogen input to a lake is still
a desirable objective.
The magnitude of nitrogen in drinking water can also be
an environmental health issue (18). Ammonia is toxic to
many organisms when present in sufficient quantities, and
nitrate is toxic to human infants (19). Therefore, control
of nitrogen is important for both lake productivity and
water resource usefulness.
The preceding discussion concludes that phosphorus is
often the most kinetically and/or stoichiometrically
limiting nutrient with respect to lake productivity. This
has been demonstrated in numerous laboratory and natural
environmental experiments. For example, one of the most
dramatic experiments was performed on a natural lake in
Ontario, Canada, which had a natural shape like a dumbbell
(6). A partition was placed in the narrow section connecting
the lobes of the lake. The partition prevented cross-flow
between the two main lobes of the lake. One lobe was
fertilized with phosphorus, nitrogen, and carbon, and the
other lobe was fertilized with equivalent concentrations of
nitrogen and carbon only. Algal biomass increased two
orders of magnitude in the lobe which received the
phosphorus, but it did not appreciably change from normal
1
V
31}
conditions in the other side. (6) Pre-experiment conditions
returned in both lobes of the lake quickly after
fertilization was stopped. Many other similar experiments
demonstrate that phosphorus inputs to a lake ecosystem can
drastically and rapidly change the biomass production rate
(20).
Most of the phosphorus (often greater than 95 percent
by mass) present in a lake at any time is not readily
available for utilization by algae (11). This unavailable
phosphorus is bound in organic phosphates and cellular
constituents of organisms, both living and dead, and is
absorbed by organic and inorganic colloids, and particulate
compounds (6). Also, the highly reactive chemical
properties of phosphorus further amplify the shortage of
this nutrient, because any supply is rapidly depleted (9).
Phosphorus exchange between lake water and sediment is
highly dependent on the oxidation-reduction conditions at
the sediment water interface, and on the mixing (turbulence)
conditions of the lake (21). In general, studies have shown
that the phosphorus budget of a lake is more complex than
the nitrogen budget, partly due to the rapid kinetics of the
phosphorus reactions which make measurements difficult (6).
32
Quantification and Prediction of Lake Productivity
The ability to quantify and predict the trophic status
of a lake can be useful when it is desired to monitor,
control, or correct the productive status of a lake (10,
14). Numerous models have been developed which insert
easily measured parameters into empirically developed
relationships. Most of these models have been developed
based on the assumption that a lake is phosphorus limited.
Since these models are empirically developed, their results
must be tempered with appropriate professional judgement
(6)-One of the first and most successful models developed
was the Vollenweider model (6, 20). This model used annual
mean concentration values of total phosphorus and
chlorophyll a to assign a trophic status to a lake.
Vollenweider then improved his model to use the annual
loading rates of phosphorus to arrive at a trophic status.
It is then easier to develop control measures to ensure
loading rates do not exceed the desired level of
productivity.The Vollenweider model is a mass balance equation for
phosphorus. The change in total phosphorus is equal to the
influent loading of phosphorus minus the sum of the outflow
of phosphorus and the sedimentation of phosphorus. The data
I
Z2 2 *
are represented by graphing the annual phosphorus loading
(mass/area/time) versus the mean depth (length) times the
hydraulic retention time (years). The abscissa in this
graph is the relative "flushing" term because it relates the
rate at which water is changed in the lake to the amount of
the lake which can produce algae due to light penetration.
The resulting curve is shown in Figure 4. Vollenweider
designated 'admissible' and °dangerous' loading levels,
which are depicted by the curves shown on Figure 4.
Vollenweider's assumptions were pointed out as
important limitations by Dillion (20); 1) the lake is well
mixed, thus ignoring stratification affects, 2) loading,
flushing, and sedimentation rates are constant, 3) the
sedimentation process is first order relative to the amount
of phosphorus present, and 4) no credit is taken for
internal loading of phosphorus.
A different type of model uses water transparency and
other parameters to arrive at a "trophic index".
In 1977, Carlson published a scheme to classify lakes
using three different Trophic State Indices (TSI) (22). He
emphasized that a TSI was not a water quality index, but
that the TSI could be useful for comparing lakes within a
region, and as a management tool for predicting productivity
34
10EUTROPHIC
Dongerous ///
Q3 /1
// //E // Perysséle9//E
/Q /P3 ,/"Ö
ii'-___-,••¢g 0.1 1o¤o,-1 0L1GO"1‘R01>1—11C
0.010.1 1 10 100
Medn Dep1n('Z)/Medn Residence T1nne(tdu)
Figure 4 - The Vollenweider Model Relatienship
E35
changes when it is used in conjunction with nutrient loading
concepts.
Carlson uses the epilimnion values of total phosphorus,
chlorophyll Q, and secchi disk reading to arrive at a TSI
for a lake. Carlson's scale is based on the increase in
algal biomass in response to an increase in the phosphorus
concentration. Many factors can affect the ability of
Carlson's model to accurately predict the trophic index of a
lake, such as seasonal changes, and highly colored or turbid
waters. He found that man—made impoundments showed
different relationships than did natural lakes. Carlson
speculated that man-made impoundments may be muddier than
natural lakes, thus affecting the secchi disk results. (1,
22)
Carlson's model yields a TSI value between 0 and 100.
However, he did not propose ranges of a TSI relative to the
older oligotrophic-mesotrophic-eutrophic system other than
to say that a higher TSI indicates an increased propensity
for eutrophic conditions.
Tables 2, 3, and 4 present the TSI scales developed by
Carlson, Sakamoto, Dobson, the National Academy of Sciences,
and the U.S. Environmental Protection Agency. The parameter
values provided are the epilimnion averages during the
summer season. (23)
A
36
Table 2 - Carlson's Trophic State Index (22)
Secchi Dish Surface SurfaceTSI Depth Total Phosphorus Chlorophyll Q
(m) (micrograms/liter) (micrograms/liter)
0 64 0.75 0.0410 32 1.5 0.1220 16 3.0 0.3430 8 6.0 0.9440 4 12 2.650 2 24 6.460 0.5 96 5670 0.5 96 15490 0.12 384 427100 0.062 768 1183
Analytical equations to generate the table given above are:
TSI Secchi (S) = 10*(6—(ln(S)/ln(2)))
TSI Total Phosphorus (TP) = 10*(6-(ln(48/TP)/ln(2)))
TSI Chlorophyll Q (Cha) = 10*(6·((2.04·0.68*lh(Cha))/1H(2))
i
\
137
Table 3 - Trophic State Indices Based on Chlorophyll QChorophyll Q in micrograms per liter (22)
TrophicCondition Sakamoto Academy Dobson EPA
Oligotrophic 0.3 to 2.5 0 to 4 0 to 4.3 <7
Mesotrophic 1 to 15 4 to 10 4.3 to 8.8 7 to 12
Eutrophic 5 to 140 >10 >8.8 >12
3 6 1I
Table 4 - EPA Trophic State Index System (22)
Trophic Chlorophyll a Total Phosphorus Secchi DishCondition (micrograms per liter) Depth (meters)
Oligotrophic <7 <1O >3.7
Mesotrophic 7 to 12 10 to 20 2 to 3.7
Eutrophic >12 >20 <2.0
I
Chapter III
METHODS AND MATERIALS
The City of Manassas has contracted with the Occoquan
Watershed Monitoring Laboratory (OWML), located in Manassas,
Virginia, to design and implement a monitoring program for
the lake and its tributaries (24). Sampling of the lake
began in October of 1984. Sampling of some of the
tributaries to the lake began as early as 1975 as part of
the greater Occoquan Watershed monitoring program. The OWML
has established schedules and procedures for the Lake
Manassas monitoring program, and the data generated from
this program is stored at the OWML and on the mainframe
computers of the Virginia Polytechnic Institute and State
University.
Sampling Program
The Lake Manassas sampling program consists of eight
sampling locations on the lake, and are designated on
Figure 5 as LMO1 to LMO8. The Lake Manassas tributary
monitoring program consists of eight sampling stations,
designated on Figure 5 as BRO2 to BRO8 and ST70. Samples
obtained at the stations denoted by the BR series are grab
samples, whereas samples from the ST70 station consist of
39
II
40
oe® NorthFork
IROS ‘’
LMO!
L L:
1
A
N
inno:A
t ROIIR02
SouthRuri
IROIIRO1
Figure 5 — Lake Manassas Sampling Stations
— _
I
K
r41
both flow weighted composite samples and grab samples. ST7O
is the only tributary to the lake that is gauged.
There is a gauged monitoring station for the outlet
from of Lake Manassas, ST30.
At the LM series lake sampling stations, field
measurements are obtained at the one-foot, two-and—a-half-
foot, and five—foot depths, and then at five foot increments
until the bottom is reached. Sampling is typically done
twice a month, slightly more often during the summer months
and slightly less often during the winter months if ice is
present. Field measurements include dissolved oxygen,
temperature, pH, and Secchi disk reading. Samples are
obtained from the one-foot depth and the bottom depth for
later constituent analysis in the laboratory. These
constituent analyses include phosphorus and nitrogen
concentrations, solids concentrations, conductivity,
chlorophyll Q, and occasionally other pollutants such as
metals.
Grab samples from the BR series tributaries are
analyzed the same as the lake samples. The flow-weighted
composite samples and grab samples from the ST70 and ST30
stations are also analyzed in a similar fashion.
One unique situation in the monitoring program is on
the South Run tributary to the lake. The water from Lake
42 :
Brittle, a state owned impoundment used as a fishing
reservoir, is monitored at location BRO7 (2). All of the
water from the South Run watershed flows through Lake
Brittle. Downstream of BRO7 and immediately downstream from
the point where a discharge from the Vint Hill Farm Station,
a U. S. Army Military Reservation, enters South Run is a
monitoring station, BR02. The discharge from the Vint Hill
Farm Station is from a sewage treatment plant, and is a
State of Virginia permitted facility (24). Finally, South
Run is monitored just before it enters Lake Manassas, ati
BRO3.
Sample Analysis
All samples and measurements made are logged by using a
unique sample identification number which is generated by
the computerized data management system. All sample
analysis techniques are performed in accordance with
Standard Methods for the Examination of Water and Wastewater
(31).
The computerized data management system which contains
the results of this monitoring program is structured and
maintained in an IBM-PC format database language, dBASE
III+, a trademark database computer language. The field
names for the database and the corresponding parameter which
I
I
43
is represented by the database fieldname are listed in Table
5. All of the fields are stored as character fields except
the fields containing date information which are stored as
date fields. All of the fields have a length of 8
characters except the time fields which are 5 characters in
length. The format for data in fields containing numerical
information is for the decimal point to always occupy the
third position from the right end of the field. If the
parameter being measured is less than the analytical
detection limit, the detection limit is entered as the value
with a negative sign in front of it.
Data Analysis
Various IBM-PC software packages were used to perform
the numerical analysis for this report and to generate the
graphical data presentations of Chapters IV, V and VI.
Most of the numerical analysis performed on the data
was done by extracting the appropriate data from the
database and importing it into a Lotus 1-2-3 spreadsheet.
Typical mathematical functions were then used to obtain the
desired values such as average concentrations. Most of the
graphs produced for this thesis are from the Lotus
1-2-3 graphing routine.
Z44
One set of graphs which were produced by another
program are the contour graphs presenting lake data as a
function of depth and time. For example the temperature
profiles over the depth of the lake for the monitoring
period. These graphs were produced using a software package
called SURFER. This program takes numerical data from a
Lotus 1-2-3 spreadsheet and uses contouring techniques to
develope the subject graphs. Different techniques can be
selected, and for this thesis the technique of inverse
distance between individual data points was used by the
program to splice contour lines between data points. SURFER
also offers another optional contouring technique known as
"krieging." This technique uses geostatistical equations to
splice contour lines between data points. However, because
the data analyzed in this case are not derived from
geological processes (i.e. erosion, faulting, or other
geologic process), this optional contouring technique was
not used. One shortcoming of the SURFER contouring
technique is that it attempts to close all contours over the
abscissa data range. This can result in graphical
anomalies. For example, in the case of temperature profiles
with depth, there are some closed loop contours within the
water column. Physically, this implies that warmer water is
both above and below a "pocket" of cooler water. This is
45
not physically possible, because the density of water
increases steadily as temperature decreases for temperature
above 4x. The cooler water should sink, not float on top
of warmer water. This limitation of the computer software
does not have a serious affect on the analyses results of
this thesis because the graphs developed are used almost
exclusively in a qualitative manner.
Another computer package utilized for this thesis is a
companion program to the Lotus 1-2-3 program (also called a
Lotus add-in) called @RISK. This program provides
Lotus 1-2-3 with additional mathematical functions used in
statistical techniques. In this thesis, the Vollenweider
model was converted into a computer "spreadsheet model" of
Lake Manassas. This spreadsheet model used the hydrologic
data determined for the lake input streams (discussed below)
and the nutrient sampling data from these streams (the dBASE
III+ database). The spreadsheet lake model used @RISK to
enable the model parameters (e.g. nutrient concentration,
stream flowrate) to be expressed as continuous distribution
functions. The model, when executed, analyzes each variable
separately according to the parameters listed in their
respective distribution functions (27). The results for
each iteration are tabulated, and another iteration of the
model takes place.
I
46
Applying the Vollenweider analysis in this way allowed
all of the environmental parameters in the model to vary
across their respective ranges independently of each other.
This methodology reduces induced biasing resulting from an
arbitrary "averaging" technique that would be normally used
in the Vollenweider analysis. Table 5 lists the various
model parameters and the distribution functions chosen for
them. The truncated lognormal distributions were chosen for
the stream total phosphorus concentration based on the
results of extensive environmental studies which showed this
distribution to be the appropriate choice (25).
All of the distributions were truncated to both the
highest and lowest observed values to ensure the model did
not select concentrations that were outside the range of
actual observed data (26). The model was executed 1000
times using a latin hypercube distribution to ensure
adequate sampling of the entire range of any parameter
value. The spreadsheet model used separate parameter
distribution functions based on median values and average
(mean) values for each parameter. This modification further
reduces biasing of results. The results of this analysis
technique are presented on the Vollenweider plot as a "box"
instead of a point. Therefore, this analysis technique
minimizes one of the shortcomings of the Vollenweider
1
I47
Table 5 — Distribution Functions for Spreadsheet Model
Yearly Rainfall Normally Distributed
Vint Hill PhosphorusConcentration Normally Distributed
All other StreamPhosphorus Concentrations Truncated Lognormal
I
I48
analysis; forcing a real world dynamic system into a static
model. The modeling technique used in this paper still
results in a single set of parameter values for predicting
the eutrophic
status of Lake Manassas, but these predicted values are the
result of allowing all parameters to vary "dynamically." A
distribution of possible results is obtained with
corresponding statistical properties, thereby producing a
better understanding of the stability of the eutrophic
status of the lake. A Latin Hypercube sampling technique
was used for the parameter distribution functions. This
sampling technique is different than the pure random
technique of Monte Carlo sampling, but it allows for
convergence on the "true mean" in fewer iterations than
Monte Carlo. Latin Hypercube essentially constrains the
sampling to the higher probablility values of the
distribution functions.
This spreadsheet model analyzed Lake Manassas at "full
pool" conditions and did not account for the yearly
drawdown—refill cycle that can be encountered under normal
operating conditions. If the model was modified to account
for a changing volume and mean depth with time, the
predicted results would a be a more accurate prediction of
the lake's eutrophic status. However, in this case the
I
49
proportional decrease in volume and mean depth would be
approximately linear, (see the range of values in Figure 6)
thereby cancelling each other out in the z/tau parameter.
The z term is the mean depth of the lake, and the tau term
is the mean residence time of a water molecule in the lake
(e.g. flowrate divided by the volume). Furthermore, the
lake drawdown level change is highly dependent on yearly
rainfall (a normally distributed variable), and the end
result should be a z/tau distribution of very similar values
to that of the current model.
Finally, there was insufficient data in the existing
database to quantify the magnitude and periodicity of the
lake drawdown cycle.
Measurements of a geographical and hydraulic nature
were made with a planimeter (27). U.S. Geological Survey
Maps served as the templates for these measurements (28).
For purposes of this study, the Lake Manassas watershed was
divided into five separate basins, three of which compose
approximately 90 percent of the total watershed area. The
breakdown was based on the hydrology of the surface water
inputs to Lake Manassas and on the database available from
the existing environmental monitoring program. Planimetric
techniques were employed to determine the basins areas.
11
50
The database also contains information on the amount of
rainfall received in the area around Lake Manassas on a
yearly basis. The rainfall data can be linked with the flow
data for Broad Run at station ST70 to develop a runoff
factor as a function of total rainfall on the ST70 basin
area. An average %Runoff curve can be developed by dividing
the yearly flow through a watershed by the yearly volume of
rainfall on the watershed. This method assumes that the
basins are of similar character with regards to runoff
potential. The predicted flows can be combined with
monitoring results for the other basins to yield loading
rates for each basin (29).
I
II
51 ITABLE 6 — Database Structure and Contents
Field name Field contents
STA Monitoring station number
LABID Laboratory ID number
DATEl Date of sample for grab samples,start of event period forcomposite samples
TIMEl Time of sample for grab samples,start time of event forcomposite samples
DATE2 Blank for grab samples, finishdate of event for compositesamples
TIME2 Blank for grab samples, finishtime of event for compositesamples
UPDATECHAR Indicates which data has beenupdated
UPDATE Date of data update or change
STRMNO Storm number for compositesamples during a storm event
SAMNO Number of samples taken tomakeup the composite sample
TYPE Grab or composite sample
DEPTH Depth of sample for lake samples
STAGE Stage of stream based on gageheight
POOLELEV Height of water in lake at thedam gage
FLO Flow rate of stream in (ffysec)
I
I
I52
TABLE 6 — continued
Field name Field contents
TOTFLO Total flow during event forcomposite samples in (ftÜ
TOTRAIN Total rain in inches for event
WFDFVOL Storm to base flow ratio
DO Dissolved oxygen in mg/L as O2
FIELDPH pH of sample measured in field
LABPH pH of sample measured inlaboratory
TEMP Temperature of sample in field_ in K2
COND Conductivity of sample measuredin field
COND25 Conductivity of sample correctedto 25 °C
PALK Phenophtalein alkalinity in mg/Las CaCO3
TALK Total alkalinity in mg/L asCaCO3
SECCHI Secchi disk reading in inches
OP Orthophosphorus concentration inmg/L as P
TSP Total soluble phosphorusconcentration in mg/L as P
TP Total phosphorus concentrationin mg/L as P
NH3_N Ammonia nitrogen concentrationin mg/L as N
T
53
TABLE 6 -continued
Field name Field contents
SKN Soluble Kedjadl nitrogen in mg/Las N
TKN Total Kedjadl nitrogen in mg/Las N
NO2_N Nitrite concentration in mg/Las N
NO3_N Nitrate concentration in mg/Las N
OX_N Total oxidized nitrogenconcentration in mg/L as N
COD Chemical oxygen demand (meq/l)
TOC Total organic carbonconcentration in mg/L as C
BOD5 BOD concentration in mg/L after5 days
BOD5I Inhibited BOD concentration inmg/L after 5 days
BOD20 BOD concentration in mg/L after20 days
BOD20I Inhibited BOD concentration inmg/L after 30 days
BOD4O BOD concentration in mg/L after40 days
BOD40I Inhibited BOD concentration inmg/L after 40 days
TURB Turbidity in (n.t.u.)
TSS Total suspended solids in mg/L
I¤
54
TABLE 6 - continued
Field name Field contents
VSS Volatile suspended solids inmg/L
TDS Total dissolved solids in mg/L
TS Total solids in mg/L
CHLA Chlorophyll by the trichromaticmethod in micrograms per liter(ug/1)
CHLAM Chlorophyll by the monochromaticmethod in ug/l
PHPA Chlorophyll by the phenophatleinmethod in ug/l
TCOLI Total coliforms as most probablenumber (MPN)
FCOLI Fecal coliforms as MPN
TAG Total silver in mg/L as silver
EAG Extractable silver in mg/L assilver
SAG Soluble silver in mg/L as silver
Other metals in the database include aluminum, cadmium,chromium, copper, iron, mercury, manganese, nickel, lead,and zinc. All are included as fields similar to silver,named by T, E, or S with their two letter chemical namefollowing.
Chapter IV
RESULTS
This section presents the results of the analysis
performed using the environmental database discussed in
Chapter III. Results from lake data will be presented
first, followed by results from stream data.
Lake Manassas Morphology
Planimetric measurements were conducted on standard 7.5
minute U.S. Geological Survey maps of the area comprising
Lake Manassas. These area measurements were combined with
elevation data to develop a hypsographic curve for Lake
Manassas (Figure 6). Table 7 gives the other morphological
characteristics measured for_the lake.
Lake Manassas Thermal Stratification
Figures 7 through 14 represent the temperature profiles
for Lake Manassas at lake monitoring stations LMO1 through
LMO8. The figures were developed by contouring the measured
temperature i11°C at a given depth (the ordinate) over the
monitoring period (the abscissa). Chapter III contains a
more detailed description of the contouring technique. The
figures are structured so that the surface of the lake is at
55
56
Table 7 - Morphological Characteristics of Lake Manassas
(at full pool of 285 feet above mean sea level)
Lake Volume 4.2 billion gallons
Lake Area 694 acres
Maximum depth 55 feet
Mean depth 11.5 feet
Length of lake 2.9 miles
Shoreline length 17.3 miles
Shoreline Development 29.5
I
* I
I
57
€ IU', I
* A I3260 LO
E0
L;.I I---2250 L
I
E H---230 ==
0 2 4(Times 1OE9)
Volume of Loke Moncssos in gollons
Figure 6 - Hypsographic Curve for Lake Manassas
II
58
the top of the graph, and the ordinate scale is denoted by
water depth in feet. The abscissa is scaled in months from
the start date of the measurements. For Figures 7 through
12, the start date was October 31, 1984. For Figures 13 and
14 the start date was August 13, 1986. The monitoring
period for Figures 13 and 14 is shorter because sampling
stations LM07 and LMO8 were added to the monitoring program
after it had been in place for some time.
As discussed in Chapter III, there may be some closed
loop contours within the figures. This is a limitation of
the computer software program used to develop the figures.
II59II
ICI I 33äöG I 32,33;; II5
cnÄ I *I I I A I I I I 19 1 — I VI I{ I I I F GI IQ I I‘° I I, 31 I I
CI G SI E N ** S Q I17 /I O O I; I II I °“
6 .2* I IQ _IpG II.; I I QI gl“* I — I I I I I I I Ic: I 0 _ O1..; QS I G I I* I I I§‘29 I I I I I I Ö 4I I; I II I2 I I I3
33 O O. I IN I I I I I IG I37 I I I I I I I I OI
I I _I I · I I I I I Q"‘ IQ I I QI I I* I I I45 . I 1 ÄLl|I¤v84 Mar 85 Jul 85 ||0v85 N|r86 älnßö ||0v86 Mar 87 JuI87 Nov 87 Har88
Figure 7 — Temperature Profile at Monitoring Station LMO1
60 Z
3 I I I ämgfvän I IIII I I °IIC I I I I
H I I I ~I 3 I IC I I 9 I __ I II I Igw I; I} I IEM QSI IEC}! I III
I I I EIBIZE OlC I I I I
P I I EQ) I I I?I I (I33 I I, I I I3* I„ }! I 9 I I 9 I3
—' · I 4
Figure 8 — Temperature Profile at Monitoring Station LMO2
I
61 II
II I I TFIIBLQS I I I SIIQIU
4 I II 6 I 9;,; I IS I I
8U”‘E II I I II I I II; 4 I
812 I III I I I I I ag I IC) I
Ü; UI m Ig;3 I
I .4 LI 4INOv84 Mar 85 JuI85 IIov85 Iurßß I•ov86 Nur 87 JuI87 Nov 87 Marga
Figure 9 - Temperature Profile at Monitoring Station LMO3
62
7 I I MI77 I3 I IIII7[Q2 7 I lg I I .
ä I ml’ I I II I 7 IQ I7 S
IEISÖI 7 I SI I <I II I I’° gl I I I Iäg ‘° “° II7I (I77 I I I I I I (I II gl I E l „l¢‘—” I I3; „ 1 4 I
Figure 10 — Temperature Profile at Monitoring Station LM04
I
I63
I 1 1 1 1 12C:I _ 66;. Ö mag, "’6„3”¤2§»6 » IÖ
@6 In ;„ I · I I Q5 1 61 1 QI ow ·> NUII
ä8 I I I I I ‘ „I 2 I5 I 5’ 1 5 5 1 @1 ~I5 °“ “ 666 „„_E (Ä) EF)0 Em ä dl QGQ wal <)I 418 Q O@2 aI ® GI IO G ·22 I I ’° I5 I I I
_ „¤I IJ I I 5 I ;,,I 455 1 1 1~» 1 6 1 1 1 ~» 61 1.. ,. ·— 0;-/
jpNov 84 Mar 85 Jul 85 Nov 85 Mar 86 Nov 86 Mar 87 Jul 87 Nov 87 Mar; 88
Figure 11 — Temperature Profile at Monitoring Station LMO5
64
KQ Q I I_ I8 I _/ I I Ig 3 , ägmß. Ä} «¤ > "*04Q n I I O I N I I"" V 70 N EQ 7 Q I I IQ 21 I8 r
Q I3 I O I I I <H’
Q /0
E Q I6 Ip es QI Io \„I5 Ä
‘Kn 1 I L 4K1
nov an nov as Jul 85 nov 85 nor 86 QQL86 nov 86 nov 87 Jul 87 nov 87 M, 88
Figure 12 — Temperature Profile at Monitoring Station LMO6
65
LArx
wG"" .4:2 .·-•
,,— 4 5 °° ·'?>° äj 9*56 „ EQ 6 6 ‘* ”P » :,4 2 626 9 ”‘
Gi? 6/0 KÜ"/
40“O
YZ • $4 ‘Unna Umcu U^P'°‘7 H- UMUB7 l3D•c87 l3Apr88
Figure 13 — Temperature Profile at Monitoring Station LM07
66
J J G2 I
G6)I
I I I I ® 6ET Q 2Z I I I I* Ggs I I I (P .
I ’\
NI I 07 U"
s_ Q AIQQIIQQQQ “°°°“ IMP"? nu l3A¤¤87 1:061:2 13 I Q
Figure 14 - Temperature Profile at Monitoring Station LMO8
u
67
Lake Manassas Dissolved Oxygen Profiles
Figures 15 through 22 represent the dissolved oxygen
profiles for Lake Manassas at lake monitoring stations LM01
through LM08. The figures are developed by contouring the
measured dissolved oxygen concentration (in mg/L) at a given
depth over the monitoring period. The figures are
structured so that the surface of the lake is at the top of
the graph, and the ordinate scale is denoted by water depth
in feet. The abscissa is scaled in months after the start
date of the measurements, as in Figures 7 through 14.
Figures 23 through 30 represent the percent saturation .
of dissolved oxygen for Lake Manassas at lake monitoring
stations LM01 through LM08. These graphs are a combination
of the temperature profile graphs and the dissolved oxygen
profiles. The percent oxygen saturation corresponding to
each dissolved oxygen measurement was calculated based on
the measured temperature at that location. These graphs are
structured the same as Figures 15 through 22.
Note that for these figures closed loop contours are
both possible and expected because of the presence of
submerged microorganisms (algae) producing oxygen by
photosynthesis.
LI
ÜII/III1I//Aix O
gw J )\§/ OO L/66 L IE IZIIQIQI·III QQ31
“V‘IL“VI°Figure16 - Dissolved Oxygen Profile at Station LMO2
I
70
0 I I4 9 °O E oo °°O
vu //8 8 I Q 0)/IIll(O co-•-{ <O
I6 g' \ /0/\ 88 \\ }¤°° 5 2 ram O
. /\ _I „ IIIZIONVN wlhrö JH85 I0v85
A·hvö lhr87 JAI87 hv87 hrs!
Figure 17 - Dissolved Oxygen Profile at Station LM03
III
72
N Ä I I > IX I I I III IIP4I I ’ — I I ‘I. II I I I I*’ ,/I I O I II I
LI I I I 8/I I I (I / Ä F/I I I17 I
IIII I II I I FS I/I 0
,' . I1__¤•
II II I ;C, I III°° II IG I I I OV I
I /0 / \‘X22* 8, kJ I II/cI I II 6=
2O VLOII,/I II
/I /I85 88I
88Figure19 - Dissolved Oxygen Profile at Station LM05
73
IIUI
x\I""
/7 Ix „ ß \ I I5 // III IQ4 ‘ ‘ ’ / I gI1 G? xx (O OG //
R 5/ ~Xy \_‘I7„X „ I 7/ IX \/ \/F}‘\.
'’
"I I I}§>xf~8ÄW¥ m•·2?s—'° u¤v6s‘“'°°nTWi"§l?6‘i "i•6§66‘¤§·’67 adi 87*--Tov 87 niä
Figure 20 - Dissolved Oxygen Profile at Station LMO6
I
74
I I I ^ I 3 I I ·I
I I ‘ E °° ·I @*H ·\I I I F¤ XX I @3 I I I *3 / I·•-I 4
I \\u ‘— I S' \) io _ /7 I3 c¤ OI I II \ • I I I I '„ II rl /I I‘i;W§?•€—’ II *i$‘¤¢T662"‘* ia ^TIIW"““F¤ä’——‘—ü@—*—‘
Figure 21 - Dissolved Oxygen Profile at Station LM07
11
7 5
O1
1 1 1 1 1 1 Q 12 6 1 1/‘1 9 \ 1 111
Q 1 1 OO 1 1 1U 6 6 1 ; 1 1 1 1 L1 ÄQ 1 1 / 1 1
1 1/‘*·‘
1 rx \11 V 1 1 1 1 1 Q-/1161., „' 1 1 1/„¤
1 1 1/ „ 1 1 1 Q8, 1 1 1 1 1 /— 7G! Ä 1Q 1 ¤¤ 2 1 2 1 1 11 / 1 °°J1’1 1/ 1 1 1 «’1 1^\ 11 1 1 1U 1
13 MTU 13 Dec 86 13Apr 87T1
13Aug 87 1 13 Dec 87 Apr 88Z
Figure 22 - Dissolved Oxygen Profile at Station LM08
Ä . ~ Ä igix j Ä O9 *9 ÖO 99 M ./OÄÄ Ä
99 Ä 99 QSÄ Ü Ä4“9Ä..®ÄjÄ?Ä(.lÄ]<@>Ä ..< Ä„... .. .. . 9..]* ..>.
81
u 3 //,’ /·=/'\
2 7 \_/ U( O /1
‘*~·@ ¤ 7@ F 3 Q, g1 •• mas mas mas ••••-aa #26 man mar mar ama: man
Figure 28 - % Saturation DO Profile at Station LMO6
82
·* U 2 / 7 ~ in 7Ä \ 6 6 Ä ) an
. ~ /g ,7 "
7 ‘\
>A4 \ /U / j
E n ‘ \ O? <>“7M)8
-l[._.n..4..l..na£n.- .names nn¤•¤a6 neuw “_ne~·¤w num; „„„„
Figure 29 — % Saturation DO Profile at Station LM07
i
83
·"—’*—Y"T“Ä—°"fgf
3 Üg lg *\}<;>\\°••
){C}tg
lyß2/l/ 2
\\un.;umen 13l•r87 H- llmßl 130•c87 xappaa
Figure 30 · % Saturation DO Profile at Station LMO8
I
II
84
A different presentation technique for the dissolved oxygen
data was use in Figures 31 through 34. Figure 31 is the
dissolved oxygen data for monitoring station LMO1 plotted
against time. Two curves are plotted, one curve
representing top waters for samples taken at the one foot
depth, and the other curve for bottom waters representing
the samples taken at the lake bottom for that monitoring
station. These plots are called bottom and top plots.
Figure 33 is the same as Figure 31 except that the percent
saturation dissolved oxygen data are plotted.U
Figures 33 and 34 are the same as Figures 31 and 32
except that the data for monitoring station LMO8 are used.
It should be noted that the LMO1 figures represent
approximately four years of environmental monitoring data,
whereas the LMO8 figures represent approximately two years
of environmental monitoring data. Additionally, some of the1
top and bottom plots indicate that values have approaching
zero. The author considers it important to stress those
data points that were measured at less than the detection
limit for that parameter. By graphing these data points as-
as half their detectable limit, the data is emphasized.
Furthermore, it helps overcome some of the scaling problems
associated with graphing data that extends over orders of
magnitude.
I
1II
8514.00 II1
12.00 IIII„„ I I I
Äu /+/ II II H [ II uT10.00II_ / I II I I I Iu I
I II „ za II I I IIII I I nv n IIII u EI. I I n I I
I| I I II I II I I- ·I .. = = " ·
I I III I I é I
I I M I u I I
é I I B II I u I I_I I "' IS · 1 T Y Y I Y IO I I ' I I I ‘
O I I I I I I II I4.00 · · I I I ‘I ,
I I I 1 I I I II II I I
III ‘I'I
II I I I I +\ I2.00 I I 1 · X I
\ I II II I I I \
\ * II I
**+~+/*" + 4+ 4 +’ "** I0.00 " eiI Apr-84 Jun—85 JuI—86 Aug—87 Sep—88
Ü SIS Sat DO Q surface I % Sat DO Q bottom
Figure 31 — Top and Bottom DO Profiles at Station LM01
86
160.0011140.00 " 411
120.00 .1 {O
hull V4
R" JO 100.00 ¤ ,_ ~1 6 4 Qc " „ r 1* ‘ ° "rg 1. 'J 1 J1 1 J1 T
E 4_ ,·t{ Ä\
n E/ 1 J
2 80.00 Q1- Q /4; 4 ·· I 1 Q1I0 1 J
1,1 J ‘1 Q1 1 ·· ; 14 ·& 6000 Ä J ’ 1 '
‘ '' QJ4 T 4 1T·1 I ‘ Ä
‘. E 1J J I
+ 1 1 1 1
40.00 Q‘4 1 Ä 1 1 1
l 4 l \ I1 1 Ä ‘ Ä 1 Ä ,1 1
‘ 12000 1 1 Q 4 Q
‘\Q 1
J 1 J 1 „1 J ‘ 1 1. JJ
11-0001 “Apr—84 Jun—85 Ju|—86 Aug—87 Sep—88
D % Sat DO @ surface + % Sat DO 0 bottom
Figure 32 · Top and Bottom % Saturation DO Profiles
at Station LM0l
1II
87
14.0011
II I1 I~ ¤ \ I+ I
12.00 , ~__ I
/ \\
I+ I
I1 n /¢ I1 \ / II
_I \\
+ I1 ‘ 1 I ”IIII I I „ \ I If
10.00 . ~ I 1 In II ‘ I I ‘ / I II u I ¥ \c( 1I
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II II ; IE 8.00 I I I + I,xy
I + I 'I I Eu u I I+ \ “
II + u III I II I 1 I3 1 " I ‘ I II 1 1 1 ' 1 I
6.00 I II . , I I1 II /I 1 I I \III I 1 1 I I'4 I I \ I
I I 1 II1' I I
I1 1 I I4.00 II I I
I1 xlI 1I1
2.00M¤r—86 Oct—86 M¤y—87 Nov—87 Jun—88
EI DO ct Top I DO ot bottom
Figure 33 - Top and Bottom DO Profiles at Station LMO8
II
88
140.00III
120.00 Q+~
_ +IIEI
III III Ia I I010000 Ä IQ \ I III II /\ \ I; I I I gg IE I Q I I I T T3 \ / I I \ 1 I I I I I'°ö II I I T I I I I I IVI 80.00 I I I'
‘I ,‘ ‘I I II I' IR 0 I ’ I 1 I, III + II I \ / I I I
/I I \ / I I I II I \ / I I I;II II 4- I I 4 I
I
6000 ß Q · II · .' I
I II I
*II
X-40.00“¤'·86 O¤t—86 M¤y—87 ~¤v—67 Jun-66
G SIS Sot. DO ct top + % Sot. DO ot bottom
Figure 34 - Top and Bottom % Saturation DO Profiles
at Station LMO8
I
89
Chlorophyll a Profiles
Figures 35 through 42 are plots of the Chlorophyll Q
concentration at the lake monitoring stations. Contours
with depth of Chlorophyll Q are not possible because this
parameter is not measured at depths other than the surface
(one foot depth).
I
II
90 II
30 II2826I[PI24 I I1 I
22 II 1““ I I¤I1 IuE16o „ I
i 14 n II Yl.c u IS12 „ ,E n u IE 10ll9 „ ·· I I8 I” I6 'J “ ==!¤ u ” J®fB\$ II,¤ u 1
4 B “ uu H u nn
0 2 2Aug—84 Feb-85 Sep—85 Mor—86 Oc1—86 Moy—87 Nov—87 Jun—88
Figure 35 - Chlorophyll Q Profile at LMO1
. I
91
30 I28I26 I2422 II
II I IS”20 IIV u IE 18 u 1 I¤ I IZ 16 ¤ tp;
E n uIQ_14IEI 19 12 v•ib‘ :° 10 n H1 18 ” E S . · u III I
'I Il
6 u rs ZZ I ZZ U uI„ , J u
4 E J n u “ n VII1 1 KK I
() 2 = 2 ::
Aug-84 Feb—85 Sep-85 Mor-86 Oct-86 Moy—87 Nov—87 Jur1—88
Figure 36 - Chlorophyll Q Profile at LM02
92
3028 12624
22g,20 \ 13 1. E18¤16
: II 1Q 14 n I¤.S 12 Ié 10 10 rs“
u “ ,E || II
8 Q; 1H B16¤‘ u H ¤¤ ¤ ' 1
ra W ‘¤ ”‘=¤_ „4 n
“1“ ..2 LJ
Q FJ 2 2 IAug——84 Feb-85 Sep—85 M¤r—86 Oc1—86 Moy—87 Nov-87 Jun—88
Figure 37 - Chlorophyll Q Profile at LM03
93
30 I2826n I
H24 n I,3 22 II $1g, 113/ 20II2
*8 il11 "1_16 u v: :• II;_ II IIIä14 u I In u u I IE 12 ·· \ I IE u u IU 10 n“ u
XR1" I
8 1[lu u M I
4“ Ü
Ü:.6 ” 6111 I
SI2„Aug—84Feb—85 Sep-85 Mor—86 Oc1—86 Moy—87 Nov—87 Jun—88
Figure 38 - Chlorophyll Q Profile at LMO6
94
so
28262422
In 1.6 18 I“ I.2 I IO 16 ¤=• /2,4% I
i 14 n n Iä
‘ E0 12 an I5 „ „ ILE) 108
„ ‘ II6 “ I
41I:IZI
I I2 III
0 22Aug—84Feb•85 Sep-85 Mor—86 Oc1—86 Moy-87 Nov—87 Jun—88
Figure 39 - Chlorophyll Q Profile at LMO7
I
I
95
30 „-IQI
III25IIIII II I
| IIIQ
20 III I II ‘ II I3 IIIcI I I
E I I I I15 I II
I I I
: I I I 1I Il I
E II II II Q I III3 I: :2 I I J !
Q I II I I I
10 I I I I I I II I II I — I I I I II I II I \ I// \I/ I I] I II \ /I\II
/\ I I \III \ / I I I I I I I I II Q
5 I II I I I I I I I III I I I I II II I I I I I I III] I \/ I I] I
I I I FII
III
III II
II I0 I ‘
Apr-84 Jun—85 JuI—86 Aug-87 Sep—88— LM01 ° ' LM02
Figure 40 - Chlorophyll Q Profile at LM01 and LM02
96
301
1ie 425 ’ „ 1
I „
I I Ii ;I u ' >ll I ä‘: u'
20 l I I l‘ ;‘ 1/\ \ 1 \ I \ I
( Q ,Qg°'Ä ,’
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V \ IE: ^lä
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Ijl I
,ln I \ I
%x , I s zw 1
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: 1* ‘ ’ "\' :‘ :\\· 1OwL
In ‘1 \' *
\ I x' I ‘1 ä
O'
• ‘J I In I m' ¤ *
I\—¤ z «
6 10 ,l‘:
’ 'I l" I ‘ I : I, I‘I x ' I
"‘ I a ‘ ‘ \ ° i
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‘ \ I }
' „· ' . ‘
· ·{\ I l \' \ I 1
5ll ‘ I ‘« IV x '\ I \| ‘|4«
, «!\„ ,· „INI I 3 i
O iApr—-84 Jun—85 Ju|—86 Aug—87 Sep—88— LMO3 “ ’ LMO6
Figure 41 - Chlercphyll g Profile at LMO3 and LM06
97
30 I
I25 IIIIQ 20 I
II I1C/I 1 IO I I I: I
,_I I /“I>~
15 I I II I 1IEI Ä I I
I I / I 1 E
I II :\ / III I Il\
J I I I
I II II I I I I I II III II I I II ‘ II I II I I I I
1O I I II II II I II I I I II I I I I I II II I II I I I I I II I' II I I I 1 I II I
III II1 I I I I I I I 1 I II I
1 II I I I III I I I II I
II III
I III II I I I II I I I I
5II I I II I I II I
II I1 I IIZI III II}I
O IApr—84 Jun—85 Ju|—86 Aug—87 Sep—88
LMO3 " ° LM07
Figure 42 — Chlorophyll g Profile at LMO3 amd LM07
98
Figures 43, 44, and 45 are additional comparative plots
of chlorophyll a concentration at different locations in the
lake. On Figure 45, the data for station LMO7 do not span
the entire range of the abscissa
I
|
II
99
Z5
II 1IIIIII
1 II20 I II II II 1I I
\ 1 IEI ' 1I 1~/15 I , IE 1, 1 I¤• „I· ,'I
II II II IIO- 1 I I I 1 I9 I I 1 I 1 I
9 10 1 I I I I I 1.C 1 , I 1 I I I IO I\ I 1 I 1 I I 1I I I II I III II
_ I II I I II I \ I I II I I I II II I I I I II I I ß I II
I I \1 III I I " ” I II
/ I \ I_5 II \I I II ~ I I I \Il
[ I I I I \ I[ I I I II \ I
I I II II I 1I I II \ I\ I II IIII II IIII I II
OApr—84 Jun—85 JuI—·86 Aug—87 Sep—88_°
LMOI ° ° LMO}
Figure 43 - Chlorophyll Q Profile at LMO1 and LM03
100 I
30
/
25 1{I I
I I 1 II1 I I
1 I I I II Iew I 1 { {Y I;I‘ 'I Y II II
E II I III 1IV .1 1 , J1 .1
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II / \I I I I I I I I II I
\I
- 1 I 1 II I I I 1 1 IIC I I 4 I \
O IO II I 1/ I ’ I I I I II { ‘III I 1 I I 1 I I I
I I 1 I I I II I I II 1 I 1 II ' 1 II 1 I I II 1 I 1 I1 ' II I IY . I 1 '1 ·T 15 I I 1 I In
x I 1:\I II
Q AApr-84 Jun-85 JuI—86 Aug—87 Sep——88— LM01 ' ' LMO6
Figure 44 — Chlorophyll a Profile at LM0l and LMO6
I
101
30
25
20E .\/ I1E llo I "_ \ _I1
· /:15 *1 ’ 111 I I01. 1 1 * 12 ~
,‘1 1 1
I I1 I\ I I
O'
II I 1 1 I*I«<> 1 · fl J J 1 1 JII
' * 1 * ' II 1 * 11* * 1
*“II 1 ' 1Il
* 1 ***11 11 I1' * 1 *,*11 1 1II *1 *::11 1 ~
I I I5 1 1’ ;;1 Z, I1* 1:\‘
1 II III II
O‘
Apr—84 Jun-85 JuI—86 Aug——87 Sep—88_LM06 '°' LM07
Figure 45 - Chlorophyll Q Profile at LMO1 and LMO7
1
102
Lake Manassas Nitrogen and Phosphorus
Figures 46, 47, and 48 are plots of ammonia and
oxidized nitrogen in the bottom waters at LM01, LM06, and
LM07.
Figure 49 is a plot of the oxidized nitrogen in the top
and bottom waters at LM01.
I
II
103
2.5II
IIII2 IZ I"' I° 2/'\
},, 1.5 I\./
Ec2E Ibc 1 I¤ Ic I° I° I
x I1 I\
’ \ 1‘ IO‘5
/’\ A I J \ I \ 1 \ I[ \ /\ \ [ \ I \
[ ~ I I \ , \ 1 x
/ I , \ / \ /\ 1 1
//
" "
\\ //\\ /
O \ I ~ /Oc+—84 JuI—85 Apr—86 Nov—86 Jun-87 061-87 M¤y—88
” NH3_N of boffom ' ' OX_N ci boffom
Figure 46 - Nitrogen in the Bottom Waters at LM01
I
104
2.5
I2 IZ IM I0 IQ I\ ICD 1E1.5g
I* Ic I_g It“ Ic¤ 1U IC .o0 ,I _ I!‘ [I 11 II ~ / II11\ I ‘I I, II I1 1I I
1 1 I I , I 1 ‘« IO.5 I I 1 I I , I I I1 1 / I , I ^ 1 1 II I I! \ I \ ,,I\\ I 1 1 ,1.I!\\ I/I II I Il I I III
\ \I \ 1 1 / II 1 \ I 1 , /. I
0ct—84 Ju|—85 M¤r—86 Sep-86 M¤y—87 Sep-87 Apr—88— NH3..N ot bottom ' ' 0X-N ot bottom
Figure 47 — Nitrogen in the Bottom Waters at LM06
I
II
105
2.5 4IIIII2I
Z I3 I3,1.5 IÄ IE IE I6 1 Ij; I¤ I° 2U Ig IU 1- ·I40.61 *4 ,’ \„1, 1 * / \ I/
\ /Ä\1
4 4 I1 ’ I1 IO ‘ W , W W .. W I
Aug-86 Jon—87 M¤y—87 Jul-87 $6p—87 Dec—87 Apr—88““ NH3-N ot bottom ' “ OXWN ot bottom
Figure 48 — Nitrogen in the Bottom Waters at LMO7
1
106
2.5 ,1 1
12 1Z 1w 1Q 1
°’1E 1.5V 1E 1S 1·;: 1E 1E 12: ‘ 1c 18 1
x 1 1x \ 1
0.5 A I \\ /\ 1 \ \\ / \ I \ \
// \\ I1 \‘ \\/ \ l \ " ^\ \ —\‘ ‘ \
061*-84 Jul-85 Apr—86 Nov-86 Jun—87 06t-87 Moy—88—' 0X-N ct Top ' ' 0X_.N ot bottom
Figure 49 - Oxidized Nitrogen at the Top and Bottom at LM01
uu
107 IFigures 50 and 51 are plots of the total nitrogen and
total phosphorus in bottom waters at LMOl and LM06.
Figures 52 and 53 are plots of the phosphorus
concentrations in the bottom waters at LM01 and LM06.
Figure 54 is the plot of total phosphorus in the
surface waters at three monitoring stations, LM01, LM03, and
LM06.
I
108
3 II I
2.5 I I
S I IU1(IE I2:1.52*6
I,2 I¤ I02 , I6 II II I I\
I/I I~\ /I I
Q_5l\II
x_‘
A// \
\
OOcI*—84 Jul-85 Apr—86 Nov—86 Jun—87 0cI—87 ”McIy—88— TKN cf Boffom ’ ' To+¤| P of Boffom
Figure 50 — Nitrcgen and Phosphcrus at the Bettom of LMO1
I
II
109
3 II
2.5 II
2 IE IE IV IE I.5 Ic I2 IB It I¤ IÜ Ic I I<> IU II
0.5{/^\
/ — r-Il \\
\ A /O ————·' ‘——-··^~ ‘ *-9 x’\»~--—~__ , ’ r —1 ~»\tOct—84 Ju|—85 Mcr—86 Sep—86 M¤y—87 Sep—87 Apr—88
V V TP ct Bottom ’ TKN ot Bottom
Figure 51 — Nitrogen and Phosphorus in the Bottom at LM06
l
1
O.3 I I1‘I 1 I 1
1 ' I 1 1 11 ‘
I 1 1 11 ‘
1 1 1‘ 11 ‘1 1 1//1 1 ‘
I 1 1 10.25 I I 1 1 I I 1 II II 1 1 ' I 1 ' ..111 ‘ 1 ' II 1I I l I 1I 1 1 I 1 1 1 1 I1 I II \1
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EI 1 l 'I\I I I \ I11I
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I \ / I 1I I- — d / I I 1/ I I I I1 I1 1 \ 1 1 II \1 +1*- II 1 ' 1 . \ /‘_ 1 „ ‘
I 1 ·, _, ‘ ’ X VO
Oct-84 Ju|—85 Apr—86 ‘ *Nov—86 Jun—87 Oct—87 Moy—88
Ortho P ct Bottom TSP ot Bottom “ TP ct Bottom
F1gure 52 - Phosphorus lh the Bottom at LMOl
I
Illl
O.1 I1I I 1 I· · 1 1 ;I I II III1 II I 1 II ' II 1 I I1 II1 I I II II1 I 10.08 1 1 ' I' 1 I 1
1I 1 I II I I II1 , 1 II 1 I 11 1I1 1 I II I I IIIII 1 I 1 I 1 II I
I 1 IIII II I
II I\ I I II II I I |‘
II II II
IO, [I I I I IIII II I I I I IIII1 \ 1 I I 1 1 111 I1 II 1 1 I1 I11I1II I1 I1 I II. I I1 I1 1 1E ,I I11 II 1 I [I1 1 11I II 1 I jI I 1II I1 i
C I I 1 I I 1 I II III 1 I I 1I 1 I1 I I II II II1 1·
I ,I1 1 I 1 1 I I 1I 1 1 11 II 1 1 I I*6 I 1 I 1 1 1 1 I I 1 I 1I 1 1 1’ I I Ix-
Il 1 II 1I I | I II II I I 1 I*_ I 1 I I I 1 I 1 I 1 I 1 I1 I I ,
E 1 I I 1 I 1 I 1 I 1 I I I II 1 I¤>¤-O4 ' ···· 11 1I / I 1 1 1 I I 1C 1 1 1 I 1 1II II II I I I II III I1
I II III
III-1 1I I1 ·1I 11 I I I1 I I II 1 1 I1 I1I I 1 1I 1 1 1 I I —1 11
I1 1 1 I II \ 1 II I0 O2 I I I I I 11 I I 1 I I·
I ' 1 I 1 1 ‘ I;II 1 1 1 1 III I 1 1 1 1 I
1 IIII \L T1 IIIIII I
Q 1Oct—84 Ju|—85 M¤r—86 Sep-86 M¤y—87 Sep—87 Apr—88
' ' OrthoP ot Bottom — TSP ot Bottom ' TP ct Bottom
Figure 53 - Phosphorus in the Bottom at LM06
I
II
112
O.1
ä1
0.081
¤.*6" }n Tc 0.06 ·· , i\ M ,' 1U) • 1 ‘ '
E I Y I‘
\/ I \ T IC 1 \ ‘
I „Ic I · TO { \ 1 „ ' ‘
f i%0.04 :·‘, ‘ · ‘ · - _.tIll \' lv ‘ ll \\ VM. I I II {"‘E¤ ·#’ I w —·— I Ä " ‘L T; x
IIII jr _ ~_ ‘ , . · ' · ‘ — . ' TE ' ' ~ ‘'
\\ Ü,· ' l. "‘ Il, «\ [Ü '/"{
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I \"i'T\ / 1 /¤» T
002 . ' { T', N ‘M · ,, V · ^¤ / • ,T.
,\ 'I · I ‘ L1 V'
‘ /· \\ V,1*
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\, J ‘ ,’ ,I ‘. [ I I ‘"Il I I I
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\ I 4 I I /‘/ I / ‘ / [ ‘!
‘, \_1 _—· \‘-J' \/ ‘ ”'1
OOCT"84 JuI—85 Apr—86 >Iov—86 Jun—87 Ocf—87 May-88
—' TP ct LMO1 ' ' TP cf LMO3 ' TP of LMO6
Figure 54 - Total Phospherus in the Tcp
at LMO1, LMO3, and LMO6
113 ILake Manassas Watershed Properties
Table 8 gives the data for the five basins used for
this thesis. Figures 1 and 5 show the relative location of
the basins.
Figure 55 is a plot of rainfall in the Lake Manassas
watershed on a yearly basis.
Figure 56 is a plot of the Percent of Runoff for the
ST7O basin as a function of rainfall. In Figure 56, the
points represent actual data and the straight line is a
regression fit of that data.
I
114
Table 8 - Properties of Lake Manassas Watershed BasinsBasin Area Percent of
Tributary Name (sg. miles) Total Area
BR03 - South Run 7.47 10.2
BRO4 - North Fork 8.32 11.4
BRO5 - Northern Arms 3.11 4.3
BR06 - Southern Arms 2.67 3.6
ST7O - Broad Run 40.43 70.5
115
w*Q " u
„ 40 V \‘IIIIIIIIIlll' -.C S _
.E „ , ¤
Z so ‘
'ö(Z 20—
Xo
W—1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987
Year
Figure 55 - Rainfall in Lake Manassas watershed
l
ll6
50 ($lrcighl line ls c regression fil)/
45 "/ ܤ //
L. 40 /OC3M
3; 35_ E
Ou0)
f 50O.C: ¤E 25EUM ¤“6B? 20 D
15
1O
lnches of Roinfoll in a year
Figure 56 — % Runoff into Broad Run versus Yearly Rainfall
117
Lake Manassas Watershed Environmental Monitoring Data
Table 9 is a summary of the database for the sampling
of the drainages into Lake Manassas. The table contains the
maximum, minimum, average, median, and the standard
deviation values for the listed parameters. For sampling
station ST70 a flow weighted average value is also listed
because flow data existed for this station. When the
database was analyzed, if a given constituent was less than
its detectable limit, it was evaluated at half the value of
the detectable limit. This way a parameter value of zero
was not "averaged into" the analysis. In most cases, if
this was not done, over half of the data in the database
would have been evaluated at zero, and underestimated the
predicted values. It should be noted that this is slightly
different than the data presentation technigue of the top
and bottom plots where these values were plotted as negative
values.
Table 10 is the summary of data for the monitoring of
pollutant metals in the streams. The format for Table lO is
similar to that of Table 9.
1.1 8
Table 9 - Sxnaary cf Ezvzronnental Hcnztcrzng iata ferZraznages gnto Lake Aanassas
<a11 neasurenents ;n ng7L*
!on;t:ring Station nonber 9203
9203 T0 430 SAT TALK OP TSP TP !H3_! SK! TK! 0K_! TSE FE
Average z 9.70 195.00 42.16 0.09 0.11 0.15 0.07 9.54 0.67 1.10 8.37 6.9Haxaana E 14.00 177.00 86.10 0.42 0.42 0.47 0.54 0.94 1.61 4.04 33.00 1.4Eedian 1 9.90 98.00 38.00 40.91 0.05 0.09 0.02 0.51 0.61 9.61 8.00 7.1Aininun ; 5.30 17.00 25.90 0.91 0.01 0.03 9.01 0.17 0.29 0.03 0.00 5.3St. 0ev. 4 2.45 22.00 14.40 0.09 0.10 0.10 0.09 0.16 0.23 0.88 13.31 0.5
Aonntoring Station nunber 9204
3904 4 00 820 SAT TALK 0P TSP TP !H3_! SK! TK! 01_! TES PE
Average 4 9.05 83.00 50.20 0.02 0.04 0.07 0.03 0.51 0.60 0.12 11.45 6.4Haxinun 4 13.40 119.00 215.10 0.11 0.17 0.30 0.46 1.20 1.45 0.48 84.00 7.3Aedian 4 10.20 80.00 42.90 0.02 0.02 0.04 0.02 0.64 0.58 :0.01 5.00 6.6Hiniaun 4 2.50 28.00 19.80 40.01 49.01 40.01 40.01 40.01 10.01 40.01 0.50 6.9St. 0ev. i 2.71 17.60 47.60 0.02 9.03 0.05 0.06 0.20 0.26 0.13 14.93 1.1
Aonitorang Station nunber 9205
BR05 4 DO 000 SAT TALK OP TSP TP !H3_! SK! TK! OK_K TSS PE
Average 4 9.98 89.10 39.02 0.03 0.05 0.07 0.03 0.45 0.56 0.18 14.60 6.5Aaxinun 4 13.00 107.21 186.00 0.59 0.65 1.09 0.26 1.52 3.69 1.13 177.00 7.5Aedian 4 11.20 88.00 48.00 40.01 0.02 0.02 40.01 0.30 9.34 40.01 2.90 6.4Aininun E 3.55 44.50 40.01 40.01 40.01 40.01 40.01 40.01 40.01 40.01 2.50 5.'St. 0ev. 4 2.10 11.20 43.30 0.08 0.09 0.14 0.04 0.27 0.52 0.24 31.60 0.4
Aonitoring Station nnnber BR06
9906 2 00 980 SAT TALK OP TSP TP !H3_! SK! TK! 0K_! TSS PH
Average 4 9.10 83.00 39.40 0.93 0.04 0.09 0.04 0.54 0.77 0.24 27.20 6.4Aaxinuu E 13.20 110.80 190.10 0.20 0.22 0.50 9.38 1.77 2.42 2.56 383.00 7.4ledian 4 9.40 93.00 50.00 40.01 0.02 0.03 0.02 0.61 0.66 40.01 7.00 6.1lininun 4 4.00 30.30 20.80 40.01 40.01 40.01 40.01 40.01 40.01 40.01 1.00 5.9St. Uev. 4 2.80 18.80 37.20 0.04 0.04 0.09 0.06 0.27 0.50 0.40 63.19 0.4
44
1.1.9
Table 9 - conrzaaei
ionztcring Static: nanber ST73ST70 1 23 10C SAT 9121 3P TSP TP K83_0 S28 TTN 3X_T TSE FE
2lov1t1vg E *.30 -— 22.1 43.01 3.03 0.10 0.04 0.39 0.59 0.*4 E'.4E —~Average . 9.70 96.4 45.3 0.01 0.03 0.37 0.34 0.29 3.54 0.51 26.3 6.'Aaxinnn E 15.4 132 63.8 0.08 0.18 0.64 0.39 1.09 2.1 1.51 371 7.9Median 2 12.6 103 50 40.01 0.02 0.32 40.01 0.3 0.41 40.01 4 6.3Aizinua L 4.7 56 3.8 43.01 40.01 40.01 0.01 0.08 3.11 40.31 0.2 5.7St. Zev. 4 1.5 12.5 9.6 3.32 3.03 0.12 0.04 0.38 3.54 3.51 26.3 3.8
Monitornng Station nunber 02034re;eateA for conparison with 3102 and 320**
3103 E 30 100 SAT TALK CP TSP TP KH3_K S11 TK! 3K_T TSS PE
Average 2 9.70 105.00 42.16 0.09 0.11 0.15 0.07 0.54 0.67 1.10 8.3* 6.9Haxinun 4 14.00 177.00 86.10 0.42 0.42 0.47 0.54 0.94 1.61 4.04 88.33 8.4Hedian 4 9.90 98.00 38.00 40.01 0.05 0.09 0.02 0.51 0.61 0.61 3.03 '.1Ainiann i 5.00 17.00 25.90 0.01 0.01 0.03 0.01 0.27 0.29 3.08 0.33 5.8St. 0ev. 4 · 2.45 22.00 14.40 0.09 0.10 0.10 0.09 0.16 0.23 0.88 13.31 0.5
Aonitoring Station nunher 3102
8102 E 30 120 SAT TALK 0P TSP TP IH3_H SKK TK! 0X_K TSS P3
Average 4 9.30 90.10 43.37 0.16 0.19 0.23 0.17 0.73 0.83 1.93 12.5' 6.”
Haxinun 4 11.20 123.00 87.60 0.77 0.79 0.82 1.31 2.26 2.16 11.19 180.00 ’.“Hedian 4 8.60 84.00 29.80 0.06 0.10 0.12 0.02 0.70 0.68 0.58 2.00 6.5Hininun 4 4.00 45.00 26.70 40.01 0.02 0.04 40.01 0.31 0.36 0.16 0.50 5.9St. 0ev. 4 2.34 15.90 14.32 0.16 0.17 0.17 0.27 0.30 0.35 2.39 28.80 3.4
Monitoring Station nnnber 3107
8107 4 00 100 SAT TALK 0P TSP TP KH3_I SKK TK! 0X_K TSS PH
Average 4 8.94 87.40 38.68 0.01 0.03 0.05 0.13 0.54 0.71 0.20 8.94 6.6laxinun 4 13.20 111.30 71.40 0.13 0.16 0.23 0.69 1.01 1.99 0.61 80.00 7.5Median 4 7.60 90.00 36.00 40.01 0.02 0.03 0.06 0.46 0.66 40.01 4.00 6.5Iininun 4 4.60 45.50 24.00 40.01 40.01 40.01 40.01 0.24 0.34 40.01 0.00 5.5St. 0ev. 4 2.47 15.60 12.50 0.02 0.03 0.04 0.12 0.19 0.28 0.13 11.47 0.5
1.220
Table 13 - Sannary ai Hetal Cantent afEra;:ages to Lake Aanassasiall neasnrenents are 1g;1
!::itor;:g Stat;on 4 ER03
BR03 E EAG EAG T10 ECE ECE ECE ECE ECE SC0 SEE EEG EEG EAE SEE EE} SEC EPS SPE EZE EZE..........7 ................................................................,,.___,_,_,__________,______________
4 sanplesl 4 1 4 9 11 11 11 15 11 11 4 3 8 12 2 4 15 11 13 114 ‘ AEL 1 3 3 3 9 11 11 11 ' 11 0 2 2 0 1 Z 4 9 11 1 7Average E 3.9 0.6 1 21 228 0.4 10.5 176 46 11.3 18.8 11.8Eaxznna E 1 110 580 0.5 795 210 17.4 99 21Aaninan E 1 3 22 0.3 13 3 4.4 3 7
Aon1tor;:g Station 4 8E04
EE04 E EAG EAG ECE ECE ECE ECE SCR EC0 SC0 SEE EEG EEG EE! SEE EEI SE1 EFH SEE EZE SIE!
4 sanplesl 2 · 2 6 9 8 9 11 9 9 2 — 6 9 — 3 11 9 13 94 7 AEL E 1 - 2 5 8 6 9 4 9 0 2 - 0 1 - 3 6 9 1 3·Average 2 7 7 1 11.8 488 155 144 18.8 14.4 9.1Eaxinun E 44 890 1050 884 68.9 18 12 EEininun 1 2 271 49 6 4.4 3 5.
Eonitoring Station 4 EA05
BR05 E TAG EAG ECE EC0 SC0 ECE SCR EC0 SC0 SEE EEG EEG EHI SAE EEI SE1 EPB SEE EEE SEE!
4 sanples! 2 - 2 7 9 9 9 14 9 9 2 · 7 10 1 3 14 9 13 10 74 7 HDL E 2 — 2 7 9 8 9 4 9 0 1 - 0 2 1 3 7 9 E 1;Average E 1 7 483 1.4 75 19.4 23 17.6 11.4 10.1Eaxinun 3 32 1120 312 29 19.7 80 14~lininun 1 1 195 15 9 6.4 2 5
Eonitoring Station 4 BR06
BE06 ! TAG EAG TCD EC0 SC0 ECR SCR ECU SC0 SEE EEG EEG EAI SEE EE1 SG1 EPB SPE EZE SEE!
4 sanplesi 2 · 2 7 8 10 8 15 8 8 2 - 7 8 1 3 14 8 12 94 7 IDL ! 2 - 1 6 8 8 8 3 8 0 1 · 0 0 1 1 7 8 0 4·Average 1 0.6 6 1.5 6.75 628 0.8 166 78.8 8.9 21.5 8Eaxinun 1 2 16 995 305 264 18.5 118 14Hininun 1 1 2 240 11 21 2.1 6 5
B
1.211
Table 19 · :o:t1:ae1
!:;itcr1ng Star;on 4 9103
BR03 1 TAG EAG TCS ECS SCS ECR SCR ECS SCU SFE THG EEG EHI SAR EHI SRI AFB SPE E13 5151
4 sanplesi 4 3 4 9 11 13 11 15 11 11 4 3 8 12 2 4 15 11 13 124 1 ASL E 3 3 3 9 11 ll 11 7 11 0 2 1 0 1 2 4 9 ll 3 7Average i 3.9 0.6 1 21 Z28 1.4 10.5 176 46 11.3 15.8 11.8Ällllül 1 1 110 580 0.5 795 110 17.4 99 20Einanun E 1 3 22 0.3 13 3 4.4 3 7.
Hcnztoring Station 4 5102
5102 i TAG EAG TCD ECE SCS ECR SCR ECS SCS STE THG EEG EH! SAR SR1 SX1 ETB S25 EZ! SZR1
4 sanplesi 5 3 5 9 11 14 11 15 11 11 5 3 8 12 3 4 16 11 16 114 < HDL 1 4 3 3 9 11 14 11 6 11 0 3 2 0 2 1 4 9 11 2 7Average 1 3.6 0.3 7.7 270 1.7 1.6 246 58 27 11.5 17 32Haxrann E 0.4 13 780 2.2 1131 160 20.6 130 114Aininun E 0.2 1 35 1.2 36 22 4.4 1 5
Honitcring Station 4 5107
SR07 i TAG EAG TCS RCB SC0 ECR SCR ECU SC0 SPE THG EEG EAR SH! ER! SRI EP5 SPS EAN SZR1
4 sanp1es1 4 3 45 11 11 14 11 18 11 11 4 3 10 12 1 4 16 11 16 114 1 HDL 1 4 3 1 10 11 13 10 10 11 0 2 2 0 0 2 4 10 11 5 9Average 1 0.3 6 1 205 4 430 1.9 2.2 348 171 8 22 7.5Haxrnnn 1 0.4 8 592 975 540 18.6 106 10Hininun 1 0.1 1 50 61 32 4.4 2 5
a
122 ·
In order to further characterize the Lake Manassas
watershed, the data from station ST7O were used to develop
cumulative loading curves for various nutrients. Figures 57
through 63 are the nutrient cumulative loading curves for
the Broad Run drainage into Lake Manassas. The straight
lines represent the linear regression fits to the data
plotted. The loading data is plotted versus time in months.
The regression lines were calculated forcing them through
the origin.
123
(straight line is regression fit)18.0016.00.714.00
1s 13 12.00 1VI/\
1U vi: *0 1J :10.00 1O O¤.v» 1J1
mf 8.00 1sv1U1O 1 13 6.001
4.001112.00
'
11¤ 10.00 · J0.00 40.00 80.00 120.00Time in months
Figure 57 — ST7O loading of Orthophosphorus
124
(straight line is regression fit)
40.0066.00..1
60.00 Q°— Ivg I
° IS/$25.00Ic ‘¤
3 C I33 IC g20.00
.1:EC€15.003IlI
10.00III
5.00 I
rl0.00 '
0.00 40.00 80.00 120.00Time in months
Figure 58 — ST70 Loading of Total Soluble Phosphorus
125 .
(strcight line is regression fit)120.00 i
1IFI I100.00I
/ I“ I3 80.00 1U|,\ I
UCU
3 C I° O 0 Iag 6000EJg °1E 1E 1
3 40.00I
20.00I
Y} I0.00 ·0.00 40.00 80.00 120.00Time in months
Figure 59 - ST7O Loading of Total Phosphorus
126
60.00 (stroight line is regression fit)lII l50.00 1
Z I
in 1
° Igc40.00 1:10
Eä 1°’ ¤c 30.006 g [ IQ O9z/ p
*5 20.00 1E IE 1E I3 1‘
10.00 1I.1 I
0.00°·°° 4O-GO 80-OO 120.00Time in months
Figure 60 - ST70 Loading of Ammonia Nitrogen
II
127
(straight line is regression fit)600.00
500.00‘
Zvi l0 I
·· IU IS400,990I
°^ IviE2 I23 I·_6 3 300.00 I9 0Bf tmv ‘.2E 200.00
‘
3EEJ
U 100.00 I
0.00 Ä0.00 40.00 80.00 120.00
Time in months
Figure 61 — ST7O Loading of Oxidized Nitrogen
1I
128
(stroight Iine is regression fit)700.00 II600.00I
Z··· . I¤ 600.00IVI2 Ics0°^400.00 IC (0” E@2” :1TS ¤600.00
O .C1*;¤ I2 I0 I— 200.00 .4 I:sE IE I3 I100.00 I
0.000.00 40.00 80.00 120.00Time in months
Figure 62 · ST70 Loading of TKN
I
I
129
(straight line is regression fit)500.00Il
IZ 400.00 „ IW I° IW 1E I3 I¤^300.00 I2 3 ICDC I2 §¤ 'Q .C_C200.00 I02*2 I3 IE I8 100.00 I
III
lI0.00 I0.00 40.00 80.00 120.00
Time in months
Figure 63 — ST70 Loading of SKN
I
130
Prediction of the Eutrophic Status of Lake Manassas
As discussed in Chapter III, application of the
Vollenweider analysis for this project involved development
of a computer "spreadsheet model" of Lake Manassas.
The spreadsheet model is shown in Figure 64. The
numbers shown in Figure 64 represent the results for a given
"run" of the modeling program. The program automatically
records the results for each run for subsequent statistical
analysis.
Figures 65 and 66 represent the summary statistical
analysis for the current total phosphorus loading to the
lake using both median and average distributions. Figures
67 and 68 represent the graphical equivalents to the data
contained in Figures 65 and 66.
The output data for the total phosphorus loadings and
the z/tau hydraulic parameter for the lake are combined to
produce an "operating box" on the normal Vollenweider plot.
Figure 69 shows the "operating box" for the model output of
the currently predicted eutrophic conditions in Lake
Manassas. The box of Figure 69 represents the area of the
Vollenweider curve which, with a probability of
approximately 90%, is the current eutrophic condition of
Lake Manassas. The box is clearly well above the
"Dangerous" loading curve established by Vollenweider.
AAAAAAAA4AAA4AAAAA4AAA444AAAA4AAAA44AAAvAAY‘”_—-——————————————_—_______________________-_____----------_-—----—-
I
l 3 1
Lake Area Late 8o1unein acres = 694 in ga11ons= 4.28+09
This spreadsheet uses the Lotus nodeling Tearly Aainfall Lake 8ean 0epth IzIprograa called 08IS8. in inches = 37.0900 in neters = 3.51
Iersion 2 5/8/09 8888808 8888808 880188 880188Basins to Strean Basir Area Percent Tearly Flos Total P P Loading Total P P Loading
Lake Code Ittll ot Area Ift3I Ing/LI Iga/a2/yrI Ing/LI Ign7a2/yrIBread 8uu ST70 1.448+09 70.5 1.838+09 0.094364 1.736 0.036946 0.681Iorth Fork 8804 2.128+08 11.4 2.948+08 0.068509 0.203 0.039780 0.118Iorth Aras 8805 8.688+07 4.3 1.108+00 0.070992 0.079 0.040457 0.045South Aras 8806 7.458+07 3.6 9.448+07 0.086562 0.082 0.038049 0.036South lan 8807 2.088+08 10.2 2.648+08 0.048557 0.129 0.031068 0.0838int 8111 8802 8\8 IIA 1.318+07 2.543067 0.336 2.543067 0.336
2.608+09 2.578+00 = Load = 1.308+00Lake Infloa/Lake 8o1une ItauI = 4.631 z/tau = 0.758A 8888808 8888808 880188 880188
Total P P Loading Total P P LoadingIng/LI Iga/a2/yrI Ing/LI Iga/a2/grI0.0984 1.740 0.036986 0.6810.0605 0.203 0.039700 0.1100.2499 0.278 0.070992 0.0790.0866 0.083 0.030049 0.0360.0486 0.129 0.031068 0.0832.5438 0.336 2.543067 0.336
2.778+00 = Load = 1.338+002004 Iaorease in the Iorthern Aras
Total P Concentration
8888808 8888808 880188 I80I88Total P P Loading Total P P Loading(ag/LI (gn/a2/yrI Ina/LI Ion/a2/grI
0.094364 1.740 0.036946 0.6810.060509 0.203 0.039700 0.1180.070992 0.079 0.040457 0.0450.086562 0.003 0.038049 0.0360.048557 0.129 0.031068 0.083
8/8 8/8 8/8 8/8
2.238+00 = Load = 9.638-01
lliainate 81nt 8111 Total P content
Figure 64 - Spreadsheet Statistical Mcdel for Lake Manassas
II
132
Figure 65 - Current Average Phosphorus Loading
CURAVGLOAD QRISK Risk Analysis 08—May—1989
Expected/Mean Result = 2.625 Maximum Result = 17.05 Minimum Result = .387
Range of Possible Results = 16.666 Probability of Positive Result = 100%
Probability of Negative Result = 0% Standard Deviation = 2.149 Skeuness = 2.477 Kurtosis = 11.439
Variance = 4.620
Probability of Result > 0 = 100%> 2 = 50.7%> 4 = 16.2%> 6 = 7.6%> 8 = 2.9%> 10 = 1.8%> 12 = .8%> 14 = .3%> 16 = .2%> 18 = 0%
Probability of Result <= 0 = 0%
Percentile Probabilities: (Chance of Result < Shoun Value)< .387 = 0%< .7005 = 5%< .8637 = 10%< .9972 = 15%< 1.1463 = 20%< 1.2609 = 25%< 1.3819 = 30%< 1.5154 = 35%< 1.6509 = 40%< 1.8254 = 45%< 2.0286 = 50%< 2.196 = 55%< 2.3703 = 60%< 2.5494 = 65%< 2.7891 = 70%< 3.13 = 75%< 3.5893 = 80%< 4.2797 = 85%< 5.2896 = 90%< 6.7701 = 95%< 17.0532= 100%
1
1
Il
133
Figure 66 - Current Median Phosphorus Loading
CURMEDLOAD SRISK Risk Analysis 08-May-1989
Expected/Mean Result = 1.345 Maximum Result = 20.629 Minimum Result = .351
Range of Possible Results = 20.278 Probability of Positive Result = 100%
Probability of Negative Result = 0% Standard Deviation = 1.486 Skewness = 6.041 Kurtosis = 58.255
Variance = 2.209
Probability of Result > 0 = 100%> 2.25 = 10.3%> 4.5 = 2.9%> 6.75 = 1.5%' > 9 = .7%> 11.25 = .3%> 13.5 = .2%> 15.75 = .2%> 18 = .2%> 20.25 = .1%> 22.5 = 0%
Probability of Result <= 0 = 0%
Percentile Probabilities: < .3513 = 0%< .4652 = 5%< .5175 = 10%< .5686 = 15%< .6169 = 20%< .6648 = 25%< .7113 = 30%< .7579 = 35%< .8113 = 40%< .8665 = 45%< .935 = 50%< 1.0197 = 55%< 1.1146 = 60%< 1.204 = 65%< 1.3068 = 70%< 1.4605 = 75%< 1.644 = 80%< 1.9643 = 85%< 2.2777 = 90%< 3.3592 = 95%< 20.6293= 100%
1
134
ExpectedResult:2.625803 @RlSK Slmulotlon Som ling: Lotin H ercub
CURAVGLOAD8.0096··········
P....O
EB EA4.8%BEl E
L3.2%I
TY 1.6%01.75 3.5 5.25 7 8.75 10.5 12.25 14
Loaolng lgm P / eq. meter yrl
Figure 67 - CURAVGLOAD Output Distribution Graph
u135 l
ExpectedResult: .1.545842 @RlSK Slmulotlon Somlin: otin Hygercuéé
CURMEDLOA0 ¤Trlols:100020%P
; lR16%OE lBA
12%’’'°'°"1BEl E
' ET : _Y. ..
.,0%01.25 2.5 5.75 5 6.25 7.5 8.75 10
Loücmg (Qm P / SQ. meter vr;
Figure 68 - CURMEDLOAD Output Distribution Graph
1
136
10
EUTROP1—11C
Dangerous /
ä ä///
5 / //‘$ 1·’
- / /E // Permxsséie
E ______ __„// //E /E / /
P3 ,»·/
E Ü.lE3
OLIGOTROPHIC
0.010.1 1 10 100
Mean Dept11('Z)/Mean Residence T1I“I1€(1GLl)
Figure 69 - Vollenweider Plot of Current Conditions in Lake
Manassas
137
Two other cases were analyzed by the model; a case for
increased concentration in the total phosphorus in runoff
from the Northern Arms area (the area for proposed
development as a resort area), and a case for the
elimination of the sewage treatment plant input from the
Vint Hill Army Station.
Table 11 summarizes the predicted total phosphorus
loadings for the lake in all three cases. Inspection shows
that for the case of a 200% increase in the Northern Arms
total phosphorus contamination, the total phosphorus loading
to the entire lake does not change substantially. This is
because the flow contribution from the Northern Arms
watershed is a small fraction of the total lake watershed
flow (approximately 4.3%). Graphically the difference
between these two cases is very small and Figure 69 would
not change perceptibly.
The elimination of the Vint Hills sewage treatment
plant point source from the lake phosphorus input sources
results in an improvement in the predicted eutrophic status.
Not only are the predicted loadings lower, but the "box"
grows in size. This increase in box size is due mainly to
the logarithmic nature of the graph. Figure 70 shows the
operating boxes for both the case of eliminating the Vint
Hill point source.
138
Table 11 - Summary of Results from Spreadsheet Modelof Lake Manassas
Net Loading (gm/m2/yr)Case Assumptions Average Values Median Values
#1 - Current Conditions 2.54 1.35
#2 - Increase Northern Armsby 200 % in Total P 2.63 1.38
#3 - Eliminate Vint Hill PointSource discharge 2.29 1.00
139
10
EUTROIPHIC
Donqerous //% /s.„92A / /G1 1 „’ /
E / P /_ / eryssibleS1 „/ /\/D.// /
E / /P3
//
Ö—_—.___;•¤¢
E 0.1”O .OO...1
OLIGOTROP1-IIC
0.01 ·0.1 1 10 100
Mech Depth('Z)/Mech Reskiehce "1“1me(tou)
Figure 70 - Vollenweider Plot of Lake Manassas after
eliminating the Vint Hill point source discharge
140
Table 12 represents the results of applying the other
eutrophic models discussed in Chapter III.
¤
141
Table 12 - Suumary of Other 'lrophic Models ·
Secchi Dish Surface T'P Surface Chla TSI(S) TSI (TP) TSI (Cha)
(meters) (ug/1) (ug/1)
LM01 avg 1.34 24.79 8.6 56.58 50.16 58.85
std 0.47 16.45 5.5 4.6 6.66 6.12
LM02 avg 1.31 23.13 7.6 56.7 51.9 58.85
std 0.52 17.57 5.86 4.88 5.28 5.93
H403 avg 1.22 24.17 7.33 57.81 51.55 58.84
std 0.41 17.54 4.65 4.46 6.61 4.75
LM06 avg 0.99 26.04 11.4 60.34 53.69 62.08
std 0.32 18.34 5.9 4.20 5.39 5.76
LM07 avg 0.89 32.29 9.7 62.00 53.61 60.68
std 0.24 32.16 4.6 3.58 9.84 6.07
Based on Table 4 — These data show the lake to be Eutrophic for Average Total
Phosphorus and Secchi Dish reading and Mesotrophic for Average Chlorophyll a_
Based on Table 3 — These data show the lake to be at the high end of the
mesotrophic and into the low end of the eutrophic range.
I
I
Chapter V
DISCUSSION
Discussion of Monitoring Program Results for Lake Manassas
Table 7 lists the morphological characteristics of Lake
Manassas as measured for this thesis. The volume of 4.2
billion gallons agrees well with some previous studies (1).
The lake was originally designed for a volume of
approximately 5.8 billion gallons. However, the original
engineering company which designed the lake has recently
performed another study to measure the lake's volume.
Although the results of that study were not available at the
time this thesis was written, unofficial results confirm
that the lake's volume is closer to a figure of 4.2 billion
gallons (2).
The temperature profile data, Figures 7 through 14,
show that Lake Manassas is a monomictic lake, with typical
fall turnovers. The summer stratification is very evident,
especially in the deeper portions of the lake. There is no
quantifiable winter stratification, however when ice is
present, sampling is not performed. This unavailable data
makes it difficult to make conclusive statements regarding
winter stratification.
142
1I
143'
Figures 8, 9, 11, and 12 show that at depths of over 30
feet (the hypolimnion) the temperature rarely, if ever,
rises above 10b. These figures also show that during
periods of turnover, the entire water column reaches a
temperature of 10%L
Figures 9, 12, 13, and 14 are useful for characterizing
the epilimnion of Lake Manassas. These figures show that
the epilimnion extends to a depth of 12 to 15 feet during
the summer months. Figure 12 shows that at Station LMO6,
there is almost no stratification to a depth of 15 feet in
the summer months. Figure 9 shows that at Station LMO3
there is an approximately TC layer at 15 feet. This
difference may be due to the location of the two stations.
Station LMO3 is at the end of a narrow arm of the lake,
whereas Station LM06 is in the center of a relatively broad
section of the lake and is significantly further from land.
Therefore, wind forces on the lake at LM06 may induce better
mixing conditions than at LMO3. Given the small thermal
gradient present between the surface and 15 feet, this small
difference in wind mixing force would probably be enough to
account for the difference between LM06 and LMO3.
The DO contour figures further confirm these
conclusions, and provide further insight into Lake Manassas
dynamics. Figures 15 through 22 provide the DO contours,
1144
and Figures 23 through 30 the percent of DO saturation
contours. Figures 15, 16, and 18 clearly show the
stratification of DO in the water column of the lake. DO
levels in the epilimnion during summer months typically
exceed 10 mg/L. Figures 23, 24, and 26 confirm that these
DO levels are at or above the saturation level of DO,
corrected for actual temperature at that location. This
pattern of DO content indicates that oxygen producing,
photosynthetic organisms are prolific during the summer
months. Therefore, the addition of copper sulfate to the
lake during the spring and fall may help reduce the
magnitude of the spring and fall algal blooms, it does not
strongly affect the warm season algal crop.
The transition from epilimnion to hypolimnion is more
dramatic on the %DO saturation contour figures. Figures 23,
24, and 26 show that at a depth of 11 to 12 feet, the % DO
saturation begins to change rapidly with depth.
Referring to Figure 6, a depth of 12 feet corresponds
to an elevation of 273 feet above mean sea level, or a lake
volume of 2.0 billion gallons. Therefore, the epilimnion
volume is estimated at (4.2 — 2.0) or 2.2 billion gallons,
and comprises approximately 52% of the lake volume.
Figures 31 through 34 also clearly depict the
hypolimnion DO conditions. Figure 31 clearly shows that DO
145
at the lake bottom of station LMO1 essentially goes to zero.
This means that anaerobic conditions are quite prevalent for
the 4 to 5 month summer period. Figures 31 through 34 also
clearly show the mixing periods of lake turnover.
Figures 33 and 34 are the top and bottom DO curves for
station LMO8. For the two year monitoring period contained
in the database, the top and bottom DO concentrations at
LMO8 showed little difference except for a 6 month period in
the summer of 1986, when some stratification did occur.
However, the conditions were not as severe as in deeper' portions of the lake. The lowest DO concentration reached
was 3.3 mg/L which corresponded to a 40% DO saturation
level.
Figures 35 through 42 present the data for
chlorophyll g in the surface waters at the sampling points.
The data clearly show the presence of chlorophyll g at all
locations in the lake. The peaks do not always concur at
the same time of year or at the same date from location to
location. This time disparity may be due to the addition of
copper sulfate to the lake, the difference in time between
sampling and the copper sulfate addition, and the
nonuniformity of the copper sulfate addition.
Figures 43 through 45 are a different presentation
technique for the chlorophyll a data. Figure 43 shows that
146
the chlorophyll Q concentration at stations LMO1 and LMO3
behave very similarly. The maximum peaks are very similar
in magnitude. The time at which the maximum occurs is,
however, different. Figure 44 is a comparison of the
chlorophyll Q at stations LMO1 and LMO6. The chlorophyll Q
at LMO6 has slightly higher peaks, but, more predominantly,
a higher average concentration. This is most likely due to
the better availability of nutrients in the area around LMO6
from South Run. Figure 45 is a comparison of chlorophyll Q
at LMO6 and LMO7. This figure shows that LMO6 is a more
productive region for chlorophyll Q than is LMO7. This may
not be expected because LMO7 is a shallow area, and the
better light penetration should help produce more littoral
communities at LMO7. However, the better availability of
nutrients at LMO6 has a stronger affect on the net
productivity.
Figures 46, 47, and 48 are plots of the ammonia and
oxidized nitrogen in the bottom waters of LMO1, LMO6 and
LMO7. The pattern of the data is quite evident. The
oxidized nitrogen follows a cyclical pattern, with the
ammonia nitrogen cycle being in an exactly opposite phase
pattern. However, there is a distinct difference between
the data from LMO1, and that from LMO6 and LMO7. At LMO6
and LMO7, the oxidized nitrogen peaks are substantially
147
higher than expected for the amount of ammonia present. At
LM01, the ammonia peaks correspond with fall turnover, and
the oxidized nitrogen level which follows does not
correspond to the peak value expected. The major difference
between LMO1 and the other stations is depth. Note that
when corrected for scale differences, the peak values of
oxidized nitrogen at all three stations is very similar.
Therefore, it appears that either the sediment releases
oxidized nitrogen at LMO1, or, at the shallow depths of LMO6
and LMO7, the ammonia adsorption to sediment and the
nitrification reaction may be great enough to keep the
ammonia concentration very low.
Figure 49 is a top and bottom plot of oxidized nitrogen
at station LMO1. The plot shows a clear agreement between
oxidized nitrogen in the top and bottom waters of LMO1.
There is a cyclical pattern, with peaks in the spring and
early summer, and lows in late summer and fall. There is no
apparent difference in magnitude or periodicity between the
top and bottom waters.
Figures 50 and 51 are plots of the bottom
concentrations of total nitrogen and total phosphorus at
stations LM01 and LMO6. The plots show periodicity
agreement between the nitrogen and phosphorus in the bottom
waters at these locations. The relative magnitudes are
148 Fdifferent, which is as expected because the two parameters
are not related.
Figures 52 and 53 are plots of the various phosphorus
parameters in the bottom waters of LMO1 and LMO6. The plots
show that the total phosphorus is about twice the value of
the total soluble phosphorus.
Figure 54 is a plot of the total phosphorus in the
surface waters of LMO1, LMO3, and LMO6. This graph shows no
apparent difference between the peak concentrations at LMO1,
LMO3, and LMO6. However, the average concentration at LMO6
does appear to be higher than the other two locations. This
corresponds with the chlorophyll Q data of Figures 43 and
44. Also, there appears to be a trend in the data towards a
lower average phosphorus concentration at all the sample
locations over the monitoring period analyzed. This trend
follows Figure 55 which shows a decreasing rainfall rate
over the same monitoring period analyzed.
Inspection of Figure 55 clearly shows that as yearly
rainfall increases, the amount of runoff increases. This
observation makes sense because consistently wet conditions
indicate the soil will be saturated more often, encouraging
runoff. Figures 54, 55 and 56 indicate a strong connection
between the rainfall rate and the amount of phosphorus
present in the lake. This confirms the connection between
11
149
the lake and its watershed: it is unlikely that there are
other substantial sources of nutrients into the lake.
Figure 56 shows that as rainfall rate increases, so
does the amount of runoff. As stated previously, this
observation is also fundamental. The predicted values for
percent runoff agree well with the long term runoff rate of
35%, measured by the U.S. Geological Survey in the
region.(30)
Discussion of Monitoring Program Results for the Lake
Manassas Watershed
Table 9 summarizes the conventional and nutrient
monitoring data for the various surface water drainages into
Lake Manassas. The first observation is the adverse impact
of the Vint Hill treatment plant discharge on the quality of
the water in South Run. South Run at station BRO2 contains
significant quantities of both phosphorus and oxidized
nitrogen. There is not a substantial increase in ammonia
nitrogen. Therefore, the Vint Hill treatment plant does
appear to have an efficient nitrification system.
Some general conclusions for the lake's drainages can
be made:
150
1. The pH values of the drainages are at or
slightly below neutrality. None of the drainages
differ significantly in the parameter.
2. The average and median total suspended solids
concentration values appear to be low; some high values
do appear, but are generally associated with storm
events. Typical average values between 8 and 20 mg/L
and typical median values of 7 mg/L. Maximum values
ranged from 80 mg/L to 383 mg/L.
3. The dissolved oxygen content of all thei
streams is near saturation, with typical median and
average values above 87% saturation. Station BR03 had
the highest maximum at 177% saturation. This data
indicates that (a) the biological oxygen demand in the
streams is not large enough to produce an oxygen
deficit, and (b) photosynthesis is occurring in the
streams.
4. The conventional nutrient concentrations in
all the streams are similar, except in South Run.
Average and median total phosphorus concentrations
correspond closely between the streams with values from
0.05 to .10 mg/L. In contrast BR02, the Vint Hill
discharge, has an average and median value between 0.10
and 0.20 mg/L. The maximum observed total phosphorus
151
at BRO2 was 0.82 mg/L, over twice the maximum observed
in any other stream. However, oxidized nitrogen at the
BRO2 station is the most significant nutrient.
Oxidized nitrogen at BRO2 has an average of 1.93 mg/L
and median value of 0.58 mg/L. These values are
between a factor of 5 and 10 times higher than the
other stations. Ammonia nitrogen is not significantly
higher in BRO2 than other stations with an average and
median value of 0.17 and 0.02 mg/L respectfully.
Table 10 summarizes the metal pollutant monitoring
data for the various surface water drainages into Lake
Manassas. In general, inspection of the data shows no
significant metal pollution in any of the drainages into
Lake Manassas. Only iron, copper, manganese, and zinc
appear consistently at concentrations well above detection
limits, however, these metals are found commonly in soil
(15). The high levels of these metals correspond with
periods of high total suspended solids, indicating the
connection between the metal content and the sediment
entrained in the stream flow. Most of the other metals were
not detected above their respective detectable limits. One
exception is lead, which was detected in about half of the
samples for which it was analyzed, with an average value of
11
152
20 ug/L. Most of the detectable lead concentations occurred
in the early dates of the sample period. The lack of lead
being detectable in the later samples may be an indication
of the effectiveness of unleaded gasolines. .
Figures 57 through 63 represent the cumulative loadings
curves for the conventional nutrients from Broad Run (ST70).
The curves show some cyclic behavior, related to the
rainfall patterns. However, in general the plots show that
the loading curves follow a straight line quite closely.
This indicates that the magnitude of the nutrient input from
the Broad Run watershed did not change over the monitoring
period.
Discussion of the Modeling Results Predicting the Eutrophic
Status of Lake Manassas
Application of the Vollenweider model to Lake Manassas
shows that the lake is eutrophic, with the yearly phosphorus
loading rate well above the "dangerous" curve as defined by
Vollenweider. The computer model developed for Lake
Manassas predicts a small effect on the overall quality of
the water in the lake if the runoff from the Northern Arms
area of the lake changes substantially. The predicted
changes in the lake's eutrophic status would probably not be
detectable in the lake, but monitoring the runoff into the
1
153
lake should detect any adverse effects. There could be a
localized increase in the algae growth of the Northern Arm,
similar to the behavior of LM06 versus the rest of the lake.
Elimination of the major point source to the lake, the Vint
Hill sewage treatment plant, would have a more pronounced
effect, but it would not lower the predicted phosphorus
loading rate below the "dangerous" curve.
Application of the other eutrophic index models shows
the lake to be either very high in the mesotrophic range or
well into the eutrophic range, depending on which parameter
is used for indexing. Most of the parameters indicate that
the lake is eutrophic. In particular, the Carlson TSI
method shows the lake does tend toward the eutrophic region,
based on the historical data.
1I
Chapter VI
CONCLUSIONS
1. Lake Manassas is a eutrophic lake. Some
established eutrophic prediction models show the lake to be
"seriously" eutrophic, others show it higher than average,
tending toward being eutrophic. The Vollenweider model
shows the lake is well above the "dangerous" loading curve.
Monitoring results show that the watershed nutrient
properties have been relatively constant over approximately
the last ten years. Therefore, the eutrophic condition of
the lake is not rapidly degrading.
2. Current eutrophic conditions in the lake indicate
that there is no "quick fix" alternative. Morphological
characteristics such as shoreline ratio and flushing time
are such that substantial improvements (approximately an
order of magnitude) in watershed water quality would be
required to improve the overall eutrophic status.
3. The development of the Northern Arms watershed, and
the associated potential for an increased nutrient loading
(i.e. phosphorus) to the lake, should not result in a
significant change in the eutrophic status of the lake.
However, any additional nutrient loading to the lake would
be an undesirable situation.
154
fl
i
155
4. The addition of copper sulfate to the lake may help
minimize the peak values of spring and fall algae blooms.
However, this chemical addition does not have a substantial
affect on the overall net biomass production.
5. The current monitoring program established for Lake
Manassas and its watershed is sufficient for tracking the
lake's status. The monitoring program adequately monitors
both the significant point and non-point sources to the
lake.
Chapter VII
RECOMMENDATIONS
1. The computer model developed for predicting the
eutrophic status of Lake Manassas could be improved by
incorporating the effects of the withdrawal-refill cycle
normally associated with reservoirs. The existing
environmental monitoring database contains a field for pool
elevation in the lake. Recording the value of this
parameter during environmental sampling would enable this
improvement to the computer model to be made.
2. In order to better understand the absolute affects
of the copper sulfate addition, it may be desirable to
devise an experiment where one of the smaller arms of the
lake actually not be treated with the other arms of the
lake. The chlorophyll Q concentration in the untreated arm
could then be compared to the treated arms. If this type of
experiment is considered to be too risky, perhaps a sliding
scale of copper sulfate dose could be developed with
commensurate chlorophyll Q monitoring. This type of
experiment could help to better quantify the benefits of
copper sulfate addition.
3. The policies of nutrient control within the Lake
Manassas watershed (as part of the greater Occoquan
156
uuu
157
Watershed) should continue to be observed and enforced.
Further degradation of the watershed water quality will only
magnify an existing unsatisfactory situation.
4. Further research into sediment—water interactions
may help develop a methodology to minimize nutrient release
from the sediments in the lake.
Chapter VIII
REFERENCES CITED
1. Laufer, Susan M., "Nutrient Dynamics in the Lake Manassas(Virginia) Watershed." M.S. Thesis, Virginia PolytechnicInstitute and State University, Blacksburg, VA (1986).
2. Whetzel, Wade, Chief Operator, City of Manassas WaterTreatment Plant, Greenwich, Virginia, personal interview.
3. Commonwealth of Virginia State Water Control Board, Policyfor· Waste‘ Treatment and ‘Water* Quality Management in. theOccoguan Watershed, State of Virginia, Document Number RC-4-1, revised December 12, 1980.
4. Jones-Saunders Associates, "Residential Planned CommunityZoning Report, Robert Trent Jones International, PrinceWilliam County, Virginia, Chatham, New Jersey (1986)."
5. Northern Virginia Planning District Commission, "NonpointPollution Analysis of the Robert Trent Jones InternationalRezoning Proposal." Final Report..Annandale, Virginia (1986).
6. Whetzel, Robert G., Limnology, Second Edition, SaundersCollege Publishing, New York, NY, 767 pp. (1983).
7. Welch, Paul S., Limnological Methods, McGraw—Hill BookCompany, Inc., New York, NY, 370 pp. (1948).
8. Boyd, Claude E., Water Quality in Warmwater Fish Ponds,Craftmaster Printers Inc., Opelika, AL, 359 pp. (1979).
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11. Marvan, P., Pribil, S., Lhotsky, O., Algal Assays andMonitoring Eutrophication, E. Schweizerbart'scheVerlagsbuchhandlung (Nagele 11. Obermiller), Stuttgart, W.Germany, 253 pp. (1979).
158
159
12. Averett, Robert C., McKnight, Diane M., Chemical QualityWater and the Hydrologic Cycle, Lewis Publishers, Inc.,Chelsea, MI, 382 pp. (1987).
13. dewit, C.T., Goudriaan, J., Simulation of EcologicalProcesses, John Wiley & Sons, New York, NY, 174 pp. (1978).
14. Rohlich, Gerald A., Eutrophication: Causes, Conseguences,Correctives, Proceedings of a Symposium, National Academy ofSciences, Washington, DC, 661 pp. (1969).
15. Connell, D.W., Miller G.J., Chemistry and Ecotoxicologyof Pollution, John.‘Wiley' & Sons, New' York, NY, 444 pp.(1984).
16. Benefield, L.D., Randall C.W., Biological Process Designfor Wastewater Treatment, Teleprint Publishing Inc.,Charlottesville, VA, 526 pp. (1985).
17. Chan. E.C.S., Pelczar, Michael J. Jr., Krieg, Noel R.,Microbiology, McGraw-Hill Book Company, New York, NY, 918 pp.(1986).
18. Eckenfelder, W. Wesley Jr., Principles of Water QualityManagement, CBI Publishing Company Inc., Boston, MS, 717 pp.(1980).
19. Orten, James M., Neuhaus, Otto W., Biochemistry, TheC.V. Mosby Company, Saint Louis, MS, 925 pp. (1970).
20. Dillon, P.J., "The Application of the Phosphorus LoadingConcept to Eutrophication Research." Canada Centre for InlandWaters, Burlington, Ontario, 28 pp. (1976).
21. Grizzard, T.J., Randall, C.W., Sherman, T.E., Weand,B.W., and Hoehn, R.C., "Management of Sediment PhosphorusCycling by Nitrate Addition." Paper presented at Congres dansles Eaux, Paris, France, October 22-24, 1985.
22. Carlson, IL ‘E., "A Trophic State Index for Iakes."Limnology and Oceanography, gg, 361-369 (1977).
23. Reckhow, K.H., "Quantitative Techniques for theAssessment of Lake Quality." Office of water Planning andStandards, EPA-440/5-79-015, USEPA, Washington, DC (1979).
24. Grizzard, Thomas J., Director, Occoquan WatershedMonitoring Laboratory, Manassas, VA, personal communication.
l6O ~
n
25. Tasker, G.D., Driver, N.E., "Nationwide Regression Modelsfor Predicting Urban Runoff Water Quality at UnmonitoredSites," Water Resources Bulletin, American Water ResourcesAssociation, Vol. 24, No.5, October 1988, p. 1091.
26. Northern Virginia Planning District Commission,"Washington Metropolitan Area Urban Runoff DemonstrationProject," Final Report, April, 1983.
27. Breed, Charles B., Hosmer, George L., ElementarySurveying, John Wiley & Sons Inc., New York, NY, 717 p.(1958).
28. U.S. Geological Survey, U.S. Department of Interior, andthe Commonwealth of Virginia Division of Mineral Resources,7.5 Minute Series Topographic Maps for the following Virginiaquadrangles; Throughfare Gap (1983), Gainesville (1983),Middleburg (1978), Rectortown (1981), Marshall (1983), Catlett(1978), and Warrenton (1978).
29. Dymond R.L., McDonnell, A.J., "Determination of Ungaged_ Tributary Flows and Intersegmental Reservoir Flows using
Spreadsheet Software", Water' Resources Bulletin, AmericanWater Resources Association, Vol. 24, No. 5, October 1988, p.1065.
30. Water Resources Data — Virginia, Water Year 1985, U.S.Geological Survey Water Data Report VA-85-1.