MODELING OF FLOW AND WATER QUALITY
IN HENRY HAGG LAKE NEAR
FOREST GROVE, OREGON
p by
MICHAEL T. KNUTSON
Technical Report EWR-4-93
A thesis submitted in partial fulfillment of the S requirements for the degree of
MASTER OF SCIENCE in CIVIL ENGINEERING
Portland State University U 1993
ENVIRONMENTAL AND WATER RESOURCES ENGINEERING DEPARTMENT OF CIVIL ENGINEERING PORTLAND STATE UNIVERSITY PORTLAND, OREGON 97207-0751
ACKNOWLEDGEMENTS
The research presented inthis thesis represents a small portion of a research projectgranted to faculty at both
Portland State University and OregonState University to study of the TuaTtatin RiverBasin by the Oregon Department Environmental Quality. Much gratitude is owed to the D.E.Q. for their support in this project,without which I would not have been here. I would also like to thank Dr.Scott Wells for his support and helpfulness onthis project and throughout my studies at P.S.U.I would also like torecognize the other people involved in this project at P.S.U.,Dr. Roy Koch, Chris
Berger, Fei Tang, and Patrick Moore. The diversity of this group led to some veryinteresting conversations which Iwill miss. I would especially like to thankMarsifor her continued support and for being my bestfriend throughout the struggles of graduate school.
TABLE OF CONTENTS
PAGE
iii ACKNOWLEDGEMENTS vii LIST OF TABLES viii LIST OF FIGURES
CHAPT ER 1 I INTRODUCTION The Tualatin River Basin 1
Henry Hagg Lake 4 8 II LAKE AND RESERVOIR MODELING Definition of modeling 8
A Brief History ofLake and Reservoir Modeling 9 16 IIITHE CE-QUAL-W2 MODEL...... Introduction 16 Model History Model Capabilities Model Limitations Model Layout and InputRequirements
Model Theory 20 Surface Heat Exchange Hydrodynamics and Transport Numerical Solution 27 IV HAGG LAKE MODEL SETUP Hagg Lake Bathymetry 27
Hagg Lake MeteorologicalData 31 V
Hagg Lake Inf lows andOutflows 32
Other Input Files 35
V HAGG LAKE CALIBRATION 36 Introduction 36
Hagg Lake Initial Conditions 36
Calibration of Hydraulics 40
Calibration of Water Quality Constituents and Temperature 46
Hagg Lake CalibrationConclusions 62 64 VI HAGG LAKE VERIFICATION Introduction 64 Verification of Hydraulics 65
Verification of Water Quality 66
Verification ConclusionS 71
VII ADDITIONAL FLOW ALTEPNATIVE 72 Introduction 72
Lake Water Quality ViolationAnalysis 72
VIII RESERVOIR SEDIMENTATIONANALYSIS 85 Introduction 85 Particle Size Distribution Addition to Hagg Lake Model 90
Observations of Sedimentation at Hagg Lake 96 A Simulation of Sedimentsin Hagg Lake 98
IX SUMMARY AND CONCLUSIONS 106
REFERENCES 111 vi
APPENDICES 115
A WATER QUALITY CYCLES IN CE-QUAL-W2 115
B BATHYMETRY FOR HENRY HAGG LAKE 133
C A DESCRIPTION OF FILES USED IN THE HAGG LAKE MODEL 136
D PLOTS OF SEDIMENTATION PROCESSES IN HAGG LAKE 140
LIST OF TABLES
PAGE TABLE 56 Hagg Lake CalibratedCoefficient Values
Water Quality Goals forDissolved Oxygen, pH, and Chlorophyll-aIfl Hagg Lake 73
iii. Engineering Properties of Melbourne Silty Clay Loam 91 Particle Size Distribution ofPeavine Silty Clay Loam 93 Particle Size Distribution of a clayey_Kaolinitic_NesiX_Xeric_HaP]0h1JmtI from Nevada County, CA 93
Fraction of Clay Particles -for 94 the Hagg Lake Model Fraction of Silt Particles for the Hagg Lake Model 94 Sediment Settling Rates for HaggLake 96
Inorganic Suspended Solids Concentrations Used for Inf low to Hagg Lake 1990 99
LIST OF FIGURES
FIGURE PAGE
Tualatin River Basin 2
Tualatin River Daily Flowrate for 1991 at West Linn 4
Three-Dimensional view of Henry Hagg Lake's bathymetry 6
CE-QUAL-W2 grid layout: x = location of U, A, D, and 0 = location of W, A, and D; + = location of p, 8, P1 and B 26
2-dimensional plot of Hagg Lake created by SURFER for bathymetry estimation 29
Hagg Lake longitudinal cell delineation 29
CE-QUAL-W2 method for vertical cell delineation 30 Volume versus Elevation curve for Henry Hagg Lake 31
Summer initial temperature profile (May 1, 1990) used for Hagg Lake Calibration (simulated) 38
Summer initial conditions (May 1, 1990) used for dissolved oxygen profiles in Hagg Lake (simulated) 39
Total Hagg Lake inflows computed from "change in storage" data versus total Hagg Lake inflows computed by model for the summer of 1990 42
Hagg Lake Outflow Intake Structure - Plan view location 43
13. Hagg Lake Outflow Intake Structure - Profile View 44 ix
Hagg Lake water surface elevation predicted versus actual for the summer of 1990 45
Hagg Lake calibration results for Chlorophyll-a, PO4-P, 2' and Temperature for the summer of 1990 48
Hagg Lake calibration results of NH3-N, Detritus, NO3-N, and Zooplankton for the summer of 1990 49
Hagg Lake calibration results for Inorganic Carbon, Alkalinity, pH, and CO2, for the summer of 1990 50
Hagg Lake calibration results for TDS, TSS, and BOD for the summer of 1990 51
Hagg Lake calibration results for Bicarbonate, Carbonate, and profiles of Temperature and 02, for the summer of 1990 52
Hagg Lake calibration profiles of Chlorophyll-a, PO4-P, NH3-N, and NO3-N for the summer of 1990 53
Water Surface Elevation simulation versus actual for verification year 1991 65
Verification of Chlorophyll-a, 02, PO4-P, and Temperature, summer 1991 67
Verification of NH3-N, NO3-N, Detritus, and zooplankton, for summer of 1991 68
Verification of TDS, TSS, BaD-U, and pH for summer of 1991 69
Base Case for Hagg Lake Dissolved Oxygen violations summer of 1990 (Average violation =5.35mg/i) 76 Dissolved Oxygen Violations with additional 100 cfs outflow from 6/15 through 9/15 1990 (Average violation 5.12 mg/l) 76
Base Case for Hagg Lake pH violations, for the summer of 1990 (Average violation =8.65) 77 x pH violations base case with 100 cfs additional flow from 6/15 through 9/15 1990 (Average violation = 8.65) 77
Base Case for Hagg Lake Chlorophyll-a violations, for the summer of 1990 (Average violation = 40.15 pg/l) 78 Chlorophyll-a violations base case with 100 cfs additional flow from 6/15 through 9/15 1990 (Average violation = 40.65 iig/1) 78
Hagg Lake Outflow Temperature, Water Surface Elevation, pH, and Chlorophyll-a concentration base case 1990 versus base case +100 cfs from 6/15 through 9/15 1990 81
Hagg Lake Outflow Dissolved Oxygen, Ortho- phosphorous, NO3-N, and NH3-N Base Case 1990 versus Base Case +100 cfs additional flow from 6/15 through 9/15 1990 83
Hagg Lake site location for graphing suspended particle results 100
Concentrations of inorganic particles versus Julian day at longitudinal cell 14, vertical cell 9, 1990 101
Sum of inorganics suspended solids versus Julian day at longitudinal cell 14, vertical cell 9, 1990 101
Concentrations of inorganic suspended solids versus Julian day at longitudinal cell 22, vertical cell 9, 1990 102
Sum of inorganic suspended solids versus Julian day at longitudinal cell 22, vertical cell 9, 1990 102 Concentrations of inorganic suspended solids versus Julian day at outlet intake structure, 1990 103
Sum of inorganic suspended solids versus Julian day at outlet intake structure, 1990 103
CHAPTER I
INTRODUCTION
THE TUALATIN RIVER BASIN
The Tualatin River is an 86 mile long river with a
drainage basin of 711 mi2 (Wolf, 1992). The river flows
mainly in Washington County, Oregon, eventually reachingthe
Willamette River(see Figure1). Combinations of urban growth, increased agriculture,and low summer flows have caused the water quality in the Tualatin River to decline.
The Tualatin River Basin today is a complex mixture of agricultural, forestry, and urban landuses (Miner & Scott,
1992). The Basin is located inthe foothills of the relativelylow Oregon Coast Range. Streamf lows in the
Tualatin Basin are dependent on rain events for there isno contribution from snowpack in thisrange during the summer.
During the summer months,the Tualatin Riverbaseflow decreases considerably. The River has had flow rates of 2000 to 3500 cfs in the winter months, but the naturalflow during the summer has dropped below 46 cfs (U.S.A.,1991) (see Figure
2). The summer low flow condition causes the riverto become a slow moving lake in its lower reaches. Henry Hagg Lake was built primarily to provide water to the Tualatin RiverBasin 2 during the summer months for both irrigation demand and enhanced water quality (Otto, 1991).
Figure 1. Tualatin River Basin.
The area of the Tualatin Basin was one of the earliest farming settlements in Oregon. Agriculture developed quickly in the basin because existing open areas made clearing the 3 ground easy, and the soils of thebasin were rich. As time went on, timbered tracts were clearedand more land came under cultivation (Johnson et. al., 1985). Hay, grain, and livestock production were the basis of theearly economy and they are still an important part ofthe economy today. As population increased in the area, irrigationwater and flood control demands increased, and the need for a newreservoir to supplement the summer low flow months andcontrol floods during the wet winter became apparent (Johnsonet. al., 1985).
During the 1960's, the lower WillametteRiver was studied because of its poor water quality, andsteps were taken to
reduce waste loads to the river and enhancethe water quality.
A report on the Willamette RiverBasin was written in 1967 by the Federal Water Pollution ControlAdministration which outlined the immediate needs ofthe Willamette River to
enhance its quality. The following excerpt concerningthe Tualatin River was taken from this report (FWPCA, 1967,pg.8): The Tualatin River's need for augmented summer flows is perhaps the most immediate andpressing in the Wjllamette River Basin. The watershed of the Tualatin already provides an average level of waste reduction that exceeds 90 percent, yet dissolved oxygen in the lower riverconsistently drops below the 5 mg/i required for fish passage; and other quality parameters present an equally dismal picture. Projections of population and industrial output indicate that by 1985 a flow of at least 260 cfs at and below Farmington will berequired at all times if passage for fish runs is to bemaintained. Development of advanced waste treatment and additional storage fromreservoir sites being studied on other tributaries of the Tualatin will be required if nuisanceconditions are tobe averted in the future along this waterbody marked by rapid population growth. 4 A storage reservoir,Henry Hagg Lake,was built to
augment flows in the Tualatin, and the FWPCA's forecastwas
correct. Today scientists and engineers are looking forways to improve the Tualatin's water quality.
TUALATN RIVER AT WEST LJNN JANUARY TO S[PT[MR[R 1 99 1 9000
8000 - ' 7000 U ''600O - 5000 4000 -
3000 -
2000 - 1000-J
0 0 30 60 120 150 180 210 240 270 JULIAN DAY
Figure 2. Tualatin River Daily Flowrate for 1991 at West Linn.
HENRY HAGG LAKE
Henry Hagg Lake is a "multi-purpose reservoir", builtby the U.S. Bureau of Reclamation in 1972 andput into service in
1974. The reservoir is owned by the Bureau of Reclamationand operated by the Tualatin Valley Irrigation District (Washington County). The reservoir was named in honor of 5
Henry Hagg, a prominent Oregon dairyman and Washington County
official who passed away in 1971(Johnson et.al., 1985).
Hagg Lake was formed by damming Scoggins Creek, a tributary on the upper end of the Tualatin River,near Forest Grove, Oregon. Scoggins Dam is a 151 foot high earthf ill structure (Johnson et. al., 1985).
The reservoir is used for many other purposes besides providing flow to the Tualatin River for enhanced water
quality. The lake is used for flood control, municipal and
industrial water demand, and recreation (Otto, 1991,
Washington County, Johnson et. al., 1985).Boat launching and
mooring facilities have been constructed, the lake is stocked
annually with rainbow trout, and there are large day-useareas with picnic tables, shelters, and water facilities (Johnson
et. al., 1985). The area around the lakeis used for fishing, picnicking, water-skiing, boating, and bicycling.
During the late 1960's, the Bureau of Reclamation didan operation study on the Tualatin River to see how much storage
was necessary (FWPCA, 1967). The study used the 1944 water
year (a dry year) to calculate the amount of storage required
to maintain adequate flow in the Tualatin during thesummer.
The study found that 46,260 acre-feet of water storagewere required, of which 10,400 acre-feetwere required for water quality releases (FWPCA, 1967).Figure 3 shows the bathymetry of Henry Hagg Lake as it was constructed. 6
Figure 3. Three-Dimensional view of Henry Hagg Lake' s bathymetry.
Hagg lake has a storage capacity of 59,910 acre-feet, where 53,640 acre-feet is active storage and 6,280 acre-feet is "dead storage" used for sedimentation (Otto, 1991). The top 20,300 acre-feet is used for flood control(ample to attenuate a 50-year flood), 14,000 acre-feet is stored for municipal and irrigation water supply, and 16,900 acre-feet is stored for water quality enhancement (Johnson et. al., 1985). The pool is drawn down during the dry summer months by an average of 22 feet (Johnson et. al., 1985) and filled again during the wet winter months. According to the Scoggins Dam Operator, the reservoir is to be filled by May 1st at an 7 elevation of 303.50 feet M.S.L.(Otto, 1991). Outflows are dictated by flood conditions, water purchase demands,and minimum requirements. The minimum outflow requirement is 10 cfs from December through September, and 20 cfs from October through November (Otto,1991). At full pool (303.50 feet M.S.L.), the lake covers 1153 acres having a maximumdepth of 110 feet and an average depth of 51 feet (Johnson et.al.,
1985) The drainage basin of Hagg Lake covers an area of 37.5 square miles located in the foothills of theOregon Coast
Range (Johnson et. al., 1985). The highest point in the basin is Saddle Mountain, at 3535 feet M.S.L., which is also the highest point in the northern portion of the Oregon Coast
Range. Most of the areais forested with second-growth
Douglas fir. The area is covered by thick soils of clay and silt overlying bedrock that is a mixture of sandstone and older volcanic rocks that typify this region (Johnson et. al.,
1985). A computational model of the hydrodynamics and water quality of Henry Hagg Lake was created in order to model its relationship with the Tualatin River.This model was used to show the effects on Hagg Lake if additional flow to the
Tualatin during the summer season were allowed.The model was also used to look at turbidity and sedimentation cycles in
Hagg Lake. CHAPTER II
LAKE AND RESERVOIR MODELING
DEFINITION OF MODELING
In the introduction of the book"Principles of Surface Water Quality Modeling andControl",Thomann and Mueller (1987) define a mathematicalmodel as follows:
A theoretical construct, togetherwithassignment of numerical values to model parameters, incorporating some priorobservationsdrawnfrom field and laboratory data,andrelating external inputs or forcingfunctionsto system variable responses.
Models are often created forwater bodies so that water quality changes toa water body can be predicted basedon changes in forcing Conditions. Also, structural and non- structural Changes toa water body can be simulated to look at their potentialeffects before such changes are made. Engineers have used and continueto use models for design and planning of most projects,whether they are buildinga new skyscraper, designing thespace shuttle, or constructinga heart valve. Modeling has becomeanimportant part of engineering,and with the increased demandplaced on our natural environment, modelingof water bodies wasa natural step in engineering them forour future. 9
With advancesin science, mathematics, and computer technology, full scale mathematical models have been refined to simulate chemical processes, biological productivity, and hydrodynamic processes in reservoirs and lakes.This chapter reviews some of the history of lake and reservoir modeling, leading to models used today. The chapter is a synopsis of literature found on lake modeling and represents a small portion of a vast amount of research performed by others.
A BRIEF HISTORY OF LAKE AND RESERVOIR MODELING
Mathematical modeling of water bodies began in the early
1900's(Orlob, 1983),when it became apparent that man's pollution problems could not be solved by mother nature alone. The first known mathematical model f or a water body was the Streeter-Pheips Equation describing the balance of dissolved oxygen in a stream (Orlob, 1983):
The governing equation has the form: dO2 dO2 dt-Q dV'°28°2) -k(L) and the steady-state solution is: kL.(e-e") +D.ed
where: 02 = Dissolved Oxygen concentration V = Control volume Q = Volumetric Flowrate k = BOD decay rate ka = reaeration coefficient °2s= Dissolved Oxygen saturation concentration L = BOD concentration D02 = Dissolved Oxygen deficit (O-O) 10
= Residence time (V/Q)
This relatively simple equation was developed in the 1920's when the Ohio River Commission began a study of the effects of pollution on domestic water supply (Streeter and Phelps, 1925).
Duringtheseearly stages of modeling, fullscale
mathematicalmodels ofwaterbodiessuch as lakesand
reservoirs were impractical since computers and even
calculators were not available. In the late 1950's, with the advent of the computer, mathematicians developed techniques
for solving large sets of simultaneous algebraic equations and
differential equations using finite difference approximations
(Orlob, 1983). This new technology openeddoors for mathematical modeling of water bodies.
The firstlake modelscreated wereconcernedwith modeling thermal stratification (Orlob,1983, James,1984, Orlob, 1981). In the mid 1960's attention brought about by environmentalists was directed toward water qualityproblems associated with the installation of surface water impoundments
(Orlob, 1981). These first mathematical models of reservoirs were used by engineers modeling temperature stratification in reservoirs and limnologists predicting eutrophication inlakes (Orlob, 1983, James, 1984, Orlob, 1981). These models were one-dimensional and did not incorporate hydrodynamics. They modeled the thermal regimeof systems well (i.e., deep- stratifiedlakes), but were inadequatefor allsystems, 11
especially those with relatively large inflow to size ratios
(Orlob, 1981)
The next advancement in lake modeling was the addition of
water quality constituent cycles to the already developed one-
dimensional thermal stratification models (Or lob, 1981). This
addition was accomplished by applying the advection-diffusion
equation to each process (i.e., dissolvedoxygen - BOD
relationship). The advection-diffusion equation is a mass balance equation performed on a particular constituent of
interest.The equation remains the same for each process with
the exception of the source-sink term.The other terms (i.e., advection and diffusion) are a function of the fluid. The chemical and biological interactions are lumped into the
source-sink term. The equation has the form:
avCQac 8C5,18 (3) at ax ax2
where: C =Constituent of interest Q =Volumetric Flow V Control Volume X =One-Dimensional direction D =Coefficient of diffusion S/S=Sources and Sinks
The most significant problem with these first models was their inability to model systems where hydraulics played an
important role (Orlob, 1981).Therefore, the next step in the history of modeling lakes was to add more dimensions to the 12 models. With the addition of more dimensions, Navier-Stokes equations for the conservation of momentum combined with Reynold's turbulent transport concepts were added to the models to improve the prediction of the hydrodynamics of lakes
(Orlob, 1983)
The equation below represents the Turbulent Momentum Equation for the X-direction:
Ll E9uu Buy Bái 8uv 8uWFla+0 (4) at Bx a a ax ax By Bz
Where: t =time x,y,z 3-dimensional coordinates u,v,w = mean velocities in the x, y, and z- directions uvw = time-averaged turbulent eddy transport of momentum g = gravitational acceleration constant p = fluid density p = pressure F = Coriolis parameter u = kinematic viscosity
Similar equations exist for the Y and Z momentum equations.
The U.S. Army Corps of Engineers were one of the first groups to develop multi-demensional water quality models. In the early 1970's the Corps of Engineers were trying to predict temperature effects of impoundments placed in the Columbia
River Drainage, and their resulting effectson anadromous fish populations (Orlob, 1981). These impoundments were designed for hydroelectric power generation, not water storage. Thus, the prior one-dimensional thermal stratification modelswere 13
unable to predict the temperature regime of these impoundments adequately, and the Corp developed a two-dimensional water quality and hydrodynamic model for stratified flow systems. They successfully applied this model to the Lower Granite
Project on the Snake River in the early 1970's (Orlob,1981).
With the development of higher-order models of lakescame
an enormous increase in computational needs. The computational needs of these higher-order models increased exponentially. Both finite element and finite difference
numerical techniques are used to solve thenumerous equations
associated with these higher-order models. Therefore, in the early days of lake modeling, only large institutions with
mainframe computers were able touse these models, and even
then modeling simulations would takeenormous computational time.
The most significant, next advance in lake modelingcame from advances in computer technology. What once took large
institutions with mainframe computers toaccomplish could now
be performed on advanced personal computersby any individual with a good understanding of modeling inless time. This led to the proliferation ofmany new models. However, most of these models were poorly documented, limiting theiruse to their creators (Orlob, 1981). Also, computer advancements have led to the use ofmany models by people without the proper training or experience, who view a modelas a "black- box". 14
With all the advancements made in modeling, the use of sophisticated models still liesin research institutions, whereas in practice, the simpler one-dimensional models are
used. In the literature on modeling, the term "technology
transfer" is often seen. This term refers to the need for the
high technology possessed at research institutions to be used
in more practical situations in the "real" world. As Gerald Orlob put it in the preface of his book on water quality modeling (1983):
. .despite the enthusiasm with which modeling of aquatic systems has apparently been embraced, there exists a gap between conception of the model as an exercise of the mind and its use as a practical tool. One only has to examine the literature to see that comparatively few water quality models have attained the status that enables the technology they representto betransferred to others.
During the past decade, modelers have been researching better ways to represent water quality cycles and hydrodynamics which are simpler and rely less on empirical formulations. They have also tried to address the need for
"technology transfer", and more models have been adapted for use as tools in science and engineering practice. This thesis represents the application of CE-QUAL-W2
(Corps of Engineers, 1986), a model which could be considered
"the state of the art", to Hagg Lake. The Hagg Lake Model is a sub-model of a complete model of the Tualatin River System, which has been created as a working tool for use by scientists 15 and engineers evaluating the Tualatin River system. The adaptation of a multi-dimensional model is a very complicated and time consuming task. The adaptation of CE-QUAL-W2 to Hagg
Lake took about a year. CHAPTER III
THE CE-QUAL-W2 MODEL
INTRODUCTION
This chapter is a review of the CE-QUAL-W2model, its application, history, capabilities, limitations,options, and theory. The majority of the chapter represents asynopsis of the more detailed users manual (Corps ofEngineers, 1990)
CE-QUAL-W2is a two-dimensional,laterally averaged, dynamic model of hydrodynamics and waterquality. The model can be applied to: rivers, lakes, reservoirs, and estuaries. The model was chosen for use in themodeling of Hagg Lake for the following reasons: (i) modeling of water quality in two- dimensions could be accomplished, showing bothlongitudinal and vertical transport, (ii) over 20 waterquality parameters could be modeled,(iii) the FORTRAN code could be modified, and (iv) hydrodynamic mixing would be modeled moreaccurately than with a one-dimensional model.
Model History The CE-QUAL-W2 code has been in developmentsince 1975. It began as alaterally averaged reservoir model (LARN)
(Edinger and Buchak, 1975). subsequent modifications to handlemultiplebranches andtidal boundary conditions 17 produced the "Generalized Longitudinal-VerticalHydrodynamics and Transport Model" (GLVHT).Next, water qualityalgorithms were added to the model,and CE-QUAL-W2 was born. Additional modifications over the years to increasemodel efficiency, stability, and to make the model easier to usehave improved the CE-QUAL--W2 model. The model is still in adevelopment stage, and even during the modelingof Hagg Lake, changes in thesourcecodeandinput files were performedonthe continuously updated model.
Model Capabilities The CE-QUAL-W2 model is able topredict the hydrodynamics
of a water body including:water surface elevations,vertical velocities, and horizontal velocities. Themodel includes its
temperature calculations withhydrodynamics because of effects
on water density. This allows one to model temperatureand hydrodynamics independent of water quality. The CE-QUAL-W2 code has the ability to modelupto 20water quality
constituents, including a conservative tracer, coliform bacteria, inorganic suspended solids, totaldissolved solids,
labile organic matter, refractory organicmatter, an algal
group, detritus, ortho-phosphorus,ammonia, nitrate-nitrite, dissolved oxygen, iron, sediment, alkalinity,carbon-dioxide,
inorganic carbon, pH, bicarbonate, and carbonate. Since the
code is so versatile, other waterquality parameter additions
have been included: zooplankton,CBOD, and 5 additional inorganic suspended solid size fractions (See ChapterVIII) 18 have been added to the HaggLake model.
The model can handlemultiple point sourceand non-point and distributed source inflowsin the forms of tributaries used in many situations tributaries. The model can also be and such as complex riversystems, dendritic reservoirs, estuaries because it has thecapability to simulateice cover, bodies. variable head boundaries,and multi-branched water The model can be runefficiently for largetime periods, because it has anttautosteppiflg" timestepalgorithm which during a given allowsthe user to vary the timestep capabilities which make simulation. The model has many other Corps of it efficient, details ofwhich can be found in the Engineers (1986a) and the Corpsof Engineers (1990).
Model Limitations Since the model istwo-dimensional, governingequations layer are laterallyaveraged. Governing equations are also Water averaged, however,layers can have variablesizes. quality biological sources andsinks are inherentlysimplified descriptions of a much more complexaquatic ecosystem (see
Appendix A). The model includes only onealgal compartment. MacrophyteS are not includedin water qualitycalculations. The model uses the "QUICK"quadratic upstreamdifferencing partial algorithm (Leonard, 1979) asits method to solve can introduce differential equations, and this method numerical diffusion, which canhave a higher magnitudethan
actual physical diffusion.Also, truncation errorsin solving 19 finite-differences can be important asthe timestep and spacing are increased. High water surface slopes can cause numerical instability, however, in theHagg Lake model this was not encountered.
Model Layout and InputRequirements
The first step in modeling awater body with the CE-QUAL-
W2 model is to set up thecomputational grid. The geometry of a water body isinput to the CE-QUAL-W2 modelthrough three parameters: the longitudinal spacing, thevertical spacing, and the average cross-sectionalwidth. The longitudinal into spacing is determined by breakingthewaterbody longitudinal cells, parallel to oneanother and perpendicular to the centerline of horizontalflow. The vertical spacing is determined in the same manner, except thesecells go from the water surface to the bottom boundaryof the water body. By interpreting cross-sectional data from thewater body, average cross-sectional widths are determined foreach vertical cell.
One must evaluate a number offactors when determining the longitudinal and vertical spacing of awaterbody, including: computational time, bottom slope, surfaceslope, and areas of strongest gradients. There are two types of cellsin the CE- QUAL-W2 model: active cells andboundary cells. Boundary cells are placed at the top of theuppermost activecell, the bottom of the lowest active cell, atthe upstream side of the first active longitudinal cell, and atthe downstream side of the last active longitudinal cell. These boundary cells have 20 zero widths, and areused for boundary conditionsin solution to the finite difference equations. The main input file f or running theCE-QUAL-W2 model is the control file. This file contains initialconditions for the model simulation including thesimulation time period, surface layer location, temperature and constituent concentrations, location of all inflows, outflows, and withdrawals, coefficients for modelingwater quality kinetics, and hydrodynamic parameters. The control file also tellsthe program where it canfind necessary inflow, outflow,and geometric data (i.e., file names)
MODEL THEORY
Surface Heat Exchange
The CE-QUAL--W2 model uses eitherequilibrium temperatures for calculating surface heat exchange(Brady and Edinger,
1975) or a "term-by-term" surface heatflux calculation (Corps of Engineers, 1990).For the Hagg Lake simulation,the "term- by-term" algorithm of the surface heatflux was used. A meteorologicalfilewascreatedfor a model simulation containing average air temperature, average dew point temperature, cloud cover, wind speed, andwind direction on a daily basis. Other meteorological factorsincluding latitude, solar radiation absorption coefficients,and gas exchange coefficients are input in the control file. In the term-by- term surface heat exchange analysis,the model calculates the I I 21 net solar radiation from the time of day, thelatitude, and
the cloud cover for every time step. Other terms in the heat are calculated every time step frominput values and
Ibalancecalculated water surface temperatures.
Hydrodynamics and Transport and hydrodynamics are calculated in CE-QUAL-W2
ITransportfrom six equations with six unknowns. The equations were Iderived from laterally averaging the three-dimensional equations of fluid motion (Edinger and Buchak, 1975). The
equations along with their descriptions are as follows:
Horizontal Momentum
8(BAaU) aUBaUUBaWUB__1 8BP x Bi (5) I at 3x az p3x ax
I Where: u = longitudinal, laterally averaged velocity (m/sec) B =water body width (m) I: =time (sec) x longitudinal Cartesian coordinate z vertical Cartesian coordinate ItW vertical, laterally averaged velocity (m/sec) I p =density (kg/rn3) P =pressure (N/rn2) A =longitudinal momentum dispersion coefficient (rn2/sec) I =shear stress per unit mass resulting from the vertical gradient of the horizontal velocity (m2/sec2) I The first term is the time rate of change of horizontal I
I 22 momentum, while the second andthird terms represent the horizontal and vertical advection ofmomentum.The first term on theright-hand-side is thepressure force fromthe horizontal pressure gradient, the second term is the
horizontal dispersion of momentum, and the third term represents forces due to shear stress. TurbulenceISmodeled
by eddy coefficients.
Constituent Transport
a(BD--)a(BDZd) (6) aBoauBo awBo ax -q0B+SB at 3x az 3x az
Where: 0 = laterally averaged constituent concentration (mg/i) D = longitudinal temperatureand constituent dispersion coefficient(m2/sec) = vertical temperatureand constituent dispersion coefficient(m2/sec) q0 = lateral inflow oroutflow mass flow rate of constituent per unit volume (mg/ 1/sec) Sk = kinetics source/sink term for constituent concentrations (mg/ 1/sec)
The first term in this equationrepresents the time rate
of change of constituentconcentration, and the second and third terms are the horizontal andvertical advection of
constituents. The fourth and fifth terms are thehorizontal and vertical diffusion of constituents.The first term on the right-hand-side represents lateral inflows oroutflows of
constituents, and the last term represents allkinetic sources 23 and sinks of constituents. Details of kinetic sources and sinks for each parameter may be found in Appendix A.
Free Water Surface Elevation
h h (7) aBWafuBdz-fqBdz ax.! at w w
Where: B = time and spatially varying surfacewidth (in) w = free water surface location (in) h = total depth (m) q lateralboundaryinflow oroutflow (m3/sec)
Hydrostatic Pressure
(8)
Where: P = pressure(N/rn2) p = fluid density(kg/in3) g = gravitational acceleration (rn/sec 2)
Thishydrostatic pressureequation is thevertical momentum equation with the elimination of all acceleration terms. Vertical velocities tend to be low and vertical accelerations tend to be verylow compared to pressure differences, therefore, these terms are insignificant. 24
Continuity
UB aWB-qB (9) 3x az
Where: q = boundary inflow oroutflow (-) per unit volume per second(sec')
Equation of State
p=f(0) (10)
Where: f(0) = function for densityof fluid which is dependent upon temperature, total dissolved solids, salinity, and suspended solids
Computation of Hydrodynamics and Transport
Six unknowns result from these sixequations:
free water surface elevation, w pressure, P horizontal velocity, U vertical velocity, W constituent concentration, 8 density, p
Thesolution of these six equationsfor these six unknowns forms the basic structure of theCE-QUAL-W2 model. The reduction of these equations to twocoordinates is the main feature that reduces computational time andstorage over the three-dimensional case. Lateral averaging eliminates the
lateral momentum balance, the lateral velocitycomponent, and 25 the Coriolis acceleration termin the momentum equation.
Numerical Solution
The partial differentialequations for the water surface elevation are solved using animplicit, space-staggered,
finite difference solution algorithm. The "QUICK" (Leonard, of the 1979) solutionalgorithm is used for solution temperature and constituentequations using a Crank-NicolSon
implicit algorithm. The gridis referred to asspace- staggered because some variables aredefined at one location
and the remainder are displacedby Ax/2 or Az/2. Variables
defined at the boundary of cells includethe velocities (U,W),
the dispersion coefficients(Ag, D, A, and D),and the internal shear stress (r) . The density (p), the pressure and all (P), the average cross-sectional idth (B), constituent concentrations and temperature(0) are defined at
the center of each cell. Figure 4shows how CE-QUAL-W2
interprets these coefficients. I
I 26 I Schematic of CE-QUAL-W2 Grid Layout I tr SwOrkvat &ent ii / at i
I + +
n U U
- z 1 Lverk-1 + + 0 0 0 A + Cell lie + layer li y(b) I 0 0
+ Layerli+l + - I 0 & 0 Delta C 1 I Figure 4. CE-QUAL-W2grid layout: x = location of U, A,D, and r; 0 =location of W, A, and D; + I = location of p, e, P,and B. I Each variable is a function of itsspatial location (I,K) and its time (n). The solution proceeds as follows: knowing velocity field at time n, the I!' the water surface elevations and water surface elevations aresolved for at time n+1. Using I these updated surface elevations,horizontal velocities are solved for at time n+l. Vertical velocities are then solved I f or at time n+l from thecontinuity equation. The new I constituent concentrations are then computed from the constituent balance. These computations are thencontinued I for the next time step. I I CHAPTER IV
HAGG LAKE MODEL SETUP
HAGG LAKE BATHYMETRY
Creating the CE-QUAL-W2 model of Hagg Lake consisted of
creating the necessary input files listed in Appendix C.This chapter is intended to show how the input files were set up. The first step in creating the CE-QUAL-W2 model of Hagg
Lake was generating the bathymetry file for the lake. The main source of data came from a highly detailed topographic map of the Hagg Lake area created by the U.S. Bureau of
Reclamation before construction of Scoggins Dam. The map was
digitized using the major topographic lines outlining the lake
with AUTOCAD. A "dxf't file from AUTOCAD was sorted into an
ASCII file with three columns for the x, y, and z coordinates of each point digitized. The ASCII file was used with a
software package called SURFER which created interpolated two- dimensional and three-dimensional plots of the lake. Using the two-dimensional plot (See Figure 5), the lakewas broken into longitudinal cells thatwere each 550 feet (167.64 m) in length. A 5 foot (1.52 m) spacing was chosen for vertical cells based on memory requirements and modelingaccuracy.
HaggLakewasthen dividedinto 31 longitudinal cells (including 2 inactive cells on either end) and 26 vertical 28 cells (including 2 inactive cells one at the topand one at the bottom). By drawing a line through the centerof each longitudinal cell and picking off two points, oneat either side of the lake, a blanking file was createdfor use with
SURFER. A blanking file for SURFER allows oneto determine the elevations along any delineated line by theplacement of two points in the blanking file. Using the SLICE utility within SURFER and the blanking file, cross-sectionsfor each longitudinal cell were determined. A sorting program then converted the SURFER file into the proper formatfor CE-QUAL-
W2. This file was then checked for errors andverified. Figures 6 and 7 show how longitudinal and vertical cells were delineated for the Hagg Lake Model. To keep grid errors low, cell widths between neighboring cells werekept within a factor of 4. 29
I 205570001 207-057.001 29Q3.4-.0O 1301231 0013031 1 8.001105005.001306692 00
oeeg1 .00
Figure 5. 2-dimensional plot of Hagg Lake created by SURFER for bathymetry estimation.
Figure 6. Hagg Lake longitudinal cell delineation. 30
Schematic For CEQUALW2 Vertical Cell liayout For EachCrossSection
Vertical Cell # Top Width of Cell 2
Top Width of Cell 3
3 Top Width of Cell 4
4 Top Width of CeLl 5
5 Top Width of Cell 6 vvqv"
There Are 26 Cells in the Hagg Lake Model
Figure 7. CE-QUAL-W2 method for verticalcell delineation.
As mentionedbefore, HaggLake hasan approximate capacity of 59,910 acre-feet for water storage. The bathymetry delineation of Hagg Lake waschecked by creating a volume versus elevation curve. Using SURFER, volumes were calculated for elevations of the lake at 5foot intervals.
The volume of Hagg Lake vs. elevationis shown in Figure 8. 31
HAGG LAKE VOLUME VS. ELEVATION
300
285 ? 270 uU U' Li Li 3O3. , 255 z P 240 F- 225 : 210. 195.U
180 60 0 5 10 15 20 25 30 35 40 45 50 55 VOLUME (ACREFEET) (Thousands)
Figure 8. Volume versus Elevation curvefor Henry Hagg Lake.
According to Figure 8, the SURFERgenerated bathymetry agreed well with prior estimates ofthe full pool volume of
59,910 acre-feet. The Manning coefficient forfriction is specified for
each cell and is located in thebathymetry file.However, for
the Hagg Lake Model, velocities are solow that friction does not play a large role. A value of 0.020 was usedfor all
longitudinal cells. 32
HAGG LAKE METEOROLOGICAL DATA
The meteorological data necessaryfor running the Hagg
Lake model were obtained from numeroussources for the years
1990 and 1991. Air temperature data wereobtained from Mr. George Taylor, the OregonState Climatologist. These data were taken dailyin the form of T(min), T(max),and T(ave) Basin: from three different stations in the Tualatin Hilisboro HillSborO, Forest Grove, andBeaverton. The temperature data were the mostcomplete, therefore, they were used for model simulations. Since there were no complete relative humidity data available forthe basin, the daily as an T(min) data compiled by Mr. Taylor wereused approximation for the dew pointtemperature. Hourly wind speed, hourly wind direction, andhourly cloud cover data were obtained from the Hilisboro Airport,these data were then averaged to daily values. The cloud cover dataobtained were based on an observed 0 to 100percent cloudy basis.
These data were placed intotwo files as input to the CE-
QUAL-W2 model, "MET9O.NPT" and"MET91.NPT", based on Julian
day.
HAGG LAKE INFLOWS AND OUTFLOWS
The Hagg Lake model was createdusing one branch with an
inflow at the upper end (ScogginsCreek) and an outflow at the
opposite end (Scoggins Dam). Two other main tributariesfeed
into this lake, gain Creek and TannerCreek. Tributary files 33 for each Samand Tanner Creeks were createddesignating flow, temperature, and water qualityparameters as a function of
Julian day. CE-QUAL-W2 requires an outputfile at the end of every branch (cell 30for Hagg Lake). Since the outflow intake structure is not located atthe dam, the outflow file consisted of zero flow.A withdrawal file wascreated for the
outflow intake structurelocation (cell 29)(see Chapter V).
In researching the historicalrecords of Hagg Lake, no previous detailed water qualitystudies had been done on this lake and water quality data were verylimited. The only water-quality data found on the lake werefrom the Unified
Sewerage Agency (U.S.A.). These consisted of sporadicwater quality and temperature data from the summersof 1978 through
1985, and more complete data fromits three major tributaries
(Scoggins Creek, SamCreek, and Tanner Creek) from the summer
of 1989. Because these data wereincomplete and out of the model study period, they were usedonly as a reference. Other
water quality data were foundin the "Atlas of Oregon Lakes" for two dates: 5-9-75 and 10-7-81(Johnson et. al., 1985).
Some data were also obtainedfrom a volunteer "CitizenLake Watch" program for the summer of 1990that provided some
temperature and turbidity data. Good hydraulic data (i.e., inflows,outflows, change in storage, etc.) existed for HaggLake. A monthly report,
"Scoggins Dam Reservoir Operations",has been maintained by the Scoggins Dam operatorfor every month of thedam's 34 operation. This report was obtained from theTualatin Valley Irrigation District (T.V.I.D.) for allmonths in the study and period.The report has daily inflowmeasurements for Sam Scoggins Creeks, daily water surfaceelevations, daily outflow
releases, dailycomputedchanges in storage, and daily computed total inflows (change in storageminus the outflow). Therefore, inflow files were set upfor Scoggins and Sam
Creeks from these data and TannerCreek flows were estimated
(see Chapter V). CE-QUAL-W2 requires three files for everyinf low: a flow
file,a temperature file,and a constituentconcentration
file. Since no inflow temperature dataexisted for the study period, these parameters were estimatedfrom temperature data
of creeksin nearby sub-basins. Using U.S.A.data from Carpenter Creek and the UpperTualatin River, and comparing these Creek's temperatures with data onScoggins, Sam, and
Tanner Creeks in 1989 (U.S.A.),trends in temperature were determined and inflow temperature files werecreated for Hagg
Lake inflows. No inf low water qualityconstituent data existed for these creeks in the studyperiod either, and they
were estimated. Afterreviewing data on creeks in nearby sub- basins, it was determined that waterquality parameters were
fairly consistent from one summer to thenext.Also, a report
on the Tualatin RiverBasin by Miner & Scott (1992) showed that most of the inflow during the summermonths came from
groundwater sources and there arerelatively few storms during 35 the summer. Therefore, constituent inflowfiles were created for the three creeks using the 1989U.S.A. data.
OTHER INPUT FILES
As mentioned in Chapter III, themost important file for running CE-QUAL-W2 is the controlfile. This file contains all of the coefficients for themodel simulation,initial
conditions, time step parameters, therunning time, the output control, and maps to other inputfiles. Since determining many of the values forthis file was a process ofcalibration, this file is discussed in thefollowing chapter. Another important input file is theIlinclude filet1. This
file tells the program where the controlfile is and it also
lists important parameters for modelsimulation, such as the
number of tributaries. Other files were also created f ormodel output. One may
see a list of all filesused in the Hagg Lake Model alongwith their description in Appendix C. CHAPTER V
HAGG LAKE CALIBRATION
INTRODUCTION
Theprocess of modelcalibration is the most time consuming and the most important stepin creating a complex hydraulic-water--quality modelof a natural system. The calibration process consists of settingpreliminary values of model parameters, running the model, comparing model predictions with measured data, and iterating onthis process while changing input parameters until areasonable model-data agreement existed. This iterative process wouldcontinue until a "satisfactory"correlation existed between model output and the data (Walesh, 1989).
However, since water quality and somehydrologic data for Hagg lake did not exist, the lake wascalibrated with the
limited data available. The model was calibrated forthe
summer of 1990. Summer runs of the lake were madefrom May 1st to October 31st, since the lake wasto be filled by May
1st. HAGG LAKE INITIAL CONDITIONS
The initial conditions of HaggLake were of utmost
importance to predicting the summer waterquality of the lake 37 because detention times are approximately onthe order of 1 year. During the summer, downstream demands are attheir peak and there is very little inflow to thelake, therefore, at the beginning of the summer when the lakeis full, the initial concentration of water quality parametersmust be specified correctly so that water qualitypredictions of the lake will be accurate. Most of the water quality andhydraulic parameters, as well as initial concentrations, were setthrough trial & error during the calibration process. However, with some of the limited data available, some initial conditions were established. The data from the "Atlas of OregonLakes" provided some profiles of temperature anddissolved oxygen for the beginning of Nay, 1978 (Johnson et.al.,1985). Since summer runs began on May 1st, theprofiles-of dissolved oxygen and temperature were good referencesforinitialsummer conditions. Initial summer profiles for both temperatureand dissolved oxygen were obtained from springmodel runs. For temperature, an initial temperature of 6°C wasassumed and the lake was assumed to be well-mixed on March 1, 1990. The 1990 model was run, and a profile of temperature forMay 1, 1990 was created. An initial summer profile for dissolved oxygen was obtained from the same modelsimulation using a well- mixed-initial-saturated dissolved oxygenconcentration at 6°C
(equal to 12.45 mg/l). These profiles were checked against the profile data from 1978. The profiles were very similar 38 and the ones generated by the model were used for1990 initial conditions. Figures 9 and 10 show simulatedprofiles for
April 1,1990 and May 1, 1990 for temperature anddissolved oxygen, respectively. The initial profiles for May 1st were used for the 1990 initial conditions.
TEMPERATURE PROFILES FOR 320 - HAGG LAKE Spn tng 1990
300 -
280
tJ26O
240-
220
200 - G.-e-o pr I y
l 11111 if 1 B2 I Ill If I 4 6 8 10 12 14 16 TEMPERATURE (C)
Figure 9. Summer initial temperature profile (May 1, 1990) used for Hagg Lake Calibration (simulated). 39
DISSOLVED OXYGENPROFILES FOR 320 - HAGG LAKE Sp ng1990
300 -
280-E
Li260-i
240
LiJ220
opr U 1 200 - -e-e- Mo y IIIllhhhIhhI itlilTi I 1111111 I . III!I IT 18(2) - 8 0 10.0 12.0 14.0 4.0 6.0 DISSOLVED 02 (mgVl )
1990) Summer initialconditions (May 1, Figure io. in Hagg Lake used for dissolvedoxygen profiles (simulated).
Watch" providedSecchi The data from"the Citizen Lake summer of 1990. Two of Disk depths forfive days during the "overcast", the two these days were"sunny", and three were data points "sunny" days werethrown out andthe "overcast" secchi disk depth. Many were averagedto give an average depth to lightextinction empirical relationsof secchi disk SverdruP et al.(1942) and in a water body havebeen made. have developed empirical Beeton (1958) and others depth and thetotal relationships betweenthe secchi disk and Mueller 1987): light extinctioncoefficient as (Thomanfl 40
_l.8 C S and X is the total Where Z is the Secchi Diskdepth (m) m1 was found extinction coefficient(m_1). A result of 0.46 coefficient. using this equation forthe total extinction coefficients CE-QUAL-W2 sums threedifferent extinction light extinction dueto for the totalextinction coefficient: particles, and light water, light extinctiondue to inorganic extinction due toorganic particles. The two particle respective extinction coefficients weremultiplied by their and these organic and inorganicconstituent concentrations coefficient due to water. values were added tothe extinction extinction coefficient Since CE-QUAL-W2determines the total concentrations, the total as a variabledependent on particle above was used as a extinctioncoefficientcalculated calibrated, average reference value. Oncethe temperature was multiplied organic and inorganicparticle concentrations were The results were by their calibratedextinction coefficients. to summed with thecalibrated waterextinction coefficient coefficient value of compare to thereference total extinction
0.46 m1.
CALIBRATION OF HYDRAULICS
inflows and outflows As shown before,data for Hagg Lake Operator on a dailybasis. were recorded bythe Scoggins Dam daily basis of the two Inf low data consistof flow rates on a 41
Some ScogginS andSamCreeks. main tributariesto the lake: Creek inflows,but not during data wereavailable for Tanner flowed at TannerCreek apparently the studyperiod. of Sam Creek during a approximatelyone-third the volume were available. Therefore, period when datafor both creeks multiplied byone-third to estimate Sam Creek inflows were lake Other minortributaries to the Tanner Creekinf lows. In additionto thesedata, wereconsideredinsignificant. on adaily basis,and these staff gaugereadings were taken the daily "changejfl storage" from data wereconverted to a for this lake. This "changeIfl volume versuselevation curve of hour changefrom all processes storage"represents the 24 (i.e., preciPitatiofievaporation, thelaketSwater budget the seepage.). CE-QUALW2 has inflow, andoutflow including and precipitationstorage capability ofcomputing evaporation simulations wereduring the changes, however,since the model precipitation was precipitation occurs, summer, whenlittle predicts theHaggLakemodel turnedoff. Therefore, and outflows wereinput to evaporation only. Daily inf lows
the model. water budgetfor Hagg Lake,a In order tocalibrate the by themodel (i.e., jnf low- graph of theinflows computed computed from the"change lfl evap.) werecompared to those jflf10_p.+pr jp.seepag)(see Figure storage" data (i.e., During used to calibratethe inflows. 11). This graph was predicted inf lows,the inflows periods when themodel over 42 were reduced by theappropriate amount. This reduction is justified by the error involved inusing a point measurement for inflow when comparedto the actualvariation of inflow see that the during a daily period. From the graph, one can two curves fit each otherwell, but the curvecomputed from the "change in storage" datais unsteady, shifting upand down
across the model's curve. These differences couldbe due to
errors in reading thestaff gauge at Hagg Lake orfrom diurnal
storage variations notaccounted f or in the model.
HAOG LAKE CALIATION 100 TOTAL INFLO..IS - MOIFL VS. DATA S1J11ER 1990
80
60
40
C) 20
0
-20 - T0L.I tIo,t.o. ( tfI ...... o.. -40 250 50 1 3 150 2 JUL IAN DAY
Figure 11. Total Hagg Lake inflowscomputed from "change in storage" data versustotal Hagg Lake inflows computed by model forthe summer of 1990.
Outflow data from the lake werenot calibrated since
these data were known.However, calibration wasperformed on Dam the outflow hydraulics of the outlet structure. 43 construction records were analyzedto place theoutflow
structure in the model. The intake to theoutflow structure vertical cells 14, 15, was placed inlongitudinal cell 29 and created to account for the and 16. Three new parameters were amount of outflow from eachof the three verticalcells (fracti-fractiOn of outflow fromcell 14, fract2-fraCtiOflof
outflow from cell 15, andfract3-fraCtiOfl of outflowfrom cell varied via a new input 16) . The three new parameters were file (outlet.npt) which wasread at the beginningof each
model simulation. The following twodiagrams show how the outflow intake structure wasmodeled. Figures 12 and 13 show
the longitudinal celllocation and the vertical cellplacement
of the outflow intakestructure, respectively.
PLAN VIEW HAGG LAKE INTAKE STRUCTURE:
HACG LAKE
Intake Structure CeU 28
Figure 12. Hagg Lake Outf lowIntake Structure - Plan view location. 44
Hagg Lake Ouflet WorksIntake Vertical Cef Struclure Profile (nof toscale) I DiscretiZat ion Cell 14 trashroCO
238.5 ft. %4SL I - . EL 238.0 tI. Cell 15 I iii 233.5 ft. htSL Ii I IrcshrOCkS Cell 16 'p
El. 229.0 ft. I 228.5 ft. ttSL OUTFLOW I Cell 17
Structure - I Figure 13. Hagg LakeOutflow Intake Prof lie View. 1 predicted the In order tosee howwellthe model shows themodeled water I hydraulics of thelake, Figure 14 surface datacompiled surface elevationpredicted versus water I the TualatinValley by the DamOperator andobtained from simulation period. I Irrigation Districtduring the 1990 summer I I I I I 45
HAOG LAKE CALIBRATION MATER SURFACEELEVATION - SUMMER1990 304 -: 300-
296 - 292-- L288 284-
280-: uJ - - ''276 -:
272 -
- - - - I . I t (o. 268 - T.V.ID. O,to
1 1 I I I I I I I I I I 264 J 140I 160 180 200220 240260 280 300 100120 JULIAN DAY
surface elevation Figure 14. Hagg Lake water predicted versus actual forthe summer of 1990.
water surface From Figure 14, themodel predicts the same simulation as the data. elevation for the first 45days of the 13), From Julian day 165(June 16) to Julianday 225 (August approximatelY five the model over predictsthe water level by simulation, the inches.From Julian day 225 tothe end of the at an almost model begins to divergefrom the actual curve where it over- constant rate, until theend of the simulation, foot predicts the water surfaceelevation by approximately one begins to four inches. At the same timethat the model demand diverge from the actual curvearound Julian day 225, and drawdown of the from the reservoirbegins to peak, 46
If the bathymetrY reservoir begins to becomesignificant. FOOlthan wasactually usedin the model has alarger this differenceiflvolume available duringthis period, then discrepancy. This theory versus elevationcould cause this used to establishthe has merit sincethe topographic map construction of the bathymetry of the lake wasmade during the In the twenty yearssince reservoir in approximately1970. lake bottomcould causethis then, sedimentation in the Since the discrepancy difference in volumeversus elevation. Also, this error was minor,the bathymetry wasnot changed. through the dam andother could be fromneglecting seepage minor sources andsinks of water.
AND TEMPERATURE CALIBR1TION OF WATERQUALITY CONSTITUENTS
water-qualitY For this study,17 of thepossible 22 BOD-R, Detritus, parameters (ChloroPhYlla,TDS, TSS, BOD-L, Carbon, Alkalinity, CO2, PO4-P, NH3-N, NO3-N, 02, pH, and temperature were Bicarbonate, Carbonate,and Zooplanktofl)
calibrated. obtained from Summertime water qualitydata records were ScogginS Creek, forall years U.S.A. for theoutlet channel, Since these data werethe only in thestudy period. were both inthe historical records ofwater quality that these data wereused to study period andsomewhat complete, For a givenmodel calibrate the waterquality of the model. point of outflow were simulation, modeloutput data at the 47 compared to U.S.A. data on Scoggins Creek. It was assumed thatlittle change occurredbetweentheoutflow intake structure and the point of sampling downstream(approximately
1300 feet). This meant that for any given constituentbeing analyzed, a proportion (fractl, fract2,and fract3)of its concentration from vertical cells14, 15, and16 within longitudinal cell 29 were summed and comparedto available
U.S.A. data downstream. The CE-QUAL-W2 model places model outputresults in a large snapshot file(snp.opt) which makes thecalibration process tedious. Some minor additions to the sourcecode were made which placed model predictions of waterquality from the outlet intake cells in a format that couldbe analyzed more easily. In order to plot these data readily foreach of the Hagg
Lake model simulations, a series of FORTRANsorting programs were run in a batch file thatplaced results in a form compatible with the software program GRAPHERwhich in turn plotted the results. The following six figures (figures 15, 16, 17, 18, 19, and 20) contain thegraphs of water quality constituents used for calibration of each modelsimulation.
These graphs were from the final calibration run. As one can
see, of the 17 water quality constituents (including temperature), only seven constituents (PO4-P,temperature,
NH3-N,NO3-N, pH, TDS,and TSS)had data for calibration
comparisons. 48
CkIAT1C WC.G L.AE CU8PAT104 cQ EO1ENT 2caLS 14-16) Ct-A SENT 29(cELLS 14-16) 10,0- 20.0- it*Iat%H
9.0
0 8.0
10.8 7.0
0 5.8 6.0 .tt.U.'
0.0 i",.''"I 50 100 150 280 250 JuIn DAY iuim DAY
I4AGO LAKE 0JTFLC1 W3 LME CALIATICt1 1990 CAL1ATIC 29 (CELLS 14-16) PO4 ECNT 29(CELLS 14-16) 16.0
14.4
12.8
U.fl. 4,L
9.6
8.0
6.4
4,8 U.S.A.IliLt*t4 1'i 3.21 1111111 lilt... II till! 111111 111111 lIlt 1111111111 50 100 lEO 280 250 100 150 200 250 JUIM4 DAY
calibration resultsfor FigUre 15. Hagg Lake for the ChlorophYlla, PO4-P, 02,and Temperature summer of 1990. I I 49
HAGG LAKE CALIATICt I3 LAKE CALI3AT1Ct'1 133 SEC(NT 2CELLS 14-16) I 0.060- 1*43 sEaENT 29(ILLS 14-16) I e.0 0.25 I 0.20
I 9 0.0 0.10 1
0.010 U.S.A. 4.t. 5.83. 4.t. _OI ,I.U.. ..d.I I.It
I 0.00 Ir,nh11lhhhhhhhhlhuhuhhu1hhhhhuhhhhuhhhhh 100 ISO 200 I 3ee 50 o 10 200 JUJAH DAY JtLJ4 DAY
F1AGG LAKE CAL1ATICt4 1W3 LAKE CALI9T1ON ZPL.ANKTC*4 SEatNT 29(CELLS 14-16) ft EQNT 29( CELLS 14-16) 0.40 tTR1Tt
I I
I 0.10
11 0. 0.00 50 100 150 200 250 300 R.LIfrN DAY JU.JM1 DAY $
Figure 16. Hagg Lake calibrationresults of NH3-N, I Detritus, NO3-N, and ZooplanktOflfor the summer of 1990. I I I I, 50 V
RA3G LAKE CALIATICt HAC3 LAKE CALI8ATICt1 fjT 29 .cais 14-16) DCGANIC CA(4 SEGENT 29 (CELLS 14-16) ALKALINITY I 6.80 26.0
I 6.70 25.6 I -, 6,60 I t 6.40 2, 4 6.30 ..dI...I*tIi I 4.I SIM,ttI. 24.0 6.201 ... .. ,u.. 1 ''''' I 100 150 200 280 300 so 100 150 250 3 SO JIJ..IAN DAY JUJN4 DAY
NA3 LAKE CALIATI 14*03 LAZE CAJ_1AT1I 0)2 SNT 29 (CELLS 14-16) I pH SECENT 29 (CELLS 14-16) 1.00 1
I a .sd.I .1I.IW .I U..A. 4St4 -
0.00ll!flhtll('llI'''''IT'''''''' 160 200 $ tea iso 200 250 a 60 100 JUJM DAY JIJJAJ1 DAYS I Figure 17. Hagg Lake calibrationresultsfor Inorganic Carbon, Alkalinity, pH,and CO2 for the summer of 1990. I I 51
HO3 LAKE CALIBRATION HAGG LAKE CALIBRATION 1DS S83104T 29(CEt.LS 14-16) TSS SEGOlT 2cELLS 14-16) 120 6.0
100 5,8
80 4.8
-'60 0) 0) a 0) 0-
40 2.8
i.e _d,( U.S.A. d0). U,$.A. a. - ..dsI tIit
l,l,,,lIIjIIIIF8IlI1llIlJIj11i1hhhhhjhhhhuhhI 01 0.8 203 250 303 So 110 2 50 180 150 JLUA#DAY JLIIAN DAY
F*O3 L.A1E CALIBRATION 1.60 B0 SEGENT 2CELLS 14-16)
1.50
1.40
-.1 .3o
1.10
1.00
0.90 - s,41
0.801 50 100 ISO 200 250 303 uim DAY
Figure 18. Hagg Lake calibration results for TDS, TSS, and BOD for the summer of 1990. I I 52
RGG LAKE CALIATICt HNG LAKE CALIATI4 CARB4ATE SEGNT 29 (cal S I 4-16) I 8ICA&kTt SEGENT 29 (cLS 14-16) 0.025
,t.l,tll 1 0.020
I 0.0l5 I I-. e.010
0.005 I ..4sI II.1I4U 0,000 S 100 XIIAN DAYS JlJ1AN DAYS
I ILES FC FILES Fc DI$SOEO OXYGEN TEtFRATUE HACi3 LAKE Sw'ER 1990 I 111103 LAKE SlJtR 1990 I I I I
180I * 2 4 6 8 10 12 14 DISS1D 02 (m9/I) I T8fERAT (0 for Figure 19. Hagg Lakecalibration results Bicarbonate, Carbonate, andprofiles of Temperature and 02, for the summer of1990. 53
Ot-A PRcFILES F PO4 PRCFILES F HA LACE SUtER 19% 320 HAGG LACE SIJtER 1990
280
I- - 260
240
200
180 11111j11114(IllfflhI$ 111111 180 utiiiii&iiiii.ii jul11. IlIjI llIlIIljlhllIIlIlIlIlI 411111 0 40 80 120 160 0. 0.002 0.004 0.006 0. 0.010 0,012 OiX{flJ-A (U3it) PO4-P (ii) tC3 PRCILES FC MC PRCFII..ES FC HAGG LAKE SIftER 1990 t4AOG LAKE SItER 1990
280
I- 260
240
1801 1801 0. 0.01 0.02 0.03 0.04 8. 0.06 0.07 0.800. 0.100.160.200.26 0. t+t3-N (,i) 3 (rg/l)
Figure 20. Hagg Lake calibration profiles of Chlorophyll-a, PO4-P, NH3-N, and NO3-N for the suimner of 1990. 54
Since only 7 of the 17 constituents modeledincluding temperature had field data available forcalibration, precise calibration was difficult. The calibration process went as follows. First temperature was calibrated with thewater quality constituents turned off. Next, all water quality constituents shown above besides inorganic carbon,alkalinity, CC2, bicarbonate, carbonate, and pH, wereturned on and TSS was calibrated. TSS and BOD were treated differentlyin the modeling process than other constituents. CE-QUAL-W2 simulates inorganic suspended solids (ISS),but not total suspended solids (TSS), therefore, detritus, algae, zooplankton, a fraction of BOD-L (25%), and afraction of BOD-
R (75%) were summed with ISS to determine thetotal suspended solids concentration. As forBOD, CE-QUAL-W2 simulates labile-BOD (BOD-L) and refractory-BOD (BOD-R), but nottotal
BOD, therefore, a fraction (50%) of detritus andof algae were summedwith BOD-L and BOD-R toachieve a total BOD concentration. Calibration of total dissolved solids (TDS) followed, however, the model treats TDS as aconservative parameter, therefore, an initial condition of 63mg/i was set for TDS from analysis of the TDS field data. PO4-P, NH3-N, and NO3-N, were calibrated next. These three parameters are highly dependent on algae populations, which are dependent on most other parameters being modeled. Algal limiting factors were shown in the "snapshot" outputfile produced by CE-QUAL-
W2. Algal populations were limited by ortho-phosphorus 55 rather than nitrogen £ or nearlythe entire simulationperiod.
This was due to the very lowortho-phosphoruS concentrations used in the lake fromanalysis of U.S.A.field data. A chlorophyll-a to algae ratio of 50jig/i chlorophyll-a to 1 mg/i algae was used. The fact that the CE-QUAL-W2model was only able to model one algalpopulation with one chlorophyll-a production rate for the dynamic summerseason limited the carbon, waterquality calibration. Finally, inorganic alkalinity, co2, bicarbonate, carbonate,and pH were added to the model. Data on Scoggins Creekexisted for pH, and these six parameters were calibratedusing these data. This consistedprimarily of establishing appropriate initial conditions for these parameters. The following method was used to establish initialconditions for these six parameters:
Alkalinity and bicarbonate used U.S.A.data averages for years
1978-1985; CO2 and carbonate wereproportioned from average bicarbonate concentrations (Wetzel,1975); and the initial inorganic carbon was determinedusing the initial pH and alkalinity from a chart in principles of Surface Water
Quality Modeling and Control" (Thomannand Mueller, 1987).
The following table lists allmodel coefficients, their
description and values used forcalibration of the CE-QUAL-W2
model for Hagg Lake. I
56
TABLE I I HAGG LAKE CALIBRATEDCOEFFICIENT VALUES
COEFFICIENT HAGG DEFINITION: I (Variable in LAKE Source/Sink MODEL Term in VALUE: I Appendix A): ITEMP -1 Initial water temperature (-1 = initial profile in VPRfile) I (C). WSC 0.95 Wind sheltering coef. (1.0 = maximum wind, 0.0 = no wind) I for AX 10.0 Horizontal dispersion coef. momentum (m2/sec)
I IDX so.o Horizontal dispersion coef. for heat and mass(m2/sec)
AZMIN l.4e-6 Minimum Horizontal Dispersion I coef. for momentum(m2/sec) coef. DZMIN 1.4e-6 Minimum vertical diffusion I for heat and mass(m2/sec) coef. DZMAX i.o Maximum vertical diffusion for heat and mass(m2/sec). I water EXH2O 0.40 Light extinction coef. for (if1). EXINOR 0.05 Light extinction coef. for inorganic particles (rn/mg/i).
EXORG 0.05 Light extinction coef. for organic particles (rn/mg/i).
BETA 0.40 Fraction of solar radiation absorbed at surface (-).
COLQ1O 1.04 Ql0 modification forcoliform die off rate. I (d1). COLDK (Kr) 1.4 Coliform decay rate SSETL (w3) 0.05 Suspended solids settling rate 1 (rn/day).
AGROW (Kg) 4.0 Maximum gross photosynthetic I production rate(d). I $ I
57 TABLE I
HAGG LAKE CALIBRATED COEFFICIENT VALUES I (continued)
COEFFICIENT HAGG DEFINITION: I (Variable in LAKE Source/Sink MODEL Term in VALUE: I Appendix A): I AMORT (1cm) 0.02 Maximum algal mortality rate (d AEXCR (Ke) 0.04 Maximum excretion rate or photorespiration rate (d1).
I ARESP (Krs) 0.05 Maximum algal dark respiration rate (d'). I ASETL(3) 0.07 Phytoplankton settling rate (m/d). ASATUR 20.0 Saturation light intensity at I the maximum photosynthetic rate (W/1n2). ALGDET 0.80 Fraction of dead algae which I becomes detritus, the fraction (l-ALGDET) becomes BOD-L (-). I AGT1 0.0 Lower temperature bound for algal growth (C). AGT2 9.0 Lowest temperature at which I growth processes are near the maximum rate (C) AGT3 18.0 Upper temperature at which I growth processes are near the maximum rate (C) I AGT4 30.0 Upper lethal temperature (C). AGK1 0.1 Temperature rate multiplier for I AGT1. AGK2 0.98 Temperature rate multiplier for AGT2. 1 AGK3 0.98 Temperature rate multiplier f or AGT3. AGK4 0.1 Temperature rate multiplier for p AGT4. I 1 58 TABLE I
HAGG LAKE CALIBRATEDCOEFFICIENT VALUES (continued)
COEFFICIENT HAGG DEFINITION: (Variable in LAKE source/Sink MODEL Term in VALUE: Appendix A): Liable DOM decay rate(d1). LABDK (Kd) 0.05 Transfer rate fromliable to LRFDK (Kt) 0.001 refractory DON(d1). Refractory DOM decayrate (d'). REFDK (Kr) 0.001 Detritus decay rate(d'). DETDK (Kdt) 0.02 velocity DSETL (w2) 0.50 Detrital settling (m/d). bound f or ONT 1 4.0 Lower temperature organic decomposition(C).
25.0 Temperature whereorganic OMT2 decomposition is nearmaximum (C). multiplier for OMK1 0.1 Temperature rate OMT1. multiplier for OMK2 0.98 Temperature rate OMT2. rate (d 0.06 Sediment decomposition SEDDK(K9) 1) sediment oxygen SOD (X1) 0.30 Maximum rate of demand (g/m2/daY). (d1). KBOD not Decay rate for CBOD used CBOD decay TBOD not Temperature coef. for used rate correction. consumptiOn of RBOD not Decay rate for 02 used CBOD (d1). of SOD which PO4 PO4REL (X2) 0.015 Rate as fraction is released fromsediments during anaerobicconditions (g/m2/day). I 59 I TABLE I HAGG LAKE CALIBRATEDCOEFFICIENT VALUES I (continued)
COEFFICIENT HAGG DEFINITION: I (Variable in LAXE Source/Sink MODEL Term in VALUE: I Appendix A): PARTP (A2) 0.005 Maximum amount of PO4 absorbed per gram of solids (g Pm3/g I solidin3). AHSP (A1) 0.002 Adsorption coef. of PO4 for use I in the Langmuir isotherm(m3/g). NH3REL (X3) 0.08 Rate as fraction of SOD which NH4 is released from sediments during anaerobic conditions I (g/m2/day).
NH3DK (Ka) 0.07 Ammonia decay rate (di). I PARTN (A4) 0.005 Maximum amount of NH3 absorbed per gram of solids (g Nm3/g I solid in3). AHSN (A3) 0.007 Adsorption coef. of N for use in the Langmuir isotherm(m3/g). NH3DT1 2.0 Lower temp. bound at which ammonia nitrification continues I (C). NH3DT2 32.0 Lowest temp. at which nitrification is occurring near I the maximum rate (C). NH3K1 0.1 Temperature rate multiplier for NH3DT1. I NH3K2 0.98 Temperature rate multiplier for NH3DT2. NO3DK (l() 0.20 Denitrification rate of the I nitrite plus nitrate-nitrogen I compartment - anaerobic only (d NO3DT1 2.0 Lower temp. bound at which I denitrification continues (C). I I I 60 TABLE I
HAGG LAKE CALIBRATEDCOEFFICIENT VALUES I (continued)
COEFFICIENT HAGG DEFINITION: I (Variable Ifl LAKE source/Sink MODEL Term in VALUE: I Appendix A): NO3DT2 20.0 Lowest temp. at which denitrifiCatiofl occurs near 1 maximum rate (C) multiplier for NO3K1 o.i Temperature rate NO3DT1. I multiplier for NO3K2 0.98 Temperature rate NO3DT2.
I CO2REL o.io Fraction relating SOD to inorganic carbon production (-). SOD which FEREL (X4) 0.50 Rate as a fraction of I Fe is released fromsediments (g/m2/day). Fe FESETL 2.0 Rate at which particulate I (4) settles (m/day). Maximum ingestion rate for ZMAX (Kmax) 0.5 I zooplanktOfl(hr'). ZooplanktOfl mortality rate(hr I ZMORT(Kzm) 0.001 efficiency ZEFFIC(Ze) 0.50 ZooplanktOfl ingestion (-) I Preference factor ofzooplanktOfl PREF1 (P3) 0.50 for algae (-). zooplankton I PREF2 (P3) 0.50 Preference factor of f or detritus (-). Zooplanktofl respiration rate(hr ZRESP(Kzr) 0.14
concentration for ZOOMIN (Z1) 0.01 Low threshold zooplanktofl feeding(g/m3).
ZS2P (Z112) 0.30 Half-saturation coef. for zooplanktOn ingestion(g/m3). I I I I 61 TABLE I I HAGG LAKE CALIBRATED COEFFICIENTVALUES (cant inued)
COEFFICIENT HAGG DEFINITION: I (Variable Ifl LAKE Source/Sink MODEL Term in VALUE: I Appendix A): ZOOT1 0.0 Lower temperature boundfar I zooplankton growth (C). ZOOT2 20.0 Lowest temperature at which growth processes are near I maximum (C) ZOOT3 26.0 Upper temperature atwhich growth processes are near I maximum (C) for ZOOT4 36.0 Upper lethal temperature I zooplankton (C). ZOOK1 o.i Temperature rate multiplier for ZOOT1.
I ZOOK2 0.98 Temperature rate multiplier f or ZOOT2. I ZOOK3 0.98 Temperature rate multiplier for ZOOT3.
ZOOK4 o.i Temperature rate multiplier for I ZOOT4. 02NH3 (5) 4.57 Number of grams 02 reqd. to I oxidize 1 g of NH4 to NO3. O2ORG (&om) 1.4 Stoichiometric requirement f or 02 to decompose organics (-). I O2RESP (&) 0.6 02 requirement forbiological respiration (-). I O2ALG (6f) 1.4 StoichiometriC equivalent for 02 production during photosynthesis (-) I BIOP (&) 0.005 Stoichiometric equivalent between organic matter and I orthophosphate (-). I I I 62 I TABLE I HAGG LAIKE CALIBRATED COEFFICIENT VALUES I (continued) COEFFICIENT HAGG DEFINITION: (Variable in LAKE I Source/Sink MODEL Term in VALUE: I Appendix A): BION (8) 0.08 Stoichiometric equivalent between organic matter and I nitrogen (-). BlOC (6j 0.45 Stoichiometric equivalent between organic matter and I carbon (-). O2LIM 0.50 Dissolved02concentration which triggers anaerobic conditions I (mg/i) FRACT1 0.3333 Fraction of outflow and proportion of constituent from I vertical cell 14 (-). FRACT2 0.4034 Fraction of outflow and I proportion of constituent from vertical cell 15 (-). FPACT3 0.2633 Fraction of outflow and I proportion of constituent from I vertical cell 16 (-). I HAGG LAKE CALIBRATION CONCLUSIONS I In order to calibrate a model as complex as CE-QUAL-W2, one would like to have as much historical water quality data I on the water body being studied as possible. However, for most water bodies, including Hagg Lake, little water quality I data exist.The calibration results show that the exact water I quality dynamics were not captured, but the major processes I were. Of the seven parameters with U.S.A. field data, model I 63
dlffjCult to simulations of ortho-phOSPh0rU5were the most However, U.S.A. correlate with U.S.A.ortho-phosphorus data. (1991) were ortho-phoSPhorUS data forthe verification year calibration year(1990). much different thanthe data for the calibration year and the Good correlationsexisted between the with U.S.A. verification year for theother six parameters uncertainty in the field data. Hence, there maybe further
field data forortho-phOSphOrUs. inflow during Since Hagg Lake is areservoir with little season forthis the summer months,calibration of a summer If more time lake was highlydependent on initialconditions. available, a long term run were availableand more data were order to establishthe (i.e., 2 years) wouldbe desirable in this, more initial conditions forthis lake. In addition to further capture the parameters could beadded to the model to the algal compartment dynamics of this lake. For instance, population to grow could be changed toallow for more than one the year. in the reservoir atdifferent times during CHAPTER VI
HAGG LAKE VERIFICATION
INTRODUCTION
the Verification refers to the process of taking calibrated model,and without changing anyof the model coefficients, running the model for adifferent time period and comparing model predictionsto field data. If results of this verification period arein similar agreement withmodel output, the model is said to be"verified". The verification process is performedto further prove thereliability of the model to produce outputwhich is a reflection of the processes of the actual water body. The Hagg Lake model was run forthe verification period
of 1991. Once again the model was runfrom May 1st through October 31st. The only changes that weremade for the verification run were changes ininitial conditions. Before water the verification run could be started, initial temperature and dissolved oxygenprofiles were estimated. As
outlined before, these profiles wereestimated by setting the initial temperature equal to 6°Cand the initial D.O.to (Thomann & saturation at 6°C , equal to 12.45 mg/i D.O. Mueller, 1987) throughout thelake on March 1st. The model
was run from March 1stto May 1st of 1991. The other changes 65 to initial concentrations were made by reviewing the 1991
U.S.A. data on Scoggins Creek.Water quality contituents with
U.S.A. data on Scoggins Creek were ortho-phosphorous, temperature, ammonia-N, nitrate-N, TDS, TSS, and pH.
VERIFICATION OF HYDRAULICS
The model hydraulics were again verified first.
HAGO LAKE VERIFICATION 1-JATER SURFACE ELEVATION - SUMMER 1991 304 -:
300 -
296 -
292 -: - 288 - 284-
280 -:
276- - 272 -: 268 -Ln.Ittn 264 T.V10. 1991
I I 1 I I I I I I I I I I I I I I I 2,0- 4 4 4 4 4 100120140 160 180 200 220240 260 280 300 TULIAN DAY
Figure 21. Water Surface Elevation simulation versus actual for verification year 1991.
Figure 19 shows that the water surface elevation during the verification period performed well.The model simulation run diverged from the actual water surface elevation at an 66
the approximatelycontinuous rate, and at the end of This simulation was about 2 feethigher than actual. divergence occurred also during thecalibration run and was
thought to be caused by inconsistentbathymetrieS between the model and the lake.
VERIFICATION OF WATER QUALITY
The following three figures (22, 23, and 24)contain
graphs of water quality constituents fromthe verification run versus the 1991 U.S.A. data onScoggins Creek. As one can (PO4-P, see, only seven water quality constituents temperature, NH3-N, NO3-N, TDS, TSS,and pH) had U.S.A. field
data available for verification. 67
Gt-A SEQt04T 2cLS 14-16) 02 ENT 2CELLS 14-16) SUtER 1991 11.5- SIJtER 1991
-Iwl ..4,I aJ,Ia(*..
810.5
U
10.0
a
9.5 5.0 -I 44I sj,ft(aa
I I 9.0 150 2 0 3 50 180 ISO 280 31LLN tY JLI4 Y FW3 LArE ER1FICATIC PO4 SEO'ENT 2(ELS 14-16) HAOO LAKE WTftC4 TEFRATU 1991 YERIFICATI0 S3lJ4T 29 (CB±S 14-16) 0,020 itER 1991 17.6
aI.aIaUia 16.0 l,, U,S.& a..
0.015
U '12.8
a 11.2
8.0
6,4 -.Pd.I I.a,Itsa a.... t9I U.s.A. 4IA e.aoe 4.81 .....i 68 100 160 200 250 380 0 50 100 ISO 280 260 300 0 JUJM DAY JUJMDA1
Figure 22. Verification of Chlorophyll-a, 02,PO4- P, and Temperature, summer 1991. I 'I 68
t+i3 SENT 29(CELLS 14-16) PiD3 EGEN1 2CaLS 14-16) I SIJtER 1991 0.36 SitER 1991 I 0,30 I 0.3 I
I 0,10
0. ,(.,I,U,. -,I I 11 U.$.*. 4.J.4 11 U,$.* 4..
50 100 150 200 3030 360 60 100 150 200 250 300 360 JUJN4 DAY JILIM4 DAY I IW3 LAKE VEPIFiCATICA HAIG L.AtE IFICATIO C1RI1t SEQ9ff29(caLS 14-16) oL*iTc SET 29(CftLS 14-16) I itR 1991 SIttER 1991 I 0.011 I
F'2° I e.15 I 0,10 0.007 - 199 ,..i.tw. 4I .II.tW.
II,, (liii if ilium1111111 millIulil I (iliflI 111111 jmm.ruiium4 I I 100 150 200 30 300 60 100 150 200 250 30 I JtLIN4 DAY JIL!M4 DAY Figure 23. Verificationof NH3-N, NO3-N, Detritus, I and Zooplankton, for summer of 1991. I I 69
18$ SE0ENT 2CaLS 14-16) 10$ SEGtENT 2CELLS 14-16) SIttER 1991 SIttER 1991 120 8.0-
100 6.0:
\ OI ,tI,U.. 9l U.S.A. 4.a
2.0
40 ..4,I .I..l.4. ,,1 U.S.A. d.ti
0.0,niinii.1ncnlhnr hii 20 n.." I pn..n..jnn.". 80 100 156 280 300 0 so igo ISO 290250300 0 JILIAN OM' JLIIMI D F.'O3 L&E VERIFICAT1t1 HACA3 LACE VER1F1CATICt pH SEOENT 29 (CELLS 14-16) R SEGt841 2cELLS 14-16) SIFtER 1991 1.50 SIttER 1991 8.00
1.40 7.80
1.30 7.69
1.20 7,40
I 16
7.20 1.90
7.00 0.90 .4I.Uo' IWI U.S.A. 41.a -t1 0.4.1 a*.a141..
I I"'",'' I 0.90 I 159 250 so iea ISO 290 20 0 50 100 lILIAN DAY 1111N4 DAY
Fiqure 24. Verification of TDS, TSS, BOD-U, and pH for summer of 1991. 70
From Figures 22 through 24,the verification run was similar to the resultsobtained for the calibration run.
U.S.A. data on Scoggins Creekfor 1991 was verysimilar to the which had 1990 data for most parameters. The only parameters significant differences were po4-P,temperature,and TSS. the entire Algal growthwas PO4-P limited for nearly verification period due to lowPO4-P concentrationsin the from 1990 to 1991 were lake. Differences in ortho-phoSphoruS discussed earlier, and thesedifferences may be relatedto
measurement error. Since thereported ortho-phosPhoruSlevels PO4-P were so low in 1990, exact measurements of concentrations at that low of levelwould be very difficult.
The temperature of outflowin 1991 was higher in 1991than in verification run show that 1990. Results of the temperature the dynamics of the temperature curvewere captured, but the
peak value was not (off byapproximately 1 °C). The TSS data
for 1991 were morescattered than in 1990, andverification results showed that the modeldid not capture thedynamics of
TSS in 1991. However, model predictionsof TSS are not as accurate as they could be, and asshown in Chapter VIII steps were taken to refinecalculations of inorganicsuspended constituents were very solids.Verification results of other good, and reflected thecalibration results. 71
VERIFICATION CONCLUSIONS
Output for three of the seven (temperature, NO3,and TDS) water quality parameters with U.S.A. data onScoggins Creek showed good agreement between the model andthe data. This was especiallytruefortemperature. Themodelagain predicted a well defined epilimnion, thermocline, and hypolimnion. The model also showed reasonableagreement with the data for hydraulics. Much of the dynamics of water quality in Henry Hagg Lake would be betterunderstood if dynamic data were available within this lake. With the limited data set, firm conclusions about thevalidity of the entire model would require further field data. CHAPTER VII
ADDITIONAL FLOW ALTERNATIVE
INTRODUCTION
Once a model has been calibrated and verified with data, the model can be used as a management tool to predict the outcome of man made or natural changes to a water body.This chapter reviews the first management alternative the Hagg Lake model was subject to.
As the FWPCA predicted back in 1967, the water quality of the Tualatin River today is considered poor.The river is not meeting state standards for water quality, and the Oregon
State Department of Environmental Quality is looking at ways toimprove the quality of this river. One management alternative proposed, is to further increase the flow in the summer. The source of this extra water is undetermined, but may entail increasing the outflow of Hagg Lake during lowflow conditions. The Hagg Lake model was run for the summer of the calibration year, 1990, with an additional 100 cfs outflow from June 15th through September 15th (the "dry season't). I I 73 I LAKE WATER QUALITY VIOLATION ANALYSIS A water quality analysis was performed f or threekey I parameters: dissolved oxygen (D.O.), pH, and algae concentrations (measured as chlorophyll-a concentration) I Water quality criteria or goals for these parameters were I itemized in Table II. Hence, a surface water body would be in violation of a Oregon State Water Quality Goal if it failed to I meet one of the criteria shown in Table II at anypoint in I time or space. TABLE II 1 WATER QUALITY GOALS FOR DISSOLVED OXYGEN, pH, AND CHLOROPHYLL-a IN HAGG LAKE
I PARAMETER WATER QUALITY GOAL Dissolved Oxygen > 6.0 mq/l I Chlorophyll-a < 15 jig/l I pH <8.5 To determine how Hagg Lake was performing with respect to
I the water quality criteria, a subroutine was placed in the CE- I QUAL-W2 code that flagged cells that were not in compliance with these criteria. During the modelsimulation, the I subroutine scanned all cells in Hagg Lake every 30 seconds and recorded the number of and concentrations of any cells not
I meeting any of these criteria. At the end of the simulation, I the number of cells within a specified range ofttviolationfl were summed. These statistics were placed in a bar graph to I I 74 show the magnitude and range of violation forthe lake. Equation 12 shows how the model calculated a violationfor each water quality goal.
NIT NCELLS1 I N] it (12) 1=1E En=1 NCELLS1 T
Where: NIT = # of time steps I = time step number NCELLS1 = number of model cells at timestep 1 n cell number N. = number of violations atinterval j model time step (30 sec) T = simulation time period j = range of violation forhistograms
An "average violation" was computedor each of the three
parameters. This "average violation" was computed at the end
of a simulation and was the result of multiplying the magnitude of a given violation by the time step duringthis violation, summing all of these factors (violation timestime
step) for the entire simulation, and dividing this numberby
the total simulation time. This calculation yielded an average number of cells that would bein a particular
violation range at any given time.The number of active cells
was also calculated every 30 seconds, and the numberof cells
in violation for any given parameter was divided by the active
cells to determine a percentage of active cells in violation.
Thus, these "violations" represent the average percentage of 75 active cells in violation in the lake at anypoint during the simulation period. The following six figures show histogramswhich compare violations for the three critical parametersmentioned above for thebasecase andthe additionalflow alternative. Figures 25 and 26 contain histograms of thedissolved oxygen violations for the base case and the additional flow alternative, respectively. Figures 27 and 28 contain histograms of the pH violations and Figures 29and 30 contain histograms of the chlorophyll-a violations. Since these six plots do not show how water quality wouldchange for all aspects of the lake, including how downstreamwater quality would be impacted, graphs of outflow waterquality were also made. Figures 31 and 32 contain plots of temperature, water surface elevation, pH, chlorophyll-aconcentration, dissolved oxygen concentration, ortho-phosphorusconcentration, nitrate- N concentration, and ammonia-Nconcentrations coming out the outletduring the base case and the additional flow alternative. 76
BASE CASE - DISS. OXYGEN Hagg lake Simulation 12
cn
6 C
0
. 0 -2-1.2 -0.4 0.4 1.2 2 2.8 3.6 4.45.2 -1.6 -0.8 0 0.8 1.6 2.43.2 4 4.8 5.6 DO. (mg/i)
Figure 25. Base Case for Hagg Lake Dissolved Oxygen violations summer of 1990 (Averageviolation = 5.35 mg/i).
+100 CFS - DISS. OXYGEN Hagg Lake Simulation
-2-1.2 -0.40.4 1.2 2 2.8 3.6 4.45.2 -1.6 -0.8 0 0.8 1.6 2.4 3.2 4 4.8 5.6 D.O. (mg/i)
Figure 26. DissolvedOxygenViolations with additional 100 cfs outflow from 6/15 through 9/15 1990 (Average violation = 5.12 mg/i). 77
BASE CASE - pH Hagg Lake Simulat ion
2
* 8.5 8.9 9.3 9.7 10.110.5 10.911.31 1.71 2.1 8.7 9.1 9.5 9.910.310.71 1.1 11.5 11.912.3 p'-1
Figure 27. Base Case for Hagg Lake pH violations, for the summer of 1990 (Average violation = 8.65).
+100 CFS - pH Hagg lake Simulation
4.5
3.5
022.5 1.5 C) 1 1
. 0 8.58.99.3 9.710.1 10.5 10.9 11.3 11.7 12.1 8.7 9.1 9.5 9.910.310.7 11.111.5 11.9 12.3 pH
Figure 28. pH violations base case with 100 cfs additional flow from 6/15 through 9/15 1990 (Average violation = 8.65). 78
BASE CASE - CHLOROPHYLL-A Hagg Lake Simulation
15 35 55 75 95 115135155175195 25 45 65 85 105125145165185 205 CHIOPOP}IYLLA (ug/l)
Figure 29. Base Case for Hagg LakeChlorophyll-A violations, for the summer of 1990 (Average violation 40.15 ig/l).
+100 CFS - CHLOROPHYLL-2A Hagg Lake Simulation 25
20
15
010
15 35 55 75 95 115135155175195 25 45 65 85 105125145165 185 205 CRIOR0PHY1LA (ug/1)
Figure 30.Chlorophyll-A violations base casewith 100 cfs additional flow from6/15 through 9/15 1990 (Average violation = 40.65tg/l). 79
As one can see fromFigures 25 through30, there was the additional little difference betweenthe base case and The followingthree flow alternative forviolation goals. paragraphs summarize thereasoning for theslight differences the additional flow that occurred betweenthe base case and alternative violations. quality with The base case hadslightly better water level respect to D.O. One may expectthis since the pool greater algal would be lowered causinghigher temperatures and concentrations forthe growth, resulting in lower D.O. dissolved oxygen in the additional flow case. In both cases, growth, but overall lake is somewhatstratified due to algal
D.O. concentrations areadequate for fish survival. were quite As for pH, the resultsof the two simulations had slightly betterwater similar. The additional flow case result of quality with respect to pH.This was most likely a in the increased flow, thus, greatermixing in lower layers pH of Hagg Lake was additional flow case. In both cases, the
somewhat higher than neutral,but overall verygood. Chlorophyll-a concentrations werevery similar forboth higher for the additional cases.The number of violations was smaller pool flow case, but not bymuch. One would expect the the base for the additional flow caseto heat up more than the base case. case and thus havegreater algal blooms than
However, the actualsurface area of thetop layers decreases this surface area as the pool lowers. It is believed that 80 for the reduction offsets thewarmer-loWerP00l conditiOn additional flow case. Thus, the two caseshave similar algal populations. the This exercise in comparingstandard violations for entire lake did not show thedifferences in outflowwater quality, which would be of concernfor the TualatinRiver. outflow Theref ore, Figures 31 and32 were added to compare water quality for the base casewith that from theadditional flow alternative. I I 81
O3 LAKE +100 CFS ALT4ATIVE 1 HAGG LAKE ()JTFL0 TBFERATLPE (4ATER ACE ELEVATtCfr' - SUtER 1990 p100 es ALTER4ATIVE VS. BASE CASE 1990 304 19.2 300 I 296 16.0 292
288 I °12,8 .284 - 280 I < 9.6 276 272
268 p '6.4 Ui264 260
3.2 266 4d *tt+ - ,1 .s 645-A61q98 I : 1% 262 III[lIIjI{II111l11 lillIllIll lfI.l(l11I11hlt,,, II JI(llll,I(IlhtIituht 0.8 100 128140 1601 :200220240260280 150 3 250 50 100 JIIIAN DAY JUIA DAY O3 LAKE +100 cl's AT4ATIE $AO LAKE +100 cFs L14ATIVE 0J1FL0.1 01.-A BASE CASE VS. .100 CFS I OJTFLCL4 pH BASE CASE VS. .100 CFS
26.0
J I -il6.0
I 10.0
I 6.0 e o. UU.ATtGl
0.01 I 20 'sVoo'so' lILIAN DAY I uJmDAY Water Figure 31. Hagg LakeOutflow Temperature, Surface Elevation, pH, and Chlorophyll-a I concentration base case1990 versus base case+100 /15 1990. I cfs from 6/15 through 9 I I I 82 As shown in Figure 31, the outflowtemperature increased as expected for the additionalflow case. Also, with the
decrease in volume, the lag time for temperaturetransfer from
the air to the lake was reduced and thepeak temperature was shifted to the left, thus occurring earlierin the season.
The water level was reduced from anend-of-period elevation of approximately 276 feet to 253 feet, a differenceof 23 feet.
Since the top of the outflow intake structureis located at
238 feetM.S.L., therewouldbe ample space for this additional amount of water to be withdrawnduring this type of
withdrawal season.However, the decreased surface areaof the lake would severely affect recreation onthe lake. Outflow pH
is slightly higher for the additional flow case,and outflow
I chlorophyll-a concentrations are much greater for the I' additional flow case. I I I I I
V 83
NA LACE .100 cf. ALTATIYE HACG LAKE .100f, LTEATI 00TFLCI BASE CASE VS .100 di OJTFLW 02 BASE CASE VS. .100 cf, 0.012 10.0
0.010 9.0
8.0 0 0 0,00o uJ > 7,0 0. 00
6. 0.002 -4,., ,.n ts,I,tL* -- - H.. oZ1c-/l l% -1 ,. l, - H
0.000 5.0 50 100 150 200 280 100 150 200 250 50 JIJ..JAN DAY JL1IM DAI
HA LACE .100 cfs ALTEATI HA00 LAKE .100 eft ALTERATIVE C1JTFLCL M-0 BASE CASE VS. .100 c WTftCl O3 BA' CASE VS. .100 cfs 0,060 0.25-
0. 060 0.20
\Ø,Ø4Ø 0.1s
z
g.1e
0,020
- 14H H$4 t% - H44 I ,1I,L1,, ,f, ö/lS.,/1 ¶i iee.v ,is. e,IS l% -
0,010IrIIIIlIlIllI111t1I11T1ii rIjIlIIIrIllIlIII liii 0.00 iiiiiiiiiiiii IIIIIII(II 50 100 150 200 250 100 160 200 260 50 JIJJAN DAY JLL1N DAY
Fiqure 32. Hagg Lake OutflowDissolved Oxygen, Ortho-phosphOrOUs, NO3-N, andNH3-N Base Case 1990 versus Base Case +100cfs additional flow from6/15 through 9/15 1990. 84
As shown in Figure 32, outflow D.O. concentrations are greater for theadditional flow casedue to increased photosynthesis in the lower layers. The three nutrients that are important for algal growth (ortho-phosphorus, NO3-N, and
NH3-N) show their response to the increased and earlier algal growth in the lower layers. Ortho-phosphorus andNO3-Nget stripped out earlier from the algal growth, and NH3-N dynamics are shifted to the left due to the earlier reduction in pool level followed by algal growth in the lower layers.
This additional flow analysis showed that during a summer season such as 1990, additional flow to the Tualatin River could be supplied by Hagg Lake. The water quality of this additional outflow would be worse than previous outflow, but it may suffice the needs of the Tualatin River. The water quality of Hagg Lake would not be severelyaffected.However, the lowering of the lake may severely affect boating and other water oriented recreation at this lake.Also, with more shore surface area exposed, problems with scouring of bank sediments may be more important. CHAPTER VIII
RESERVOIR SEDIMENTATION ANALYSIS
INTRODUCTION
The processofdamming a naturalstreaminherently
changes the patterns of sediment deposition in that stream.
Most natural streams eventually deposit their sediment load at their confluence with a larger river, which in turn carries this sediment in the same process, until finally the sediment
is deposited in the ocean. However, the construction of a dam and reservoir on a stream greatly changes this process. Sediments remain suspended in a stream as long as there is enough energy to keep them there.Once this necessary energy is reduced, particles settle out. When a stream flows into a reservoir, its energy is greatly reduced and sedimentation occurs. Furthermore, the clearing of natural vegetation from a reservoir's banks drastically increases the erosive effects of wave action and precipitation at the reservoir site. The useful life of a reservoir is dependent on many factors:sediment types, inflow, capacity, sediment load, and trap efficiency (Lopez, 1978). Sediments are characterized by their particles. Different soils have differing amounts of three major inorganic particles, namely, sand, silt, and clay.
These three particle types are characterized by their sizes, 86
from with sand having the largestparticles (of the three), size range, from 0.0625 nun to 2.0 mm,silt having the median smallest sized 0.004 mm to 0.625 mm,and clay having the particles, less than 0.004 mm(Lopez, 1978). Besides being a reservoir is also a function of soil type,sedimentation in a practices, function of its watershed: topography, management most rapidly in a andhydrology. Sedimentationoccurs feeds it reservoir that is small inrelation to the river that rapidly if the (Lopez, 1978). Sedimentation also occurs more resides has large river basin in which the reservoir agricultural runoff or severelogging (Lopez, 1978;Klingemafl reservoir refers to et.al., 1971). The trap efficiency of a sediments. Many a reservoir'sability to retain suspended etc.) empirical relations (i.e.,Borland, 1971; Brune, 1953; have been proposed tocompute the trapefficiency of a
reservoir, and they usuallyrelate the percentageof sediments retained to the inflow andthe capacity of thereservoir were (Lopez, 1978). Generalized trap efficiency curves By developed by Brune (1953)for storage typereservoirs. annual inflow, taking the ratio ofreservoir capacity to mean the trap efficiency maybe determined fromthese curves. Operator Using the 1990 Hagg Lakeinflow computed by the Dam computed for (T.V.I.D., 1990), a trapefficiency of 95 % was all fine sediments f or this lake. This means that nearly designing a sediments settleout in Hagg Lake. When reservoir, engineers musttake all of these factorsinto 87 account and decide on the amount of storage thatwill be allotted for sedimentation. In deciding on a reservoir's sediment storage capacity, they are deciding on how longthe reservoir will operate.Once the reservoir fills the allotted sedimentation storage, it may be rendered useless.
When inflow to a reservoir reaches the pool, itbegins to lose velocity, hence energy, and the largestparticles (i.e. sand and gravel)in the sediment load begin to settle out
(Lopez, 1978) . This trend continues as the flow loses more energy and silt is eventually deposited furtherinto the pool
(Lopez, 1978). Clay particles may remain in the water column, but if thedetention time is large enough, theywill eventually settle out as well (Lopez, 1978). Therefore, the deposition of sediments in a reservoir will consist of a backwater deposit,a sand and gravel delta,and a bottom deposit of silt and clay (Lopez, 1978). The backwater deposit is that portion of sediment deposited at the stream-reservoir interface, and it may grow both out into the reservoir and back up the stream channel. Stagnant pools combined with rootedplantgrowth canoccur in the backwater areas, resultingin undesirable environmental conditions inthe backwater zones (Lopez, 1978).The finest particles may flow through the reservoir as a density current until they enter a slack water condition in which the load is deposited (Lopez,
1978). The bottom sediments have been observed to deposit most everywhere in a reservoir, but mainly in regions of low 88
particles that remain velocity (Lopez, 1978). very fine clay of a reservoir in the water columnincrease the turbidity of light which results in unsightlyconditions and reduction penetration in thereservoir. the In a reservoir, there aretwo sources ofturbidity: watershed feeding thereservoir and thereservoir's shoreline. surrounding Hagg Lake Most forested watershedssuch as that by man or natural have fairly stablesediments unless altered disturbances such aslandslides or severeslumping (Klingeman, When theseforestsare 1971;washington county, 1983). logging road cuts logged, vast acres ofclear-cut tracts and substantially.Sub- can increasesedimentation in a watershed been logged basins in the areasurrounding Hagg Lake have 1992). However, the anywhere from 0 to50 % (Fromuth, mostly covered by drainage basin contributingto Hagg Lake is and some second-growth Douglas Fir,with a few small farms al.,1985). open grasslandused for grazing (Johnson,et. tothe lake from Therefore, contributions of turbidity extensive logging and roadcuts are believedto be minimal. Lake could be Another possible sourceof turbidity in Hagg There are threepossible caused by shorelinesedimentation. erosion and shifting of sources ofsediment from a shoreline: reservoir pool, terraces during raisingand lowering of the during low pool level sheet and gullyerosion of the shore periods, and wave action onthe banks of theshoreline during From normal pool operations(Klingeman, et. al., 1971) . 89 observations at Hagg Lake, it appearsthat all three of these processes are occurring to somedegree. However, Klingefllafl, Valley et. al.(1971) showed, from studiesof 12 Willamette majorityof Reservoirs (excludingHagg Lake), thatthe sediments that settled inthese reservoirs camefrom their watersheds, rather than fromtheir banks. These watersheds were in regionsof heavy loggingactivities which attributed that most of the to their sediment loads. It was also shown sediments came from a few stormsduring the wet wintermonths performed on from November to February. A similar study was Soil the Upper TualatinRiverbythe Washington County Conservation Service in 1983, theyconcluded that as much as Tualatin 75% of the total yearlysediment load in the Upper
River could be attributed to 4to 5 Winter Stormswhich lasted approximately 10% of the totaltime. Normal stream sedimenttransport rates forNorthwest mile per Oregon range from 0.1to 0.2 acre-feet per square factors year (U.S.D.A.-S.C.S.,Dec., 1974).By applying these miles, a normal to the Hagg Lake WatershedArea of 37.5 square sediment transport range of 3.75to 7.5 acre-feet per yearis
obtained. Since the Hagg LakeWatershed iS mostly forested, it would probably have asedimentation rate in the lower the range. However, according tothe Scoggins Dam Operator,
U.S. Bureau of Reclamationleft approximately 6,280acre-feet life of of dead storage forsedimentation, based on a 100 year transport rate of this reservoir. This reveals a sediment 90
62.8 acre-feet per year, 10 times higher than thatpredicted for "normal Western Oregon streams". Therefore, the Bureau of Reclamation must have been anticipating high erosion to take place in and around Hagg Lake. In order to get anidea of the nature of sedimentation in Hagg Lake, the CE-QUAL-W2 model was adapted to account for various particle sizes.
PARTICLE SIZE DISTRIBUTION ADDITION TO HAGG LAKEMODEL
As shown in Chapter III, inorganic particles aremodeled by CE-QUAL-W2in one compartment. There are no sources besides inflows from tributaries or distributed tributaries, and sinks are treated by a single settling rate. Besides sedimentation additional sediment transport may be caused by thehydrodynamicsofthe system (i.e., horizontal and vertical advection). CE-QUAL-W2 bases the settling rate on
Stoke's Law for settling velocity (see equation 12). It would be extremely rare to have a soil with only oneparticle size fraction, and this is a limitation of the model. In order to model anatural soil more accurately, more particlesize fractions were included in the model with their respective differing settling rates according to Stoke's Law.
According to the Washington County Soil Survey (Green,
1982), the Hagg Lake Watershed is overlain with thefollowing sediments: Hembre silt loam, Pervina silty clay loam, Oylic silt loam, Tolke silt loam, and Melbourne silty clay loam.
With Melbourne silty clay loam, Pervina silty clay loam, and I I 91 Olyic silt loam being the most extensive. Melbourne silty I clay loam lines much of the lake andsurrounds the entire lake shore. Since this soil is exposed to all ofthe shoreline sedimentation processes, this soil was chosenfor further I analysis. Table III shows the engineeringproperties of Melbourne silty clay loam (Green, 1982)
TABLE III I ENGINEERING PROPERTIES OF MELBOURNE SILTYCLAY LOAM Percent Pass inq Sieve $ Depth Class # 4 #10 #40 #200 Liquid Plasticity Unified Limit 0"- ML, CL 95- 95- 95- 75- 35-45 10-20 I 18" 100 100 100 95 18"- MH, ML 95- 95- 95- 80- 45-60 10-20 I 66" 100 100 100 95 I From the sieve analysis performed onthis soil, the soil I was made up of mostly clayparticles. The Washington County Soil Survey (Green, 1982) classifiesthis soil in the I following family and subgroup:Clayey_Kaolinitic-MesicXeric Haplohumult. The terms are defined as follows: Clayey is a I description of the soil particles; Kaoliniticis the soil I class which describes the mineralogy of thesoil (greater than 50% kaolinite); Mesic is the class ofsoil temperature regime I for soils with a mean annual soil temperatureof 8°C to 15°C; Xeric is the moisture regime of soils wherewinters are moist I and cool and summers are warm and dry;and Haplohumult is a I I 9:2 great group of the Utisol class, whichfurther distinguishes different soil types (U.S.D.A.-S.C.S., 1975). Since a more thorough particle size analysis was notfound for this soil,
particle size analyses of two othersoils, similar in nature
and belonging to a similar family andsubgroup, were used to establish a finer soil particle sizefraction for Melbourne
silty clay loam. A soil survey of the Yamhill Area(Otte,
1974) had a particle size analysis ofPeavine silty clay loam
which was performed in a laboratory using the"pipette
method". This soil was classed in the family ofClayey-Mixed-
Mesic, and in the subgroup of: Typic-HaplohumUlt. This soil was chosen asa good approximation forthe particle size distribution of Melbourne silty clay loam becauseboth soils
are categorized as clayeyand both aiein the group of
Haplohumults. In soil classification, thesoil class (i.e., clayey) and the soil group (i.e.,Haplohumult) distinguish
particle sizes of the soil. Therefore, the two soils should
have similar particle sizes. Another laboratory analysis was
found for a soil from Nevada County,California, and this soil
was classified as aC1ayey_Kaolinitic_Mesic_Xeric_HaPl0humti
which was the same classification as MelbourneSilty Clay Loam
(U.S.D.A.-S.C.S., 1975, pp. 712-713). Tables IV and V show the particle size distributions of thetwo soils chosen for
extrapolation to the study area. I
I 93 TABLE IV
I PARTICLE SIZE DISTRIBUTIONOF PEAVINE SILTY CLAY LOAM (Otte, 1974) I' Depth 2-1 1- .5- .25 .1- .05- <.002 .2- .02- (in.) mm .5 .25 -.1 .05 .002 mm .02 .002 I mm mm mm mm mm mm mm 0-4 .8 1.7 1.1 2.0 3.1 54.2 37.1 25.8 32.6 4-10 I .5 1.3 1.0 1.9 3.5 55.6 36.2 25.7 34.3 10-15 .2 .7 .7 1.2 2.2 43.0 52.0 18.9 27.0 I 15-26 .2 .4 .3 .7 2.1 29.5 66.8 8.6 23.4 I 26-36 .1 .5 .4 1.1 3.2 40.9 53.8 13.2 31.6 I TABLE V PARTICLE SIZE DISTRIBUTIONOF A CLAYEY-KAOLINITIC-MESIC_ XERIC-HAPLOHUMULT, FROM NEVADA COUNTY,CA (U.S.D.A. -S.C. S, 1975)
Depth 2-1 l-.5 .5- .25- .1- .05- .02- <.002 I (in.) mm mm .25 .1 .05 .02 .002 mm mm mm mm mm mm I 0-18 1.6 4.2 3.3 7.4 6.7 13.7 25.7 37.4 18-36 .9 2.8 2.9 I 6.6 6.1 11.4 23.9 45.4 I From Tables IV and V,an average sediment distribution was calculated for the top 36 inchesof soil at Hagg Lake. In I order to define actual particlesizes from the givenranges, average particle sizes were chosenfrom the given size ranges. I Six particle sizeswere chosen to model the sedimentation processes in Hagg Lake. These particles would comprisethe I clay and silt components of soil, since larger particleswould I settle rather quickly.Table VI shows the clay particlesizes I I'
I 94 and percentages chosen for the Hagg Lake model. Table VII I shows the silt particle sizes and percentages chosen for the a Hagg Lake model. I TABLE VI FRACTION OF CLAY PARTICLES FOR THE HAGG LAKE MODEL
Clay Particles Very Fine Clay Fine Clay Coarse (SS1) (SS2) Clay (SS3) I Particle Size 0.0002 mm 0.0008 mm 0.0014 mm I Percentage 16.60 % 16.60 % 16.60 % I TABLE VII FRACTION OF SILT PARTICLES FOR THE HAGG LAKE MODEL
I Silt Particles Very Fine Silt Fine Silt Coarse (SS4) (5S5) Silt (SS6) I Particle Size 0.002 mm 0.010 mm 0.030 mm I Percentage 14.90 % 14.90 % 14.24 % I From Tables VI and VII, the fine soil particles account for 93.82 % of the soil, and the coarse material is 6.18% of I the soil. Thus, six particle size fractions were added to the Hagg Lake model (SS1, SS2, SS3, SS4, SS5, and SS6). These $ size fractions could be adjusted in the future for any soil I type, for they were placed in the model as variables, dependent on their settling velocities which are chosen and I placed in the revised CE-QUAL--W2 control file by the user (see I Appendix A). As mentioned before, Stok&s Law was used to I 95 derive settling velocities for the Hagg Lake Model.
Stoke's Law is given by (Thomann & Mueller, 1987):
g [PSP1,2 (1:3) 18.0
where: V5 = settling velocity (m/day) g = gravitational acceleration = particle density (g/cm3) p = density of water(g/cm3) = dynamic viscosity of water d = particle diameter (jim)
While evaluating particle data for the Sacramento-San
Joaquin Delta in California, Di Toro and Nusser (1976) derived the following empirical relation for a particle's density:
P=2 . 0d°'5 (14)
where: = particle density (g/cm3) d = particle diameter (jim)
Using this empirical formula, particle densities were calculated for the six particle sizes listed before. By applying Stoke's Law to the six particles,the following settling rates were obtained. These settling rates were required in the control file for the Hagg Lake CE-QUAL--W2 model. TableVIII showsthemean particle size, the calculated density, and Stoke's settling velocity for each Ii
I 96 I particle used in the Hagg Lake model. As one can see from Table VIII the particle densities calculated from Di Toro and $ Nusser's empirical formula appear to be very high for clay particles. Asoildensityof 2.5 g/cm3wouldbe more 'I reasonable. However, the densities calculatd and listed in I Table VIII were used and this was a conservative approach. I TABLE VIII I SEDIMENT SETTLING RATES FOR HAGG LAKE Particle: Mean Particle Calculated p Stoke's Size (mm) (q/cm3) Settling Velocity I (rn/day) SS1 0.0002 7.176 0.0021 I SS2 0.0008 5.829 0.023 SS3 0.0014 5.359 0.059 I SS4 0.002 5.08 0.1080 SS5 0.010 3.99 1.390 I SS6 0.030 3.38 6.080 I OBSERVATIONS OF SEDIMENTATION AT HAGG LAKE V In1989, the Oregon Department of Forestry began an I analysis of water quality in the headwaters of the Tualatin River Basin(Fromuth,1992). They performed analyses of $ several water quality parameters including suspended solids Dairy Creek, Gales Creek, 1 from the following sub-basins: I McKay Creek, and the Upper Tualatin. These analyses were I 97 performed during the summer months from 1989through 1992. Although the Hagg Lake sub-basin was notmonitored, many of these monitoring stations were locatedin very similar sub- basins as that of Hagg Lake. A review of the dataperformed by Aqua Tierra Environmental(Fromuth, 1992) showed that some of the laboratory analysis wereincorrect and some of the data were thrown out. plots of the satisfactory datashowed that a definite correlationexisted between suspended solidsand total phosphorus concentrations at manyof the sites. The data also showed that flow rates were veryminimal during the summer months. The report concluded that there was aneed to monitor these streams during the wintermonths, especially during large rain events. The researchers hypothesizedthat the correlation between sediment andphosphorus transport may be dramatic during large winter stormevents. Researchers studying the Tualatin RiverBasin at Oregon
State University (Miner and Scott, 1992)also reviewed the
Department of Forestry's data. They found that suspended solids concentrations tended to be low, and thatmost of the flow during the summer period wasreflective of groundwater both in quantity (between storm events)and quality. The following excerpt was taken from their review offour forested sub-basins (Gales Creek at Highway 6, Gales Creekat Forest
Park, East Fork Dairy Creek at Fern FlatRoad, and Upper McKay
Creek) in the Tualatin Watershed(Miner and Scott, 1992, pg.
8) 98
In total the forestry stationssuggest that the streamflow during the summer monthsconsists of groundwater inflow. There is no indication of surface runoff, nor is there anyindication that forestry management practices arecontributing to the level of nutrients in the streams.
One must remember that thisstudy was performed during the summer season only and thatthe weather patterns during the summer in the TualatinBasin are much different than the winter. As mentioned before, it hasbeen found that a few (4 the majority of to 5) major winter storms contribute to suspended solids in this region. Therefore, the majority of sediments that eventually settle in Hagg Lake maybe products of a few winter storms. In order to see how thesestorms could effect the turbidity of Hagg Lakein the summer, an exercise was performed using the Hagg Lakemodel to simulate these processes.
A SIMULATION OF SEDIMENTS AT HAGGLAKE
In order to track the fate ofsediments in Hagg Lake, the following "exercise" was run using the HaggLake model. The model was run from January 1, 1990 throughOctober 31, 1990.
Winter and spring storms were observedfrom analyzing inflow datato Hagg Lake (T.V.I.D., 1990). These storms were categorized by the amount of runoff flowinginto the lake. Since no inflow suspended solids dataexisted, suspended solids concentrations were estimated fromdata taken by the
Oregon State Department of Forestryat two adjacent sub-basins 99
These datadid (Clear Creek and LeeCreek) in 1991 and 1992. during winter storms, not show suspendedsolids concentrations the therefore, these data wereestimated. Table ix lists inflows to Hagq Lake. suspended solidsconcentrations used for
TABLE IX CONCENTRATIONS USED FORINFLOW TO INORGANIC SUSPENDED SOLIDS HAGG LAKE 1990
Severe Summer Normal Mild Flow Storm Winter Category Springor Winter Spring or Storm Winter 16 mg/i 30 mg/l S.S. Conc. 1-3 mg/i 5 mg/l
broken up into These suspendedsolids concentrations were earlier accordingtothe thesix particlesizeslisted the fractions listed in TablesVI and VII. They were input to files for Scoggins model via inflowconstituent concentration Since the suspended Creek, Sam Creek, and TannerCreek. initial conditions were solids concentrationsfor inflow and at best be the estimated, the magnitudesof the results may that actually occur. sameorder_of-magnitude as those Lake were Six graphs of the fateof particles in Hagg Figure 33 shows thelocationlfl made (Figures 34through 39). suspended particles was thelake where modeloutput of
analyzed. 100
CREEK HE'/EY HAGG lAKE SCOSGNS
SUSPENDED PAiflLCLE SUTE I,CELL L4 9
3C/SPENDED LAJmcLF: IUrD/ CELL 22.
SUSPE'1IJED PALDSCLE Cr75 CREEK SITE 3,OUTLET ENTAKE
27 /
S CO CC' S OA
Figure 33. Hagg Lake sitelocation for graphing suspended particle results.
Figure 34 shows the fate ofeach particle size classat
cell 9) as a site i (longitudinal cell 14, vertical concentration versus Julian day. Figure 35 shows the sum of these particles (totalinorganics) at the samelocation (site each particle size classat 1). Figure 36 shows the fate of cell 9) as a site 2 (longitudinal cell 22, vertical concentration versus Julian day. Figure 37 shows the sumof
these particles at the samelocation (site 2). Figures 38 and
39 show the same the samerespective processes asmentioned
above f or the outletintake structure (site 3). 101
HAGO EAKE SEDINENTATI0N4ANJAYSIS IMOGAMIG SOEIDS AT ONJ0 GEL 14. -- 3 -® VEFTICAE CEL_L 9 1
E20 15
551 S52 553 555;5s1 0-E; ss5
0.0 100 200 300 JUEIANI DAY
Figure 34. Concentrations of inorganicparticles versus Julian day atlongitudinal cell 14, vertical cell 9,1990. HADO LAKE SUSPENDEDSOLIDS ANALYSIS 12 SUN OF ALL PARTICLE SIZEERACTIONS AT LONG. CELL 14. VERT. CELLS -1550
10.
8.0-i
20 195;5; t-100EL SIL1LJLATION
0.0 100 300 0 JUL IAN DAY
Figure35. Sum ofinorganics suspended solids versus Julian day atlongitudinal cell 14, vertical cell 9, 1990. 102
HAGG LAKE SEDINEMTATIONJ ANJALYSISCELL 22. 30 INJOfROANICVERTICAL SOLIDS CELL AT LONJGS - 1 550 , /__// /1
I'
ss1' 662 S53 sss564 SS/,
00 100 200 300 JULIAN DAY
Figure 36. Concentrations of inorganic suspended solids versus Julian day at longitudinal cell 22, vertical cell 9, 1990.
HAGO LAKE SUSRENDED SOLIDS ANALYSIS SUM OF ALL FARTICLE SIZE FRACTIONS AT LONG. CELL 22. VERT CELL 5 10. 0i::
0) E 8.0
40
2.0 199e r1ODEL SIMULATION 00 0 J0 jO 300 JULIAN DAY
Figure 37. Sum ofinorganicsuspendedsolids versus Julian day at longitudinal cell 22,vertical cell 9, 1990. I.
103
ANALYSIS IMOGAMICHAGO LAKE SOLIDS SEDIDENTATION AT OUTLETINTAKE - 1S0
7- J /7
N Ny N N N N N ss1 SS2 N N ss;SS3 SsS S
00 100 200 300 0 JUl_IAN DAY
Figure 38. Concentrations of inorganic suspended solids versus Julian day at outlet intake structure, 1990.
HAGG LAKE SUSPENDED SOLIDSANALYSIS 1 2 0-SUM OF ALL RARTICLE SIZEFRACTIONS AT OUTLET 190
1 0 0-
8.0-
6 0-
4.0-
2 0- 1790 100EI_ SIM(JLATIOI4 0_0_ 0 100 200 300 JUL IAN DAY
Figure 39. SUIn ofinorganicsuspended solids versus Julian day at outletintake structure, 1990. 104
From Figures 34 through 37, one can seethat no change occurs between site 1 andsite 2, they both have nearlythe same curves for allparticle sizes. Both of these sites are located at the same depth (verticalcell 9), therefore, the plume of sediments must be wellmixed throughout the lake for most of the period between sites 1and 2. Graphs for site 3 (Figures 38 and 39) show a slightlydifferent sedimentation pattern than sites 1 and 2. Curves for the foursmallest
particles are much more gradual thanat sites 1 and 2. Site
3 is located deeper (verticalcells 14, 15, and 16) thansites 1 and 2 and local hydraulics maydraw particles toward the
outlet. The lake appears to be wellmixed in its upper layers because maximum concentrations arethe same at all three sites, and at the end of thesimulation (Julian day 300)
concentrations of all particles approach the same
concentrations. However, from Julian day 90through Julian
day 280, the outlet has higherconcentrations than the other
two sites. From Figures 34,36, and 38, one can see thatparticle sizes greater than SS4 (0.002 mm) settledout quickly (before
May 1st). The smallest clay particles (SS1,SS2, and SS3)
remained in the water column throughoutthe entire simulation.
Figure 39 (outlet) shows that the totalparticle concentration
on Julian day 120 (May1st) was higher than U.S.A. TSSfield data on Scoggins Creek for the samedate. An initial profile concentration on Julian day 120 for ISSof 7 to 1 mg/i was 105
used in calibrating themodel and figure 39 shows a concentration of 8 mg/l at the outlet for this same date.
Therefore, assumed storm loadings were high, however,
sedimentation processes would be similar for lower
concentrations of inorganics.
Further analysis of the sedimentation processes in Hagg
Lake can be found in Appendix D. Appendix D contains Figures
D.1 through D..5 which show sediment particle concentrations for the entire lake from this simulation using color plots produced from TECPLOT. CHAPTER IX
SUMMARY AND CONCLUSIONS
The modeling of Hagg Lake using the CE-QUAL-W2 model presented a "real" world difficulty.The difficulty with this model, as with many others, was that very little waterquality data existed for this lake. In order to capture the complex water quality cycles of a water body such as Hagg Lakeusing
CE-QUAL-W2, one would need a complete water quality data set spanning over at least one year. Included in this data set would be profile data for temperature, dissolved oxygen, and chlorophyll-a concentrations. Also, water quality data for the tributaries that flow into the lake would be necessary, especially during the wet winter and spring months.For ideal modeling conditions,one would also like to have a local meteorological data set taken at the actual site during the study period. The meteorological data set used for the Hagg Lake model was from the Hillsboro Airport, approximately 15 miles to the east. The two sites are at similar altitudes. However, the influence of the Coast Range on Hagg Lake could provide drastic differences in wind patterns between the two sites. With the limited data set available, the Hagg Lake model produced results of varying accuracy. The modeled nitrate 107
reasonably. and temperature output curvesfit the outflow data appeared to resemble Modeled temperatureprofiles for the lake expect with a well- a profile for HaggLake that one might However, defined epilimnion,thermoclifle, andhypolimniOn. would be without actual profiledata forthe lake, it accurate. Other impossible to say if thismodeled profile was data (i.e. PO4, modeled water qualityparameters with outflow ballpark", but did not NH3, TSS, TDS, andPh) were "within the show the dynamicsthat existed for thedata. The hardest part of thecalibration process wasin trying the water column near to get PO4 and NO3to be stripped out of (approximately August 15th). the middle of the summerseason model which had much In the end, theonly mechanism in the algalgrowth. effectonPO4 and NO3concentrations was algal bloom had to Therefore, to strip outthese nutrients, an that would produce begin at the middle ofthe summer season structure. high algal populations nearthe outlet intake was located at However, the outlet intake structure significant depth even atthe end of thewithdrawal season. sensitivity to light By adjusting thecoefficient for algal occurred at depth intensity (ASATUR), largeralgal populations This resulted in analgal and PO4 and NO3 werestripped out. Thisalgal populationthatwasvery light sensitive. during the population survived atdiffering water levels The nutrients summer seasondepending on the lightintensity. this occurred at the were stripped out asthe data showed, but 108 cost of having an algal populationwhich may not have been representative of the actual populations in HaggLake.
A sensitivity analysis was notperformed for coefficients used in the Hagg Lake model. There are nearly 100 coefficients used in the CE-QUAL-W2 modeland time did not
allow for a sensitivity analysis. The Hagg Lake model was observed tobe most sensitive toinitialsummerseason
conditions. As explained earlier, due to low summerinflows, initial water quality conditions in HaggLake direct the fate of water quality in the lake forthe summer season. The
fractions of water taken at the outflowintake structure from
vertical cells 14,15, and 16 (FRACT1, FRACT2, andFRACT3)
were also very sensitive duringcalibration. Slight changes
in the percentages of water taken from thesecells changed the
location where the epilimnion, thermocline, and the hypolimnion occurred. Thus, the temperature andwater quality
regime was shifted, resulting in differentmodeled output for
the outflow to Scoggins Creek. From observations of the lake itselfand the available
data, no water quality problems appear toexist at Hagg Lake. When compared to water in the lowerreaches of the Tualatin River, it could be said that Hagg Lake hasexcellent water
quality. The Hagg Lake model provides waterquality and hydraulic simulations that areItwithin the ballparkt' as an
average. Temperature,nitrate, and hydraulic predictions
appearto bevery realistic. Themodelhas notbeen 109 calibrated f or winter (Novemberthrough April)conditions.
Thus, it would be unwise tospeculate on its accuracy forthis period without field data. The Hagg Lake model was used todetermine the effects on water quality if additionaloutflow were allowedduring the withdrawal season. An additional 100 cfs wasadded to the outflow from Hagg Lake from June15, 1990 throughSeptember analysis showed that water 15, 1990. The results of this quality would not be drasticallyeffected. Outflow water quality would not be a good as previous,but it may be adequate for the Tualatin River. Recreation at Hagg Lake would be most severely impacted. DependingOfldownstream demands, the pool in the lake maydrop to levels where most recreation at the lake would not bepossible. Since high
recreational demands occur duringhigh withdrawal seasons (dry and warm), the two could notcoexist with this additional
outflow. Additional outflow from Hagg Lakecould be provided lake through by increasing thestorage capacityofthe dredging or raising the dam.However, this alternativecould
be very expensive. Five additional inorganic particlesizes were added to
the Hagg Lake model. This allowed one to track thefate of
six different inorganic particlesizes with different settling
rates in Hagg Lake. An exercise was performedwith the model to show the destiny of sixparticles associated with soils
which are predominant on the shoresof Hagg Lake. The bulk of 110 this suspended sediment was introduced into the lake through its tributaries from five to six winter and spring storm events. The exercise reinforced the hypothesis that very fine sediments may remain suspended in the lake throughout the summer season as a result of runoff from a few winter and spring storm events.
Due to time constraints, other sources of turbidity were not examined. Observations at Hagg Lake confirmed the fact that shoreline erosion is taking place at Hagg Lake from both waves crashing on the shore and lowering the pool.It appears that these processes are occurring at fairly high levels. The soils around Hagg Lake tend to be fine to very fine silty clay barns which may remain suspended in the water column for long periods of time. Further turbidity problems could result from increased logging in the watershed around Hagg Lake should it occur in the future.The watershed is largely privately owned and the second growth douglas fir which covers most of the watershed has matured to harvestable timber. REFERENCES
Readings and Beeton, A.M., "Relationshipbetween Secchi Disk Light Penetration in Lake Huron,Transaction, American Fisheries Society, vol. 87,1958, pp. 73-79. Efficiency of Reservoirs,"Transactions, Brune, G.M., "Trap 407- American Geophysical Union,Vol. 34, No. 3, 1953, pp. 418. DiToro, D.M. and Nusser, J.,"Particle Size and Settling Velocity Analyses for Bay AreaWaters," Hydroscience, Inc., report prepared for CaliforniaDepartment of Water Resources, 1976. Edinger, J.E., and Buchak, E.M.,"Numerical Hydrodynamics of Estuaries," Estuarine andWetland Processes withSpecial Emphasis on Modeling, ed. by P.Hamilton and K.B. MacDonald, Plenum Press, NY, 1978, pp.115-146.
Federal Water pollution ControlAdministration, "Summary - Willamette River Basin WaterQuality Control and Management," u.s. Department ofthe Interior, Northwest Region, Portland, Oregon, 1967. River Fromuth, c., "PhosphorousMonitoring in the Tualatin Basin - A Review of the OregonDepartment of Forestry Program for a TMDLBasin 1989-1991," AguaTierra Environmental Consulting, areport prepared for the Oregon Department of Forestry, 1992.
Green, G.L., "Soil Surveyof Washington County,Oregon," U.S.D.A. Soil ConservationService, in cooperationwith Oregon AgriculturalExperimentation Station, 1982.
James, A., "Introductionto Mathematical Modelling," fl Introduction to Water QualityModellinq, ed. by A. James, John Wiley & Sons Ltd., 1984, pp.1-17.
Johnson, D.M., Schaedel, A.L.,et. al., Atlas of OreqonLakes, Oregon State Univerisity Press,Corvallis, Oregon, 1985.
Klingeman, P.C., et. al.,"Hills Creek ReservoirTurbidity Oregon Study," Water ResourcesResearch Institute, No. 14, State university,Corvallis, Oregon, December, 1971. 112
Leonard, B.P., "A Stable and AccurateConvection Modelling Procedure Based on Quadratic UpstreamInterpolation," Computer Methods in AppliedMechanical Engineering, No. 19, 1979, pp. 59-98. Linsley, R.K., Franzini, J.B., WaterResources Enqineeriflq, 3rd ed., McGraw-Hill Book Company,1979.
Lopez, S., "MathematicalModeling of Sediment Depositionin Reservoirs," Colorado StateUniversity Press, Fort Collins, Colorado, No. 95, July, 1978.
Madsen, o.s., "Sediment Transportand Coastal Processes," lecture notes on Mechanics ofSediment Transport in Steady Flow, M.I.T., Department ofCivil Engineering, 1975.
Miner, J.R., Scott, E., "AnAnalysis of Water Quality Datain Tualatin River Tributaries with ThreeDifferent Land Uses," Tualatin River Basin Water ResourcesManagement Report, No. 3., Oregon Water ResourcesResearch Institute, July, 1992.
Oregon Department of EnvironmentalQuality, "Citizen Lake Watch," unpublished data, Portland,Oregon, 1990.
Orlob, G.T., "One-dimensionalModels for Simulation of Water Quality in Lakes and Reservoirs,"Mathematical Modeling of Water Quality: Streams, Lakes, andReservoirs, ed. by G.T. Orlob, John Wiley & Sons, 1983, pp.227-268.
Orlob, G.T., "Models forStratified Impoundments," Models for Water QualitY Management, ed. byA.K. Biswas, McGraw-Hill Inc., 1981, pp. 272-312. Otte, G.E., et. al., "Soil Surveyof Yamhill Area, Oregon," U.S.D.A. Soil ConservationService, coop with Oregon Agricultural ExperimentationStation, 1974.
Otto, W., personal communication,Tualatin Valley Irrigation District, Hilisboro, Oregon, 1991.
Port of Portland, Portland-HilisborOAirport, unpublished data, Hilisboro, Oregon, 1990, 1991.
Streeter, H.W., Phelps, E.B., "Astudy of Pollution and Natural purification of the OhioRiver," U.S. Public Health Service, publication Health Bulletin, no.146, February, 1925.
Sverdup, H.U., Johnson, M.W.,Fleming, R.H., The Oceans, prentice-Hall, Englewood Cliffs, NJ,1942. 113
Symons, J.N.,Water Quality Behavior in Lakes and Reservoirs, U.S. Dept. of Health, Education and Welfare, 1969.
Taylor, G., unpublished data, Oregon State Climatologist, Oregon State University, Corvallis, Oregon, 1990, 1991.
Tchobanoglous, G, Schroeder, E.D., Water Quality, Addison- Wesley Publishing Inc., 1985. Thomann, R.V., Mueller, J.A., Principles of Surface Water Quality Modeling and Control, Harper and Row Publishers Inc., NY, NY, 1987.
Tualatin Valley Irrigation District, unpublished data, Hillsboro, Oregon, 1990, 1991.
Unified Sewerage Agency, unpublished data, Hillsboro, Oregon, 1990, 1991.
U.S.A.C.E., "CE-QUAL-W2: A Numerical Two-Dimensional, Laterally Averaged Model of Hydrodynamics and Water Quality: Users Manual," Environmental and Hydraulics Laboratory, Waterways Experiments Station, Vicksburg, Mississippi, 1986a.
U.S.A.C.E., "CE-QUAL-Ri: A Numerical One-Dimensional Model of Reservoir Water Quality: User's Manual," Environmental and Hydraulics Laboratory, Waterways Experiments Station, Vicksburg, Mississippi, 1986b.
U.S.A.C.E., "DRAFT- Updated CE-QUAL--W2 User's Manual," Waterways Experiments Station, Vicksburg, Mississippi, 1990.
U.S.A.C.E., "HEC-6 - Scour and Deposition in Rivers and Reservoirs: User's Manual," U.S. Dept. of Commerce, Springfield, Virginia, June, 1991.
U.S.A.C.E., "DRAFT- Updated CE-QUAL-W2 User's Manual," Waterways Experiments Station, Vicksburg, Mississippi, 1992.
U.S.D.A., Soil Conservation Service, "Erosion, Sediment and Related Salt Problems and Treatment Oppurtunities," December, 1974. U.S.D.A., Soil Conservation Service, Soil Taxonomy - A Basic System of Soil Classification for Making and Interpreting Soil Surveys, Agricultural Handbook no. 436, December, 1975.
U.S. Dept. of the Interior, Bureau of Reclamation, unpublished data, Boise, Idaho, 1970.
U.S.G.S., Quadrangle Topographic Maps, Portland, Oregon. I
I 114 Walesh, S.G., Urban Surface Water Management, John Wiley and I Sons, 1989, pp. 337-354. Washington County, Soil and Water Conservation District, "Upper Tualatin River Streambank Erosion Control Project: I Summary Report," June, 1983. Washington County, "Henry Flagg Lake, Scoggins Valley Park," Brochure, Washington County Dept. of Support Services, I Facilities Management Division, Hillsboro, Oregon. I Wetzel, R.G., Limnology, W.B. Saunders Company, 1975. Wolf, D.W. Literature Review: Land Use and Nonpoint Phosphorus Pollution in the Tualatin Basin, Oregon," Special I Report no. 898, Oregon State University Extension Service and Water Resources Research Institute, Corvallis, Oregon, I 1992. I I I I I
p I I I I I APPENDIX A
WATER QUALITY CYCLES IN CE-QUAL-W2
(Corps of Engineers, 1986a, 1990) 1
I 116 I The source/sink term for each water quality constituent (Skin equation 6)in the CE-QUAL-W2 model are quantified in I Table A-i. The water quality cycles that these equations correspond to are shown graphically in Figures A.1 through
I A.14 for algae, coliform, detritus, oxygen, inorganic carbon, I suspended solids, labile dissolved organic matter, ammonia, nitrite+nitrate, ortho-phosphorus, refractory organic matter, I sediment, iron, and zooplankton. I TABLE A-1 SOURCE SINK TERN EQUATIONS USED IN THE MODIFIED VERSION OF I CE-QUAL-W2 Parameter Variable Source/Sink Term Conc. I' (g/m3)
1 Conservative I Tracer C1 S1 0 I 2 SS1 C, wVC, - s=J I 2 AZ I 3 Colitorm Bacteria C3 S3 -KO(T-20)vc3
I 4 Total Dissolved I Solids C4 S4=O(cotservative)
I I
117
I Parameter Variable Source/Sink Term Conc. (g/ni3) I 5 Liable BOO C5 S=KVC7+(1_Pj)IcVC7
I yllKdVCS-KVC5 I 6 Refractory BOO C6 S =K1VC5--y11KC6 I 6
7 Algae I C7 S7=KgVC7 rs7Ke VC7 -K2 VC7
If PKC77VC7W 3VC7 I - F1 AZ p 8 Detritus Cs ()2VC8 S8=P1KVC7-K(14VC8- I z p +VC [K ±(K.(1-P5))] I 27 viz I I I I r
V 118
* Parameter Variable Source/Sink Term Conc. (g/m3) I 9 Phosphorus C9 S =(K I 9 rs-K)5pJ/C7+KdSp]lJ/C±Kd8pJlVC8
11VC1±K 76C ±X21 I 16 2/s I VA7(w 1C7+w 7C8±w C7±flw I AZ
I ±VK2JC27R, I 10 Ammonia- Nitrogen C10 C10 S rK VC $ 10 rs5NVC7K6 ±KQ5-y1JVC. - 7C10±Cl1 - - I
±KN11VC ±KdS 1VC8 ±KS 18y,4C13 a t ±X31J7y7/±KNy3VC Ka7i2VCio I VA/4( 1C,+w 7C8±i 3C7flw 4C20)C10 I AZ
I ±VKC K. I zr27z I I 119
I Parameter Variable Source/Sink Term Conc. (g/m3)
I 11 Nitrate- Nitrogen C11 S11 =Kai7VCj0_Knj3VCjj I
C -KôVC(1- 10 $ gN C 10c11
12 Dissolved I Ogen C12 S12 =K ;VC7 -K VC7 Ka5 J71CJ()
-K6 0y VC8-KS 018y74C1 I VC() 18 74 GA1VCçKOM Ii I I ±ALJE(C -C17) - VK C77 * 13 Sediment C13 dC13 ,VC8 3VC7 -y18y78KC13 I di=AZ± AZ where 013 is in units of sediment mass, gm; first- order decay of organic solids: algae and detritus 'I I I I I 120 a Parameter Variable Source/Sink Term Conc. (g/m3) I' 14 Inorganic Carbon C14 S14=(K -K) VC7±KdS y14VC6 a I +KdY1JSVC±K11 (VC(±X117S I +Ky 1828SC13 +AAE(C C17) ±VKC7R1 I
15 Alkalinity S15 = 0 (conservative) I C's
V 16 pH Equations for solution based on the carbonate C16 bicarbonate equilibrium reactions:
I CO, ±H,0H,COrH*±HCO I * HCO3CO32H
I H2OH +OJ-1 I 17 Carbon Dioxide -Same as pH I C17 I I I 121 Parameter Variable Source/Sink Term Conc. I (g!m3)
18 Bicarbonate -Same as pH I C18
19 Carbonate -Same as pH Cl9 1
20 Iron C, VwC, I S,0=X41878A-
21 BOD-5 C21 S21 =-KO2C2J V
22 SS2 V C22 S22 I
23 SS3 )VC C23 6 23 I 23 I
24 SS4 C )VC7 24 I s-24 I I I I I
I 122
$ Parameter Variable Source/Sink Term Conc. (gIm3)
25 SS5 C25 I 25 AZ
I 26 SS6 C26 26 Az
I 27 Zooplankton C27 S27 = -Z1)/(F1 +Z117)I VC27 I -(1 -y ,)KVC,7- JK)/C77 V I' t Table A-2 provides variable definitions for thevariables in Table A-i. It also lists variable names that arein the
I modified CE-QUAL-W2 control file. Variables where "not used" I is listed under "Control File" are either computedby the program, or not input by the user, but arevariables "hard I wired" into the actual program. I I I I I t 123 TABLE A-2
VARIABLE DEFINITIONS FOR WATER QUALITYCYCLE EQUATIONS USED IN CEQUALW2
Control Eq. Definition Control Eq. Definition File Var. File Var. partitIon coefficient for I AHSP A1 PO4 adsorption ALGDET P1 coefficient, m3Ig algal mortality preference factor of PARTP A2 max. mass of PREF1 P3 I PREF2 zooplankton for algae PO4 adsorbed per mass of I solids AHSN A3 ammonia BlOC ratio between carbon adsorption and organic matter I coefficient, m3/g PARTN A4 max. mass of BION R2 ratio between nitrogen ammonia and organic matter I adsorbed per mass solids
R3 ratio between not used Ak( surface area of BIOP 1 upper model phosphorus and organic cell, m2 matter temperature of water, not used A sediment area, TEMP T I m2 not used C carbon dioxide not used V cell volume, m3 I saturation concentration, g/rn3
not used C0 saturation SOD X1 rate of sediment oxygen dissolved demand, g/m2 sec oxygen $ concentration, gIrn3
X2 anaerobic sediment not used E inorganic carbon PO4REL interfacial release rate, g!m2 sec exchange rate, rn/sec
not used E0 oxygen NH3REL X3 sediment ammonia intertacial release rate, g!m2 sec exchange rate, rn/sec I I I
I 124
I Control Eq. Definition Control Eq. Definition File Var. File Var.
not used F1 total weighted FEREL X4 sediment iron release I food for rate, g/m2 sec zooplankton, gfm3
I NH3DK ammonia- ZS2P Z112 hatf-saturation coeff. for Ka nitrogen decay zooplankton ingestion, I rate, sec' g/m3 COLDK K coliform death ZEFFIC Z zooplankton ingestion rate, sec4 efficiency
I LABDK Kd liable DOM ZOOM IN Z1 low threshold decay rate, sec' concentration for zooplankton feeding, I g/m3 DETDK KdI detritus decay not used adsorption increment for rate, sec4 Iron V AEXCR Ke algal excretion H AZ cell thickness, m rate, sec'
I AGROW Kg algal growth BlOC c5 stoichiometric coeff. for rate, sec4 carbon
AMORT K1 algal mortality BION stoichiometric coeff. for I rate, sec' nitrogen ZMAX max. ingestion O2ALG stoichiometric I rate for 02NH3 coefficients for oxygen zooplankton, hr O2DET O2LAB * NO3DK K nitrate-nitrogen O2RESP stoichiometric coeff. decay rate, sec4 between biological constituents and 02 for I respiration REFDK refractory DOM BIOP S stoichiometric coeff. for decay rate, sec' phosphorus
$ ARESP K algal dark iiiDTl y18 temperature rate respiration rate, multiplier for ascending sec4 portion of the curve
SEDDK K sediment decay iiEDT3 -y2 temperature rate rate, sec4 multiplier for descending I the curve I I I I 125
Control Eq. Definition Control Eq. Definition $ File Var. File Var.
LRFDK K1 transfer rate iiiDT2 temperature rate from liable to iiDT4 multipliers I refractory DOM, sect temperature factor I not used K1 zooplankton not used 0 ingestion rate, hr1
I' ZMORT K71 zooplankton SSETL1 inorganic suspended mortality rate, h( solids settling velocity for smallest particles, rn/day
I DSETL detritus settling velocity, ZRESP K,r zooplankton respiration rate, rn/sec I hr4 DETDK Kb CBOD decay ASETL algal settling velocity, rate, sec1 m/sec I SSETL2 inorganic SSETL5 inorganic suspended suspended solids settling rate for solids settling 2nd to largest particles, rate, rn/day rn/day
SSETL3 w.7 inorganic SSETL6 inorganic suspended suspended solids settling rate for I solids settling largest particles, m/day rate, rn/day
SSETL4 inorganic FESETL Iron settling velocity, I' suspended rn/sec solids settling rate, rn/day $ I $ I
I I 126
ZOOPLANE TON INORGANIC CARBON
PREDATOV TAUF' NO3-N RESPRA11C. DP< REATCW OXYGEN ALGAE -OTOS .-S flTCET1 .A8lLE DISSOLVED ORGANIC MATTER ThflJNG lCTt1JJ DETRITUS
OTHER ALGAL SEDIMENT LAYERS
Figure A.1. Algae Sources and Sinks.
CDLIFORM
SINK
Figure A.2. Coliform first-order decay process. 127
ZOOPLANKTON
A
- INORGANIC CARBON CTAJTh DECEPO1 ALGAE H DETRITUS H PO4-P
NH4-N 1 sTTh
DETRITUS IN SECMENT 1OTH[R LAYERS
Figure A.3. Detritus sources and sinks.
TOSNThESS ALGAE AJRFACE EXCHN L..1. EsPA11c
y REPA11C OXYGEN ZOOPLANKTON
SEDIMENT - OXIDATC AMMONIA- NITROGEN DETRITUS CCPOJT1O .ABILE 0GM
REPRACTORV DCV
Figure A.4. Dissolved Oxygen sources and sinks. 128
DETRITUS 5UACE EXCHANGE
SEDIMENT V kLSElPAECE[ DECGC1PGSITICN INORGANIC ZOOPLANKTON LABILE CARBON DISSOLVED A ORGANICS FRCSGJ1CXJ
REER ACTORY DISSOLVED ALGAE ORGANICS
Figure A.5. Inorganic Carbon sources and sinks.
SUSPENDED SOLIDS A
EErrLJNG -J OTHER SS LAYERS
Figure A.6. Inorganic suspended solids sedimentation. 129
REFRACTORY DOM PHOTCPESP1RA i1f'J LA8FL[ ALGAE MGTAUTY DOM IN ORG A NIC CARBON
Figure A.7. Labile dissolved organic matter sources and sinks.
ALGAE
LABILE DOM PHOfC)SSIS N]TIflCtI1ON NO2+NO3 REFRACTORY RESPRA11C NITROGEN DOM
DECOC'J I DETRITUS J REDUC T1C NH4 -N PESPRAT1C ADCP 11C OTHER NH4-N LAYERS ADSCP11GJ ZOOPLANKTON ANAEPCC RELEASE V oEccMposrnc SEDIMENT
Figure A.8. Ammonia-N sources and sinks. 130
AMMONIA- NITROGEN
N!TRIRc1.:XJ
1
NITRITE PLUS NITRATE-N
V ALGAE
Figure A.9. Nitrite & Nitrate sources and sinks.
ALGAE LABILE DOM 4 DARK REFRACTORY PHOTOSrNTHESP RESPIPA 11CP DOM V RESPIRAI1ON DECC1POSSC I DETRITUS ZOOPLANKTON PO4-P
ADSCP11CA OTHER PO4-P ADSERPACX' LAYERS DECCRPCSI11CJ. ANAERCEC RELEASE
SEDIMENT
Figure A.1O. Ortho-phosphorus sources and sinks. 131
INORL A NC CARBON
PLABLE :ccPosmC REFRACTORY DOM DOM H NH4N
Figure A.11. Refractory dissolved organic matter sources andsinks.
A PESEVCR ELEVATKY'i CHANGE SETTLiNG DETRITUS ALGAE SETTLiNG
DECG*HPOSET1C 4
y NORGA NC NH4-N PO4-P CARBON
Figure A.12. Sediment accumulation/deposition. 132
I SEDIMENTS ANCC PELEE
1! TOT AL RON
SETLJNC
OTHER IRON LAYERS
Figure A.13. Total iron sources and sinks.
OXYGEN IN ORGANIC EACH ALGAL CARBON GROUP EPA1ON REP1CJ PO4-P It-CESTKIY
ZOOPLANKION NH4-N 1 A
ECES11CXJ ± MOPLAUTY DIFPuSION DETRITUS
OTHER PLANKTON LAYERS
Figure A.14. Zooplankton sources and sinks. APPENDIX B
BATHYMETP.Y FOR HAGG LAKE 134
cell described The cross-sections foreach longitudinal Figure B.l shows in Chapter IV are includedin this appendix. Hagg Lake model as the cell widths (m)for each cell in the described in Figure 7. Lfl : R 1 iI S 1 -4 g S S S S S M .4 .4 S .4 S S5 "1 S S .4S S .4 1 S 1 S'4 S .4 FI .4 S - I - . - - - - S S - - - - - APPENDIX C
HAGG LAKE MODEL FILE DESCRIPTION I 137 This Appendix is intended toshow the organizationof their I files used in the Hagg Lake model,their description and files used for the HaggLake I use. Table C-i reviews the model. Filenames are listed for themodel prior to additional I particle size additions ("1")and after additionalparticle the 1990 Hagg size additions ("2"). The files listed are for period have the same I Lake model. Files used for the 1991 I descriptions, but they are dated"91" rather than "90". TABLE C-i
I ORGANIZATION OF FILES USED INTHE ORIGINAL HAGG LAKEMODEL
I Type of File File Name File Description "1" = Original "2" = S. S. I Additions Main Control 1. haggcon.nPt control file with run File 2. hgsscon.npt information, I input/output file map, model coefficients, etc.
Bathymetry 1. hlbth.npt cell widths, cell I heights, initial water File 2. hlbth.npt surface profile, and ManningS friction factor I for each longitudinal cell Meteorologic 1. met9O.npt daily averaged values of I File 2. met9O.npt air temperature, dew- point temperature, wind speed, wind direction, I and cloud cover Branch 1. qtrl9o.npt flow rates(m3/s) as a Inf low Files 2. qtrl9O.npt function of Julian day I for Scoggins Creek (long, cell 2) 1. ttrl9o.npt temperature (°C) as a I function of Julian day 2. ttrl90.flpt I for Scoggins Creek I I I 138
Type of File File Name File Description I "1" = original = S. S. I Additions 1. ctrl9O.npt water quality 2. cssl9O.npt constituent concentrations for I ScogginS Creek as a function of Julian day (m3/s) as a I Tributary 1. qtr29O.flPt flow rates Inflow Files 2. qtr29O.npt function of Julian day 1. qtr39O.npt for Sam (2) (long, cell 2. qtr39O.npt 9) and Tanner (3)(long. I cell 14) Creeks 1. ttr29O.nPt temperature (°C) as a 2. ttr29O.npt function of Julian day I (2) and Tanner 1. ttr39O.flpt for Sam 2. ttr39O.flpt (3) Creeks I 1. ctr29O.npt water quality 2. css29O.npt constituent 1. ctr39O.npt concentrations for Sam 2. c5s390.flpt (2) and Tanner (3) I Creeks as a function of Julian day I Outflow File 1. hlout9O.flpt downstream outflow file 2. hlout9O.nPt for spillway flows(none in study)
I Withdrawal 1. hlwd9O.flpt withdrawal file for File 2. hlwd9O.npt Scoggins Dam withdrawals (long, cell 29, vert. cells 14-16)(m3/s) as a I function of Julian day
FORTRTN 1. w2hagg.for CE-QUAL-W2 model code I Source Code 2. w2hg_ss.fOr with updates and modifications
Output Files 1. conc_out.opt Concentrations at: I 2. conc3.opt outlet, cell 3, cell 9, 2. conc9.opt cell 14, and cell 22 of 2. concl4.opt active water quality I 2. conc_22.opt constituents as a 2. concout.opt function of Julian day I (every 400 time steps) I I I
I 139
Type of File File Name File Description I Original "2" = S. S. I Additions 1. snp.opt Output summary file: 2. snp.opt concentrations, temperatures, I velocities, limiting factors, etc. as a function of frequency I requested. 1. temp.out Temperature at outlet as I 2. temp.out function of Julian day 1. pro_const.out Profiles of all active 2. pro_const.out constituents and temperature at long. I cell 29 1. violavg.opt average simulation I 2. violavg.opt violation for D.O., pH, and chlorophyll-a goals 1. violcnt.opt plotable violation I 2. violcnt.opt histograms for D.O., pH, and chlorophyll-a Other Input 1. outlet.npt Input file for outlet I Files 2. outlet.npt intake structure fractions (FRACT1, I FRACT2, and FRACT3) 1. pro date.npt Dates for profiles to be 2. pro_date.npt output (Julian day) I Initial 1. vpr9O.npt Initial constituent Profile 2. vpr9l.npt concentration profiles on May 1st I Include File 1. w2_hg.inc Map file for CE-QUAL-W2 I 2. w2ss.inc source code I I I I I APPENDIX D
I PLOTS OF SEDIMENTATION PROCESSESIN HAGG LAKE I I I I I I I I I I 'I I I I 141
program TECPLOT, Using the software plotting were made concentrations of sedimentparticles for Hagg Lake period as describedin during the 1990sedimentation analysis concentrations of particlesin Chapter viii.Figure D.l shows 1st, March 1st, May the SS1 category(0.0002 mm) for February 1990. Figure D.2 1st, June 1st,July 1st, and September1, the SS2 category(0.0008 shows concentrationsof particles in June 1st, July1st, mm) for February 1st,March 1st, May 1st, concentrations of and September 1,1990. Figure D.3 shows for February 1st, particles in the SS3category (0.0014 mm) September 1, 1990. March 1st, May 1st, June1st, July 1st, and in the SS4 Figure D.4shows concentrationsof particles 1st, May 1st, June category (0.002 mm) forFebruary 1st, March 1990. Figure D.5 shows 1st, July 1st,and September 1, (0.010 mm) for concentrations of particlesin the SS5 category 1st, July 1st,and February 1st, March1st, May 1st, June (0.030 mm) ofparticles September 1,1990. The SS6 category settled out of the water was not plottedsince these particles column too fast, andall plots wereblank. 142
SSI 1. 99O IS U
particleconcentration SSlsuspended solid 1st, July Figure D.l. March 1st, May1st, June (mg/i) onFebruary 1st, 1990. 1st, andSeptember 1, 143
SS2 February 1, 1990 SS2-Mich 1,1990
SS2 May 11990 SS2 June 1. 1990
SS2 - Ju4y 1.1990 SS2-Seplernbel 1,1990
U
SS2 suspendedsolid particleconcentration Figure D.2. June 1st, July (mg/i) on February 1st,March 1st, May 1st, 1st, and September1, 1990. 144
ary I. S3 M
SSJ Jurre 1.
SS3 September 1. 1990 553 July 1.1990
SS3 suspendedsolid particleconcentration Figure D.3. May 1st, June1st, July (mg/i) on February1st, March 1st, 1st, and september 1, 1990. 145
S4 iuiuv I. 1990 SS4 - Mrrch 1.
SS4 MaI, 1990 0S4Julie 1990
SS4 July 1, 1990 SS4 September 1.1990
SS4 suspended solidparticle concentration Figure D.4. July (mg/i) on February 1st, March1st, May 1st, June 1st, 1st, and September 1,1990. 146
SS5 - February 1 1990 SS5-Marchl, 1990
0
SS5 - May 11990 SS5 Jurle 1.1990
SS5 - July 11990 SS5 September 1. 1990
7010 0941' 0_a/a
0.0726 0 S-SI 0.431 03043 i 0.210
Figure D.5. SS5 suspended solid particle concentration (mg/i) on February 1st, March 1st, May 1st, June 1st, July 1st, and September 1,1990.