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EPA 

United States Office of Research and 

Environmental Protection Development 

Agency Washington DC 20460 

Center for Environmental 

Research Information 

Cincinnati OH 45268 

Technology Transfer 

Handbook 

EPA/625/6-86/013 

Stream Sampling for 

Waste Load Allocation 

Applications 
EPA/625/6-86/013 

September 1986 

Handbook 

Stream Sampling for 

Waste Load Allocation Applications 

by 

William B. Mills, George L. Bowie. Thomas M Grieb, and Kay M Johnson 

Tetra Tech, incorporated 

Lafayette, CA 94549 

and 

Raymond C. Whittemore 

NCASI 

Medford, MA 

Subcontract No. 101 

Eastern Research Group, Inc 

Cambridge, MA 

EPA Project Officer 

H. Douglas Williams 

Center for Environmental Research Information 

Cincinnati, OH 45268 

U.S. Environmental Protection Agency 

Office of Research and Development 

Washington, DC 20460 
Notice 

This document has been reviewed in accordance with US Environmental 

Protection Agency policy approved and for publication. Mention of trade names 

or commercial products does not constitute endorsement or recommendation 

for use. 

ii 
Abstract 

This report discusses sampling requirements in support of waste load allocation 

studies in rivers and streams. Two approaches to waste load allocation are 

addressed: the chemical-specific approach and the whole effluent approach. 

Numerical or analytical toxicant fate models are used to implement the 

chemical-specific approach. Modeling requirements and sampling guidelines 

are delineated for this method. 

For the whole effluent approach, the method is first summarized and than 

instream dye study requirements are presented. The report concludes with 

example applications of the chemical-specific approach for conventional and 

toxic pollutants. 

iii 
Contents 

Chapter Page 

Abstract.. .......................................................... . . ii 

List of Figures ....................................................... . . v 

List of Tables ...................................................... vii 

Acknowledgments .................................................. viii 

1. Introduction .................................................... 1-1 

1.1 Background ............................................... 1-1 

1.2 Purposes of Handbook ..................................... 1-1 

1.3 Overview of Approach. ..................................... 1-2 

2. Sampling Requirements for Waste Load Allocation Modeling ....... 2-1 

2.1 Model-Independent Considerations. ......................... 2-1 

2.1.1 Stream Geometry Data .............................. 2-1 

2.1.2 Hydraulic Data ...................................... 2-3 

2.1.3 Meteorological Data ................................. 2-6 

2.1.4 Water Quality Data. ................................. 2-6 

2.1.5 Plug Flow Sampling ................................. 2-10 

2.2 Sampling Requirements for Conventional Pollutants .......... 2-11 

2.2.1 General Modeling Approaches ....................... 2-11 

2.2.2 Model Data Requirements ........................... 2-13 

2.2.3 Sampling Guidelines ................................ 2-14 

2.3 Sampling Requirements for Toxic Pollutants ................. 2-24 

2.3.1 Introduction ........................................ 2-24 

2.3.2 Model Data Requirements ........................... 2-25 

2.3.3 Sampling Guidelines ................................ 2-30 

3. Whole Effluent Approach ......................... ... ............ 3-1 

3.1 Overview ............................................... . . 3-1 

3.2 Tier 1 Effluent Testing-Screening .......................... 3-1 

3.3 Tier 2 Testing-Definitive Data Generation .................. 3-4 

3.4 Ambient Toxicity Testing and Dye Studies. ................... 3-5 

4. Example Application ............................................ 4-1 

4.1 Dissolved Oxygen .......................................... 4-1 

4.2 Organic Toxicant .......................................... 4-3 

5. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R-1 

6. Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1 

v 
List of Figures 

Number Page 

1-1 

2-1 

2-2 

2-3 

2-4 

2-5 

2-6 

2-7 

2-8 

2-9 

2-10 

2-11 

2-12 

2-13 

2-14 

2-15 

2-16 

2-17 

2-18 

2-19 

3-1 

3-2 

3-3 

3-4 

Summary of stream survey design consideration for water 

quality modeling approach and whole effluent toxicity 

approach to waste load allocation .............................. 1-3 

Example stream network showing reaches and computational 

elements.. ................................................. 2-2 

Physical representation of a stream by model segments ......... 2-3 

Effects of grid resolution on predicted dissolved oxygen 

profiles ...................................................... 2-4 

Derivation of cross-sectional area vs. flow and velocity 

relationships from stage-flow data ............................. 2-5 

Recommended locations for a minimal sampling program. ...... 2-7 

Recommended sampling locations at point sources .............. 2-9 

Allocation of sampling effort based on preliminary analyses. ..... 2-11 

Processes affecting dissolved oxygen .......................... 2-13 

Effect of pH and temperature on unionized ammonia ........... 2-14 

Major constituent interations in QUAL-II ....................... 2-16 

Example computation of total BOD removal rate, Kr, based on 

BOD measurements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-18 

Procedure for estimating Kd and Kr from BOD measurements .... 2-19 

BOD decay times for various decay rates ....................... 2-21 

Example sampling network for a dissolved oxygen analysis ...... 2-22 

Results of a short-term intensive survey to establish the 

dissolved oxygen profilte ...................................... 2-24 

Daily dissolved oxygen variation in two rivers ................... 2-24 

Typical concentration profiles of toxicants in rivers .............. 2-31 

Sampling locations for toxicants during low flow and 

high flow periods ............................................ 2-31 

Typical suspended solids concentrations during (a) low 

flow and (b) high flow periods ................................. 2-32 

Overview of effluent toxicity testing procedures. ................ 3-2 

Overview of ambient toxicity testing procedures ................ 3-3 

Distances below point source discharges required for 

complete vertical and transverse mixing ........................ 3-4 

Time required for a continuous release of dye to reach 

steady-state concentrations at selected locations below 

the point of discharge ........................................ 3-5 

vi 
List of Figures (Cont’d) 

Number Page 

3-5 

3-6 

3-7 

4-1 

4-2 

4-3 

4-4 

Dye lsopleths in wide and narrow rivers . . . . . . 

Regions of observable toxicity in wide and narrow rivers . . . . . . . 

Example sampling locations in wide and narrow rivers . . . . . 

Eel River and environs showing summer of 1981 water 

quality results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 

Location of sampling stations on Eel River . . . . . . . . . . . . 

El Cahon River, Lake Chabot, and environs . . . . . . . . . . . . . 

Location of sampling stations on El Cahon River . . . . . . . . 

3-6 

. 3-6 

. 3-7 

. 4-1 

. 4-2 

. 4-3 

. 4-4 

vii 
List of Tables 

Number Page 

1-1 

2-1 

2-2 

2-3 

2-4 

2-5 

2-6 

2-7 

2-8 

2-9 

2-10 

2-11 

2-12 

4-1 

4-2 

4-3 

4-4 

Waste Load Allocation Guidance Documents ................... 1-2 

Data Requirements for Hand-Calculation Techniques Described 

in WLA Guidance Documents and Screening Manual for 

Analysis of Conventional Pollutants .......................... 2-15 

Processes Simulated in QUAL-II ............................... 2-16 

Non-Toxic Constituents Included in Stream Models ............. 2-17 

Model Input Parameters for QUAL-II ........................... 2-17 

Comparison of QUAL-II with Other Conventional Pollutant 

Models Used in Waste Load Allocations ........................ 2-18 

Methods for Determining Coefficient Values in Dissolved 

Oxygen and Eutrophication Models ............................ 2-20 

Summary of Date Requirements for Screening Approach for 

Metals in Rivers .............................................. 2-26 

Summary of Data Requirements for Screening Approach for 

Organics in Rivers ............................................ 2-27 

MICHRIV Model Data Requirements ........................... 2-28 

Summary of Input Data Required for TOXIWASP ................ 2-29 

Travel Times for Various C/Co Ratios Corresponding to 

Different Toxicant Decay Rates ................................ 2-31 

Summary of Sampling Guidelines for Toxicants ................. 2-33 

Summary of Data to be Collected During Stream Survey for 

Dissolved Oxygen Waste Load Allocation. ...................... 4-2 

Properties and Fate Processes for Pyrene ....................... 4-3 

Range of 1-e k ( l *)Z . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 

K( l *)Z 

Summary of Data to be Collected During Stream Survey.. . . . . . . . 4-5 

viii 
Acknowledgments 

Many individuals contributed to the review of this handbook. Special recognition 

is given to Steven Gherini of Tetra Tech; Timothy Stuart, Elizabeth Southerland, 

and James Plafkin, Monitoring and Data Support Division, USEPA, Washington, 

DC; Steven McCutcheon, USEPA Environmental Research Lab, Athens, GA; H. 

Douglas Williams and Orville Macomber, USEPA Center for. Environmental 

Research Information, Cincinnati, OH; William Richardson and Larry Fink, 

USEPA Large Lakes Research Station, Grosse Ile, Ml; Robert Bordner, William 

Horning and Robert Safferman, USEPA Environmental Monitoring and Support 

Lab, Cincinnati, OH; Edward Woo, USEPA Region I, Boston, MA; Noel Kohl, 

USEPA Region V, Chicago, IL; Henry Holman, USEPA, Region VI, Dallas, TX; and 

Bruce Zander, USEPA, Region VIII, Denver, CO. 

Thanks is also expressed to Trudy Rokas, Susan Madson, and Gloria Sellers for 

typing and preparing the report, and Marilyn Davies for providing graphics. 

ix 
Chapter 1 

Introduction 

1.1 Background 

The United States Environmental Protection Agency’s 

Monitoring and Data Support Division is presently 

developing guidance manuals that describe approaches for allocating waste loads in rivers and 

streams, lakes and impoundments, and estuaries. 

The pollutants addressed in the manuals are biochemical oxygen demand/dissolved oxygen, nutrients, and toxic substances (ammonia, organics, and 

metals). Other manuals in the series present related 

topics, such as how to select the critical conditions for 

the waste load allocation (WLA) (e,g., the appropriate 

stream flow). Table 1-1 summarizes the documents. 

Water quality simulation models are often used for 

WLA purposes. These models must adequately 

predict water body responses to different waste loads 

when large financial expenditures are at stake. Consequently, where feasible. models should be calibrated 

and verified prior to allocating waste loads. Sufficient 

historical data to accomplish these objectives are 

often lacking and of the wrong type, and additional 

data should be collected. Water quality specialists, 

therefore, have to decide what data are missing and 

their importance, and then design surveys to gather 

any required information. This handbook is intended 

to guide specialists through these steps for waste 

load allocations in rivers and streams. Both the 

chemical specific and whole effluent approaches to 

WLA are discussed. 

• 

• 

• 

• 

• 

This handbook can be used in conjunction with Book 

II, Rivers and Streams, with Book VI, Design Conditions, and with appropriate sections of Book VIII, 

Screening Manual. Book V, The Technical Support 

Document for Water Quality-based Toxics Control, 

will be useful as well (See Table 1-1). 

Because the river water quality model QUAL-II (1,2) 

and its followup QUAL-2E (3) is widely used for WLA 

applications and is supported by the USEPA’s Center 

for Water Quality Modeling, example stream survey 

designs for this particular model are included in this 

handbook. Stream survey guidance for the toxicant 

models TOXIWASP (4) and MICHRIV (5) are provided 

as well. Users of other models will find much of the 

guidance applicable to their models because of 

similarities in model requirements. 

1.2 Purposes of Handbook 

The primary purpose of this handbook is to help water 

quality specialists design stream surveys to support 

modeling applications for waste load allocations. The 

planner is guided through the data collection process 

so that models used for WLA can be calibrated, 

verified, and applied to the critical design conditions. 

Field sampling requirements of the whole effluent 

approach to waste load allocation are also addressed. 

This handbook does not discuss a number of facets of 

stream sampling where significant reference materials already exist. These areas include: 

equipment requirements 

personnel requirements 

collection of samples 

determination of stream geometrical and flow 

characteristics 

laboratory analytical techniques. 

The Appendix summarizes the appropriate literature 

in these categories. The references are primarily from 

the U.S. Geological Survey’s Water Resource Investigation series, the U.S. Fish and Wildlife’s Instream 

Flow Information series, and from the U.S. Environmental Protection Agency. 

This handbook also recognizes that waterborne 

viruses are pollutants which produce definite health 

effects. However, these pathogens cannot be considered in the wasteload allocation process which are 

involved only with parameters that have established 

water quality criteria. 

The second purpose of this handbook is to show how 

models can be used to help design stream surveys. 

Since the models will eventually be used to predict 

the allowable waste loads, they can be set up and 

applied before the stream surveys are finished. This 

will assist planners in examining the available data, 

allow preliminary sensitivity analyses to be made, 

and thereby help identify the most needed data. 

Stream surveys can then focus on the collection of 

such data, and de-emphasize data that are less 

important or previously well characterized. 

The third purpose of this handbook is to educate field 

personnel on the relationship between sampling 

requirements and modeling requirements. Field 

1-1 
Table 1-1. Waste Load Allocation Guidance Documents 

Waste Load Allocation Guidance 

Book I. 

Book II. 

General Guidance 

Streams & Rivers 

BOD/DO 

Nutrients/Eutrophication 

Toxic Substances 

Simplified Methods for POTWs 

Estuaries 

BOD/DO 

Nutrients/Eutrophication 

Toxic Substances 

Lakes & Impoundments 

BOD/DO 

Nutrients/Eutrophication 

TOXIC Substances 

Technical Support Document for 

Water Quality-Based Toxics Control 

Design (Critical) Conditions 

Design Flow 

Design Temperature 

Design pH 

Design Effluent Flow 

Design Rate Constants 

Permit Averaging 

Screening Manual 

BOD/DO 

Toxic Organics 

TOXIC Metals 

Nutrients/Eutrophication 

Book Ill. 

Book IV. 

Book V. 

Book VI. 

Book VII. 

Book VIII. 

Book IX. Innovative Waste Load Allocations 

*Available from Monitoring and Data Support Division, USEPA 

(WH553, Washington, D.C. 20460. See latest Monitoring and 

Waste Load Allocation status report for completion dates for 

these documents. 

personnel may sometimes question why historical 

data are not adequate, why specially designed 

surveys are often required to generate the data, and 

why certain sampling locations and parameters are 

selected. By understanding the factors that go into 

the selection process, field personnel are likely to 

perform their tasks more effectively. When unforeseen field conditions dictate a change in sampling 

strategy, there IS a better basis for deciding how to 

modify the sampling program design. 

1.3 Overview of Approach 

Figure 1-1 summarizes the approach to stream survey 

design discussed in this handbook. Two parallel 

approaches are possible: the chemical specific approach and the whole effluent approach. 

The chemical specific approach is selected if the 

pollutants to be allocated are conventional pollutants, 

or if toxic pollutants are to be allocated on a toxicantby-toxicant basis. For example, if BOD/DO and copper 

are to be allocated, then QUAL-2E and MICHRIV 

might be the water quality models selected for the 

allocation. 

Sampling periods to collect data for model calibration 

and verification are then selected. Model calibration 

1-2 

refers to the process of adjusting model parameters 

so predictions acceptably match field data. Calibration 

often requires that some of the input data, particularly 

rate constants (e.g., BOD decay rate) be adjusted 

within realistic limits to provide better agreement 

between observations and predictions. Model verification is a comparison of model predictions against 

an Independent set of field data A model or model 

component is verified predictions when and observations agree without having to arbitrarily adjust model 

coefficients 

Stream surveys used to calibrate and verify models 

are typically intensive synoptic surveys. These are 

surveys that are-usually completed within a week or 

so. and are intended to provide a definition of river 

responses to a specific set of loadings. 

Since the models or calculation methods to be used in 

the WLA process will eventually be adapted to the 

river systems where sampling is to be conducted, 

model adaptation to the system should be completed 

prior to sampling. The models are used to simulate 

the parameters to be allocated and at the conditions 

expected to be encountered during the surveys (based 

on the best information available prior to sampling). 

This will encourage the specialist to examine the 

available data, determine what IS missing, and to 

estimate values of the missing data Then, by 

performing sensitivity analyses (i.e., by varying 

parameters and observing the effect on model 

outputs), the specialist can establish which data are 

more likely to influence model predictions and thus 

establish sampling frequencies and location. Locations where water quality conditions change most 

rapidly and where water quality standards are not 

expected to be achieved are the critical areas to find 

and sample. 

Stream survey design for model calibration and 

verification can then be rationally executed with 

informational needs fairly well defined. Often, dye 

studies are needed to accurately estimate pollutant 

travel time through the river. Travel time reflects the 

average velocity over distance, and can be quite 

different from the velocity measured by a current 

meter at a cross section, especially if the river cross 

section changes from location to location. Normally, 

travel time studies are conducted at more than one 

stream flow so that travel times can be estimated at 

the critical flow. 

Sampling locations are established considering accessibility, historical locations, critical points of 

maximum or minimum concentration, and other 

locations where water quality standards are expected 

to be violated Other considerations include intervals 

between samples (smaller intervals are typically used 

where stream response is most rapid) and point 

source sampling. Sampling just below a point source 

is risky because of the likelihood of obtaining un- 
Figurm l-l. Summary of atroam survey doa@n conaidontion for chamicd l pocific approach and wholo effluent approach to 

weate load allocation. 

t 

Srket WUU Load Allocation 

Approach 

I 1 

Chambl Spedfk Approach Whole Effluent Approach 

crftDrbe for sekctlon: Crltsrla for Selection 

l Connnttonal Pollutants l Complex Mwture of 

601ng Allocated Toxtcants Discharged 

0 Pollutant-By-Pollutant l More Then One Dwharpsr 

Approach used for Toxlcsntr In Close Proxlmrty or NPS we a 

Sqnlftcrnt Component 

Summartte InformatconN& 

to Use Guidance 

c CL-qmtcsl Speclflc Evrluatlon 

!c I.r,prsctical 

1 

/ l Rwr Svatom Roaches / c 

l Dwobp Data Base to Run 

Model from Avatlrble 

Hlatorlcal Data 

Perform Model Simulatlona I 

I 

f 

Daaqn Stream Surveya 

l Summarize InformatIonal Neoda 

l Design Oye Studtea if Needed 

l Eatabhah Swnpl~ng LocatIona 

l Determlrw When Semplea are 

cobcted 

l Dotermme Number and Twa of 

Samploa 

.e Doatgn Mmthcda to Eatrmata 

R8te Conat8nta 

l Eatrmate DoratIon of Sutwvr 

Whole Effluent Toxlccty 

Stream Surveys 

Perform Preliminary 

Mixmg Celculatmns 

Addmonal Conaiderattons I Design Stream Surveys 

l Profeuionrl Judgment 

end Site-Specifr 

l Dssqn Dye Studres 

l Establtah Ssmplmg 

Locarbons 

l Determme Number of 

Samples 

l Eattmate Duretlon of 

Survsvs 

I-3 
representative samples (pomt source discharges may 

not rapidly mix with stream flow), and often a massbalance calculation using the pomt source and a 

location just upstream is preferable. Where the 

pollutant sources cannot be adequately measured. a 

downstream sample will be necessary to back 

calculate the load from nonpomt source (NPS) 

pollution, agricultural runoff, or pomt sources that 

cannot be adequately measured. 

Special consideration is required for rate constant 

determinations. Typically. rate constants, such 8s the 

reaeration rate coefficient, are not drrectly measured 

but are determined through a series of indirect 

measurements, or are based on model calibrations. 

Fietddetermrnations of rate coeff icientscan be Costly. 

and the specialrst should justify the need prior to 

recommending this aspect of the field study. 

Stream survey design and implementation must be 

tempered by factors such as financial resources and 

man-power limitations and should be conducted 

during critical conditions if at all possible. The 

judgement and experience of water quality speciahsts 

who are not necessarily modelers but who have 

considerable experience with the natural waters of 

interest must also be weighed. The importance of the 

data that are to be collected can help to guide and 

prioritize sampling program activities. All environmentel monitoring tasks performed under EPA sponsorship must also be conducted under an approved 

Q.A. project plan following guidance provided by the 

EPA. Quality assurance is especially important when 

sample number is limited due to other project 

considerations. 

The second approach to WLA of toxicants is called the 

whole effluent approach. Streams that receive complex or multiple effluent discharges may present a 

complicated sampling problem. All potential pollutants in complex wastes may not be identified nor 

their interactions assessed. In turn, pollutant bioavailability may be difficult to measure. The EPA has 

recently evaluated and validated this approach for 

setting discharge limits based on effluent toxicity 

(60’11. 

For this approach, total toxicity in a river is treated 

conservatively. Under certain circumstances, an 

effective decay rate can be estimated based on 

toxicity decrease over distance below an outfall (6). 

Traditional chemical-specific toxicant models are not 

required for this approach. 

The whole effluent approach may be used alone or in 

many cases in conjunction with the chemical specific 

approach to WLA. As pointed out in EPA policy, both 

approaches will be needed In many cases. In this 

manner it may be possible to develop a more complete 

evaluation of instream effluent effects. The primary 

l-4 

objective of field sampltng in support of !he whole 

effluent toxicity approach is to determme mrxing 

characterrstics of the effluent in the stream or river 

and to determine whether toxicity is decreasing due 

to decay processes. 

Every effort should be made to visit the proposed 

sampling locations durmg a brief field reconnaissance 

before executing the stream surveys for model 

calibration/verification. This will help to estabhsh the 

accessibility of the selected locations, or to decide if 

for any other reason a sampling location change 

should be made. 
Chapter 2 

Sampling Requirements for Waste Load Allocation Modeling 

2.1 Model-Independent Considerations 

Sampling requirements for water quality modeling 

depend to some extent on the particular model or 

calculation procedure being used. This in turn 

depends on the type of problem being studied and the 

level of detail required in the modeling analysis. 

Models can range in detail from dilution models or 

simple Streeter-Phelps type models of dissolved 

oxygen to complicated models of stream ecosystems 

which include many interacting processes and variables, for example, oxygen dynamics, nutrient cycles, 

and algal and zooplankton dynamics. The major 

distinctions between different models are the specific 

parameters and processes modeled, the equations 

used to describe each process, the numerical techniques used to solve the equations, and whether the 

models are dynamic or steady-state. 

However, in spite of these differences, all models 

share many common features. As a result, many 

sampling considerations are the same regardless of 

the specific model or the particular WU problem 

being addressed. These model-independent considerations are discussed in this section. Sampling 

considerations specific to particular types of problems 

and specific models are discussed in the following 

sections. 

2.1.1 Stream Geometry Data 

All models require essentially the same types of 

information to define the geometric characteristics of 

the stream. Stream systems are divided into a series 

of reaches for model analysis, with each reach 

described by a specific set of channel geometry (i.e., 

cross-sectional dimensions) and flow characteristics 

(i.e., flow rates, depths, and velocities or time of 

travel). Reaches are defined between all major 

tributary junctions and flow diversions, or whenever 

stream geometry, hydraulic conditions, or biochemical processes (i.e., sediment oxygen demand) within 

the stream are expected to change significantly. The 

models assume that these conditions are uniform 

within each reach. 

Each reach is in turn divided into a series of model 

segments or computational elements in order to 

provide spatial variation for the water quality analysis 

(Figures 2-1 and 2-2). Each segment is represented 

by a grid point in the model where all water quality 

variables are computed. The number and size of the 

segments depends on the spatial resolution desired. 

Enough detail should be provided to characterize 

anticipated spatial variation in water quality due to 

different pollutant sources, dissolved oxygen sags, 

and other significant processes within the stream. In 

general, the model grid must have a much higher 

resolution than the sampling network for computational reasons. For example, Figure 2-3 shows the 

effects of varying the grid resolution on dissolved 

oxygen predictions. The low resolution grid flattens 

out the dissolved oxygen sag curve due to the effects 

of numerical mixing in the model. Although 10 

sampling locations are more than adequate to define 

the dissolved oxygen profile in the field, the use of 

only 10 computational nodes in the model results in 

inaccurate predictions. 

Channel geometry data are used to define the stream 

configurations and segment characteristics, regardless of the particular model being used. This includes 

both hand calculation methods and computerized 

modeling techniques. Additional types of geometry 

data may also be necessary depending on the 

hydrologic algorithm used to route the flows through 

the system. The basic types of data required for each 

reach include: 

1. segment or reach length 

2. variation of channel width and cross-sectional 

area with depth 

3. bottom slope (or bed elevations) 

4. variation of wetted perimeter or hydraulic radius 

with depth 

5. bottom roughness coefficient (Manning’s n). 

Variation of water depth with flow is also important, 

but will be discussed later in the hydraulic data 

section. All of the above parameters are typically 

assumed constant for all model segments within a 

defined reach. 

Length and average slope over long distances can be 

determined from topographic maps, while the other 

variables usually require field surveys. The first two 

2-1 
Figure 2-1. Example stream network showing reaches and computational elements (1,2,3) 

data types, length and cross-sectional area. are 

fundamental to any modeling study. The remaining 

information may or may not be required, depending 

on the type of hydraulic computations used in the 

model. For example, if stage-flow relationships are 

2-2 

used to describe the hydraulics (e.g., QUAL-2E, and 

SSAM IV (8). then only lengths and cross-sectional 

areas are required to fully define transport through 

the system. However, if Manning’s equation (e.g., 

option in QUAL-2E) or the St. Venant equations (e.g., 
Figure 2-2. Phyai4 reprmwntatlon of l rtreom by modal aogmonta (admptod from (lo)). 

RECEIV-II (9). and WQRRS (10) are used to route the 

flow, then the additional information (items 3 through 

6 above) will be necessary for the hydraulic computations. 

Many models internally compute the cross-sectional 

area as a function of depth based on idealized 

representations of the channel shape. For example, if 

a trapezoidal channel is assumed, only the bottom 

width and side slopes need to be specified. For a 

rectangular channel, only the width is needed. 

The level of detail required in describing the stream 

geometry depends on the amount of veriability in the 

system. For streams which heve uniform slopes and 

cross-sections over the study area, only a few 

transects will be necessary. However. in areas where 

the channel geometry varies widely, the stream 

should be divided into a series of representative 

reaches, and enough transects measured along each 

reach to adequately characterrze the geometry. Three 

to five cross-sections could be measured along each 

reach, and the results could be averaged to define the 

reach characteristics for the model. As a minimum, 

one representative cross-section should be measured 

in each reach. Some pool and riffle streams may 

require dye studies and measurement of as many 

cross sections as possible to obtain adequate stream 

geometry. 

2.1.2 Hyclr~ullc Data 

Hydraulic data are needed to define the velocities, 

flows, and water depthsforthe transport calculations 

that are used to describe how pollutants move down 

stream. Enough data are necessary to characterize 

the hydraulic regime throughout the study area. This 

includes the flows at the upstream boundaries of all 

channels, as well as all significant tributary inflows, 

lateral inflows (from groundwater or runoff), flow 

diversions, return flows and stage at some locations. 

In a general analysis, waste flows which represent a 

significant portion (i.e., greater than 5 to 1’0 percent) 

of the total stream flow should also be included in the 

hydraulic analysis. Enough flow sources should be 

characterized so that 90 to 95 percent of the total 

stream flow is accounted for in the analysis. 

While the upstream boundary flows, tributary flows, 

and diversion flows can be measured directly. lsteral 

2-3 
Effoctr of grfd rosobtion on prodkt~~! diuofnd o-on profibs uoing an explicit finito difforenco solution rchamo 

- Anrlyllcal 

. . . . . . . 10 Nader 1 O.ODO’ oath 

--m 40 Nodes 2500’ each 

-- 100 Nodes 1000’ each 

k. = O.S/day. t. = 2.3Idav 

1 

lO.OcQ 20,wO 30.000 4o.cmo so.wo 6oo.ooo 70.000 ao.axl 

D~runce Downstrmxm. frill - 

inflows from ground water or runoff must be estimated from differences in measured flows at different 

locations along the stream channel. 

Many models allow the specification of stage-flow 

relationships for each channel reach in the system. 

Thus requires the simultaneous measurement of 

water depth and flow for a series of flows over the 

range of interest. While a minimum of twovaluesare 

necessary to construct a stage-flow rating curve, 

three or more values are desired for more accurate 

relationships. If possible, the flows measured should 

cover the range of conditions to be addressed in the 

WLA analysis. For a preliminary analysis it may be 

possible to estimate the relationship between d, A, V 

and 0 at geugmg stations. However, these stations 

ere rarely representative of long reaches because 

these stations are located at control points in a stream 

where a unique relationship exists between stage 

and 0. 

Stage-flow curves are constructed by plotting depth 

versus flow on log log gaper since depth and flow can 

be related by’an exponential equation of the form: 

2-4 

d = al 0’1 (2-l 1 

where d = water depth 

a = flow 

a9 = coefficient of stage-flow relationship 

b, = exponent of stage-flow relationship 

The coefficient al and exponent b, of Equation (2-l) 

are determined from the intercept and slope of the 

log-log plot (Figure Z-4). Similar relationships can be 

developed for cross-sectional area and velocity as 

functions of flow: 

A=aFQ? (2-2) 

V=a3Q5 G-3) 

where A = cross-sectional area 

U = velocity 

80 = coefficient for cross-sectional area vs. 

flow relationship 

bz = exponent for cross-sectional area vs. flow 

relationship 

a3 = coefficient for velocity vs. flow relationship 

bs = exponent for velocityvs. flow relationship 
Cross-sectional area as a function of depth is obtained 

from the channel geometry data, and velocity IS 

computed from the flow continuity equation (U. = 

Q/A). These data are plotted against flow on log-log 

paper to determine the values of the coefficients and 

exponents in Equations (2-2) and (Z-3) (Figure 2-4). 

These parameters are required as input to certain 

streem water quality models. There are considerable 

geometry data available from: 1) USGS, especially 

new gauging stations, 2) COE near reservoirs and 

proposed reservoirs (also from Bureau of Reclametion, TVA, Bonneville Power), 3) FEMA flood insurance studies, 4) National Weather Service forecasting 

centers. In areas where stream bed varies with time, 

it is impordnt tG ,JDU ihu 1n0si recent geometry data. 

Both the stream geometry and flow information are 

critical to the transport calculations. When the stream 

geometry varies widely within reaches and is difficult 

to characterize in detail, or when lrteref inflows are 

not well defined (for example, because access 

problems limit measurement), it is often useful to 

supplement the hydrologic and geometric data with 

travel time studibs using tracer techniques, typically 

with rhodaminewdye. This information can be used 

to adjust the geometry or flow data so that model 

transport calculations match the results of the dye 

study. This calibrates the transport portion of the 

water quality model by defining the geometry or flow 

data to produce the net transport observed in the field. 

2. I .3 M~teotologlul Data 

Because temperature influences dissolved oxygen 

aattiratlon and the rates of almost all of the chemickl 

and biological processes occurring in streams, many 

water quality models include options for simulating 

temperature. Meteorological data are necessary to 

perform the heat budget computations in these 

models. Heat transfer at the air-water interface 

depends on several processas including shoit-wave 

solar radiation, long-wave atmospheric radiation, 

. 

20.0 . Depth = 0.312 0” 2(33c, , Ar.8 = 18.5 Oa’ 

too5 

t 

Z 

d 6.0! 

2.0 

/ 

0 

1.0, ,~ ‘.,“, 

20 50 lDO2DO 600 

Flow (~9s) 

20 so 100200 600 

Flow Mfs) 

2-5 
long-wave back redration, convective heat exchange, 

and evaporative heat loss. Most models compute 

each of these processes separately and add them 

together to give the net heat flux at the water surface. 

The alternative method is the equilibrium temperature approach in which all of the above processes are 

combined into two parameters: the equilibrium 

temperature and the surface heat exchange coefficient, both of which vary dynamically with the 

meteorological conditions. In feet, the equilibrium 

temperature formulation is essentially equivalent to 

the linearizedversion of the total heat budget which is 

used in most water quality models, including 

OUAi-2E. 

The basic types of meteorological data required are 

essentially the same regardless of the particular 

model being used: 

1. solar radiation 

2. cloud cover 

3. air temperature 

4. relative humidity (or wet bulb temperature or 

dew point temperature] 

6. wind speed 

6. atmospheric pressure. 

Many models compute incident solar radiation internally in the model as a function of latitude, longitude, 

day of the year, time of the day, and atmospheric 

scattering and absorption of light due to dust. Cloud 

cover data are then required to compute the amount 

of solar radiation reaching the water surface. The 

alternative approach used in other models is to input 

measured solar radiation directly. In mountainous 

areas, canyons, or in areas where riparian vegetation 

is dense, additional reduction in solar radiation due to 

topographic end vegetation sheding should be included in the model. This is handled by an additional 

shading coefficient, by detailed formulations which 

compute the shading dynamically (12). or by inputing 

net solar radiation values which include these effects. 

The five meteorological variables listed above can 

often be obtained from nearby weather stations. Most 

NOAA class A stations have monthly averages of 

these variables available. Long term monthly averages of these parameters baaed on several years of 

historical data are also available in the “Climatic 

Atlas” published by the National Oceanographic and 

Atmospheric Administration (13). More detailed 

records of meteorological data at 3-hour intervalscan 

often be obtained on magnetic tape from the National 

Climatic Data Center, Federal Building, Asheville, 

North Carolina 28801 (phone (704) 259-0682). 

Existing weather stations are usually adequate when 

studying larger rivers, streams near weather stations, 

2-6 

or when water temperature and volatillzatlon are not 

critical components of the model study. In other 

cases, temporary weather stations can be set up. A 

single station ‘is generally sufficient. However, m 

areas where solar radiation, atmospheric pressure 

and temperature varies over the length of a river 

(greater than 1000 feet in elevation), it may be 

desirable to set up two stations. one near the 

upstream boundary and one near the downstream 

boundary of the study reach. 

2.1.4 W&or Qudlty Data 

Given the semi-empirical nature of water quality 

models, water quality data are necessary to setup, 

calibrate, and verify any ,weter racy’+ ~*-l,’ rnr*rt 

data are needed for all param -ters whirh will r:, 

simulated. For models like QUwL-2E that simulate 

conventional pollutants, this may include tempereture, dissolved oxygen, carbonaceous BOO, phosphorus, nitrogen (ammonia, nitrite, and nitrate), 

coliforms, chlorophyll a or phytoplankton dry weight 

biomass, and conservative constituents such as total 

dissolved solids. Some mode& also includeadditional 

constituents such as total inorganic carbon, alkalinity, 

pH, inorganic suspended solids, suspended organic 

detritus, periphyton, zooplankton. and benthic organisms. Toxic fate models require data for the specific 

chemicals under investigation. 

It is only necessary to collect data for the particular 

constituents and processes which are being evaluated, plus. eny other variables which significantly 

affect these constituents. For example, if coliforms 

are not of interest, there is no need to collect data for 

them even though they may be included in the model 

since they do not influence the other constituents. 

Any arbitrary value could be assigned to coliforms, or 

they could be set equal to zero when running the 

model. Some models [e.g., QUAL-ZE]. DOSAG (14) 

RECElV-II, WQRRS (14), SSAM IV (81, HSPF (15) 

include options which allow the user to “switch off” 

many of the model constituents when running the 

model. This bypasses the computations for 

parameters which are of no importance in a particular 

application. 

This section discusses some of the water quality 

sampling considerations which are basic to all WlA 

studies. Sampling considerations which pertain to 

particular types of problems(e.g., DO/BOD analyses) 

will be discussed later. 

2.1.4.1 Sampling Locations 

After an initial estimate of the constituents end 

parameters which must be sampled in a modeling 

study, it is necessary to determine where, when, and 

how often the samples should be taken. The minimal 

instreem sampling effort should include the following 

locations (Figure 2-6): 
Figure 2-6. Aocommondod location* for l minimal sampling 

program. 

\ 

i 

\ 

3 

Polnt -2 

Source 

4 6 4 

Kw 

I Uprtream Boundary 

2 Potnt Source 

3 Uprlream of Pomt Source 

4 Mouth of Tributary 

6 Uprtroam of Tributary 

6 Upstream of Nonpomt Source 

7 Downrtrorm of Nonpomt Source 

8 Downrtrorm End of Study Area 

1. 

2. 

3. 

4. 

5. 

Nonpomt 

Source 

8 

7 

Upstream end (headwater) of each stream reach 

and tributary being modeled. 

Mouths of all significant tributaries which are 

not included in the model grid, just above their 

entrances to the main stream. 

Effluent samples of all significant point sources 

before they enter the stream. 

Upstream and downstream ends of stream 

sections where nonpoint sources are expected 

to be significant. 

Downstream end of the study area. 

Water quality data are needed at the upstream 

extremities of all channels in the modeled stream 

system in order to define the upstream boundary 

conditions (i.e., flows and concentrations) for the 

computations. The model starts with these boundary 

conditions and routes the water along the channels, 

srmulating all of the chemrcal, brologrcal, and physical 

processes whrch act to change the concentrations of 

the venous constrtuents. The water quality samples 

at the upstream boundaries also define the background concentrations in the study area before 

additional pollutant loads are added to the stream 

For tributaries which are not explicitly included in the 

model grid, water quality data are needed just above 

their mouths in order to define tributary loading rates 

for all constituents. However, if the flow contributions 

and mass loadings of tributaries are insignificant in 

comparison to the main channel ‘flows and mass 

fluxes (i.e.. less than 5 percent), they can usually be 

omitted from the analysis. Loadingsdue to tributaries 

which are included as part of the model grid are 

computed internally in the model based on the 

specified upstream boundary concentratrons at the 

head of the tributary and the simulated water quality 

changes between the tributary headwater and confluence with the main stream. 

In addition to instream concentrations, effluent data 

are needed to characterize pollutant loadings due to 

all significant point source discharges. These data 

can be obtained from the drschargers. NPDES permit 

holders, and federal, state, and local government 

regulatory agencies. However, it is most desirable to 

collect point source data during the survey, as 

historical data bases may not be indicative of survey 

loads. 

In areas where significant nonpoint source loadings 

are known to exist, both the flow rate and constituent 

concentrations should be measured in the stream 

just above and below the area of the loading. If this 

area is not so large that other water quality changes 

are likely to occur during the travel time through the 

area, it is reasonable to assume that the changes in 

concentrations are due to the nonpoint sources and to 

use these differences as a basis for estimating the 

loads. 

Water quality data should be collected at the downstream end of the study area for calibration and 

verification. While a singledownstream station isthe 

minimum requirement for short stream sections with 

no major tributaries, additional sampling stations are 

desirable to provide more spatial data for calibrating 

and verifying the model. Logical locations for additional stations are biologically sensitive areas, areas 

where water quality standards may be violated, areas 

just above major tributaries or point source loadings, 

and areas where stream changes may significantly 

cause changes in kinetics. The latter locations allow 

independent calibration of stream sections between 

each tributary or discharge based primarily on 

biochemical processes within the stream without the 

complication of water quality changes associated 

with major inflows or discharges. Water quality 

below tributary junctions or waste discharges can be 

2-7 
directly computed based on data sbove the junction or 

dischsrge site and the tributary or point source 

loading rates using simple flow weighted mixing 

computations: 

Cb = 

cLC.+Q, cc e-41 

a.+a, 

where Cb = sversge concentration below tributsry or 

discharge 

C. = concentration in stream above the tributary or dischsrge 

c, = concentration in tributary or discharge 

a. = stresm flow above the tributary or dis- 

&SW-O 

cl, = t rbutsry or drschsr .e flow rota 

These values can then be used OS upstream boundary 

conditions to calibrste the next section of the stresm. 

Since most stream models are one-dimensional, 

water quslity is sssumed to be well mixed and 

uniform over each cross-section of the stream. 

Therefore, samples token immediately downstream 

of a dischsrge or tributary would probsbly not match 

conditions in the model unless they were token far 

enough downstream for complete cross-sectional 

mixing to occur (Figure 2-6) (see Section 3.4 for a 

method toestimate the distance for complete mixing). 

If o stream branches into two separate channels 

moving downstream, it is slso useful to include a 

sampling ststion ot the hood of the brsnch to define 

upstream conditions in esch reach. 

In addition to the above ssmpling locstions which are 

bssed on the stream system configuration snd wsste 

discharge locations, it is desirable to include more 

ststions where significant wster quality gradients ore 

expected, for example, dissolved oxygen sags below 

waste dischsrges. These stations provide data to 

calibrste and verify the ability of the model to predict 

important water quality varistions. The appropriate 

locstions for these additions1 stations are often 

difficutt todetermine in advance. Simplified screening 

calculstions or preliminary model runs can often be 

useful in locating these ststions. Guidsnce for 

determining these locations will be discussed in later 

sections where sampling considerations for specific 

types of water quality problems ore discussed. 

2.1.4.2 Srmplfng Time and F requmnoy 

If possible, water quality sampling should be conducted during periods similar to the critical desrgn 

conditions which will be used in the WLA analyses. 

These genrrslly represent some type of “worst case” 

situation, such as summer minimum flow and 

maximum tempersture conditions. The procedure for 

determining these conditions is described in Book VI 

(Design Conditions) of the waste load allocation 

guidance. The selected design conditions will prob2-8 

ably represent an extreme event such as a 7-day. 

1 O-year low flow (To,01 which occurs on the average 

every 10 years. ‘Direct samplrng of such conditions 

may not be possible and although similar flows may 

occur averaging shorter perrods (e.g., 1 or 2 days) 

each year the sampling period may not be sufficiently 

long to accomplish sll of the program goals. Therefore. 

the semplmg program should be conducted at times 

most likely to spproach these conditions when the 

same water quality processes are importsnt. 

In addition to the calibration data, another set of 

water quality samples should be collected under 

different flow end water quality conditionsfor purposes of model validation. If several flow or water 

qualiry conditions will be evaluated In the WLA 

snalyses, the calibration and validatton samples 

should be collected ot times which will bracket the 

conditions of the analyses. 

The duration and frequency of water quality sampling 

depends to a large extent on whether a steady-state 

or a dynamic model will be used. Because they are 

easier to apply and require less data, steady-state 

models are generally used in WLA analyses. Steadystate models compute water quality conditions 

assuming everything remains constant through time. 

This includes: 

l flows and stream geometry (depths, widths, etc.) 

l meteorological conditions 

l temperature snd quality of the water entering the 

up-stream boundary of the reach being modeled 

(upstream boundsry conditions) 

l temperature, quality, and flow rates of all tributaries 

l temperature, quality, and flow rates of all nonpoint 

and point source loadings 

l rates of all physical, chemical, and biological 

processes occurring in the stream. 

Steady-stste models simulate spatial {downstresm) 

variations in the above factors, but not temporal 

changes. These models are appropriate for predicting 

water quality conditions at different locations in the 

stream when the sbove conditions do not chsnge 

significsntly with time. Since the travel time through 

an impacted stresm reach is generally on the order of 

days, it is reasonable to sssume that hydrologic snd 

meteorologic conditions can remsin fairly constant 

over this period snd to apply a stesdy-state model. 

Sessonal varistions can be anslyred by repeatedly 

running the model for different scensrios, for example 

monthly average conditions, monthly extreme conditions, etc. The msjor limitations of steady-state 

models are that they do not account for continuous 

flow variations or transient events such as storms or 

toxic spills, and that they do not directly simulate the 
Flgun 2-l. Racommondod urnpaling locationr at point oourco8 

Latrrrl M~xtng Zone 

Sampltng Locstlons 

lbt 

St&l View of Rwet 

diurnal dynamics of temperature and oxygen. Some 

quasi steady-srate models are available which simulate these latter effects (e.g., 16.t 7.3). 

Sincesteady-note models assume conditions remain 

constant with time, it is important to conduct the 

sampling progrsm during a period when this assumption is valid. Synoptic surveys [e.g., sampling all 

stations over 1 to 2 days) should be conducted to the 

extent possible so that water quality conditions at 

different locations are not affected significantly by 

changes in the weather or variations in the waste 

discharges. However, since temperature varies diurnally and temperature influences the process rates 

of most biological and chemical reactions, some 

variabilitywill be inevitable in the sampling results. If 

diurnal variations are important (for example, in some 

dissolved oxygen problems where algal activity is 

significant), then a 24-hour survey should be conducted for at least one station (preferably the station 

at the DO sagland usually more. Short-term intensive 

surveys (diurnal measurements over 2 or 3 days) ate 

recommended in all water quality studies, since this 

will provide enough data for sample variability (e.g., 

variances, confidence intervals, etc.) to be estimated. 

The alternative epproech to steady-state modeling is 

dynamic modeling. Dynamic models simulatestrsams 

in the same basic manner as steady-state mockts 

(i.e., they route water downstream and compute the 

physical, ChemiC81, and biological processes occurring in the stream and the resulting changes in the 

water quality parameters). However, in addition, 

dynamic models compute the continuous changes 

which occur over time due to variations in stream 

flows, upstream water quality and temperaturd, 

2-9 
tributary mflows, nonpornt and pomt source loedmgs. 

meteorology, and processes occurrmg within the 

stream. In dynemtc modeling, all of the factors which 

are assumed constant for a steady-state analysis are 

free to vary continuously with time. This allows an 

analysis of drurnal variations in temperature and 

water quality, as well as continuous prediction of 

daily variations or even seasonal variettons in water 

qU8jity. 

Dynamic model studies generally require much more 

detailed sampling programs than steady-state studies. Enough d8t8 must be collected to define the 

temporal variations In water quality throughout the 

simulation period at the upstream ends of all stream 

channels and the major pollutant loadings so that the 

model boundary conditions can be specified. Since 

dynamrc models are used to study transienr events 

such as combined sewer overflows during storms, 

toxrc spills, and diurnal variations in temperature or 

drssolved oxygen, the duration and frequency of the 

samplmg should b8 commensurate with th8 duration 

of th8 event plus the travel time through the study 

area. For toxic spills, one travel time plus the time for 

th8 tr8ijing edge t0 pass iS necessary t0 track th8 

toxicent through the system. For storm runoff problems, the duration of the storm runoff should also b8 

added to the sampling period since the pollutant 

loadings 8nd stream hydrologic response will vary 

throughout the storm runoff period. For diurnal 

studies of temperature or dissolved oxygen, sampling 

at Specified lnterV8jS (1 or 2 hours, for example) 

should be conducted over at least 24 hours. 

Long-term dynamic simulatrons of seasonal variations in stream water quality may b8 impractical. 

Where SeOSOn8l variation is of interest, the general 

practice is to run a steady-state model or 8 dynamic 

model (with short term simulattons) several times for 

different sets of conditions that represent the full 

spectrum of conditions expected over the period of 

interest. Enough d8t8 should b8 collected to characterize the seasonal verietions. 8nd to provide 

adequate data for calibrating and verifying th8 model. 

ff possible, enough d8t8 should b8 COll8Ct8d to cover 

the full range of conditions of the model analysis. As a 

minimum, this should include conditions at both 

extremes of the seesonal range, as Well 8s a few 

intermediate conditions (e.g., monthly averages). 

2.1.4.3 Use of Models in Designing Sampling 

Programs 

Models can be very effective tools in the design of 

sampling programs. This includes both computerized 

models and simple hand calculation techniques. 

Since sampling resources are generally limited, it is 

2-10 

Important to lOCat the Stations in places that will 

prOVid8 the most informatron. Prelrmrnary model 

C8lcul8tlons can be USed to determine the best 

locations for sampling, 8s well 8s the critical trmes for 

Sampling if dynamic analyses are b8mg performed. 

For eXampl8, When analyzing drssolved oxygen 

problems in streams with several dtscharges, more of 

the sampling effort should be allocated to areas 

where Water quality standards are most likely to be 

violated {Figure 2-7). Also, areas where large water 

quality gradients exist should’be sempled more 

thoroughly. These are8s can be determlned with 

Streeter-Phelps type c8lculatlons or simplified computer r. “,“, . r..J. I- 4 “rrr 9s or waste loadmgs which 

are nc : :.:r ._... -3; _ .len be omitted from these 

preliminary analyses(psrticularly if hand calculations 

8re being used). Simple mixing celculstions can be 

used to help determine which waste sources are 

significant. Mixing zone calculations can also b8 

mad8 t0 8Stimat8 th8 distance r8qUlr8d for complete 

mixing of the waste water with th8 stream, and to 

estimateconcentrstion8 within the mixing zone. Rate 

coefficients and model parameters can b8 estimated 

from literature values (18.19.20) before site specific 

measurements are 8V8il8bl8. For importsnt parameters such as the 800 decay rate (KJ, sensitrvrty 

8nafySeS can be performed to evaluate the effects of 

different Kd values on th8 location of the DO sag. 

These analyses should provide enough information 

so that sampling stations can be located on the critical 

portion of the sag CUW8. 

2.1.5 Plug Flow Sampling 

Pjug flow sampling is a type of instream sampling 

where a particular parcel of Water is followed as it 

moves downstream, and samples of water quality are 

taken from the same parcel of water 81 different 

locations. Typically 8 dye (e.g., rhodamine WT) is 

injected into the river and is used to determine When 

to sample at selected downstream locations. Passage 

of the peak dye concentration indicates when to 

sample. Centroid-to-centroid measurements (rather 

than peak-to-peak measurements) are not used 

because centroids are not readily determinable in the 

field. 

Plug flow sampling is particularly useful for r8te 

constant determinations. Suppose, for example, that 

waste loading to 8 river segment is highly time 

variable. By Sampling a particular slug of water as it 

moves downstream, the effects of time variability in 

waste loading can be eliminated. 

Accessibility to the stream or river at multiple 

locations is necessary to implement plug flow sempling. For larger rivers, 8 boat may be appropriate to 
FIQU~ 2-7 Allocation of sampling offort board on preliminary wnalysoa. 

Potnt 

Sourcs 

PollIt 

source 

1 

a 

8 

More lntrnsnm 

Samplrng Here 

----- Swam Standard 

Pow 

Source 

Less Intenstve Samplmg Here 

54 52 50 48 46 

River MIIo. Above Mouth 

move from location to location, while for smaller 

streams, land transportation may be easier. 

Before semples are COlleCt8d, the dye should be wellmixed across the river. Section 3.2 provides guidelmes on the distance required. For large rivers, 

COmpl8t8 mixing Can take many miles, 8nd plug flOW 

sampling would be ineppropriate. 

It is not always necessary, or even desirable, for the 

dye to be injected at the upstream boundary of the 

segment under investigation. The dye can b8 injected 

at some distance further upstream so that when the 

dye reaches the segment boundary, it has attained its 

one-dimenslonal profile. If the upstream boundary is 

8 wastewater treatment plant, the effluent from the 

plant is Sampled at the time the p88k dye concentration passes the plant. 8nd subsequent Samples are 

t8k8n at selected downstream locaiions when the 

44 42 40 

peak dye concentration passes those locations. Travel 

time6 b8tW88n lOCatiOnS are calculated t0 determine 

stream velocities. Two methods for Lagrengian 

sampling are: 1) find peak every 2 hours or so by 

moving boat, or 2) await arrival of peak at predesigneted sites. 

2.2 Sampling Requirements for 

Conventional Pollutants 

2.2. I Gonoral Modeling Approachor 

Most waste lO8d allocations in streams focus on 

dissolved oxygen. Dissolved oxygen dynamicsdepend 

on the interactions Of Several. COnStitU8ntS end 

processes. The constituents include dissolved oxygen, 

cerbonaceous BOD, nitrogenous BOD (emmonia and 

nitrite), temperature. and in some cases phytoplankZ-11 
ton, periphyton, and aquatic plants. The major 

processes include (Figure 2-S): 

l Reaerstion 

a CLOD decay 

l CBOD settling 

a Sediment oxygen demand 

a Nitrification 

l Photosynthesis 

a Respiration 

These constituents and processes are typically 

modeled by a set of coupled ma66 balance equations 

T*LCh .s: 

Oissolved Oxygen 

dOa hO0 

- =K.(Ou,-02)-&L- h 

dt 

- - (11 KM, NH3 

-a6Kw?NO6+(a,fl- arr)A 

Carbonaceous BOO 

dL 

-=-KdL-K,L=-K,L clt 

Nitrogen Forms 

dNH, K 

Yii =-K6~NH6+(a6r-ar~)A+ F 

dNOo 

-= 

dt - KM~ NO2 + KM NH3 

dNO3 

-= Kw2N02- a7PA 

dt 

Atgse 

dA 

- = (p-rdt 

+) A 

12-5) 

(2-W 

12-7) 

(2-8) 

Q-9) 

(2-10) 

For identification of coefficients for these equattons. 

seep. 2-34. 

The aboveequations are sunplified in that they do not 

include the pollutant loading or transport (advection 

and dispersion) terms. All of the process rates are 

temperature dependent. In addition, algal growth 

depandson light, phosphorus, and other nutrients. so 

2-12 

other equations may be coupled to the dissolved 

oxygen equation In an induect way. MlchaeltsMenten type saturation kmettcs are typically used to 

compute nutrient IImitatIon effects on algal growth, 

and often light limitation as well. Other saturatron 

relationships (21) are also used for light limitation. 

Periphyton and aquatrc plants are rarely included in 

w6ter quality models because of the difficulty IVY 

predicting these parameters. When they are, they are 

modeled by equations analogous to those used for 

algae (Equation (2-10)). except that the settling term 

is replaced by a sloughing or nonpredatory mortality 

term. 

The above equations give the general framework 

which forms the basisof all diS6OlVed oxygen models. 

However, many models use a simplified framework 

which ignores or combines some of the processes. 

For example, in systems where photosynthesis and 

respiration are not important, the corresponding 

terms and equation6 can be left out of the analysis 

(e.g., DOSAGl 1221, and SNSIM (231). Simple models 

and hand calculation techniques often lump the 

nitrogen cycle into a single nitrogenous BOO equation 

analogous to Equation (2-6) (e.g., DOSAGl, SNSIM), 

or else combine the nitrogenous and carbonaceous 

BOO into a single constituent representing total BOO 

(24). In the latter ca6e. only the first three terms of 

Equation (2-5) and a total SOD equahon analogous to 

Equation (2-6) are left in the model. 

Even when the nitrogen cycle is not lumped into a 

600 equation, models differ in the number of stagar 

included in the cycle. The complete sequence should 

include hvdrOlv6it of organic nitrogen to ammonis 

and oxidation of ammonia to nitrite and nitrite to 

nitrate. However, most models do not even inclucla 

organic nitrogen as a separate constituent (e.g., 

QUAL-II. DOSAGB, WORM). However, DUAL-2E 

does have organic nitrogen and orgsnic phosphorus 

capability. Many models alro leave out nitrite so that 

ammonia is oxidized directly to nitrate in the model 

equation6 (e.g., SSAM IV). As a result, some of the 

constituents and process rates may take on a different 

meaning since they represent two or more constituents and corresponding decay processes combinad. 

In addition to dissolved oxygen analyses. other 

conventional pollutant problems such as ammonia 

toxicity and eutrophication are sometimes important 

In waste load allocatione. 

Ammonia toxicity 16 due to the un-ionized form of 

ammonia. The un-ionized fraction of total ammonia 

increases with pH and temperature. Figure 2-g show6 

this relationship. Most currently available water 

quality models do not simulate unionized ammonia 
Fi&pura 2-6. PIOC~SHI affecting diarohd oxygen. 

. 

Atmospheric 

01 

1 

R8aersilon Raaersllofl 

\ 

CBOD 

1 Growh 

Dtssolved + 

0, 

t Resprstbon 

q-7iz-j 

SOD 

or pH. Therefore, watie load allocations which invofve 2.2.2 Mod& Dot8 Roqutremonts 

ammonia toxicity must usually be based on total 

ammonia simulation6 u6ing equations 6uch as (2-7) This section summartzsr the data requirements for 

through (2-101 above in combination with field the different types of model6 used to allocate 

measurements of pH and temperature. Unionized conventional pollutants. The modeling approaches 

ammonia concentration can be calculated from range from simple hand-calculation techniques to 

model-projected total ammonia and a relationship complex computer models. Dissotved oxygen analsuch as 6hown in Figure 2-9. yser using Streeter-Phelps type hand-calculation6 

are probabfy the most commonly used technique6 in 

Eutrophication analyses require models which simu- waste load allocation analyses. Simplified methods 

late nutrient and algal dynamics, Phosphorus and are limited for eutrophication ansly6ss since several 

nitrogen are generally the only nutrients conbidered. constituents with complex interactions are involved. 

The major processes include algal uptake, algal However, a few hand-calculation technique6 for 

excretion, sediment release, and nitrification. The predicting algal concentrations snd their effects on 

ma66 balance squations for the nitrogen cycle and dissolved oxygen are described in Chapter 2 of Boo& II 

algae wore given above in Equation6 (2-7) through of the WtA guidance document6 (see Table l-l). 

(2-10). The only additional equation required is a 

Table 2-l summarizes the data requirements for the 

mass balance for orthophosphate, which is typically various hand-calculation methods available. 

The models QUAL-II, NCASI (26). and DUAL-2E are 

dP0, 

-= 

dt (aor - aspIA+ y (2-l 1) probably the most widely used computer model for 

predicting the effect6 of conventional pollutants in 

2-13 
FIQU~O 2-9 Effect of pH and temperatwo on un-loruzod 

ammonia (From (261). 

0 5 lb 1; 26 25 3b 35 

Temperature PC) 

streams. The data requirements for QUAL-2E are, in 

general, the same as most other stream models, 

except models such as DOSAGl which are restricted 

to simple dissolved oxygen analyses and therefore 

require less data. QUALY2E simulates the following 

constitutents: 

Dissolved oxygen 

Biochemical oxygen demand 

Temperature 

Algae as chlorophyll a 

Organic nitrogen 

Ammonia 

Nitrite 

Nitrate 

Organic phosphorus 

Dissolved phosphorus 

Coliforms 

Arbitrary nonconservative constituent 

Three conservative constituents. 

The model equations and process formulations are In 

general tdentlcal to those discussed in Equations (2- 

5) to (2-l 1) for dissolved oxygen, nutrients, and 

phytoplankton. Figure 2-l 0 shows the Interacttons of 

the various constituents, 8nd Table 2-2 lists the 

proc8ss8s which are simulated for e8Ch Constituent 

Tab18 2-3 compares QUAL-2E with Other models 

commonly used in WLA analyses with respect to the 

Constituents SimUl8ted. 

Table 2-4 summarizes the input data requirements 

for QUAL-2E. Note that many of th8 process rates can 

vary with each reach. This feature is useful smc8 

waste characteristics may V8fy between different 

discharges, resulting in differences in th8 BOD decay 

rates and nitrification rates 8t different locatlons in 

the stream. Other process rates such 8s Sediment 

‘xygen demand. phytoplankton settling r8t8S. and 

,eaeration retes mey also vary with distance, since 

these are affected by the hydraulic characteristics of 

the stream. 

QUAL-2E is capeble of running in either 8 Steadystat8 or 8 quesi-dynamic mode. Thedynamic option is 

used primarily for simulating diurnal variations in 

dissolved oxygen end temperature since rhe stream 

flows, point source lO8dingS. 8nd nonpolnt source 

loadings C8nnOt be Varied during the simulation. Only 

the constituent concentretions at the upstream 

boundaries, the met8orolOgical conditions, 8nd the 

resulting w8ter quality response 8re free to change. 

Table 2-5 compares the general featuresof QUAL-2E 

with other computer models used In waste lO8d 

allocation analyses. DOSAGl 8nd SNSIM are limited 

to Steady-Stat8 OO/BOD analyses, while QUAL-2E 

and RECEIV-II can be used for eutrophication analyses as well 8s dissolved oxygen analyses. QUAL-2E 

and RECEIV-II both simulete the effects of photosynthesis, respiretion, and temperature on diurnal 

variations of dissolved oxygen. RECEIV-II is truly 

dynamic since it simulates COntinUOUS temporal 

variations in stream hydraulics and w8Ste loadings. 

QUAL-2E assumes th8Se features remain constant, 

but 8llOWS the m8teOrOlOgy 8nd W8t8r qU8llty conditions downstream Of th8 Upstream boundaries t0 

vary. 

2.2.3 Sampling Guidelines 

2.2.3.1 Constituents Sampled 

The specific constituents which must be sampled, 8s 

well as th8 sampling frequency. depend to some 

Bxtent on th8 particular modeling framework which 

will be used in the waste load allocation a’nelysis. The 

selected model should include all of the processes 

which are significant in the Stream being analyzed, 

without the unnecessary complexity of processes 

which are insignificant. A few prellmln8ry measurements may be useful to define which processes are 

important. 

2-14 
T&la 2-l. Deta Requiremen ts for l4aS Tuhnicfua Deudbd In WIA Guldana Documents l tl Suaoning Manwl 

127) For Adysk of convontlonal PoktWlts 

NgJl PredIctions AlOIl Ptedluionr 

Streetor-Phelps NH, Toxicity wnhout Wtih AlgJt Effects on AJgJI Eflects 

DJts Requrrements Do &tJma C&ulawtsb Nutrmnt Llmrtrt#onc Nutrient Limit8llw tkity AWrJQO D(r on hrd D@ 

i’f)dWUhC Jnd &JOtlW?W &rJ 

Fkrw rotus“ X X X X X X 

V*kUity X X X X X X 

aPh X X X X X X 

CrOU-4OCtiorU~ JNJ X X X X X X 

Ftoach length X X X X X X 

Reaertibon rote codticmnt 

Sediment oxygen demand 

CBOD decay rJtJ 

CBOD -1 rJtJ 

NBOD &c8y rate 

NH, oxidation mte 

oxygen per unit chbrophyil J 

Algal oxygen pmductii rate 

A&l oxygen tBs&Jtiotl mm 

hXtttW?l QfOWth t’JtJ 

i%JJ@rJttOfl fJtJ 

Settling vdocity 

Snuratmg light intensity 

hOJ@bOM hJthJturJtbn CUUlJflt 

Nit-n half-saturabon mrtt 

P?wJphoM to chbrophytl rJtl0 

Nitrogen to cftlorophyil ratio 

Light hrJllWtJ?J 

X 

X 

:: 

xf 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

ii 

X 

X 

X X 

X X 

X 

X 

X X 

X X 

Dail&$aadmtbn X X X X 

X X X X 

Lbpht oxtinctlon codkknt X X X X 

Wrester-Phdps Do calculations ore described in Chapter 1 of Book II of the WLA guidance documents (Table 1-l) and the Screening 

Manual (27). 

OAmmonia toxicity calculations ara described in Chapter 1 of Book II of the W uiciance documenta. 

Wgsl predictions and their effects on Do are discusaod in Chapter 2 of Book II o B the WU guidance documents. 

dFlow rates are needed for the river and all point sources at various points to define nonpoint flow. 

Ybnstituent concentrations are needed at the upstream boundary and all point 8ources. 

‘Chlorophyll a concentrations are also needed at the downstream end of the rssch to estimate net growth rata% 

The absolute mmimum sampling requirements for all 

dissolved oxygen studies should include dissolved 

oxygen, temperature, carbonaceous BOD, and total 

Kjeldahl nitrogen (measure of nitrogenous BOD), 

since these are fundamental to any dissolved oxygen 

analysis. BOD is typically measured as &day BOD 

(BODs). However, a few measurements of long-term 

or ultimate BOD (BODd are also necessary to 

establish the BOD&BODs ratio since ultimate BOO 

is simulated in the models. If a model which considers 

only a total BOD component is selected, the analyst 

should be aware that nitrogenous BOD and carbonaceous BOD decay at different rates, which will cause 

both the composition of the remaining BOD and the 

net decay rate to change as the waste moves 

downstream. Therefore, the total BOD approach 

should only be used in situations where the nitrogenous components of the waste sources are known 

to be unimportant (e.g., less than 10 percent of the 

total BOD). 

In addition to total Kjeidahl nitrogen (TKN), ammonia 

and nitrate (or nitrite plus nitrate) should be measured 

in both dissolved oxygen and eutrophication studies 

for models which simulate the nitrogen cycle. Even if 

they are not modeled, ammonia, nitrate, and nitrite 

2-15 
Feguro 2-10 MJJO~ conrtnuent mteroctionrinOUAL-2E 13) 

hygen 

data are useful for estimating the nitrogenous BOD 

decay rate or ammonia oxidation rate as discussed 

below in Section 2.2.3.2. Ammonia, pH, and temperature must be measured in all studies involving 

smmonia toxicity. In stresms where algae activity is 

significant, diurnal variations in pH as much as 1.5 

units per day may occur. The potential effect of pH 

variation on ammonia toxicity should be taken into 

effect when designing a sampling program. 

For models which simulate algae, concentrations of 

algal dry weight biomass or chlorophyll o should be 

measured. Orthophosphate concentrations and light 

extinction coefficientsjor Secchi depths) will also be 

needed in addition to nitrate, ammonia, and temperature for the algal growth computations in both 

Dissolved Oxygen 

Reaeration 

BOD deuy 

Ammonia oxidation 

Nitrite oxidation 

Sediment oxy~sn demand 

Photosynthetic oxygen ProductiOn 

Algal respirstion 

Advection 

Dispersion 

Carbonaceous BOD 

ZiLQ 

Advsction 

Dtspanion 

Organrc Nitrogen 

Hydrolizes to Ammonia 

Ammonia Nitrogen 

Ammonia oxidation 

Algal uptake 

Algal respiration 

Bedirnanl release 

Advection 

Dispersion 

Nitrite Nitrogen 

Ammonia oxidation 

Nitrite oxidation 

Advection 

Dispersion 

Nitrate Nitrogen 

Nitrite oxidation 

Algal uptake 

Advection 

Dispersion 

Organic Phosphorus 

Transforms to Dissolved Phorphorus 

Phosphate PtmsphanJs 

Algsl uptake 

Algal respiration 

Bediment release 

Advection 

Dispersion 

Phyloplankton 

Growth 

Respiration 

Bettling 

Advection 

Dispersion 

Coliform Bacteria 

Die-off 

Mvectiotl 

Dispersion 

Tamparatura 

Short wave solar radration 

Atmuspharic Long wave radiation 

Beck radiatii 

Evaporative heat loss 

Conduction wittr atmosphere 

A&action 

Dispersion 

Arbitrary Consewatwe Constitutent 

Advectiin 

Disperion 

Arbitrary Nonconservative Constituent 

First-order dbuy 

Arkaction 

Disparsion 

2-16 
ModeINmmeRef-00 BOO NBOO SO0 lamp P P- PO, N N- NH> NO2 N’& Cartim Chl-a ptmklon pH *II TDS bCt*rU 

WQAM 1271 x X x x x X x x x x 

CXXAGl 1221 x X X X0’ 

DOsAG 1141 X X X’ X x** X x x x X X * 

SNSIH 1231 X X X X x** 

OUAL-II (121 x X x* x x X x x x X X X 

ou*rL4* 131 X X x* x x X x x x X X X 

REcEN.II (91 X X x* x X.9 x x x x x x x X X x 

WASP I281 X X X’ x x** x x x x X X X X x x x 

AESOP I291 X X x* x x** x x x x X X X X x x x 

HSPF 1151 X X x* x x X x x x X X a x x x 

nAno3 f3ol X X x** 

FEDBAXO3 1311 X X X0’ 

MIT-DNM X X X. x x x x X X X X 

EXPLORE.1 l32l X X X’ x x** x x x x x x X X X 

WORRS 1101 x X x* x x X x x x X X x x x x X, 

l NBOO ~w,ulMacl II nWhutmon of YnmOnu 

“Temowmun npectfmd bv fmdel users 

Tab& 24. ModollnputParanutmsfofQual-2E 

VDC8bh VWbbh Vnnrbie VWlDbk 

Input Pwrmeter bv- with lime Input Peremeter bv Reach mm Ttm 

Lhuotwd Oxygen Par*moten 

Rewmtxm rate codhciwtr 

O2 wnsumptm per umt NH, oxtilon 

O2 wnsumptwn per unit NO2 oxldat#on 

O2 pmductlon per unit photosynthesis 

O2 cmsumptm per unit mw~rUm 

Se&morn oxygen dunbnd 

CDrbon- s BOO hrwmemn 

CBOO docay rote 

CBOO 8ettlmg rue 

Orpenic Nitrogen 

tfydrolue to ammoma 

Ammonu Pm8moran 

Ammoma oxidatKsn mte 

Benthlc eourc4 mts 

‘Orgmrc &osphorus 

TrDnsformd to dlU. p 

mosphus PWWmete~ 

Bemhac eource mte 

&ytoplmtion Parenmtws 

Mmmmum growh me 

Rnp1mtmn rue 

Settlmg rue 

Nitrogen heIf-uturetion constent 

hoe@horua heIf-seturetlon constent 

Laght helf-seturotlon constent 

Lqhl l xtmcbon codficwnt 

RWo of chkrofahvll l to algal k~mmu 

Nitrogen fmct~on of algal konmu 

Phosphorur tractton of algal komas 

cotitom ParDmotul 

- . Dle-ofl rue 

YOS 

YOS 

Yes 

Y.8 

YOS 

Ya 

Ya 

Ya 

Ya 

YU 

Ya 

Y8l 

Yn 

Y.8 

Nwlanuuvulw CoMt~uDnt PDml?uen 

oawy me 

Muwro4oguDl DUD 

S&r mdmon 

cloud c0v.r 

Dry bulb temperetum 

Wet bulb tempemum 

Wind apeed 

Bwomwic pwssum 

Elevetlon 

Oust attenumon coeflkient 

Evepaatmn coefftcients 

Hydrmhc DUD (WFkw Cuwo Option) 

Gmifiit fur 8ta~~-Row eqwtion 

Exponent (or aege-flow equetion 

l3Mkmw for nkYcity-flow aqwticm 

Exponmtforlfe4ocwtbvraquDtion 

tf@ruk CUD Ikknning’r Equetion Option) 

MenningL n 

Bottomwidthofchennei 

Sido~ofdunnd 

CJunnel dope 

FbwmtD 

Upstrum boundaries 

Tributary mflows 

Point 8ourws 

Nonpom oourcea 

OlVUWXlS 

CoMt~t ccuuwn~lon8 

Inlt*l conditiona 

upstmun boulMmie8 

Tributary mflom 

Pcmt wwca 

Nonpomt souraa 

YBS 

Yn 

Ya 

YOS 

YWS 

YOS 

Y.8 

YOS 

YOS 

YOS 

YOS 

YOS 

Y.8 

YO# 

YOS 

Ya 

Ya 

Ya 

Va 

Ya 

Ya 

Y.8 

Ya 

Y.8 

Yr 

YU 

dissolved oxygen end eutrophication analyses. Some fluxes obtained from light-dark bottle measurements, 

dissolved oxygen models include the effects of algal or by measuring the diurnal DO variations and 

photosynthesis and respiration without actually superimposing them on the daily average concentrasimulating algae (e.g.. 16,17). This can be done in tions predicted in the model, typically assuming a 

many cases by using photosynthesis end respiration sinusoidal relationship. 

2-17 
Table 2-s. Compwbocr of Quql-6 Wlth 0th~ Cottvomtk~~l Pollututt Mod& lJ8od h Wasto Lout Alloutions (Adapted from I1 II. 

Vanablo 

.TunQot .I VariJbillty 

Wmer Oudm, 

LoWnp Twmsof spmul Wetet Parameters Procease Sbmuleted 

Mow Wetwcbalitv I+@rwIla Rae- Loada Dmenrmnr Bo6, Chemcal~~ologcel Phywcab 

OOSAG-I Steady-state Stady-etete No mukipde l-0 strewn DO. CBOD. NBOD. 1rtQrber deuy Of ddut~on. 

point newti conuwtiive NBOO. CBOD. cou- l 6v~won. 

soumn Plow remrmmn 

SHSlM Steuiv-stme Steady-umo No nwltipk l-0 UreaIn DO. CBOD, NBOD. wnurve- let-order decay 01 ~IIUUOI-I 

pdm notwork live NBOD, CBOO. cou- edvect~. 

wuras& pled DO. benthK maemtmn 

-nt CbIIJl’Id (Sl. PhOtOuurces syrl1hesl8 ltl 

OUAL-II Steady-state Steadptme No multiple 1-o DO. CBOQ. tempermum. rm- letorder decay d dilutnm. 

W &fWIlK poim Fszrk mania. nitmte. ntttite. algae, NBOD. CBOD. cow bckmctm. 

wufas& @mQhao. wlrfolmr. non. d0d w. knthK -Non. 

nonpolnt -lvs wbotarua. ckmmd lsl. CBOO hoa 

souras rnmb c0nunm 811b- utmng (s). brlbnce 

nutrnnt-olgel cycle 

WCEN-II mm* Dytume Ye8 mukiple 1-o strum DO, CBOO. ammonu, nitrote. lste docay of dilmon. 

0oif-l 

aoumes 2% 

fmtwork or nitrlte. totA nitrogen. phos- CBOO. an~pki DO. a&action. 

Wdl- duW wntomu. l bw. tmtthic demmd rewrotmon 

mixed Ucinitv, one metal bon Id. CBOD uttling 

--w Id, nutdent-elgel 

cvck 

2.2.3.2 Field Data Used to Estimate Model 

coefficients 

Besides sampling for the constituents to be aimufated, additional measurements may be necessary to 

help quantify the various co&i icients and parameters 

included in the model equations. Coefficient values 

can be obtained in four ways, 1) direct measurement, 

2) estimation from field data, 3) literature values, and 

4) model calibration. Model calibration is usually 

required regsrdle8s of the selected approach. However, coefficients which tend to be site specific or 

which can take on a wide range of values should 

either be measured directly or estimated from field 

samples. This could include the following parameters: 

l Carbonaceous 600 dewy rate 

l Carbonaceous BOO settling rate 

l Ammonia oxidation rate (nitrogenous BOD decay 

rate) 

l Sediment oxygen demand. 

Carbonaceous BOO decay and settling rates can be 

estimated from field data by plotting CBOD measurements versus travel time on semi-log paper. The 

decay rates are estimated from the slopes of the lines 

(Figure 2-11). Slope calculations should be limited to 

reaches where tributaries are negligible. In situations 

where CBOD settling is important, a two-stage curve 

usually results, with a steep slope on the first part and 

a more gradual slope on the wcond part (Figure 2-l 2). 

The first part of the curve gives the total removal rate 

When both settling and decay are significant (K,], 

while the second part generally represents CBOD 

decay after most of the settling has taken place (Kb). 

The sattling rate (K,) can then be estimated from the 

Z-18 

difference between K, and Kd. Carbonaceous BOD 

decay rates can also be measured in the laboratory 

using nitrogen inhibited teats or calculated by other 

techniques (33), but the above approach is generally 

preferred since it reflects the actual conditions 

measured in the field. 

Figure 2-11. Exam- computation of total BOD removal 

rate. K,, bawd on 800 moasuwnonts. 

Lo = 2 3 (0 6) 

0 

t 

Pomt Source 

2 4 6 a 10 12. 

Mde 
Flgurs 2-12 Procedure for estimating K, and K, from BOD 

me8surements 

a 0’5 1'0 1’5 2’0 2‘5 

Time 01 Travel. Days 

Ammonia oxidation (or nitrogenous BOD decay) fate 

coefficients can also be esttmated from field data 

using the same graphical technique. Total Kjeldahl 

nitrogen (TKN) rather than ammonia is generally 

plotted, since TKN includes both hydrolyzable organic 

nitrogen and ammonia, both of which will uhimstely 

be oxidized to nitrate. Unfortunately, ammonia concentrations are influenced by algal uptake and 

respiration in addition to oxidation, so these processes may affect the slope of the curve. Similar plots 

of nitrate versus travel time can be used to provide a 

second estimate of the ammonia oxidation rste, but 

nitrate is also influenced by algal uptake. Unlike 

CBOD, most water qushty models do not include 

separate components for settleable end non-settleeble NBOD. If the model does include sepsrste 

formulations for NBOD settling anddecay, the settling 

r8te can be estimated using the procedure above. 

Sediment oxygen demand(SOD) should be measured 

in situ in situations where it is 8 significant component of the oxygen budget. This is most likely to 

occur in shallow streams where the organic content 

of the sediments is high. The significance of SOD ten 

be evaluated by comparing it to the carbonaceous 

BOD and nitrogenous BOD fluxes. For example, SOD 

can be neglected if: 

and 

Ksoo h << K,,, NH, 

Measurements should be taken both upstream and 

downstream of the waste discharges, since the 

bsckground SOD will probably be lower than the SOD 

in the ares impacted by the discharge. 

In addition to the above model parameters which are 

determined primarily from the results of field sampling surveys. several other rate coefficients can be 

measured in the field. For example, stream reaeration 

rates can be measured using tracer techniques 

(34.35.36.37.38). However. the usual procedure is to 

rslect an appropriste reaeration rate formula e.g., 

(39,40,41) and compute the reaeration rate 88 a 

function of the hydraulic characteristics of the stream. 

Most computer model&provide several options for the 

reaeration rateequation, since many of the equations. 

are a!$;.:Ptr!n rrc+ iruer certain ranges of depth and 

v&city 81.9 QI.IAI -2E. DOSAGS, RECEIV-It. and 

WQRRS. 

A8 mentioned rbove. algal photosynthesis and respiration rates can be me8SUred using light-dark bottle 

techniques. However, it is usually more convenient to 

estimate these rates by model calibration using field 

measurements of diurnal variations in dissolved 

oxygen and spatial and temporal variations in algal 

concentrations. 

Table 2-6 summsrizes the methods typically used to 

determine the values of each model parameter in 

Equation8 (2-5) through (2-11). 

2.2.3.3 Sampling Locations 

The general model-independent sampling locations 

discussed in Section 2.1.4.1 (i.e., upstream boundaries, tributaries, point and nonpoint sources, etc.) 

ore the minimum sampling requirements for atl 

conventional pollutent studies. in addition, enough 

nations should be sampled to characterize the shape 

of the dissolved oxygen profile below each mejor 

wastesourceindi8solvedoxygenstudies.Aminimum 

.of five or six stations are necessary to define the 

rhape of a typical DO sag, assuming the location and 

extent of the sag curve are known in advance. Since 

this is rarely the case, a few more stations (2 or 3) 

should generally be included so that at least one 

station is near the dissolved oxygen minimum. It is 

important to sample this region since this will be the 

area where water quality standards are likely to be 

violated. Where violations exist, more intensive 

sampling should be conducted in the sag region to 

determine the extent of the violations (Figure 2-7). In 

general, more sampling effort should be a(locatad to 

those waste discharges which have the moat impact 

onthestream.Thesecanbedeterminedbycomparing 

the mass fluxes of CLOD and NBOD with the corresponding ambient fluxes in the stream. In many 

cases, the DO sags from different discharges will 

overlap, reducing the total number of sampling 

locations required. 

2-19 
Tabk2-6. M8thedstorllemdhgcamcbmlVJwrhDbutved oXrfF~EU-W=thMO&l Pw8m#rr SVWlbOl Method of Deterrnindlon 

Arnrnoni8 Por8mum 

hmno4l&oxidrtiocl~ 

Benthic sourat rate 

Nitrite Pammerwa 

Niwita oxidation ram 

-- 

Benthic source rata 

mytopt8nkronP8Nmerers 

GroWh rat0 

Ruphtim me 

setttingna 

Nitrogentruthotalgalbbomau 

PhOSpbUSfNCtblOf~l#BlbiOtlUU 

liatf-saturation amstmt8tvrnutMnts 

Saturling light intmsity a hatfCompute OS I function of depth and velocity using an appropriate formula. or measure in field using tracer techniques. 

Constant food by biochemical Uoichiometry. 

constmt fixed by chemical stoichiometry. 

Literature wIuu. modal calibration md mwsuranent by light to dark 

bottles md dumbon. 

Liior8turr values and mod01 ulibation. 

In situ rne@suwnont and modal ulibrotion. 

Ptot CBOD rrwsurernents on semi-log paper or measure inCboratoty. 

Plot C800 moo----enr r-- -+hg paper and estimotr from rteop 

part ot curve. 

Ptot TKN meuu~~~~ents and NO, + NO1 meuurunmts on semi-~ 

Ei calibration. 

Uu literrtun valua and ulibrotion, tina this me b much fastor than 

the ammonia oxidation r8te. 

Literatum values md model calibratii, or meawra~nfWdu&ngIightdark bottto tmchniqwa 

LhterUum wluea and model glibration. or maasun in field using lightdark bottle techniques. 

Lltemturo values and mode! calibration. 

Litwoturr values md model olibation or Momtory dmtermiwtions 

from fiebd samples. 

Literature values and model ulibrotion or l&oratory d8tormirutiaw 

from fM umpka 

Lltwoturr values md model ullbration. 

Liiaturr vrluu l d m0ckl calibration. 

uturetion constant tar light 

Note: Liiatun vahbos for mod01 coMk&ts am avrilable in ref. (18, 19, 201 

As discussed in previous sections, l implifiod 

Streetor-Phelps calculations or prslimlnary model 

runs may be useful estimating the location of the DO 

sag prior to sampling. The total length of the sag 

region can also be estimated by conridaring the BOD 

decay rate along with the travel timos and stream 

vrlocitisr below the discharge (Figure 2-13), since 

BOO decay is generally the major procass removing 

oxygen from the nream. Howewr, this latter information doat not provide any information on the 

location of the DO minimum. 

All of the major water quality parameters of interest 

(DO, CBOD, TKN, WI. NO% POC temperature, pH, 

etc.) should be measured at each ststion in the 

sampling natwork. Some constituents, however, msy 

2-20 

be unimportant at cenain locations, i.e., BOO in the 

area of recovery (past the sag point). Algal measuremoms may not beg necesrary a! all stations in areas 

where the sampling grid is close, for exnmpk, if 

intonaive sampling is conducted in the critical region 

of the DO sag, since algal concentrations should not 

change significantly over small distances. Sedimentrelated processes such as SOD only need to be 

measured at a few locations. These locations do not 

have to coincide with the locations of the other water 

quality samples. Rnthmr, they should be located in 

areas which will characterize the diffsrencea in 

sediment characteristics throughout the study area. 

Typicrl Locations would be downstream of a major 

discharge to define the SOD in areas where significant settling of BOD occurs, and a site away from the 
Figun 2-13. SOD decay tnmor for variour decav rater fFrom I1 1 )I 

Percent Remsmlng = ema’ 

0 2 4 6 6 10 12 14 16 18 20 

influence of the discharge to characterize the background SOD. Figure 2-14 shows an example of the 

sampling locations for a typical dissolved oxygen 

snalysis. 

2.2.3.3.b Sodlment Oxygen Demand 

Measurement Strategy 

The selection of sampling locations for SOD measurement is not usually quantitatively addressed by 

water quality modelers. The first step is to determine 

which stream reaches should be selected for SOD 

measurement, and then outline a strategy for determining the measurement frequency for the selected 

reaches. 

In developing a strategy for SOD measurement, it is 

logical to assume that those factors important in 

establishing model reaches or segments are also 

relevant to selecting SOD measurement sites. The 

more important of these factors are: 

l Geometric-depth, width 

l Hydraulic-velocity, slope, flow, bottom roughness 

0 Water Quality-location of: point sources, nonpoint sources runoff, abrupt changes (large gradients) in DO/BOD concentrations, tributaries, dams 

and impoundments. 

The most important factor for SOD is likely to be the 

location of abrupt changes in DO/BOO concentrations. 

Tome. I (days) 

In the absence of historical water quality information, 

it is best to assume for planning purposes that SOD 

should be measured in each model reach. This 

recommendation is particularly important in rivers 

and streams where significant DO deficits occur. In 

these cases, it is important that the modeler obtain 

sufficient data to independently account for the 

effects of point sources and SOD on water quality. 

Lumping instream BOD decay for example, with SOD 

is not good modeling practice and should be avoided 

in models used for waste load ellocation. 

As a practical matter, however, this recommendation 

is difficult to implement completely due to a number 

of financial constraints imposed during modeling 

studies. For these situations, it is recommended that 

ths partially calibrated model be used to determine 

which stream reaches(segments)are critical in terms 

of DO concentration. SOD measurements can then 

be concentrated in these areas. 

The modeler should also be aware that the sensitivity 

of DO to SOD (and other model mechanisms) can 

change significantly when forecasts are made at the 

7010 flow (or other worst case conditions). Typically, 

the model is calibrated with water quality data 

collected at flows higher than the 7010 flow. It is 

possible in this case that the DO sensitivity to SOD is 

low, and the modeler might elect to reduce the 

number of SOD measurements accordingly. This 

action becomes inappropriate if the stream DO 

sensitivity to SOD increases at the longer travel times 

usually associated with the ato flow. 

2-21 
Fqure Z- 14 Example samplmg network for a dwsolved oxygen analysis 

Kev 

- Waste Discharge 

0 Water Qualltv Sampleample 

l SOD Measurement 

la) Aerlal View Of Rwer 

6 

2 (b) Ma~rured DO ProfIle 

Rwer Dlstsnce. Moles 

Once critical reaches are defined, several considerations that should be addressed by the modeler include: 

measurement technique, measurement precision. 

and measurement frequency. 

Although it is not the purpose of this handbook to 

review SOD measurement, it is important to note that 

there is a controversy regarding the accuracy of 

appropriate laboratory based procedures when com2-22 

pared to preferred in-situ methods (18.42). There is 

growing evidence, however, that laboratory based 

procedures can be used as a reliable surrogate for 

in-situ measurements (18). These data would further 

suggest that besin specific correlations of laboratory 

SODS with in-situ SODS are credible alternatives to 

extensive in-situ measurements. In this case, the 

modeler would collect the data to develop the 

correlation at one location and then rely upon the less 
expensive laboratory technique for remaining stream 

segments. This optlon would be especially advantageous for large basins with similar sediment 

charactertstics throughout. 

There IS some data available for SOD measurement 

precision for both m-situ and laboratory methods 

(42,43,44,45). To a large degree, the precision is a 

function of the experience of the field crew or 

laboratory analyst. For in-situ work with an experienced crew, a precision defined by the coefficients of 

variation of multiple measurements could be as high 

as f40%. With additional field experience, the 

preclsron should consistently improve to the f20% 

range. Laboratory precision is usually better than insitu precrsion.and as a rule in the range flO% to 

f20%. It IS recommended that measurement crews 

pay close attention to measurement precision in 

model studies used for wasteload allocation. Five 

duplicate measurements at one location prior to 

extenstve SOD work throughout the basin are edvisable to define this potentially important factor for 

model calibration Reference (16) presents guidance 

for both laboratory and in-situ SOD methods. 

Since most water quality models require that SOD be 

specified as a single value per reach, the input value 

must be an average for the entire reach. For large, 

slow moving rivers a minimum of 2 to 3 measurements per reach is recommended and should include 

both mid-channel and shallower stream bank areas. 

One measurement per reach may be appropriate for 

small, shallow streams if bottom conditions are 

conststent within each cross-section. Visual observatrons of the streambed should provide the modeler 

with a basis for this judgment. For all streams, 

however, dupllcatlon of at least 10% of all SOD 

measurements is recommended for quality assurance 

purposes. 

The final point to consider is thatSOD may vary with 

season. This observation is particularly relevant to 

some estuarine and impoundments dominated by 

algal activity and/or oxidation of organic and inorganic nutrients by benthal microorganisms, both of 

which may occur seasonally. The modeler should 

thus be aware of this potential concern and structure 

the SOD measurement times accordingly. 

2.2.3.4 Sampling Time and Frequency 

The general model-independent sampling concerns 

discussed in Section 2.1.4.2 aredirectlyapplicable in 

conventional pollutant studies. Most WIA analyses 

use steady-state models, except in somecases where 

diurnal varrations in oxygen are important or when 

long term eutrophication analysesare necessary. The 

analyses are typically conducted for a low flow 

condition with a high summer temperature since 

dissolved oxygen problems are usually most severe 

under these condmons. Procedures for selecting the 

approprrate flow and temperature condltlons are 

described in Book VI (“Design Condlttons”) of the 

WLA guidance documents (see Table l-1 ). The 

sampling program should be conducted durmg the 

time of the year that most closely approaches the 

conditions to be used in the analysis. Samples should 

be collected during a period when weather, waste 

loading, and stream flows are expected to remain 

approximately constant. If possible, a short-term 

intensive survey should be conducted In which 

several samples are collected at each statron at 

different trmes of the day over a period of 2 or 3 days. 

Thrs approach provides enough data to accurately 

defmethe average DO profile, as well as the variability 

In the profile (Figure 2-15). 

Diurnal variations in dissolved oxygen can be i nportant in streams when phytoplankton, periphytun, 

or aquatic plant densities are high, or in streams 

which have large diurnal variations in temperature 

(5OC or more). In the first case, the DO variations are 

due to photosynthesis and resplratron, while in the 

second case the variations are due primarily to the 

effects of temperature on DO saturation. Photosynthesis and respiration produce marlmum DO concentrations in late afternoon and mintmum concentrations in early morning. Temperature variations result 

in essentially the opposite effects, minimum DO 

levels in mid afternoon and maximum levels at dawn. 

Figure 2-16 shows examples of two rivers in which 

these effects cause diurnal variations of about 2 or 3 

mg/l. These could be significant if the background 

levels were close to the water quallty standards. 

If diurnal variations are important, a dynamic model 

or a quasi steady-state modal which simulates these 

effects should be used in the WlA analysis. Proliminary sampling over a 24-hour period at a few 

stations should first be conducted to determine if 

diurnal effects are significant. The significanceof the 

variations depends on the context of the problem. For 

example, if the daily average DO concentration is 

around 5 mg/l or less, then a diurnal variation of less 

than 1 mg/l could be very important with respect to 

meeting water quality standards, while if the average 

DO concentration IS around 10 m&l, then diurnat 

variations of 2 or 3 mg/l may not matter. However, 

these latter variations would be important if future 

projected waste loads were being analyzed since 

these loads could lower the ambient DO levels in the 

stream to a point where a 2 to 3 mg/l diurnal 

fluctuation could violate standards. If preliminary 

sampling indicates diurnal variations are important, 

then the sampling program should include 24-hour 

sampling for dissolved oxygen and temperature at all 

of the key stations. As a minimum, these would 

include the upstream boundary, all major tributaries, 

and a few stations near the low points of the major DO 

sags. If there is reason to suspect that the significant 

diurnal variations in characteristics of the waste 

2-23 
Figure 2-16. Rorukr of l rhort-term intonrtw survey to l rteblirh the drrrolved orygen profile (modified from Clrrence J Velz. 

Applied Swoam Smirarion. copright c 1994 by John Wiley & Sons. Inc.).1471 

-A Stotlons 

Dtssolved Oxygen Sample 

- Observed Mean Value 

E 9ti Confidence Range 

20 19 18 17 16 15 14 13 12 11 10 9 9 7 6 5 4 3 

Mtles Above Mouth 

Figure 2-16. Daily dimdwd oxygen variation in two 

straomr (From (27)). 

Photosvnthesls 

And Reeplretlon Wvmsn Creak. CA 

August 6. 1962 

Average 10 1 .mg,‘I r-- 

May 31. 1959 

a- Average 10 4 me/l 

& I D900 I 12ODN , 1500 I 1900 1 2100 L2400 L 0300 I D6DD 

Hourt 

discharges will occur, then the discharges should be 

sampled. These locations satisfy the minimum requirements of defining the boundary and loading 

conditions plus a few calibration stations in the 

critical portions of the DO sags. However, additional 

stations would also be desirable, for example, upstream of the tributaries and waste discharges, and at 

several locations along the major DO sags. As with 

the other data. two sets of sampling data ere required, 

one for calibration and one for verification. The 

diurnal sampling should be conducted at the same 

time or as close as possible to the rest of the water 

quality sampling. 

2.3 Sampling Requirements for Toxic 

Pollutants 

2.3.1 htroduction 

Thousands of toxic pollutants are discharged into 

rivers across the United States. The toxicants zan 

arbitrarily be grouped in many different ways(e.g., by 

use, by quentity produced, by volatility, or by mdecular structure). For design of stream surveys, the 

following categorization is convenient: 

Towcants 

/ \ 

Orgamcs Metals 

/ \ / \ 

Strong Moderate To Strong Moderate To 

Adsorptbon No AdsorptIon Adsorpt Ion No Adsorpt Ion 

To Sediments To Sediments To Sediments To Sediments 

Sampling requirements are goner&y more intensive 

when toxicants adsorb to suspended and bottom 

sediments because data are needed to quantify such 

interactions. Since not all toxicants adsorb to sedi: 

2-24 
ments, however, the assumption should not automatically be made that sediment-toxicsnt interactions 

must be quantified in stream surveys. Such an 

assumption can lead to needless expenditures. For 

example, many metals can be transported largely as 

dissolved species if river water pH is low (e.g., 6.0 to 

6.6), and if suspended solids concentrations are also 

low (e.g., 0 to 25 mg/l). These conditions pertain in 

many rivers in the Northeast and Southeast during 

moderate to low flow periods. 

Also, many of the organic toxicants are transported 

predominantly in dissolved form at low suspended 

solids concentrations. Adsorption of organicscan be 

evalun*~~ *:s+r~ l km (dl-wing expression: 

C/Cl = ’ 

1 +Kr,.S *lo-’ 

(2-14) 

where C/CT = fraction of organic toxicant in dissolved 

form, dimensionless 

Kr = partition coefficient, 1 /kg = 0.6.fc.K, 

[See (27)) for details and values of K, 

S = suspended solids concentration, mg/I 

f, = fraction by weight of organic carbon on 

suspended sediments (typically O.Ol0.10) 

& = octanol-water partition co&f icient 

For conditions when C/G approaches unity (e.g., 

Lo.9). adsorption is unimportant, and pollutant-sediment interactions can be neglected. For example, 

suppose f, = 0.03, Ka = 60, and S = 25 mg/l. Then 

1 

““= 1 +0.6~0.03-60~25~104 

= 0.9999 

end adsorption is negligible. 

Equation (2-14) has been used with limited success 

for metals as well as organics. However, the partition 

coefficient KP is ususIly taken as sits-specific for 

metals and local data for pli, suspended sediments 

and other WQ psramters are needed to reliably use 

this approach. 

The fate of organic toxicants can be controlled by 

processes in addition to adsorption such es photolysis, biodegradation, hydrolysis and volatilization. 

Surprisingly, however, the fate of many organic 

toxicants are often dominated by a singleprocess. For 

example, the following organics are commonly discherged into rivers, and are also commonly found at 

Superfund sites: 

l Trichloroethylene (TCE) 

0 Toluene 

0 Benzene 

l PCBS 

l Chloroform 

l Tetrachloroethylene. 

Volatilization probably controls the fate of five of the 

toxicants. while adsorption is most rmportant for the 

remaining one(PCBs). The volatilrration rate constant 

as shown In (27) can be found from: 

1,. 

kz 

where k, = volatilization rate 

ka = reaeration rate of dissolved oxygen 

MW = molecular weight of the organic compound 

that is volatilizmg 

Consider, for example, TCE (M:J\’ = 131 1 111 7. -‘.c:-- 

where the atmospherrc reaeratlon rate IS L.C, day 

The volatilization rate is: 

2 = 1.4/dsy 

Other processes (hydrolysis, photolysis, biodegradation) are insignificant compared to the volatilizatton 

rate. Further TCE has a low K, so that adsorption can 

also be neglected. Consequently, the atmospheric 

roseration rate is the major process that must be 

quantified to predict the fate of TCE in streams. This 

example illustrates that simple approaches can be 

used to allocate waste loads for some toxicants, and 

that instream data requirements may not be prohibitively expensive. 

When multiple processes mutually influence the fate 

of toxicants, stream surveys cannot always be easily 

designed to segregate out the significance of each 

process. However, the composite rate constant can 

be found in the same manner as for the 8OD decay 

rate by plotting toxicsnt concentration versus distance (See Section 2.2). Transformation rates for 

toxicants are usually determined from theoretical 

relationships, or in the laboratory, and the sum of the 

rate constants can then be compared to the instream 

composite rate. Only under special circumstances 

can the individual transformation processes be found 

from a stream survey (see the example problem in 

Section 3.2, for example) or by resorting to more 

elaborate approaches (Hem et al., 1983). 

2.3.2 Model Dete Requhmonts 

This section summarizes data requirements for 

methods that can be used to to determine the amount 

of toxicants that can be assimilated. The methods 

range from simple to complex: 

l screening techniques for organic toxicants end 

metals 

l the MICHRIV model, a steady-stete computer 

model for metals and organic toxicants 

l the TOXIWASP model, a dynamic computer model 

for toxic organics 

2-25 
Tables 2-7 through 2-10 summarize the data requirements for each approach. The first two tebles 

show data requirements for screenmg techniques. 

The requirements in those two tables have been 

further subdivided OS shown below: 

Metals Orgenics 

dilution only is 

considered 

0 

dilution and 

adsorption are 

considered 

0 

dilution, sdsorption, l 

and interactions wrth 

stresmbed are 

considered 

dilution, adsorption, 

interactions with 

streambed, and 

spsciation are 

considered 

dilution only is 

considered 

ditution and 

adsorption are 

considered 

dilution, adsorption, 

and decay are 

considered (often 

volstiliration, dilution, 

and adsorption are the 

most important) 

Depending on the specific srtuatron and resources 

available, the analyst can select an approprrate level 

of complexity, and collect dote accordingly. The 

screening methods ore most applicable when one or 

two sourcesof toxicants are present, when hydraulrcs 

ere simple, and when fate processes are easily 

quantified. 

The data requirements of MICHRIV (Table 2-9) ore 

similar to the most complex level of screening 

analysis. However because MICHRIV is a computer 

model, rirultiple waste sources and spatially variable 

parameters are more easily accommodated. The date 

required for metals and organics- are indicated 

separately, and those associated with adsorption are 

shown with on asterisk (‘1. 

The data requirements for T0Xl’.z~~r i I dole i- iu) 

are presented in a very summarized format. Data 

requirements are greater then for the previous 

spproaches. The analyst should consult the TOXIWASP user manual (4) for specific details. 

TOXIWASP isdesigned explicitly for organic toxicants 

(and not metsls) and requires more technical experData Data are~Used” Remark3 

Hydrrulic D8tr 

1. Rivers: 

l River flow rete. 0 

l Cross-sectional area, A 

l Water depth, h 

l Rerch lengths, x 

l Stream velocity, U 

20 Lakes: 

l Hydreullc residence time. T 

l Mean depth. H 

source curd 

1. Background 

l Metal concentrations, Cr 

l Boundary flow rates, D,, 

. Boundary suspended wlids, 

S” 

* Silt, clay fraction of suspended solids 

l Localions 

2. Point Sources 

l Locelbons 

l Flow rate, 4, 

l Metal concentration, CT* 

l Suspended wlids. S, 

2-26 

D, R, S. L 

D. R. S 

0. Ft. S. L 

R. s 

R. S 

An wcurete estimation of flow rate is very impomnt bemuse of 

dilution consideretions. Measure or obtain horn USGS gege. 

The overage water depth is cr oas-eutionrl area divided bv surface 

width. 

The required velocity is distance divided by trove1 time. k can be 

wproximated bv Q/A only when A ir representative of the reach 

being studied. 

L 

L 

D. R. S. L 

D, A. S. L 

D. R. S. L 

L 

D. A. S. L 

D, A. S. L 

D. R. S. L 

D. A. S. L 

D. R. S. L 

Hydraulic residence times of lakes can vary wewnslly as the flow 

rates through the Iakee change. 

Lake residence times and depth@ nre used to predict tiling of rbwrbed metels in lakes. 

Background conuntrrtions should generally not be set to zero 

without justification. 

One important reason for determining suspended wlids concentra. 

trons is to determine the di concentration, C, of metels, 

based on CT, S, and Kp. However. if C is known rlong with Ct 

rnd S, this information can be used to find &. 
All 

s. 1 

R 

E 

T&a 2-7. (Continwd) 

Data 

Bed Data 

l Depth of contamination 

l Porosity of sediments, n 

l Density of solids in sediments 

le.g., 2.7 for sand). p, 

Calculation 

Methodology Where 

Data are lJ&* Renurks 

Fortha scraoning l nalysb, the depth of contamination is most useful during a period of pro+ongod scour wn metal is being input 

into the water column from tha hod. 

l Metal concentration in bed 

durmg prolonged scour peried. Cn 

Derived Parameters 

l Partition coefficient, Kp 

l Settling velocity, w, 

l Resuspension velocity. w, 

Equilibrium Modeling 

Tha fwtltion cwfficiatM is a very important psrameter. Site-specific 

~ination is p&or&b. 

T)rb pWsfMtor is dOrivod bnod on wspmndsd solids vs. dbtance 

proflk. 

Thbpumtlotarb-bwmdofl wspondd so+ids vs. dbtance 

proflb. 

Water quality characterization 

of river: 

‘PH 

l Suspended solids 

l Conductivity 

l Temperature 

l Hardness 

l Total organic carbon 

Equlllkium modsling is squired only if prmdominrnt metal spacbs and -imated solubility controb are nooded. 

water quality crftorb for Inany nutals srs koyod to hardness, and 

sHowabb B im wfth incmuing lurdnus. 

l Other major cations and anions 

l D - dilution (includes total dbsotved and adsorbed phns oonantration prodictions) 

f? - dilution and resuspension 

S - dilution and suttling 

L - lake 

E - equilibnum modeling 

Tabh id. -d-v f=~Agpro#)lkrTorkchgmbehmverst2n 

Methodologywhw 

Data Data sm Undo Runarks 

Riwr Hydr8ulic Data 

l flow rate, Cl 0. DA OAK &I wcumto atlmato of flow rata b wry imporont baaur of dilltion.whbhformcmyoq#u&sbthemostimpottantproassthat 

l Cross-sections1 area, A 0,DkDAK 

9 Water depth, h DAK 

l Reach lengths, x DAK 

l Stream velocity, U DAK 

ldlusmu their fate. Measure or obtain from USGS gags. 

wamrds@hcmInfhMncenb pmcu-8 such es vobtiliz8tkn and 

-. 

U=QIAshouldkusodon)ywhermAb~ofthe 

mmchbdngeMlyzed.- dyetracws,~rmdfrom 

cantddtoantrotddthe~dyebabottumaalodof 

findh valodty Mdtmcttv ss dbtana divided by trovwl tinto). 

Sourw Oara 

t. Background 

l Toxicant concentrations 

l Boundary flow rates 

l Boundary suspended solids 

D.DkDAK 

0. DA. DAK 

DA, DAR 

2. Point Sourc43s 

CutantrMions of organk toxkents nuy k nogligibk in aron not 

i&mtadbym8n. 

~solids8nus0dtoMpdUorfnin0thadbsolvedand 

aduubd phm canantmkuu. 

l lowtions 

l Flow rates, Qw 

l Total toxicant concentration, 

CT 

l Suspended solids, SW 

D.DkDAK 

D.DA,DAK 

0.04 DAK 

Ok DAK 

2-27 
fabb 2d. (Continwddl 

Oats 

Part&Ion Coefficient and Rate 

Constant Data 

Methodology Where 

Data are Used* Remarks 

Stream wrveys can not always be easily dusrgned to calculate rate 

constants or psrtition coefficimnts for toxic organics A step-by-step 

procedure for calculating each rate constant and partition coefficrsnt discussed hem can be found in Mills ef a/. (in press). Input 

date needed to calculate rate constants and partitron coeffictents 

are identified here, and ranges of values for the data are found in 

(27. 499) 

l Solid-liquid psrtition 

coefficu3nts. K, 

l Acid-base speciation 

- Volstilization rate 

l Biodegradation rate DAK 

- Hydrolysis rate DAK 

* Photdysis rate 

DA. DAK 

DA, DAK 

DAK 

DAK 

Data requirad: 

- &* octanol-wrter partition coefficient (use literature, e.g.. Leo et 

a/. , 1971) 

l X&, organic carbon fraction of sand in suspensron ftypically 0.09 

0.05) 

- Xb,, organic carbon fraction of siklay in suspension hypicatly 

0.03410). 

Data required: 

- pH of water 

l K, or Ks. the association constant for the organic acid or base 

(from literature, e.g., (51)) 

Data required: 

- Henry’s kw Constant tfrorn) literature, e.g., (521 

l Straam depth 

l Reaeration rate for dissolvsd oxygen 

l Wind spaad (only for toxicants with small Henry’s Constant, e.g. 

KH 5 10-Y 

Typically, only an approximation of biodegradation rate is obtainable due to factors such as l daptabihty to stream environment 

Data requirad: 

* pH of rivrr 

l Acid or base wtatyzd hydrolysis rate constants (from literature. 

e.g.. 63)) 

l Neutral hydrolysis rate (from literature e.g., (53)) 

Data requirad: 

l Solar radiation 

l Water depth 

l Concentrations of light-attenuating substancss khlorophyll a. 

Dot. SSI 

l D - dilution only (total organic in wster column, sum of dissolved and l dsorbsd phases1 

DA - dilution plus adsorption (to predict dissolved and adsorbed phases) 

DAK . adsorption and rate procssses both considered 

TaMa 2-9. wdwiu Modrl Dem ttqhmma (51 

Variable Pollutant Catsgory’ RsmarWOualifications 

Channel Date 

l River flow, Q M. 0 Measure or obtain from USGS gage. 

l Velocity, U M. 0 Measure directly with time-of-passage dye study, (Ref. 1541) or 

compute from area and flow: U = D/A. 

l Cross section ama, A M. 0 Compute from measurad width and depth, or compute born 

velocity snd Row. 

l Reach length, x M. 0 Reaches determined by signifiint morphometric changes, trib 

utrries, or point sourcss; measure from charts, confirm in 

field. 

l Depth of water, h M. 0 Measure directly or compute from cross section ares and maasurcul width. 

2-28 
Tsbb 2-9. (Contfnuod) 

Variable Pollutant Category’ Rsmarks/Dualiflwt~ons 

Loadrng Data 

1. Upstream ‘Boundary’ Concentration 

l Toxiwnt, Cu M. 0 

l Suspended wlids, SW M*, 0’ 

2. Point Sources 

l Flow, Ow 

l Concentration toxicant. Cw 

l Concentration-suspended solids 

M. 0 

M. 0 

M’, 0’ 

Bad and Partrculate Data 

l Thickness of Active Sediment, Hz M*, 0’ 

l So;;o,F,Csntratton in bed, ml 

Solids type 

Sue distribution 

0 Settling Velocity. w, 

l Resuspension velocity, w,, 

l Partition coefficient, Ks 

l Sediment diffusion, K, 

* Volatilization coefficient, k, 

Reaeration coefficusnt, k7 

Solubillty, S 

Vapor pressure, P 

l Photolysis rate, kr, 

Chlorophyll a 

Diss. organic wrbon 

Suspended solids 

SolarlUV radiation 

Near surface rate 

l Biolysis rate, b 

Cell count 

Chlorophyll a 

Hydrolysis rate pH 

Direct measurement of loading data is preferable for WLA modeling. 

Me. 0’ 

M*, 0’ 

Me, 0’ 

Me, 0’ 

M. 0 

: 

0 

0 

Estimate from core samples, measunng vertiwl distribution of 

coniaminsnts; or use typiwl published values. This paramder 

has no effect on steady state results unless signifiwnt dewy 

0 ‘,JII I,; .:;o LJeti. 

Measure or estimate: mz = Ipart~cle density) (I-nl 

Estimate from particle-size distribution and stream turbulence 

coupled wtth published dats or Stokes formula. Measure with 

sedeimsnt traps or in lab. Adjust by wlibration. 

Calibrate to suspended solids data; estimate tram theory. 

Calibrate from dissolved and particulate data. Otherwise, use 

literature values (51 

Uss literature values (5) 

Calculate from theory. 

Use published data (49) 

use pubhshed data (49) 

Calculate from theory (27) or by Actinometsr. 

Meausred by Actinomster at water surface. or inlaboratory (49) 

Laboratory experiment at different pH values or from pub 

lished data (53) 

Ancillary data: temperature 0 

‘M = Metals; 0 = Organica. The asterisk (‘1 indiwtes the data are required only it sdsorption to sediments is important. 

Tab& 2-10. SummuvoftnputDatafbquimd~TDXtWASP 

Category 

Mass Exchange 

Data 

l exchange coefficients 

Volumes 

Flows 

l intetfaGal cross-sectional area 

l river segment lengths 

l volumes of segments 

l flow betwem segments 

l flow routing information 

l piecewise linear approximation of time variable Rows 

2-29 
T8bIa 2-10. (Conthud) 

megon, 

Boundary Condition 

Data 

l m- -ntiorrs 

l phawiw linear rpproximation of time variable fkws 

Forcing Functions l lo8dingmt8s 

l p&awiw line8r l pproxim6tict-n Of time vari8th function 

Constwts l 66const8nt8nquir8d 

Mi8ccAhoous Tin-u Function 

Initial Conditions l mid conc8ntr8th of lzoncmtr8tions. w8ter t8mp8l8tur8,8tc. 

St8bilit-y 8nd AccurKy 

ChtOli8 

tire and resources than the apf~oaches discussed 

previously. TOXIWASP may be an appropriate model 

to use for WLA when: 

l waste loadings (and other boundary conditions) 

are highly variable over time 

l the flow field is highly dynamic (e.g., during a 

storm) 

l other significant parameters (e.g., water tamperature) are time variable 

l detailed sediment-water column interactions are 

required (for toxicants that adsorb strongly). 

2.3.3 Samphg Guidehor 

Profiles of toxicants in rivers, under most hydrologic 

conditions, often approach gradually curved lines, as 

shown by Figure 2-17. Exceptions occur in the vicinity 

of point sources where an abrupt increase or decrease 

in toxicant concentrations may occur. Beceuse toxicant profiles do not exhibit “sag points” as do 

dissolved oxygen profiles, sampling stations can 

usually be moreevenlydistributeddownstream of the 

source. 

Oistance between sampling locations can be estimated based on the relative chanw in toxicant 

concentration desired between the stations. Table 

2-11 summarires travel times requirti for various 

C/Co ratios (ratios of downstream to upstream 

concentrations) and decay rates. Travel times greater 

than approximately 2 days between locations are not 

recommended. 

2-30 

The travel times shown in Table 2-11 can be found by 

solving the following equation: 

t = In (Co/C) 

k 

(2-l 6) 

where t = trawl time between locations where the 

concentration changes from Co to C 

k = first order decay rate, 1 /day 

By selecting a C/Co ratio and an approximate decay 

rate, the analyst can determine the travel time interval 

between sampling locations. Given the travel time 

the equivalent distance between two sampling stations (x) is approximately 

x= ut (2-l 7) 

where U = stream velocity 

t = travel time 

For toxicants that are expected to act nearly conservatively, the distance increment is approximately 

controlled by the longest travel time between sampling points the water quality specialist is willing to 

tolerate, but generally this should be less than two 

days. For toxicants that dewy, rapidly, travel time 

between sampling points are on the order of 0.2 too.5 

days for C/Co ratios of 0.5 to 0.7. This will generally 

correspond to intervals of 5 to 9 km (3 to 5 miles). 
Frgure 2- 17 Tvp~cal concentratron profiler of toxicants m 

rivers 

Pomt Source 

- Flow Drrectron 

Dtstance. km 

{al Toxrcant Prohle That Reflects 

Settlmg Or Decay 

Pomt Source 

- Flow Dtrectron 

Drstance km 

Ib) Toxrcant Profrle Thaf Reflects 

Scourtng Of Contamrnated Sedrments 

Tabha 2-11. TravdThmforVuiousC/CoRmth 

toDWhrmtToxlantDuq 

Travel ?ime (Days) 

k. (l/drvJ 

c/Co 0.05 0.1 0.2 0.3 0.4 0.5 0.6 0.6 1.0 1.5 2.0 

0.9 2.1 1:o 0.5 0.4 0.3 0.2 0.2 0.1 0.1 0.07 0.05 

0.6 - 2.2 1.1 0.7 0.6 0.4 0.4 0.3 0.2 0.1 0.1 

0.7 - - 1.6 1.2 0.9 0.7 0.6 0.4 0.4 0.2 0.2 

0.6 - - 2.6 1.7 1.3 1.0 0.9 0.6 0.5 0.3 0.3 

0.5 - - - 2.3 1.7 1.4 1.2 0.9 0.7 0.6 0.3 

0.4 - - - - 2.0 1.6 1.5 1.1 0-g 0.6 0.5 

0.3 - - - - - - 2.0 1.5 1.2 0.6 0.6 

0.2 - - - - - - - 2.0 1.6 1.1 0.0 

0.1 - - - - - - - - 2.3 1.5 1.1 

Figure 2-l 8 shows profilesof toxicant concentrations 

in a river during two seasons of the year (a summer 

lowflowperiodanda spring highflowperiod). During 

high flow it is assumed that the toxicant is scoured 

back into the water column. to produce increasing 

concentrations with distance. 

Figure 2- 16 Samplmg locatronr for toxrcantr dutrng low 

ffow and hrgh flow psrrod 

Pow 

Source 

Pornt 

Source Trrbutarr 

B 

8 Recommended 

~~‘~~e~~ 

1 

-Flow -\ 

1 1 I I I I 

5 10 15 20 25 30 35 40 4 

Drstance. km 

la) Typtcal Low Flow ProfIle 

Point 

Source 

Pomr 

Source Trrbutarv 

8 Recommended 

Samplmg Locatron 

0 Flow 

5 10 15 20 25 30 35 40 45 

Drstance. km 

(b) Tvprcal Hugh Flow Profrle 

Also shown in Figure 2-18 are suggested sampling 

locations for a minimal sampling program. Sampling 

directly below point sources is not recommended. 

Instead, samples should be collected upstream and in 

the point source (the latter should include a measurement of the discharge flow rate). At least one 

sample per reach (between sources) is recommended; 

two or more samples in one reach help sdd a degree 

of certainty to the observed profile. 

In short reaches on wide rivers, sampling should be 

conducted at several points laterally across a river if 

evidence (e.g., from a dye study) indicates that 

complete lateral mixing has not been attained. See 

Section 3.2 for general guidance on this subject. In 

2-3 1 
one-drmensronal models the predicted concentrations 

are cross-secttonal averages, which can be significantly diff erent from a single measured concentration 

if large lateral concentratton gradients exist across 

the rover. 

When adsorption to suspended solids is important 

(e.g., C/CT < 0.9). suspended solids profiles versus 

distance should be found to determine the significance of settling or scouring of sediments and 

adsorbed toxicants. Figure 2-19 shows example 

profiles of suspended solids during a low flow and 

high flow period, and can be used to help make this 

determmation. 

; a-,r ; lttfing rate (w,) and resuspension rate (w,) of 

.I,. i tids are required for use in WLA modeling, and 

can be generated from the profiles. For settling of 

solids, w, can be computed as: 

w,= - -Hu SS(x) 

X In SS(0) I 1 (2-l 8) 

where w, = settling rate 

h= stream depth 

U= stream velocity 

SS(0) = suspended solids concentrationat a reference location x = 0 

SS(x) = suspended solids concentration at locstron x 

Based on Figure 2-19(a), the approximate settling 

rate between km 50 and km 35 is: 

w,= 

0.5 x0.2 In 

30 x loJ 

x 86400 = 0.26 m/day 

where the depth (0.5 m) and velocity (0.2 m/set) are 

taken from (6). 

The resuspension velocity, w,,, can be estimated as: 

UH ASS 

Wn= mzAx-10” (2-19) 

The term ASS/Ax is the change in suspended solids 

concentration over distance Ax and m2 is the solids 

density in the bed. From Figure 2-19(b), the resuspension velocity IS computed as: 

1 *2-(25 - 12) 

wn= 

0.2*80*10’-10’ 

86400 = 1.4 - 1 O-’ m/day 

The data for velocity (1 m/set), depth (2 m) and 

bedded sediment concentration (0.2 kg/l) are also 

from (5). 

2-32 

F19ure Z-19. Typuxl suspended sollds concentrations 

durtng (a) low flow and (b) hl9h flow porlods 

y 20- 

Flow Duectton 

e 

i 

I 

1 

2 o+ , 

0 5 15 25 35 45 55 65 

Iher Kllomsters 

(a) Suspended Sohds. mg 1. Durmg Low Flow Pcrmd 

5 

s 301 I 

I 1.d.’ +..-“’ -+I 

E 24- 

2 :: la- I 

: 12- 

4.4 /.-ly”f 

T Flow Dlreclron 

8 6- 4 

2 Oi , I I 

0 10 20 30 40 50 60 70 

Awer Kilometers 

Ib) Suspended Sohds. mg,‘!. During Hugh Flow Period 

Equations 2-18 and 2-l 9 should be used cautiously 

since they give only the net settling rate and the net 

resuspension rate. 

Note that the values for w, and w,. are specific to the 

flow regime at the time of sampling. Thus, these 

values can change between the calibration period, 

the verification period, and the wasteload allocation 

period. 

Table 2-l 2 summarizes the topics presented in this 

section. Sampling requirements can be intensive if 

multiple fate processes, multiple point. s0~f~e8, 

sediment interactions, and time vanability need to be 

evaluated. However, if steady-state condition8 prevail, one well quantifiable process controls the fate of 

the toxicant being allocated, hydraulics are at steady 

state, and there is a single waste discharge, then 

stream survey requirements will be minimal. 
Two 2-12. Sumnury of *mpling Guidef&q for Totints 

Swsonal Consider8tions 

l Summer low flow conditions can rewtt in high levels of toxicants in rivers. Even if toxicants tend to be highly adsorptive. 

downstream transport in solution can still be significent due to low suspended solids concentration. This period IS often used 

for WLA analyses. 

l High flow conditions can scour toxicants from streambeds and elevate total instream concentrations. This occurs only for 

highly adsorptive toxicsnts, and elevated loadings can be offset by dilution from high flow rates during wriods of scour. 

Waste Loading Conk&rations 

l Pbirct Sources: Any diurnal variations in loadings should be established. If loadings vrry significantly TOXlWAsP wn be used 

for organics. Othermse multlple simulations with steady state models should be considered. 

l Tributaries: Sampling within tributaries is required if sources that are subject to rllocrtion ore located there. Otherwise. uinding at the mouth of the tributaries to ablish boundary conditions is acceptable. 

l Upncrerp Boundary and CMer &&ground Locutions: 6ackgrwnd concentrations rnd flow rates are required at upstream 

boundaries on rivers and tributaries. Concentratiocls of background organic toxicants ore ofen negligible. Howeve r, background 

metal concentrations can be significz9nt. 

SImpling Lotxtion Consider8tions 

l Sample upstream of point sources. 

l TwLly sample at l-2 locations per re&~, with the stations located below the zone of complete lateral mixing. 

l tf urnplea ere taken at locations where comprete mixing of upstream point sources h# not occurred, severe1 mmphs ecroas 

the width of the stream should be taken and averaged before comparing to one-dimensional model predictions. 

* The maximum recommended travel time between umpling lootions should be less than two &yr for toxicants Hut appear to 

be conservative. 

l For toxiunts with high decay rties, a spacing of 3-5 miles (58 km) between sampling -ions is appropriate. This will vary 

&pending upon fravel time. 

l For pollutants that tirb significantly, depth-overaged wrpended solids profiles should be determined for mh -son analvzed for the waste load allocation. Fairly close sp&ng of sampling stations is recommem (58 km). 

Temporal Considarbons 

l Qmpfing at M hour intemls over a day may be required when: 

- source lwdings are highb time variable. 

- the fates of the toxicants of concern are controlw by tefnperrture dependent pmumses such es voktilizotion and water 

temperature fluctuate considerbly (e.g., 5-1Qc or more over a 24 hour period). 

- photolysis (which depends on solar toditiion) is an important process for the toxicant. 

f&e Consrant umf Equilibrium Proc8ss Consi+wMons 

l Generally rate constants for toxicants are determined based on theoretical considertiions. When muttipk p- are opemtiw, the processes may be difficult to segregate brsed on instream merwrements alone. However, some wpporting instmm 

data ore required Isee Tables 2-2 and 2-3) neverthti. 

l The total rrte constant for toxicants can be determined by plotting concentration vs. distance. Settling and scour am included 

in this approach. 

l The total instreom rate constant can be compared with the theoretical rate constants for validation. 

l For metW if speciution is to be predicted, major cations and onions, plus pli, is required. Aef 65) provides 8pproprime dnr 

for’mrjor rivers through the United States. MEXAMS is a computer model which will make these predictions for arsenic, ud 

mium, copper, lead, nickel, silver and zinc. On a screening level, the methods of (27) un be used foe the seme seven met&s 

plus mercury and chromium. 

2-33 
Coeffments 

where 02 = 

0 “I = 

L= 

NH, = 

NO2 = 

NOa = 

A= 

K. = 

K,, q 

K. = 

K, = 

K SOD = 

h= 

K HI q 

K N2 = 

K BEN = 

c1= 

r = 

v, = 

(11 = 

a2 q 

a3 q 

a4 = 

a5 = 

ae = 

a7 q nitrate uptake per unit of algal growth 

drssolved oxygen concentratron 

drssolved oxygen saturatron concentratron 

carbonaceous BOD concentratron 

ammonra concentratron 

nitrite concentratron 

nitrate concentration 

algal concentration 

reaeration rate 

carbonaceous BOD decay rate 

carbonaceous BOD settling rate 

total removal rate for carbonaceous 

BOD 

sedtment oxygen dem,, w 

water depth 

ammonra oxrdatton rate 

nitrate oxidatron rate 

benthrc source rate for ammonia 

algal growth rate 

algal respiration rate 

algal settling velocity 

oxygen consumed per unit of ammonia 

oxrdued 

oxygen consumed per unit of nitrite 

oxidized 

oxygen produced per unit of photosynthesis 

oxygen consumed per unit of resplrat ion 

ammonla produced per unit of algal 

respiration 

ammonia uptake per unit of algal 

growth 

2-34 
Chapter 3 

Whole Effluent Approach 

3.1 Overview 

Guidelines have been established for the use of the 

whole effluent approach to waste load allocation (6). 

These guidelines are based on information concerning an effluent 's chemical constituents and whether 

single or multiple effluents discharge into the stream. 

The whole effluent approach should be used if: 

• 

• 

• 

• 

effluent constituents are not well characterized 

known effluent constituents have not been evaluated as to potential effects on stream biota 

the mixture of effluent constituents may produce a 

complex (additive. antagonistic or synergistic) 

instream effect 

multiple dischargers may create complicated effluent mixtures instream 

In the case of multiple dischargers, or nonpoint source 

pollution, it may not be possible to characterize the 

chemical constituents of each individual effluent. 

From the above considerations, it might beconcluded 

that only whole effluent testing should be conducted 

in this situation. However, if any of the effluents has 

been characterized as containing chemicals with bioaccumulative, carcinogenic, teratogenic, or mutagenic potential, the USEPA suggests the use of an 

integrated approach where both chemical-specific 

analyses and whole effluent analyses are conducted. 

The chemical-specific approach is discussed in 

Section 2. In this section, the data requirements for 

whole effluent toxicity testing are addressed. 

R= QR 

QE 

The whole effluent approach to waste load allocation 

involves testing of effluent toxicity as well as ambient 

toxicity testing in streams. Two tiers of effluent 

toxicity testing are defined. Tier 1 consists of screening methods and may be used to identify potential 

water quality impact situations. Where this potential 

impact is minimal, further evaluation is not required 

and the process can proceed directly to wasteload 

allocations. Tier 2 effluent testing is used to develop 

the data necessary to quantify potential effluent 

impacts. In some cases, effluent toxicity assessment 

may bypass the screening level and proceed directly 

to the Tier 2 analysis. This determination is made as 

the first step of the screening process. The overall 

process of effluent toxicity testing is presented in 

Figure 3-1. 

Ambient toxicity testing is conducted to identify areas 

in the receiving waters where ambient toxicity exists. 

These procedures consist of exposing test organisms 

to receiving water samples and can be used to 

determine whether or not the effluent has a measurable toxicity after mixing and undergoing instream 

alteration/decay processes. An overview of ambient 

toxicity testing procedures is presented in Figure 3-2. 

3.2 Tier 1 Effluent Testing-Screening 

The first step of the screening process consists of 

determining the amount by which an individual 

effluent may be diluted by stream flow and mixing. 

Effluent dilution ratios(R) are calculated on the basis 

of average effluent flow and the critical low-flow 

conditions in the following manner: 

(3-1) 

where QR =Stream critical low-flow defined by the 

state 

QE = Average effluent flow. 

The determination of effluent dilution under conditions of complete mixing requires information on the 

average effluent flow and the critical low-flow of the 

stream. Effluent flows can be obtained from plant 

operating records or NPDES permits. Stream critical 

low-flow is state-specified and may be based on a 

variety of water quality parameters. The critical lowflow typically selected is the 7Q10. Stream flow data 

vaitable from the USGS’s WATSTOR data base. 

The instream distance required for complete mixing 

of the effluent to be achieved must also be determined. This information is used to determine both the 

need for toxicity testing and the type of testing to be 

conducted as part of the Tier 1 screening procedure. 

Waste water discharged into rivers does not instantaneously mix across the entire channel. Although 

vertical mixing occurs quickly, considerable distance 

is sometimes necessary for complete transverse 

mixing to occur (Figure 2-2). The following methods 

3-1 
Figure 3-1. Overview of effluent toxicity testing procedures 

3-2 
Figura 3-2. Ovwviow of rmbiont toxicity tosting proco. 

dW@S. 

Start 

v 

Chsrsctertstlcs 

Of Each Effluent 

c 

Dllutcon l Analysts 

Chrontc ToxlCltv 

Waste Load 

r * 1 -- -- 

I Permlt Process I 

L -- -- 

CL 

J 

StOP 

can be used to estimate mixing diSt8nCOS. The 

estimated mixing distances obtained using these 

methods can be used to determine the appropriate 

toxicity tests. 

Distances below an outfall where complete vertical 

and lateral mixing are achieved can be estimated by 

the following expressions (656): 

0.4 h’/& for a bottom discharge 

X” = 

0.1 h’/&, for a mid-depth discharge 

(3-21 

and 

0.4 w’/L~, for a side discharge 

Xl q 

0.1 w~/L~ for a centerline discharge 

(3-3) 

where xV q distance required for vertical mrxrng to 

be approximately 95 percent complete. 

feet 

x1 = distance required for transverse mixing 

to be approximately 95 percent complete, feet 

h = sverage river depth, feet 

W = river width, feet 

LACY = mixing coefficients in vertical and transverse directions, respectrvely, ft’/sec 

U = stream velocity, 

The mixing coefficients cz 8nd cY are typically 

expressed as: 

cx = BhU. (3-4J 

8nd 

C” = &U. (3-5) 

where U. = (ghS)“’ = friction velocity, ft/sec 

S = slope, ft/ft 

B = 0.05-0.07, typically 

u = 0.3-l .OO, typically. 

To help estimate xr and xr, Equations (3-2) snd (3-3) 

are plotted in Figure 3-3. The distance to vertical 

mixing (Figure 3-3a) is plotted as a function of river 

depth for two different riverbed slopes. For river 

depths of 3 to 10 feet, xV is typically between 10 to 300 

feet. Even for very deep rivers, vertrcal mixing is 

typically accomplished within 600 feet. For most 

rivers, then, vertical mixing is completed quite rapidly. 

For transverse mixing (Figure 3-3b). x1 is plotted 

against W2/h’.‘, which indicates that river width and 

depth are both required to estimate x,.Typical W’/h’.* 

combinations are between 500 to 5OD0, sothat XC can 

vary from several hundred feet to many miles. For 8 

riwr 100 feet wide and 3 feet deep, for eX8mpl8. the 

mixing distance is likely to be about 2 miles for a side 

discharge. 

For particularly wide rivers, Equation 3-3 is likely to 

overestimate xl, because other factors which enhance mixing are not considered in the equation. For 

wide rivers then, dye studies (see Section 3.4) are 

more likely needed to chsracterire the multi-dimenrional aspects of mixing. 

For the purposes of determining the appropriate 

rcreening teat methods, four categories are defined 

based on the effluent dilution ratios (6): 

category Dilution Ratio 

: 

RLlODDO 

1000IR<10000 

3 100 ~R<lODO 

4 RClOO 

3-3 
Each of these categorres IS evaluated differently 

withrn the whole effluent toxicrty procedure (see 

FiQure 3-l 1. If the effluent IS diluted by a factor of 

greater than 10,000 to 1 and there is a reasonably 

rapid mrx of the effluent outside of the zone of initial 

dilution m the receiving water, then no further 

evaluation is necessary. The effluent IS assigned a 

low priority In the assessment of any potential toxic 

impacts on stream biota. If an effluent dilution is less 

than 100 to 1, then further screening is not conducted; definitive data generation, Tier 2 testing, is 

begun Instead. Thus, the toxicity tests are conducted 

as part of the screening process only for dilution 

categorres 2 and 3. 

Figure 3-3 ZB. . ,-tie Y.I.,.. ,.-A% l ourco dirchwgor required for 96 pwcont wrtiul l nd tmnawma 

miring. 

I” 

S=ODDol 

, Bottom Discharges S=DDcll 

-----‘s = ooOO, 

S 5 Bed Slope 

iI 10 2-o 3b 4-O sb 

Alver Depth Feel 

Ia! Verrwzal Maxlng Dustance 

S=BodSlops 

.- .*’ I 

10 100 loo0 lO.ooo 

(WwYth)‘/(Depth)“, (Feet?’ 

(bl Transverse Mlxlng Distance 

3-4 

The decision concerning the type of toxicity testing to 

conduct as part of the screentng procedure IS based 

on the level of dilution achieved(refer to(6), page 18). 

If dilution is between 1,000 to 1 and 10,000 to 1 

(ditution category 2) or a poorly mixed effluent plume 

is of concern, then acute toxicity tests should be 

conducted. If dilution is between 1,000 to 1 and 100 

to 1 (dilution category 3). chronic toxicity tests are 

appropriate. 

When *either chronic or acute toxicity testing ia 

performed, effluent samples must be collected. The 

selection of sample type (grab or composite) and time 

of collection should be based on information concerninQ vanability of effluent characteristics. Guidance 

for effluent sampling as well as toxicity testing 

methods are provided elsewhere (6.57.58). 

The evaluation criterion for the results derived by 

screening toxicity tests is based on the level of 

observed mortality. If mortality exceeds 50 percent in 

any sample, the potential for toxicity is aS8umed and 

Tier 2 toxicity testing is required. If less than 50 

percent mortality is observed for all samples, the 

discharge should be Qiven a low priority for further 

analysis. 

3.3 Tier 2 Testing-Definitive Data 

Generation 

Once screening has indicated the potentiel for toxic 

impact, further testing is conducted to determine 

whether or not the discharge causes unacceptable 

impact. Initially “baseline” acute toxicity testing is 

conducted using whole effluent and two species of 

test organisms. Then a simple relationship can be 

applied to determine whether to require more data 

(i.e.. additional chronic and/or acute testing (see 

Figure 3-l) or whether to stop testing end begin the 

process of establishing permit conditions. The evaluation criterion for the resutts of theTier 2 toxicity tests 

is given by the following formula: 

LC50 IWC > Level of Uncertainty 

where LC50 = concentration of effluent producing 50 

percent mortslity in toxicity tests 

IWC = lnstresm Waste Concentration 

The level of uncertainty isdetermined by a number of 

factors, e.g.. effluent variability, specie8 sensitivity 

variability and the type of toxicity test conducted. Afl 

of these factors ore defined in (6). If it is determined 

that additional data are required, further testing, 

including acute or short-term chronic testing, may be 

required to reduce the level of uncertainty by etimineting the identified sources of variability in a 

stepwise manner. 
Where more than one effluent is contributjng to toxic 

impact, additional toxicity testing may be required. 

Additional testing is only required if the regulatory 

agency decides not to treat each effluent separately. If 

effluents 8re considered as portions of an interactive 

system, testing must be conducted to ascenain the 

potential for additive, antegonistic or persistent 

toxicity. Either chronic or acute toxicity testing may be 

necessary depending on whether the receiving water 

body is considered to be: 

l “effluent-dominated” or 

a “streem-dommated” 

Guidelines for this determination have been developed end are shown in (6). 

When multiple effluents affect a receiving- water 

system it is also necessarytodeterminethe”reletive” 

and “absolute” effects of each effluent. The appropriate procedure for Conducting these etf luent toxicity 

te8ts is described in the technical support document 

(6). 

3.4 Ambient Toxicity Testing and Dye 

Studies 

Ambient toxicity testing can be used to determine 

instreem toxicity levels resutting from individual 

discharges. The same test organisms used in the 

tiered-testing procedures 8re exposed to receiving 

weter samples collected from selected campling 

stations above, at, and below the discharge point(s). 

Chronic toxtcity tests are generally conducted since 

the primary concern following dilution of the eff bent 

is the effect of chronic, lowdose exposures on the 

aquetic community. 

The number 8nd location of sampling stations should 

be besed on 8 knowledge of the mixing characteristics 

.of the effluent including the influence of other point 

8nd nonpoint sources. The best way to characterize 

the mixing and dispersion of the effluent istoconduct 

dye studies. The informetion developed in these 

studies can be Used to determine which instream 

concentration isopleths correspond toconcentrations 

used in the dilution series in effluent tens (SW 

Sections 3.2 8nd3.3). assuming the toxicants bahsve 

conservatively. 

A widely used dye for this type of study is rhodamine 

WT in 20 percent solution. The dye can be purchased 

as e liquid so that mixing of powder and water is not 

required. Often the dye is not locally available, but can 

be purchased from its manufacturer, Crompton and 

Knowles Corporation, in Skokie, Illinois. 

Rhodamine WT 20 percent solution has a specific 

weight of about 1.19. However, beC8U8e of it6 high 

solubility it mixes rapidly with the river water and 

.soon becomes neutrally buoyent. Consequently, 

mixing of the dye with solvents less dense than water 

(e.g., methanol) is not required. 

The dye should be injected continuously into the 

effluent of the discharger 60 thst It is completely 

mixed with the waste stream when it is discharged 

into the receiving water. The injection rate of the dye 

6hould remsin constant over the durstion of the 

8tudy. Based on the expected study duration, the 

quantity of dye required ten be esttmated, and 

prepar,ed beforehand. When possible, the effluent 

discharge rate should slso be kept constant. 

Some time is required before the dye isopieths attein 

their steady-state concentration6 in the river. Figure 

? -4 p3videa @delinesfqr dirtances of up to 10 miles 

t3lowa di?ochrrrgn Yecau8e of 8tream disparsion, the 

time exceeds the travel time to the location tn 

question. For example, for a stream velocity of 0.3 fps 

snd a distance of 3 miles, approximately 21 hours of 

COntinUOUS release is required to establish steadyttate dye isopleths. The trave) time is 15 hour6 and by 

then the dye has attained ebout 60 percent of its 

steady-stete concentration, based on predictions 

from the advection-dispersion equation using a 

dirparsion coefficient of 600 ftz/6ec. 

Fbw 3-4. Tlnw requ(red for l continuwr retmow of dye to 

roach 8twdyMat8 concentr8tion8 8t wkcted 

locrtkn8 bdow the point of dlwhargo. Noto: 

the curvm8 8ro bawd on l wtutlon to the 

l dvoctlon-dimpordom equation whkh ir ueed to 

pnckt when dye comontntlonawa Q6 pmcont 

of atmody-8t8.t. Imb. 

40-v 

40- V = Stream Vbloctty 

n 32- 

v = 2 0 fps 

0 1 2 3 4 5 6 7 8 9 10 

D~stsncs Below Porn of he Iqectlon. Was 

lnstream sampling should begin upstream of the 

outfall and progress downstresm. Thus, sampling 

near the outfall can commence before downstream 

dye levels have attained steah state. 

Typical backgroundfluoresence in rivers isequivalent 

to about 0.1 &I a6 rhodamine.w, 60 dye concentrations should be above background levels, but also 

within levels calibrated for fluorometers (typically 

leas than 200-300 m/l). Coneequently 8 dilution of 

3-5 
2000 or 3000 to 1 can normally be measured. If 

drlutrons greater than this are requrred for the study, 

two separate continuous releases may be required, 

one usmg a hrgher effluent concentration so that dye 

concentration rsopleths can be measured further 

downstream 

The dye mjectron rate should be selected so that the 

dye IS not visible after it has begun to mix with the 

rover water. The USGS plans dye studies so that 

concentratrons do not exceed lOm/l at water treatment plant intakes and other diversions. If the dye is 

visible, concentrat#ons will be high enough so that 

instrument readmgs will be inaccurate and adverse 

public reaction may be generated as well. 

Figure 3-5 shows example dye isopleths that might 

result from injection into wide and narrow rivers. For 

the wide river the two-dimensional profile can be 

maintained for large distances. 

Figure 3.5 Dye mopls(hr m wade and narrow rivers 

-- 

I Key 500 Dllutlon lsopleth 

I 

--- 

Flow Direction 

I Flow D~rcct~on 

I 

Potentially 

Long 

Distance 

(b) Narrow Fttver 

Dye isopleths should be generated from the point of 

discharge to below the no observable effects level 

(NOEL) as determined from toxrcrty tests. Figure 3-6 

3.6 

shows example limits of observable toxicity. For the 

narrow river, the NOEL extends to a dilution of 

approximately 1010 to 1. Once complete mrxrng IS 

attained the concentration rsopleths change very 

slowly with distance. However the NOEL may have a 

distinct downstream location that indicates toxrcrty IS 

decreasing for reasons other than dilution, as suggested in Figure 36b. 

Figure 3-6. Regions of obwrvabls toxiaty in wide and 

furrow rivers. 

F 3w Dtrectton 

Key 500 - Dtlutdon lsopleth 

I::{:::!:: Fteglon of Observable 

loamy Eftect 

Flow DIrectIon 

I 

4 20 

1 i 

“Oj . 

80 4 

90 

93 

94 

95 8 

t 

1 

Porenrlallv 

Distance 

1010 

1010 

1010 

1010 

1010 

1011 

1011 

1011 1 

(b) Narrow Fhver 

Long 

Figure 3-7 illustrates a typical sampling network for 

narrow and wide rivers. Sampling of dye concentrations at a number of transects is required. For wide 

rivers, samples should be taken from 4 to 5 points on 

the transect. By putting the fluorometer in a boat and 

moving it across the river and starting on the side that 

the outfall is located, the lateral extent of the plume 

can be readily determined. In shsllow rivers. a flat 

bottomed canoe can be used to move thefluorometer. 

On a wide river, sampling may be required only 1 CID 

feet or sobelowthe outfall, even though the river may 

be 500 feet wide. 

The fluorometer can be used to assist in selection of 

downstream transects. Generally, change in dye 
concentration (based on measurements taken on the 

same side of the river as the discharge) Should not 

exceed a factor of three to four between adjacent 

transects sothat detailed concentration isoplethscan 

be generated. 

The following formula can be used to estimate the 

number of required transects: 

N = log (QdQw) 

log RF 

where N= number of transects 

OR = river flow rate 

QW = point source flow rate 

RF = ratio of fluorometer readings between 

two adjacent transects, measured on 

the same side of the river as the 

discharge. 

For example if OR = 500, Qw = 0.3. and RF is specified 

to be 2, then 

500 

log N= 0.3 

q = 

log 2 

10.7 1 1 transects 

Flgurs 3-7 Example sampling locations in wide and nmrow 

flVWS. 

Key 500 -. Dllut~on lmpleth 

l Samplmg Statlon 

Flow DIrectIon 

(al Wtde Rtver 

Flow Dtrectlon 

I 

fb) Narrow Rover 

Once the dye readings along a transect are uniform 

(say less than 5 percent difference between readings) 

then complete transverse mixing has almost been 

attarned. so one reading per transect IS sufflclent 

further downstream. 

Sampling at multiple depths may be necessary just 

below the outfall. Since vertical mixing IS rapld (see 

Figure 3-3). vertical profiles probably are not required 

at a large number of locatlons. The fluorometer Itself 

is the best method of determining if sampling at 

multiple depths IS required. To simplify thts aspect of 

samphng, a preselected standard can be used, where, 

for .example, samples 1‘ foot off the bottom are 

uniformly taken. 

For multiple discharges, ‘ne aye studies &nd procedures outlined above a:e :+G:-.e~ soba~“tely for 

each discharge. The dye IS injected in the downstream 

discharge first, and then at the next upstream 

discharge, and so on. This will prevent upstream dye 

from contaminating earller surveys. 

The delineatron of effluent plume configurations 

using the results of the dye studies provides a basis 

for comparing mstream effluent concentrations with 

the toxicity concentrations determined In Tier 1 and 

Tier 2 toxlclty tests. Where dye study results Indicate 

thal effect-level concentratrons are exceeded instream, amblent toxicity tests should be conducted. 

Receiving-water samples should be obtained from 

sampling locations within the potential impact zones 

to conduct static-renewal exposure tests Sampling 

stations should be placed at instream locations which 

correspond toconcentratlons measured In the dilution 

series in the effluent tests. For example, where 

effluent testing shows the effluent NOEL IS 10 

percent, an mstream statlon should be placed where 

dilution IS estimated to create a 10 percent Instream 

waste concentration. The results of the ambient 

toxicity testing can be used to evaluate the persistence of effluent toxicity and the decay rate of toxicity. 

This supplementary information is of value In setting 

waste load allocations. 

3-7 
Chapter 4 

Example Application 

4.1 Dissolved Oxygen 

Figure 4-1 shows an 80 mile (130 km) stretch of the 

Eel River below the City of Dublin. Also shown on the 

figure are Cache Creek, the Dublin wastewater 

treatment plant. and historical water quality data 

collected during the summer of 1981. The data show 

that dissolved oxygen levels in the river have been as 

low as 3.5 mg/l. The dissolved oxygen standard is 6.0 

mg/l, expressed as a daily average. The state has 

mandated that the municipality reduce their waste 

loadings to be in compliance with the water quality 

standard for dissolved oxygen. Consultants for the 

municipality have been retained to design a summer 

low flow survey so that data can be gathered for a 

dissolved oxygen model of the river. 

Figure 4-1. Eel River and environs showing summer of 

1981 water quality results. 

Before deciding on their modeling approach, the 

consultants first review the historical data. Based on 

the data. they conclude that high loadings of CBOD 

and NBOD from the treatment plant are primarily the 

causes of the depressed dissolved oxygen levels. The 

data show that algal activity has been minimal and 

the river is large enough so that diurnal temperature 

changes are no more than 2 to 3°C. Based on their 

assessment of the problem, the consultants intend to 

use a steady-state approach to dissolved oxygen 

prediction, where the processes of CBOD, NBOD, 

sediment oxygen demand (SOD), and reaeration are 

simulated. 

A 7Q10 summer low flow is selected for the wasteload 

allocation period. A stream survey will be conducted 

during a summer low flow period to provide the 

necessary data to calibrate the model. The model will 

then be applied to simulate the 7Q10 conditions. The 

sampling locations selected are shown in Figure 4-2. 

They include locations to characterize: 

• background levels in the river above the treatment 

plant 

• the treatment plant effluent and tributary 

• the river just prior to mixing with the tributary 

• intermediate locations in the river necessary to 

locate the dissolved oxygen sag and to determine 

the CBOD and NBOD profile 

• water quality at the end of the reach 

Based on historical data, and a preliminary model 

application, the minimum dissolved oxygen level is 

expected to occur near location 4. Locations 3, 4, and 

5 will help to accurately establish the shape of the 

dissolved oxygen sag curve. Location 3 is far enough 

below the treatment plant that the effluent is 

expected to be well mixed before that location; 

consequently multiple samples across a section are 

not needed. 

Table 4-1 summarizes the data that are to be 

collected. Diurnal variations of effluent loading 

(station 2) and of instream quality at stations 3 and 4 

will be quantified. Diurnal variations are needed to 

predict daily average dissolved oxygen levels to 

compare with the state standard. Instream diurnal 

variations are expected to be due to wasteload 

variation, and not to temperature and algal effects. 

4-1 
Figure 4-2. Location of sampling stations on Eel River Additionally, a plug flow sampling event will be 

conducted between stations 1 and 5 to help better 

estimate NBOD and CBOD decay rates. Diurnal 

loading variations are expected to make the range of 

CBOD and NBOD concentrations at specific locations 

quite large that accurate decay rates will be difficult to 

estimate otherwise. 

In-situ sediment oxygen demand rates will be determined at stations 1, 3, and 7. Station 1 represents 

background conditions, station 3 is expected to show 

the influence of the treatment plant discharge, and 

station 7 is located in a recovery zone. 

Because the river is fairly deep (4 ft or greater even 

during low flow), the consultents intend to use an 

historical reaeration rate expression characterized by 

a depth-velocity relationship. Specific tracer studies 

are not planned. The water temperature is expected 

to remain fairly constant over time, so that water 

temperature simulation techniques are not needed. 

Rather, water temperature effects will be considered 

indirectly in terms of temperature effects on rate 

constants and temperature effects on dissolved 

oxygen saturation. Consequently meteorological data 

are not needed. 

The judgment and experience of the consultants and 

water quality specialists employed by the municipality have been combined to design this particular 

sampling program. Review of historical data, preliminary model applications to the river, and understanding the behavior of rate coefficients such as the 

reaeration rate constant, were all used to design the 

survey. 

Table 4-1. Summary of Data to be Collected During Stream Survey for Dissolved Oxygen Waste Load Allocation 

Sampling Station Parameters Frequency Comments 

1. Background station, • CBOD, NBOD, DO, • 1 per day for Station 1 is used to establish background level. 

Eel River above Temperature 7 days 

Dublin STP • Flow • USGS gage 

2. Effluent of Dublin • CBOD, NBOD, DO, • Every 3 hours for The diurnal variability is used to establish daily average 

STP Temperature 7 days loads, and to help explain time variability in BOD and 

• Flow • Continuously DO at specified location downstream. 

3. In Eel River 8 miles • CBOD, NBOD, DO, • Every 3 hours for Stations 3, 4, and 5 show the diurnal response to waste 

below Dublin STP Temperature 24 hours. plus load variations. The plug flow sample is taken to corresample for plug spond with the passage of the centroid of dye released 

flow analysis at the treatment plant. 

4. In Eel River 16 miles same as station 3 same as station 3 

below Dublin STP 

5. In Eel River just 

above Cache Creek 

same as station 3 same as station 3 

6. Mouth of Cache 

Creek 

same as station 1 same as station 1 Single flow rate estimates at the beginning and end of 

survey will be sufficient if a continuous gage is not 

available. 

7. In Eel River 4 miles same as station 3 same as station 1 Flow rates are not needed. 

below Cache Creek 

4-2 
4.2 Organic Toxicsnt 

Figure 4-3 shows two wastewnter treatment plants 

that discharge to the El Cahon River, which flows into 

Lake Chabot. A limnological investigation has shown 

that surficial sediments of Lake Chebot are contaminated with the polycyclic aromatic hydrocarbon 

pyrsne. Subsequent investigetions in the river else 

revealed high concentrations of pyrene in the bed and 

occasional high pyrene concentrations in the water 

column as far upstream OS the Bently sewage 

treatment plsnt. Ssmpling of the effluent from the 

Bently and Vallejo plants has confirmed that these 

two plants are sources of pyrene. To meet water 

quality standards, the state has decided that the 

loading of pyrene to the river is to be reduced and 

allocated between the two sources. 

F~QINO 4-3. El C&on River, Ialto Chalwt. and mvkonr. 

0 (01 3 (5) 6 1101 I 

Mks (km) 

(for maximum criteria) to perform the WlA. This 

example problem, therefore, deals with sampling 

during a low flow period. 

The state selects a dilution or mass balance epproach 

to allocate pyrene from the Bently treatment plant. 

Above thevallejo treatment plant, however, the state 

believes that pyrene concentration is not predictsble 

by pure dilution alone, based on the presence of 

pyrene in the stream sediments. 

The state decides to perform a preliminary analysis of 

the fate of pyrene in the river, and to use the computer 

model MICHRIV for the WLA (if needed) to simulate 

the transport and transformation of pyrene in the 

river between the’two treatment plants. Table 4-2 

summarizesdata the state has collectedon the fste of 

pyrene. The date show that hydrolysis is probably 

negligible, but that the biodegredstion rate, while 

unknown, is likely to be significsnt. The volatilization 

rate is not shown in the tsble, but its importance can 

be determined from Henry’s Constant: 

Kn = 

P, * MW 

760.SW (4-l) 

where P, = saturation vapor pressure, torr 

MW = molecular weight 

SW = solubility in water, mg/l 

For pyrene. 

K ” = (6.9 * 10-7 (202) 

(760) (.140) = 1.3 - 1 O-’ atm - m5/mole 

l Octanol-water partition coefkkat ld* = 2.106 

l !jaturation vapor pressers (ton at 20X). P, = 6.9.10-’ 

l sotubility (mgIl8t 25’c). s, = 140 4 

l Biwradation rate (l/day): unknown but probably rignficant from (49) 

l Hydrolysis rats (l/dry): unknown, but probabty WligiMe 

* Nerr surface direct photolysis rate (l/day at a light intensity 

I, - 2100 langleyMay), &, = 24 

* Wwelength of maximum light absorption (nm). A0 = 330 

Prior tocollecting supplemental stresm data to use in 

the WLA analysis, the state first selects a modeling 

approach snd a sampling period. Since historical data 

have indicated that pyrene levels have been highest 

during the low flow period, the state has selected both 

a lQIO period (for chronic criteria) and a &J period 

This a very small Kn, and indicates that volatilizetion 

is negligible (probably betweenO.O1 /day and0.001 / 

day based on the two-film theory of volatilization(27). 

The high octanol-water partition coefficient (K, = 2 x 

10”) indicates that pyrene adsorbs to suspended and 

bedded sediments, end will settle out in the stream4-3 
bed along with solids that are deposited there, 

consistent with historical observations. 

The near-&face direct photo&is rate is 24/dsy. The 

expected photolyris rate in the stream can be 

approximated by (6): 

- 

where ka= near surface rate, 1 /day 

I,lo = intensity of radiation from sunlight and 

from laboratory source, respectively 

0.0, = distribution coefficients in river and in 

cleai water, respective)y 

Z= water depth. m 

k((A*) = light attenuation in water at wavelength 

A*, 1 /meter 

The light attenuation term in Equation 4-2 can be 

estimated from Table 4-3, excerpted from Mills (26). 

For the El Cahon River during low flow conditions, the 

attenuation factor is on the order of 0.1 for water type 

Cwithdepthof 1 m.Sincelo=21001angleys/dayandI 

= 640 langleys/dsy, 

Additionally, because of the potential importance of 

biodegradation, the state decides to determine the 

biodegradation rate by a plug flow sampling event at 

night when photolyais is negligible. The biodegredation rate can be determined by a plot oi pyrene 

concentration versus distance (the effects of settling, 

if important, also have to be accounted for). The state 

feels that for WLA purposes, it is important to quantify 

the individual processes affecting the fate of pyrene, 

so that model processes can be rationally adjusted for 

WLA conditions. 

Table 4-4 summarizes the data the state intends to 

collect. Locations of sampling stations are shown in 

Figure 4-4. Four instream stations are chosen in 

addition to effluent sampling at the two treatment 

plants. No sampling stations are required below the 

Vallejo plant. 

Figum 4-4. Location of umpling stations on El C&on 

River. 

k,,-(24)(.1) = = O.G/day 

2100 

T&b 43. -e.dgtg 

Depth of Water (rn) 

Ynm) Water Typ@ 1 2 3 5 10 

mo A 0.9 0.8 0.9 0.6 0.4 

: 0.51 0.406 0.204 0.1403 0.071 

0 0.03 0.01 0.009 0.005 0.003 

340 A 0.9 0.6 0.7 

: 

x:; 09 

o-5 04 

0.2 0:ofJ 0:cm Eci xi2 

D 0.04 o-02 0.01 o:OO7 oio4 

‘Water Type CM8 (rngdl DOC (rn0/1) SS (rngnl 

A 0.0 0.0 0.0 

8 0.001 \oligoftophic. 

e.g., Lake Taho.1 

c 0.01 butrophicJ 8.: 

0.5 

0 0.1 (highly wtmphic) 2:0 2:: 

Hence, photolysis is an important process for pyrene. 

This can be compared to the volatilization rate of 

O.Ol-O.OOl/day to show that volatiliratlon is unimporter& 

Based on this preliminary enalysis and orevious 

historical data, the state decides to determine the 

diurnal variation of pyrene discharged from each 

treatment plant and also the diurnal variation of 

concentrations in the river, the latter caused both by 

daily variations in loading and variations In the 

photolysis rate. 

44 

0 IO) 3 l5l 

L1’ 

Moles (km) 

0 I Oenotes Semphng 

LocatIon 1 

1 

‘. : ‘. 

t 

‘. * 

i-\1 . 

The stations between the two point sources are 

selected based on an assumed travel time of sbout 

0.7 days between siations (it is assumed that the 

state had previously determined travel times), and 

considering that pyrene may photolyze and biode- 
T&k u. swtt~dDamtokcoaatmd owhgS-~-V 

Sampling Station Parameters Frequency cunilmtfa 

1. Background station in 

El Cahon Aiwr l hdw 

Berttly STP 

2. Effluent ot Bently STP 

In El C&on river 6 mi 

(10 km) Mow Bentty 

STP 

In El Cahon Riwr 

12 mi (20 km) taolow 

mtly SrP 

In El C&on River just 

below Vallejo ST-P 

Etfluent of Vallejo 

STP 

Plug flow sampling: 

hemmen stations 3 

and 4 (rppmximaWI. depending 

on the trmml time 

corraPonding to 

l Suspended solids 

l Pyrerte, total 

l Flow rate 

l Suspended roli& 

l f+yrene, total 

l Flow rate 

l Suspended solids 

l PylwM3, toM 

l f’ymne, diuotwd 

l Water temper8ture 

l Cros8-urctionsl area 

l Waer depth 

l Same n at Station 3, 

plus: 

l Chlorophvll I 

l Dinlowd orfpnic 

carbon 

l Same l Station 3 

l Same as StAon 2 

l Dve 

l Total pyrene 

l Dkdwd pyreno 

l Suspended solida 

l Three times during 7dsy sunwy 

l Three times during 7dry survey 

l Continuously (USGS gage) 

l Ewry3hounfor7daw 

*Every3hounfor7days 

* Continuously 

l Twice during 24hour period 

l Ewry 3 hours for 24 hours 

l Twice during 2Chour period 

l Ewry 3 houn 

l Dnce 

-0na 

l Twice during 24-hour period 

l Twice during 24hour period 

l Same 18 Station 3 

l Same 8s Strtion 2 

l Ewry two houn.from sunset to 

wnriw beginning near Station 3 

l used to ntablish backQrwnd hwk 

l undtoamfirmthDtbacQrourKl 

pyrolu - l nogligible 

l Same8ast8tkn3 

l SarnonSt8tion2 

l ThedyahinjoctodintothoEl 

CahohRinurthoRanttvSTP8o 

thanltkw&lmlxodbythetirwtt 

pawssmkxl3. 

sunrme 

grade fairly rapidly. Based on the mixing characteristics of the river, it has been established that 

complete mixing of effluent and stream water is 

achieved upstream of station 3. Thus, the state does 

not need to take multiple samples laterally across a 

transect. 

The state chooses to sample at three hour intervals, 

over e 24-hour period at stations 3,4 and 5. Due to 

manpower limitations, the stations are sampled 

sequentially, beginning with station 3. The state is 

aware that this is not as desirable as sampling 

simultaneously at the three stations because of the 

time variability of the waste loadings. The effluent 

quantity and quality of the treatment plants are 

monitored for a period of one week, beginning the day 

before the instream sampling begins at station 3. 

At the upstream boundary station, a nearby USGS 

gauge continuously records the flow. Becausepyrene 

contamination has never been found in the river 

above the Bently treatment plant outfall, only three 

background grab samples are taken during the 

sampling period (one every two days). 

Once sampling is completed at stations 3.4 and 5, the 

plug-flow sampling event is begun. Dye is injected 

into the stream at the Bentlytreatment plan3 so that it 

is well-mixed at station 3 and arrives near sunset. The 

effluent loading of pyrene at the time of dye injection 

is recorded. Sampling for pyrene then begins at 

statton 3 as the peak dye concentration passes. 

Samples are collected approximately every two hours 

based on passage of peak dye concentrations, and, 

continues through the night. Suspended solids 

4-5 
concentrations are also taken to see if settling of 

solids is significant. The state realizes thai the plugflow sampling event has to be carried out accurately 

in order to determine the decay rate, because of the 

time limitation (approx. 12 hours) before photolysis is 

again active. 

Once the state has completed the seven day sampling 

program, enOUgh information has been collected to 

analyze the fate of pyreno in the river, and to calibrate 

MICHRIV. The agency intends to run MICHRN a 

number of times, with different loading rates to see 

how well the predictions match the envelope of 

instream concentrations observed at locations.3, 4 

and 5. 

following model oalibration, it is expeoted that the 

state will conduct a second survey for modal verification. Different conditions will intentionally be chosen 

between the calibration and verification periods. For 

axsmple, if the calibration survey vwrre conducted 

under cloudy or rainy conditions when the solar 

radiation is suppressed by as much as 50 to 70 

percent, the verification survey would be conducted 

under clear skv conditions. 

4-6 
Chapter 5 

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12. pp. 2869-2689. 

Rathbun, R.E., D.W. Stephens, D.J. Shultz, and 

D.Y. Tai. 1978. Laboratory Studies of Gas 

Tracers for Reaeration, ASCE, J. Environmental 

Engineering Division, Vol. 104, No. EE1, pp. 

215-229. 

O’Connor, D.J., and W.E. Dobbins. 1958. 

Mechanism of Reaeration in Natural Streams, 

ASCE Transactions, Paper No. 2934. pp. 641- 

884. 
40 

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45 

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1964. Some Reaeratlon Studies In Streams, Int. 

J. Air Wat. Poll., Vol. 8. pp. 469-486. 

Churchill, M.A., H.L. Elmore. and R.A. Buckingham. 1962. The Predictlon of Stream Reaeratlon 

Rates, ASCE, Journal Sanitary Engineering 

Division, Vol. No. 88. SA4, pp. l-46. 

Whittemore, R.C. Implementation of In-Situ and 

Laboratory SOD Measurements in Water Quality 

Modeling, in Sediment Oxygen Demand: Processes. Modeling, and Measurement. K. Hatcher 

(ED), lnstituteof National Resources, U Georgia, 

(In Press, .1986) 

Whittemore, R.C. Recent Studies on the Comparison of In-Situ and Laboratory SOD Measurement Techniques. Proceedings, Stormwater 

and Water Quality Management Modeling 

(SWMM) Conference, Dee 5-6. 1985. Toronto, 

Canada. William James, McMaster Univ. (Ed). 

Whittemore, R.C. A Review of In-Situ and 

Laboratory SOD Measurement Comparisons, 

NCASI Technicat Bulletin No. 386, NewYork, NY 

(Nov. 1982). 

Whlttemore, R.C. A Review of Uncertainty in the 

In-Situ Measurement of Sediment Water 

Column Interactions. NCASI Technical Bulletin 

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Hatcher, K.J., and D. Hicks (Eds). 1986. Sediment Oxygen Demand; Processes, Modeling 

and Measurement. Proceedings of the WPCF 

Symposium, Published by Institute of National 

Resources, Univ of Georgia, Athens, GA. 

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John Wiley and Sons. New York, NY 10016. 

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J.E. Pollard, A.B. Crockett. 1983. Guidelines for 

Field Testing, Aquatic Fate and Transport 

Models. U.S. Environmental Protection Agency. 

EPA-60014-85-030. 

Lyman, W.J., W.F. Reehl, and D.H. Rosenblatt. 

1982. Handbook of Chemical Property Estimation Methods: Environmental Behavior of 

Organic Compounds. McGraw-Hill Book Compaw. 

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Volume 71, No. 6. 

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and W.H. Brooks. 1979. Mixing in Inland and 

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Measuring the Acute Toxicity of Effluents to 

Aquatic Organisms. 3rd Ed. Office of Research 

and Development, Cincinnati, OH. EPA-600/4- 

85-013. April, 1985. 

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Measuring the Chronic Toxicity of Effluents to 

Aquatic Organisms. Office of Research and 

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014. 

5-3 
Chapter 6 

Appendix 

References for Instream Data Collection and 

laboratory Techniques for Analysis of Water and Waste Water 

Techniques of Water Resources Investigations 

(U.S. Geological Survey) 

Barnett, P.R. and E.C. Mallory Jr. 1971. Determination of Minor Elements in Water by Emission 

Spectroscopy. 31 p. Bk 5, A2 

Benson, M.A. and Tate Dalrymple. 1967. General 

Field and Office Procedures for Indirect Discharge 

Measurements. 30 p. Bk 3, A1 

Bodhaine. G.L. 1968. Measurement of Peak Discharge at Culverts by Indirect Methods. 60 p. Bk 3, 

A3 

Buchanan, T.J. and W.P. Somers. 1968. Stage 

Measurements at Gaging Stations. 28 p. Bk 3, A7 

Buchanan, T.J. and W.P. Somers. 1969. Discharge 

Measurements at Gaging Stations. 65 p. Bk 3. A8 

Carter, R.W. and Jacob Davidian. 1968. General 

Procedure for Gaging Streams. 13 p. Bk 3, A6 

Craig, J.D. 1983. Installation and Service Manual for 

U.S. Geological Survey Manometers 57 p. Bk 8, A2 

Dalrymple, Tate and M.A. Benson. 1967. Measurement of Peak Discharge by the Slope-Area Method. 

12 p. Bk 3, A2 

Davidran, Jacob 1984. Computation of Water-Surface 

Profiles in Open Channels. 48 p. Bk 3, A15 

Friedman, L.C. and D.E. Erdmann. 1982. Quality 

Assurance Practices for the Chemical and Biological Analyses of Water and Fluvial Sediments. 

181 p. Bk 5, A6 

Goerlitz, D.F. and Brown. 1972. Methods of Analysis 

of Organic Substances in Water. Bk 5, A3 

Greeson, P.E., T.A. Ehlke, GA Irwin, B.W. Lium, and 

K.V. Slack (editors). 1977. Methods for Collection 

and Analysis of Aquatic Biological and Microbiological Samples. 332 p. Bk 5. A4 

Guy, H.P. 1969. Laboratory Theory and Methods for 

Sediment Analysis. 58 p. Bk 5, C1 

Guy, H.P. 1970. Fluvial Sediment Concepts. 55 p. Bk 

3. C1 

Guy, H.P. and V.W. Norman. 1970. Field Methods for 

Measurement of Fluvial Sediment. 59 p. Bk 3, C2 

Hubbard, E.F., Kilpatrick, F.A., Martens, L.A., and 

Wilson, J.F., Jr., 1982. Measurement of Time of 

Travel and Dispersion in Stream by Dye Tracing. 44 

p. Bk 3, A9 

Hulsing, Harry. 1967. Measurement of Peak Discharge at Dams by Indirect Methods. 29 p. 

Jenkins, C.T. 1970. Computation of Rate and Volume 

of Stream Depletion by Wells. 17 p. Bk 4, D1 

Kennedy, E.J. 1983. Computation of Continuous 

Records of Streamflow. 53 p. Bk 3. A13 

Kennedy, E.J. 1984. Discharge Ratings at Gaging 

Stations. 59 p. Bk 3. A10 

Kilpatrick, F.A. and V.R. Schneider. 1983. Use of 

Flumes in Measuring Discharge. 46 p. Bk 3. A14 

Kilpatrick. F.A.. and Cobb, E.D. 1985. Tracer Discharge Measurement. Bk 3, A16. 

Laenen, Antonius. 1985. Acoustic Velocity Meter 

Systems, TWRI. 38 p., Bk 3. A16 

Matthai, H.E. 1967. Measurement of Peak Discharge 

at Width Contractions by Indirect Methods 44 p. Bk 

3, A4 

Porterfield, George 1972. Computation of FluvialSediment Discharge. 66 p, Bk 3, C3 

Riggs, H.C. 1968. Some Statistical Tools in Hydrology. 

39 p. Bk 4, A1 

Riggs. H.C. 1968. Frequency Curves. 15 p. Bk 4, A2. 

Riggs, H.C. 1972. Low-Flow Investigations. 18 p. Bk 

4, B1 

Riggs, H.C. and C.H. Hardison. 1973. Storage Analyses for Water Supply. 20 p. Bk 4, 82 

6-1 
Riggs, H.C. 1973. Regional Analyses of Streamflow 

Characteristics. 15 p. Bk 4, B3 

Skougstad. M.W. and others (editors). 1979. Methods 

for Determination of Inorganic Substances in Water 

and Fluvial Sediments. 626 p. Bk 5, A1 

Smoot, G.F. and C.E. Novak. 1968. Calibration end 

Maintenance of Vertical-Axis Type Current Meters. 

15 p. 

Smoot, G.F. and C.E. Novak. 1969. Measurement of 

Discharge by Moving-Boat Method. 22 p. Bk3, A11 

Stevens Jr., H.H., J.F. Ficke, and G.F. Smoot. 1975. 

Water Temperature Influential Factors, Field 

Measurement and Data Presentation. 65 p, Bk 1, 

D1 

Thatcher, L.L., V.J. Janzer, and K.W. Edwards. 1977. 

Methods for Determination of Radioactive Substances in Water and Fluvial Sediments. 95 p. Bk 5, 

A5 

Wershaw, R.L., M.J. Fishmen, R.R. Grabbe, and L.E. 

Lowe. 1984. Methods for the Determination of 

Organic Substances in Water and Fluvial Sediments. 

Wilson Jr., J.F., Ernest D. Cobb, and Frederick A. 

Kilpatrick. Fluorometric Procedures for Dye Tracings. 1984. Bk 3. A12 

Instream flow Information Publications 

(U.S. fish and Wildlife) 

Bayha, K.D. 1978. Instream Flow Methodologies for 

Regional and National Assessment. Instream Flow 

Information Paper No. 7. U.S.D.I. Fish and Wildlife 

Service. FWS/OBS-78/61. 98 p. Available from 

NTIS (PB 80181100). 

Bovee, K.D. and T. Cochnauer. 1977. Development 

and Evaluation of Weighted Criteria, Probability-ofUse Curves for Instream Flow Assessment: Fisheries. Instream Flow Information Paper No. 3. 

U.S.D.I. Fish and Wildlife 

Service. FWS/OBS-77163.39 p. Available from NTIS 

(PB 286 848). 

Bovee, K.D. 1978. Probability of Use Criteria for the 

Family Salmonidae. Instream Flow Information 

Paper No. 4 U.S.D.I. Fish and Wildlife Service. 

FWS/OBS-78/07. 53 p. Available from NTIS (PB 

286 849). 

Bovee, K.D. and R.T. Milhous. 1978. Hydraulic 

Simulation in Instream Flow Studies: Theory and 

Techniques. Instream Flow Information Paper No. 

5. U.S.D.I. Fish and Wildlife Service. FVVS/OBS78/33. 143 p. Available from WELUT and NTIS (PB 

287 015). 

Bovee, K.D. 1982. A Guide to Stream Habitat Analysis 

Using the Instream Flow Incremental Methodology 

Instream Flow Information Paper No. 12. U.S.D.I. 

Fish and Wildlife Service. FWS/OBS-82/26. 248 

p. Available from NTIS (PB 83 131 052). 

Grenney, W.J. and A.K. Kraszewkr. 1981. Description 

and Application of the Stream Simulation and 

Assessment Model Version IV (SSAM IV). Instream 

Flow Information Paper No. 17. U.S.D.I. fish and 

Wildlife Service. FWS/OBS-81/46. 199 p. Out of 

print. Available from NTIS (PB 82 241 712). 

Hyra, R. 1978. Methods of Assessing Instream Flows 

for Recreation. Instream Flow Information Paper 

No. 6 U.S.D.I. Fish and Wildlife Service. FWS/ 

OBS-78/34. 52 p. available from NTIS (PB 285 

967) or GPO (024-010-00469-0). 

Lamb, B.L. and D.A. Sweetman. 1979. Guidelines for 

Preparing Expert Testimony in Water Management 

Decisions Related to Instream Flow Issues. Instream Flow Information Paper No. 1. Revised. 

U.S.D.I. Fish and Wildlife Service. FWS/OBS79/37.33 p. Available from NTIS (PB 80-162761). 

Lamb, B.L. (editor). 1977. Protecting Instream Flows 

Under Western Water Laws: Selected Papers. 

Instream Flow Information Paper No. 2. U.S.D.I. 

Fish and Wildlife Service. FWS/OBS-77/47.65 p. 

Available from NTIS (PB 272 691). 

Milhous, R.T., D.L. Wegner, and T. Waddle. 1981. 

Users Guide to the Physical Habitat Simulation 

System (PHABSIM). Instream Flow Information 

Paper No. 11. U.S.D.I. Fish and Wildlife Service. 

FWS/OBS-81/43 (revised). 475 p. Available from 

NTIS (PB 84 199 736). 

Olive, S.W. 1981a. Protecting Instream Flows in 

California: An Administrative Case Study. Instream 

Flow Information Paper No. 14. U.S.D.I. Fish and 

Wildlife Service. FWS/OBS-82/34.32 p. Available 

from WELUT and NTIS (PB 83 169 482). 

Olive, S.W. 1981 b. Protecting Instream Flows in 

Idaho: An Administrative Case Study. Instream 

Flow Information Paper No. 15. U.S.D.I. Fish and 

Wildlife Service. FWS/OBS-82/35. Available from 

WELUT and NTIS (PB 83 169 490). 

Olive, S.W. 1983. Protecting Instream Flows in Iowa: 

An Administrative Case Study. Instream Flow 

Information Paper No. 20. U.S.D.I. Fish and Wildlife 

Service. FWS/OBS-83/18. 35 p. Available from 

WELUT. 

Pruitt, T.A. and R.L. Nadeau. 1978. Recommended 

Stream Resource Maintenance Flows on Seven 

Southern Idaho Streams. Instream Flow Information Paper No. 8. U.S.D.I. Fish and Wildlife Service. 

FWS/OBS-78/68. 67 p. Available from NTIS (PB 

287 849), or GPO (024-010-00496-7). 

6-2 
Sweetman, D.A. 1980 Protecttng Instream Flows in 

Montana, Yellowstone River Reservation Case 

Study. lnstreem Flow Information Paper No. 10. 

U.S.D.I. Fish and Wildlife Service. FWS/OBS79136 75 p Aveilable from NTIS IPB 81 236 069). 

Theurer, F.T., K.A. Voos, and W.J. Miller. lnstresm 

WaterTemperature Model. lnstresm Flow Informetion Paper No. 16. U.S.D.I. Fish and Wildlife Service. 

FWS/OBS-84115. 372 p. Aveilable.from WELUT 

and NTIS. 

Wassenberg. P.S.. S. Olive, J.L. Demott, and C.B. 

Stalnaker. 1979. Elements in Negotiating Stream 

Flows Associated with Federal Projects. lnrtreem 

Flow ;rliul ,;,ocion Paper No. 9. U.S.D.I. Fish and 

Wild1 (nS;e~+; rtrJS/OBS-79103.41 p. Available 

from NTIS (PB 80 146 2021. 

U.S. Environmentel Protection Agency 

Plumb, R.H. 1984. Characterizatfon of Hazardous 

Waste Sites. a Methods Manuel. Volume III. 

Available Laboratory AnalytIcal Methods. EPA600/4-84-038. USEPA, EnvironmentalMonitoring 

Systems Laboratory, Las Vegas, NV. 

U.S. EnvIronmental Protection Agency. 1977. Ssmpling and Analysis Procedures for Screening of 

Industrial Effluents for Prlorrty Pollutants. USEPA 

Washington, DC 20460. 

U.S. Environmental ProtectIon Agency. 1978a. Data 

Collection Quality Assurance for the Nationwide 

Urban Runoff Program. Water Planning Division, 

USEPA Washrngton. DC 20460.41 p. 

U.S. EnvIronmental Protection Agency. 1979. Handbook for AnalytIcal Quality Control in Water and 

Wastewater Laboratories. EPA-60014-79-01 9. 

Environmental Monltortng and Support Laboratory, 

Cincmnati, OH. 

U.S. Environmental Protection Agency. 1979b irevised March, 19831. Methods for Chemical Analysis 

of Water and Wastes. EPA-60014-79-020. Envlronmentel Monitoring and Support Laboratory, 

Cincmnsti, OH. 

U.S. EnvIronmental ProtectIon Agency. 1982b. 

Handbook for Sampling and Sample Preservation of 

Water and Wastewater. EPA-600/4-82-029. Envlronmental Monitorrng and Support Laboratory. 

Cincinnati, OH. 

Miscelleneous 

American Public Heelth Association. American Water 

Works Associetron. Water Pollution Control Federation. 1981. Standard Methods for the Examination 

of Water end Wastewater-15th Edition of American Public Health Assoclatlon, Washington, DC, 

1139 p. 

American Society for Testmg end Materials 1992. 

Annual Book of ASTM Standards. Pert 31. Water. 

ASTM, Philedelphia, PA. 1544. p. 

American Society for Testmg snd MeterIsIs. 1983. 

Annual Book of ASTM Stendards. Water and 

Environmental Technology. Volume 11 .Ol ASTM, 

Philadelphia, PA. 752 p. 

USCOE, USEPA. 1981. Procedures for Handling and 

Chemical Analysis of Sediment and Water Samples. WaterwaysExperiment Station, P.O. Box631 

Vicksburg, MS 39180. 

Ingram, W.M., Mackenthun, K.M.. and Bertsch, A.F. 

1967. Biological field Investigative Data for Water 

Pollution Surveys. FWPCA. Superintendent of 

Documents, U.S. Government Printrng Office. 

USGS. Development and Testing of Highway StormSewer Flow Measurement and Recordmg System. 

Water-Resources tnvestigatlons Report 85-41 11. 

Hem, J.D. Study end lnterpretatron of the Chemical 

Characteristics of Natural Water. Third Edition. 

USGS Water-Supply Paper 2254. 

Gordon, A.8.. and Katrenbach, M. 1983. Guidelines 

for the Use of Water Quality Monitors. USGS OpenFile Report 83-681. 

Rantz. S.E., and others. 1982. Measurement and 

Computatton of Streamflow; Vol 1, Measurement 

of Stage and Discharge; Vol 2, Computation of 

Discharge. USGS Water-Supply Paper 2175.631 p. 

U.S. EnvIronmental Protectron Agency. 1979. Momtoting Requrrements. Methods and Costs for the 

Natlonwtde Urban Runoff Program. Water Plennrng 

Division, USEPA, Washington, DC 20460. 

6-3