DCN: 45,037 

Section: 2 1.4.2 

EPA-907/9 -74 -CO 1 

? February 1974 -y- . . ­

*.. , *- -a-,LT:;." r: .-.-e.. WATER .. QUALITY INDEX APPLICATION -:- ' -

:. 

' 

* 

..*_ .,? .- . .1 _ - - ... 

' IN TKE' .. 

*., .. 

BASIN .. 

t 

BY 

Nina I. McClelland, Pn.D. 

Contract No. 68-01-0761 ' 

Project Officer 

Aleck Alexander 

Air & Water Programs Division 

Environmental Protection Agency-Region VI1 

-.-* 1735 Baltimore Street 

Kansas City, Missouri 64108 

. . .. 

-. . 

Prepared for 

U is. Environmental Protection Agency-Region VI1 

1735 Baltimore Street 

Kansas City, Missouri 64108 .' 

I 
'1 

ABSTRACT 

The Water Quality Index (WQI) is an empirical expression 

which integrates nine significant physical, ckemical, and 

microbiological parameters of water quality into a single 

number. It was developed by the National Sanitation 

Foundatlon (NSF) In response to the need for a uniform 

method of .measuring and reporting water quality in donsistent, comprehensible terms. 

To meaningfully demonstrate the responsiveness of WQI 

to variations in water quality, and to determine optimum 

frequencies for computing and reporting WQI, a comprehensive 

field samFling, laboratory analysis, and data management 

program was systematically developed for applying WQI to 

selected sites on the'Kansas River and its major tributaries. 

Nearly 600 samples from 26 sites - 14 main stem and 12 

tributary - were included in the study. Seventeen parameters 

were measured in the laboratory - the nine in WQI and eight 

closely related parameters - to determine the validity of 

term substitution in the index expression. Parameters most 

responsible for quality variation in both main stem and 

tributary stations were identified by least squares regression. 

Results, "-. expressed as WQI, indicated that the NSF water 

quality index is an effective method for measuring and reporting overall quality variations in the Kansas River. The 

operational methodology and results .. of the study are presented in detail in this report. .I 

This report was submitted in fulfillment of Contract Number 

68-01-0761 by The National Sanitation Foundation under the 

sponsorship of the Environmental Protection Agency. Work 1 

was completed as of January 1974. 

ii 
-- ---- --- 

! 

. Ann Arbor, Michigan, -4fH-05 

68-01-0761 

Coked 

14. 

d 

16. Ansrrnds4; V

'The National Sanitation Foundation's (NSF) Water Quality J Index Y&QI) is an 

empirical expression which integrates nine significant physical, chemical, and microbiologicat parameters of water quality into a single number to provide a uniform,

consistent, and comprehensible term for measuring and reporting water quality.

To demonstrate the responsiveness of WQI to variations in water quality and to 

determine optimum frequencies for computing and reporting WQI , a comprehensive field 

sampl ing, laboratory analysis, and data management program was developed for applying

WQl to selected sites on the Kansas River and its major tributaries. Seventeen 

parameters were measured (the nine in WQI and eight related parameters) on nearly,600

samples from 26 sites '(14main stem and 12 tributary)..trPkame*ters most responsible

for quality variation in'both main .stem and tributary stations were identified by

least s uares regression. Results indicated that the NSF Water Quality Index (WQI) is an e9fective method for measuring and reporting overall quality variations in the

iver. �PA) -. 17. Kcy \vnr.t5 ~nc'lh~cumcnrAn~l:%:x. 170. l)cF:rtptar:, 

e

Kansas River Basin (&&,) 

Topeka (Ka*, I a d/ 

Water Qual i ty Index. 

! . . .... . I -.-__-
UNITED STATES ENVIRONMENTAL PROT�CtlON AGENCY 

August 12, 1974 

To: Recipients of �PA Report 907/9-74-O01, "Water Quality Index 

Application In The Kansas River Basin" 

An omission has been found in the report "Mate- Quality Index 

Appl ication In Tne Kansas River Basin", EPA-907/9-74-001, 

February 1974, which we recently sent to you. Please insert the 

following EPA Review Notice on the inside of the front cover of 

the subject report: I 

. EPA Review Notice 

. This report has been reviewed by the Environmental 

Protection Agency and approved for pub1 ication. 

Approval does not signify that the contents 

necessarily reflect the views and policies of the 

Environmental Protection Agency, nor does mention 

of trade names or commercial products,constitute 

endorsement or recommendation for use. 

I 

T 

.. 
.

. __. 

CONTENTS 

.-- . 

. Paqe -. 

. Abstract 

List of Figures 

List of Tables 

Acknowledgments 

Section 

ii 

iv . 

V 

vi 

1 

- 3 

4 

. 19 

28 

35 

37 

57 

68 

70 

I 

I1 

111 

IV 

VI 

VIII 

IX 

I 

Conclusions 

Recommendations 

The Water Quality Index 

Pro3ect Description 

Experimental 

Results 

Discussion 

Special Studies 

References 

Appendices 

.._\ 

iii 

. 
i 

'_.. 

. - 2 

3 

4 

5 

6 

. 7 

8 

9 

10 

FIGURES 

Schematic Illustration of Sampling Sites 

in Kansas Iiiver Application of WQI 

Sample Distribution and Handling Scheme 

for Chemical and Physical Parameters' 

Mean Values for WQI(A) and WQI(M) at all 

Stations for entire Observation Period 

Mean, High, and Low WQI(A) for Kansas 

River Stations 

Mean, High, and Low WQI(M) for Kansas 

River Stations 

Mean, h'ic;h, and Low WQI(A) for Tributary L f

Stations ~ d. 

Mean, High, and Low WQI(M) for Tributary 

Stations 

Initial and Final WQI(A) Values for all 

Sampling Stations 

Effect expressed as WQI (A) of three 

tributaries on quality in Kansas 

River at Topeka and Lecompton 

Profile of Kansas River at 7th Street 

.-= Bridge, Kansas City, Kansas 

iv 

Page ­ 25 ? 

* . 30 

. .. 38 

39 

40 

41 

42 

47 

50 

63 

.. 
.. TABLES 

No 

- *_ Page

*1 Parameters Considered for WQI in . . I.. 

.- Questionniire No. 1 

2- .,- Significance Ratings and Weights for Nine 11 

?arameters Included in the WQI 

List of Participants in Initial Field 14 

Application of WQI 

Sampling Station Locations 21-24 

Summary of Analytical Metkods 31-34 

Summary of WQI(A) and WQI(M) for Kansas 44 

iiiver and Tributary Stations I 

7 Sampling Frequency 54 

8 Regression Analysis of WQI ParGeters by 56 

Forward Selection 

9 Correlation Coefficients for Selected 58 

Parameters 

10 Correlations - Summary 60 

11 Hourly Variations 61 

12 Results of Microbiological Study Kansas 64 

River at Kansas City-7th Street

..-. 

13 Data from Study of Transverse and Vertical 65 

Quality Variations in the Kansas River at 

Kansas City-7th Street. 

..: 

V .. 

7 
. -... . ACKNOWLEDGMENTS 

-. 

The outstanding,cooperation of Jerome H. Svore, Regional 

Administrator, EPA Region VII, and' Aleck Alexander, Project 

- 'Officer, is gratefully acknowledged. Special appreciation 

is also ex;?ressed to EPA Region VI1 personnel who cooperated 

with the project staff by providing guidance and assistance 

in developing the study plan; providing laboratory space, 

equipment, and analytical services: collecting special 

samples; and entering the data to the STORET system. 

The cooperation of Melville W. Gray, Chief Engineer and 

' - Director, Division of Environmental Health, Kansas State 

Department of Health and the assistance of members of his 

staff in selecting sampling locations ana providing reports 

and equipment for use in the project is also greatly 

appreciafed. 

The project was directed by Dr. Nina I. McClelland. The 

field staff, headquartered at the EPA Region VI1 laboratory 

in Kansas City, Kansas, included Steven W. Weeks, chemist, 

in res;;l'nsible charge of laboratory and field opesations; 

. Carroll E. Reynolrfs, chemist; Joyce E. Thale, microbiologist; 

and Larry M. Pope and Bill I?. Brown, sample collectors. 

i)r. Rolf A. Deininger and Jurate PI. Landwehr served as . - consultants to the profect for designing the sampling 

program and processing data through the Michigan terminal 

system at the University of Michigan. 

vi 
SECTION I 

CONCLUSIONS 

To insure continued public and private support for water 

quality improvement programs, a uniform, comprehensible 

format must be adopted for measuring and reporting progress - or lack of progress - in attaining current and future program objectives. Through widespread applicatim of the 

water quality index (WQII, developed and applied by the 

National Sanitation Foundation (NSF) , a specific, simplistic 

method is available for quantitative, consistent practice 

in measuring and reporting water quality. 72 *ib ernphahized 

Itkt W27 ia a managemebzt and geneaal adminiathative tool 

ictonded gotr UA e in communicating water, quality in{o,tmaXian 

ttc .tile lay public afid 20 legihlative decihiobl mahexa. 1.t 

Lid not a complex ptredicziwe model Act& technical aizd hcienzigic application. 

The.WQI was applied to selected sites in the Kansas River and 

major tributaries through a comprehensive three month field 

sampling, laboratory testing, and data analysis program. 

Results of this project demonstrated that: 

WQI is responsive to changes in water 

quality resulting from discharge of 

municipal and industrial waste effluents 

and agricultural runoff in the study area. 

WQI can be used effectively in 

optimizing sampling frequencies. 

Four specific parameters - BOD5, 

turbidity, phosphates, and fecal 

coliforms - are responsible for 

more than 90% of the variation 

in quality, expressed as WQI, in 

1 

c 

.. 
. . ­ . :-i 

.. 

4) 

river and tributary statiqns included 

in this study. Although the same _. .. . . ..4 

four parameters are indicated in . 

main stream and tributary data, 

their order of relative importance. ._ 

’ varies. 

Two sets of parameters are highly 

correlated in both main stem and 

tributary stations - suspended 

solids with turbidity, and total 

coliforms with fecal coliforms. 

Other parameters are not closely 

related and cannot logically be 

substituted in calculating WQI 

for the Kansas River. 

WQI is an effective method for 

indicating and reporting overall 

quality and expressing quality 

trends in the study area. 

J 

.. 

2 
, 

SECTION I1 

RECOMMENDATIONS 

Data acquired during this study should be expanded to include all seasons of the year. Changes in quality which 

occur as normal seasonal variations are not reflected 

in this report as a result of the limited period of performance. A program should be implemented for applying 

WQI as a continuing water qlality management tool 

throughout Region VII. 

Comprehensive planning for future water quality objectives in Region VI1 should include the use of WQI as an 

integral part of interpreting changes in the overall 

quality of streams in the Region and reporting these 

changes to the public. 

An education/public information program should be . 

developed in Region VI1 to acquaint water quality 

control administrators legislative decision makers, 

and the public with the meailing and use of WQI in 

evaluating stream quality. 

-.-. WQI should be adopted on a national level to provide a 

basis for uniform water quality management operations. 

It is strongly recommended that programs similar to the 

Region VI1 study be implemented at the earliest opportunity in at least three additional regions. These 

regions should be widely separated geographically to 

demonstrate that WQI is responsive to changes in quality 

without respect to location. Each of these demonstrations should include an education/public information 

component. 

3 
SECTION I11 

THE WATER QUALITY INDEX 

Definition 

By definition, the Water Quality Index (WQII is a single 

numerical expression which reflects the composite influence 

of nine significant physical, chemical, and microbiological 

parameters of water quality. It was developed and field 

evaluated by the National Sanitation Foundation (NSF) .to 

provide a uniform method for indicating and reporting the 

benefits - or lack of benefits - realized from billions of 

public and private dollars invested in stream quality improvement program. 

Rat ionale 

The need for a water quality index is well documented. In 

January 1959 the Committee on National Water Policy of the 

Conference of State Sanitary Engineers (CSSE) .proposed that 

an objective study be initiated to develop a uniform method 

for indicating water quality. As a result of this action, 

. 

the CSSE Committee and the Conference of State and Interstate 

Water-'-Pollution Control Administrators (CSIWPCA) began 

developing criteria for demonstrating the progress of water 

pollution control programs, but nothing tangible emerged from 

this effort. 

In 1965 the Environmental Pollution Panel of the President's 

Science Advisory Committee recommended that the federal 

government stimulate development of an index of chemical 

pollution, which would "allow us to follow many important 

changes in general water quality. " (1) 

4 
The Environmental Study Group of the National Academy of 

Science proposed that various environmental indices, including , 

"water purity" be developed and weighted into an overall 

Environmental Quality Index (2), a concept supported in a 

report to the Senate Committee on Public Works (3). 

In its third annual report, the President's Council on Environmental Quality'stated that, "Accurate and timely information on status and trends in the environment is neeessary to shape sound public policy and to implement environ-. 

mental quality programs efficiently. Further, the American 

people are entitled to know whether the public and private 

money being spent to protect the environment returns a cpmmensurate improvement in environmental quality."(4) 

The Honorable Russell E. Train, in addressing the National 

. Conference on Managing the Environment, said "Accurrate and 

timely in&oztma.tianon the dta;tu~06 the enwimnment id necedba/ry .to ahape hound pub2ic poLicy and do implement enwihon- * 

menxnt quality pttogkarnA eJiicienttg. It ii6 vitrtuatty impadbible to develop ebdec.tive pjzogtramh and to manitoh .theitr 

irnplernenta&i.anwithouX good monitoaing data. Veky detailed 

data ahe necebda/ry dok ceh.tain type4 05 planning and endoacement, Fat'"h~pmanngemenrt and generral public. policy development, maniltoking da-ta muad be dhaped in20 ea.!,y-ta-undeka.tand 

indiced 2tha.t aggnC8aXe daXa into unde&dtandable dorrm~. I am 

convinced that much muhe ed60a.t mud2 be placed on the development 06 bettet maniltotring ayhternn and indice4 than we have 

in the pabt. failuae .tto.do 40 will ke~utltin dub-optimum 

achievernenlt 06 goab 2 muck glreaxetr expend e.'' (5) 

These statements and recommendations are consistent with 

stated objectives for the NSF Water Quality Index, to: 

5 
Make available a tool for dependably 

treating water quality data and presenting them as a single numerical 

index, and 

Promote utilization of a process for , 

effectively conununicating water quality 

conditions to all concerned. 

Methodology 

Development of WQI was undertaken by NSF as an unsponsored 

project. The basic .methodology attempted to incorporate 

many aspects of DELPHI (6) an opinion research technique 

developed by the Rand Corporation. Individual judgements 

of a large panel of experts .were integrated to produce a 

group decision. Through controlled feedback, each panelist 

was given the opportunity to compare his individilal response 

tqith that of. the group, and to change his response to more 

nearly conform with the group if he considered it desirable 

to do so. 

A panel of 142 persons with expertise in water quality 

management was carefully s.elected for this study. Wide . 

geographical. distribution and diverse. specialties - regula-. 

tory 're.sponsibility.{federal,..interstate, state territorial 

and regional) I' local pubiic utilities. management, consulting, 

and teaching - were .represented. The.panelists received a 

series 'of mailed questionnaires . 

In the. first questionnaire the respondents were asked to 

consider the 35 parameter-s, shown in Table 1, for possible 

inclusion in' a water quality index. Opportunity was provided to include' additional parameters. Each parameter 

was to be designated according to one of the following 

categories : "do not include, I' "undecided, 'I or "include. " 

. 

I 

6 
-- 

._. - . + -

Table 1. PAXQiTERS CONSIDERED FOR WQI

-. _ - . -,.

- . . -i.-..

IN QUESTIOi?NAIRE NO. I . > . 

.^ 

. 

Parameter 

Dissolved oxygkn 

Fecal coliforms 

Ph 

Biochemical oxygen demand 

(5-day)

Coliform organisms

Herbicides 

Temperature

Pesticides 

Phosphates

Nitrates 

Dissolved solids 

Radioactivity

Phenols 

Chemical oxygen demand 

Carbon chloroform extract 

Ammonia 

Total solids 

Oil and grease

Turbidity 

. . - - . - ...

. - .-*..~ 

I 

.. . 

.. 

. . Chlorides 

Alkalinity

Iron 

Color 

Manganese

Fluorides 

Copper

Sulfates 

Calcium 

Hardness 

Sodium and potassium . Acidity 

. Bicarbonate 

Magnesium

Aluminum 

Silica 

7 
' 

.I 

Respondents were asked to rate only those parmeters marked 

"include,'I according to their significance to overall water 

quality. This rating was done on a scale of I'l" (highest I 

.. 

relative significance) to s5'8 (lowest relative significance). Of the total panel of 142 members, 102 respondents (72%) 

completed and returned the first questionnaire; however, 

of these, only 94 wcre returned in time to be included in 

the second round. 

The second mailing included a computer printout of results 

from the first questionnaire. Respondents were instructed 

to note their individual responses for each parameter and 

coinpare them with those of the entire grou?. In view of 

this feedback information, respondents were then asked to 

review their original judgements and modify them if they 

wished. The intent was to gain greater convergence of 

opinion concerning how the various parameters rated with 

respect to their effect on overall water quality. (However, 

there was little change in the significance ratings expressed 

in Questionnaire No. 2 when compared with the initial round.) 

Nine additional parsmeters, added to the first questionnaire 

by several respondents, were introduced for group consideration in the second questionnaire: chromium (hexavalent), 

total organic carbon, cyanides, conductivity, lead, arsenic, 

cadmium, selenium, and zinc. In addition, panelists were 

asked to design'ate not more than 15 parameters, which they 

considered to be the "most important" for inclusion in a 

water quality index. The complete list of parameters was 

presented, arranged in decreasing order of significance as 

determined by the average rating of the entire group from 

Questionnaire No. 1. Of 94 responGents receiving the second 

questionnaire, 77 completed and returned it for an 82% 
' response rate., Utilizing expert opinion derived from initial \ 

rounds of the study, I1 parameters, or' groups- of parameters, 

were listed for further consideration. 

In Questionnaire No. 3, respondents were asked to assign 

values for the variation in level of water quality produted 

by different levels of the nine individual parmeters. This 

was accomplished by utilizing a series of graphs. Levels 

of "water quality" from 0 to 100 were indicated on the 

ordinate, and various levels (or strengths) of the particular pzrameter were arranged along the abscissa. 

The respondents were asked to draw a curve which, in their 

judgement, represented the variation of water quality produced by the various possible measurements of each respective parameter. "Judgements" of all panelists were then 

combined to produce a set of "average curves" - one for each 

parameter. A complete set of curves is included as 

- Appendix A of this report. 

Special procedures seemed necessary for "pesticides" and 

"toxic elements, two "groups of parameters, and the respondents were asked to evaluate these. For pesticides it 

was proposed +hat "ifthe total content of detected pesticides 

(of all types) exceeds 0.1 mg/l (100 ppb) I the water be automatically registered at zero, the lowest value on the water 

quality index scale." The suggested procedure for including 

"toxic elements" in the WQI "would be to set a critical 

upper limit for the presence of each element. If any toxic . 

element exceeded its assigned upper limit, the water quality 

index would automatically register as zero." The maximum . 

permissable levels for toxic elements contained in the 

current Drinking Water Standards (7) were Proposed as those to 

... 

9 . 
. ... .. a .. . .. 

-. be .observed. The panelists agreed with this procezure . .- . .. . .for ..-

handling each of the groups of'parameters. 

I 

The third mailing also sought information which contributed 

to the formation of "parameter weightings" in a final numeri­

.cal expression. Thus, respondents were askei! to compare . 

relative overall water quality, using a scale of "1" 

(highest relative value) to "5" (lowest relative value). 

This operation differed from the initial rating of significance 

(Questionnaire No. I) in that now only the final 11 parameters 

(or groups) were being considered. From these data, 

weightings were derived for each parameter included in the 

final WQI, according to the following procedure, summarized 

in Table 2. 

1) Arithmetic means were calculated for the 

significance ratings returned for all 

parameters (except "pesticides" and 

"toxic elements"). 

Ratings were converted into weights by 

assigning a "temporary weight" of 1.0 

to the parameter which received the 

highest significance rating; i.e., 

dissolved oxygen. 

To preserve the ordering and relative 

ratios returned by the panelists, 

other temporary weights were obtained .. by dividing each individual mean 

,ratinginto the highest rating. 

Each "temporary weight".was then 

divided by the sum of all weights 

to obtain the final weights, wi0 

10 
~ .

. -- 1 - e. ~ 

Table 2. SIGNIFICANCE RATINGS AND WEIGHTS FOR 

NINE PARAMETZRS INCLUDED IN THE WQI 

Mean of all significance ratings returned Temporary Final 

Parameters by respondents Weights Weights 

Dissolved Oxygen 

Fecal Coliform Density 

PH 

Biochemical Oxygen Demand (5 -day) 

i\jitrate s 

Phosphates

Temperature 

Turbidity 

Total Solids 

1 

I 

1.4 1.0 0.17 

1.5 0.9 0.16 

2.1 0.7 0.11 

2.3 0.6 0.11 

2.4 0.6 0.10 

0.10 

2.4 0.6 

2.4 0.6 0.10 

2.9 0.5. 0.08 

3.2 0.4 0.07 

Total = C = 1.00 

11 
With parameter selection, quality curves, 

meter significance determined, the project 

an additive expression for WQI: - __ . n 

WQI = C wi qi 

and relative parastaff proposed 

number between 

i=l 

the Water Quality lndex, a 

0 and 100 (theoretical), 

where WQI = 

= qi 

wi = 

n = 

the quality of the ith parameter, a number 

between 0 and 100, (read from the 

quality curves), I 

the unit weight of the ith parameter, a 

number between 0 and 0.17, and 

the number of parameters. 

In the WQI expression (Equation 1), n = 9 and includes: 

dissolved oxygen (DO) ., expressed as percent 

saturation 

fecal coliform density (FC), no./100 ml 

PH 

nitrates (NOj), mg/l N03-N 

phosphates (PO4) 8 mg/l PO4+ 

5 day biochemical oxygen demand (BOD5) mg/l 

temperature (T) , OC departure from equilibrium* 

total solids (TS), mg/l, and 

turbidity, JTU (Jackson turbidity units) , 

*"Equilibrium" temperature is defined as that which is known 1 

to occur without the influence of heated or cooled discharge. 

In field application of WQI, two temperatures are taken: 
one at the sam2ling site and one at some point upstream where 

heated or cooled discharge is known to be absent. 

For samples from stations known to include pesticides or 

toxic elements, laboratory analysis of these'constituents is 

required. When any level exceeds its maximum permissible 

iirriit, the index is automatically "zero. '' 

Field Evaluation 

Progress in developing WQI was first reported in a paper 

presented, at the National Sym?osium on Data and Instrumentation for Water Quality Xanaqement, held in Madison, Wisconsin 

in July 1970 (8). Consistent with the concern that WQI be 

' used responsibly, data from the quality curves (qi) were not 

made available in this presentation. 1n.response to requests 

. 

for qi data, NSF proposed that field application of WQI be 

undertaken as a coordinated effort. As a result, water 

quality management agencies (listed in Table 3) reported 

laboratory data to NSF from routine surveillance programs 

at more than'80 sites for periods up to 15 months. Again, 

this activity was entirely unsponsored. Site selection and 

sampling frequency were, in general, a function of availability of staff and fiscal resources within the participating agency. Data for the nine parameters in WQI were 

reported monthly; WQI's were calculated at NSF and returned 

to each participant. 

A wide variety of quality characteristics were reflected in 

the data. Samples were taken from clean, upper reaches of 

13 

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al

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c, k 

4 1 

a 

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X al 

P; w 

0 rl

h 

m

u 4J k 

c c 

1

al 4J

2 c, z til m-rl m 

a rcr Ql

al 0 

n 4J 

sr 

c Li 

2 a 

- k 

4J

E 

d

7 

k

0 a 

U Ql

al

k 

a

E al al -4 c, 4J k a a a c, U

-4 v3 a 

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.ri c al al 

c, 9 al a u1 4J 10 cn al

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14 
small streams, downstream from municipal wastewater treat­

-t. ment plants and points of industrial waste discharge, and 

lakes with seasonally diverse population densities. Results 

of the study showed clearly that quality variations are consistent with - and can be reported by - changes in WQI. 

They illustrated dramatically the fallacy of reporting 

quality variations in terms of changes in single parameter .. . 

values. For example, at one station in Pennyslvania, downstrean from two overloaded package wastewater treatment . 

plants, least squares regression analysis of the data from 

40 samples taken during the period July-1971 to August 1972 

established that approximately 87% of the variation in WQI 

(A2=0.8695) was determined by DO, BODg' pH, and total solids. 

At a station further downstream, just below the discharge 

from a mine pamp, 92% (R2=0.9169) of the WQI .was detenined 

by fecal coliform density, pK, and phosphates. 

Quality profiles from three stations on a Michigan stream 

with recreational lakes scattered throughout the area reflected changes at.tributed to high density vacation populations. Flow patterns and mixing characteristics of treated 

wastewater effluent from a large city in Michigan were 

observed by plotting WQI values 'from stations on both sides 

of the receiving stream, above and below the treatment plant. --. 

These data are described in detail in a paper presented at 

the ASCE National Meeting on Water Resources Engineering (9), 

and in the final report prepared for each participant in the 

'study (10). 

. -

Further Efforts to Evaluate WQI 

Despite the apparent responsiveness of WQI to changes in 

water quality conditions, analysis of data from the field 
. ---study suggested that the additive WQI lacked sensitivity in 

adequately reflecting the effect of a single low value para-

. meter on overall water quality. Initially, the additive 

model was selected because it is conceptually simple, easy 

to calculate, and entirely reproducible. O'Connor noted 

~ that, "the additive model is a good choice when all -parameter: 

are within a reasonable range, but a multiplicative form is 

more sensitive to discontinuities in overall quality which 

may result witn zero or poor quality in any parametric 

dimension. I' (11) 

As a result, a multiplicative form of WQI was proposed ( g ) : 

where WQI (MI = the multiplicative water quality index, 

a number between 0 and 100 (theoretical), 

. qi = the quality of the ith parameter, a 

number between 0 and 100, 

wi = 

the.unit weight of the ith parameter, 

a number be tween 0 and 0 1 7, and 

--* n = the number of parameters. 

. To determine relative merits of adopting the additive WQI 

(WI;rI(A)> versus WQI(M) historical data for both "good" and 

rpoor" quality stream conditions were accessed from STORET. 

WQI(A) and WQI(M) were calculated for all data and differ- ' 

ences in the two values evaluated with respect.to physical 

conditions known to exist at each reported site. Again, a 

wide variety of quality conditions were considered: upstream and downstream from refineries, steel mills, and 
municipal wastewater treatment plants. Data influenced by 

industrial wastes were significantly different when reported 

as WQX (A) versus WQ3 (M) As expected, WQI (M) was significantly more sensitive to the. effect of a single bad parameter. 

In addition to evaluating historical data, a questionnaire 

was mailed to 160 water quality management experts - more 

tnan 70 who participated in developing WQI, and others 

assumea to be new to the concept. The questionnaire was 

designed to determine, I) how water quality ratings assigned 

by the experts related to WQI(A) versus WQI(M) , and 2) whether 

or not original group judgement differed significantly from 

the opinions of other water quality experts., 

Values for each of the nine WQI parameters in 20 actual 

'stream samples - data from the Kansas study, the initial 

evaluation of WQI in Pennsylvania, Michigan, etc. and 

data accessed from STORET*- were included in the questionnaire. The experts were asked to review the data for each 

individual sample and return both a numerical (0 to 100) 

and a verbal ( "excellent, " "good,'' "medium, 'I "bad, I' or 

"very bad") rating which, in their judgement, described 

the quality-'of that sample. 

More than LOO responses were returned, with 30 from the 

ociginal group. Results of the survey to date indicate that: 

I) Calculation of WQI by the additive 

model produces a number which averages 

10 to 15 WQI units higher than experts 

judgementally rate the same water. The 

difference is greatest at the low end . 

of the scale. 

17 
Calculation of KQI by the multipli­

.". _--. . cative model produces a number which 

averages 6 WQI units different, 

distributed above and below the experts' judgemental ratings. 

There is no significant difference 

between the way original and new 

expert panelists rate water quality. 

Although results of this survey are not yet complete, it is 

clear tnat the multiplicative WQI is closely related to expert judgement of water quality conditions. NOTE: Becauae . 

lthia JLepozZ uan compeelted p/rio/r tc Rlie bitrvey, da.ta in Xtab,lea 

and digutrea ane hspckted paincipaUy aa WQl (A]; howeve&, 

Wzl(bi) vutuea have been adied 20 Rite Rabteb in Appendix D, 

and ptotlted, do/r putponea 06 cornpaniaon, in Figuae 3, 5, and 7. 

Questionnaire responses differed widely with regard to verbal 

ratings. A feedback questionnaire, to be mailed in the near 

future, will permit each panelist to review his response with 

respect to group judgement, and attempt to bettsr define 

what the expert calls ''good" or "bad" water quality. -.­

18 
. .. SECTION IV 

PROJECT ' UZSCRIPTION .. . * ... . . .... .I . ..-. . _. . ­ . 

'..;Objectives - .. 

... .. .. . 

Principal objectives of this project were to: . __ ...- ~. 

1) Apply WQI to selected sites in the 

. Kansas River Basin through a corn-

_ - . prehensive field sampling and laboratory analysis program, and

-~ 

2) Evaluate the effectiveness and 

utility of WQI as an indicator of 

water quality variations. -

Secondary objectives included determ'ining optinum frequencies 

for sampling I computing , and reporting WQI. 

- Study Area 

Tne main stem of the Kansas River originates at the confluenceof the Republican and Smoky Hill Rivers, east of Junction 

City, and empties into the Missouri River 170'miles to the

-. 

.. east at Kansas City. It is a wide, shallow river of moderate .-. . . .. 

yelocity with a shifting sand bottom. In terms of flow, it 

- is the largest stream in Kansas. 

Treated municisal wastes from more than 40 cities and towns 

ranging in population from 106 to 123,000, and effluents 

from at least 20 small wastewater treatment plants serving 

restaurants, mobile home parks, high schools, etc. are 

discharged to the Kansas River (12). The largest city, 

. Kansas City, .is heavily industrial; Topeka and Lawrence are 

19 
characterized by light industry-(principally food and . 

'\ kindred products, printing and publishing, fabricated metal 

products, and chemical processing). Other portions of the 

study area are essentially rural-agricultural, with - - river 

valleys comonly devoted to truck farming, and hilly areas, - - to pasturelands.-

Selection.of this area for application of WQI was a direct 

result of the high level of interest which water quality 

administrators in the area continue to express for the index 

concept in general, and WQI in particular. Abinistrative 

and technical staffs from EPA Region VI1 and the Kansas 

Department of Health contributed extensively to planning and 

conducting the.,project. 

... ...._ Samp'ling Sites 

Twenty-six sites between Junction City and Kansas City - 14 

on the Kansas River and 12 on major tributaries - were 

sampled for this study. Routine surveillance sites and 

stations from previous special studies were included. Intermediate sites were added when long distances occurred between the regular stations. 

Sampling'locations are listed in Table 4 and shown schematically in Figure 1. It is apparent from Figure 1 that flow in 

the study area is affected by a number of large impoundments, 

constructed for flood control, water supply, conservation, 

augmentation of flow for downstream uses, and recreation. 

Sampliqg was limited to sites downstream from the reservoirs. 

Sampling Scheme 

In designing the sampling program, a principal concern was to 

20 
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24 
25 
provide a sufficiently large data base to be statistically 

significant in the evaluation process. A uniform.pattern 

was established for sampling nine main stern stations considered to be critical for reflecting quality variations . (high frequency stations) ; five main stem and four tributary 

stations considered somewhat less critical (medium frequency 

stations) ; and eight tributary stations (low frequency 

stations). The high frequency stations were sampled every 

other day; medium frequency stations, every fourth day. 

Sarnpling times for these stations were coincident with 

every second sample of the high frequency series. 

Low frequency stations were sampled every eighth day, with 

samsling times coincident with every second sample in the 

medium frequency series, and every fourth sample in the high 

frequency series, One extra set of -the-'low frequency samples 

was included in the schedule to compensate for the period 

when no low frequency samples would be collected if the every 

eighth day algorithm were strictly observed. 

The overall sampling scheme, shown in Appendix B, is summarized as follows: 

11 days, 26 stations (9+9+8) = 

8 days, 18 stations (9+9) = 

--. 18 days, 9 stations = 

TOTAL 

286 samples 

144 samples 

162 samples 

~ 

592 samples 

The desirability of reflecting day to day variation was also 

considered in designing the sampling schedule.. Sampling * 

.every second, fou-rth, or eighth day over an eight week period 

insured that at least one sample would be taken from each 

station on each day of the week. Variations which could be t 

attributed to morning versus afternoon sampling times were 

26 
--- 

I considered by varying the direction of sampling; i.e. east 

to west or west to eastf according to a predetermined pattern. I - . . - I II 

To optimize mileage logged for sampling, two sample collectors 

worked on the project. One, 'based in Kansas City, routinely 

sampled stations numbered-1 through- 12; the pther based in . . -., -.. ._ _,.... .< ' . . .3 ._...- .

. I. -:7 ~ -. 5.' . -.. ._. .; . -.:. .. . . - ,. .. . - .. ._ -

'Topeka, sampled stations 13 through 26, always in numerica;l .. . .* .. .. 

order; ' e..g. 1 through 12 or 12 through 1. On high &equency . .. . .. 

. . sampling. days, ._. one man collected 'all nine samples-.. The ., . . . .. - ._ 

'' Topeka-based collector worked on "west to east days," and -. -

the Kansas City-based collector worked on ''east to west days." 

. Time of travel for sampie collectors ranged from five to 

eight hours in accordance with the predetermined daily 

schedule. I -

-. 

. ­

27 
.. '1, SECTION V 

L :- -.. 

EXPERIMENTAL c 

Sample Collection and Preparation 

- Samples were coliected from the downstream side of bridges, 

approximately midway across the stream and from a depth of 

two feet (except when river staging was too low to permit 

sampling at this Ziepth). Bacteriological samples were collected in sterile bottles and iced for transport to the 

,* ' . 

. .. EPA Region VI1 laboratory in Kansas City, Kansas, which 

served as project headquarters. Samples for physical and 

cnemical analyses were collected with an APHA-type DO 

sampler, drop2ed three tines at each station. One, 300 ml 

BOD bottle was filled in the sampler, fixed in the field, 

and returned to the laboratory in a dark box for measurement 

of DO by the Winkler nethod. Excess sample was placed in 

two, one liter cubitainers and iced for transport. Temperature was measured in the field. 

Sample preservation and maximum holding periods were in 

accordance with those described in Standard Methods (13) or 

the EPA -Methods Manual (14). Maximum time lapse between

collection and receipt of samples at the laboratory was six 

hours 

At the laboratory, DO titrations, BOD dilutions, and all 

bacteriological samples were processed immediately. Approxi- . mately 800 ml was-removed from one cubitainer for the BOD 

test. The excess was preserved with mercuric chloride'(Hg . 

C12, 1%)and refrigerated for subsequent analysis of nutrients L 

(X03+N02, NH3, and PO4). A sample from the second cubitainer 

was placed in a four ounce bottle, preserved with HCI (2 ml), 

28 
.... . 

,, and refrigerated prior to shipping to Ann Arbor for-measuring \%,, 

., TOC. Excess sample was refrigerated overnight (approximately ;a ; .. 

12 hours) at 4OC. The following morning, it was warmed to 

2SoC, mixed by inversion, and used for -immediate determination 

of pH, conductivity, and turbidity. The excess was again 

refrigerated for subsequent chloride, solids (total and 

suspended), and ’COD analyses. A schematic illustration of 

sample distribution and preparation is shown in Figure 2. .. 

Me tnod s 

Seventeen parameters were measured in the laboratory - the 

nine in WQI and eight closely related parameters - to determine the validity of term substitution in the index expression. (The eight additional parameters included: suspended 

solids, chemical oxygen demand (COD), total organic carbon 

(TOC), total coliform density, and fecal streptococci.) 

Analytical procedures were performed in accordance with 

Standard Methods (13 ) or the EPA -Methods Manual (14). The 

specific methods used in this study are shown in Table 5. 

Quality control procedures were employed routinely throughout 

the laboratory phase of this project. EPA analytical reference standards for all parameters were included at random 

with routine analyses. Instruments were standardized regularly 

before and during each use. In general, quality control 

procedures were performed in accordance with the EPA -Eandbook 

-for Water -and Wastewater Laboratories (15). 

29 

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SECTION VI. 

, ' XESULTS 

WQI(A) and WQI(M) were calculated for all sampling days except October: 6 when aliqdots prepared for N03+N02 (and NH3) 

were accidentally discarded. In all calculations, temperature, 

expressed as degrees C departure from equilibrium, was 

assumed to be zero. No effects of heated or cooled discharge were known to occur at any sampling station included . 

in the study. Two tenperatures were taken during the early 

sampling runs - one at the site and one upstream - to confirm 

this hypothesis. 

Data for each of the 17 individual parameters and time of 

sampling are mown by station in Appendix C (Tables C-1 

through C-26). Flow, provided by the U.S. Geblogical Survey 

from gauging stations in the study area, are also reported 

in tables in Appendix 'C. WQI (A) , WQI (N), and quality ratings 

(4.) for each parameter in WQI are reported by station i n 1 -.. 

the tables (3-1 through D-26) in Appendix D. Note that 

temperature qi is cansistently reported as 94.9 as a result 

of assuming zero degrees departure from equilibrium for all 

samples. 

Summary statistics for each variable in WQI(A), including 

the number of analyses (n), arithmetic mean, standard deviation, standard error of the mean, minimum, and maximum 

values are shown in Appendix E (Tables E-l through E-26) for 

each individual station. 

In Appendix F (Figures F-1 through F-26) , WQI(A) is plotted 

versus time (date) of sampling for each station. 

Water quality index profiles - WQI(A) versus distance - are 

shown in Appendix G (Figures G-1 through G-36). Note that 

35 . 
. -- 

-- 

-- 

distances ' (station locations) are approximate in this series 

of figures. River stations -are connected by solid line; + -. 

tributary WQI Is are shown - as .individual poinfs8 not connected

,-,.... - -....-.- . ... - - .. -2; 1J.Y ..: ... ,* 3.1.1.- *.*.:J.'kZl7 to.;the..solid'.:.line* ,i ...... ._... '" . , . . Numbers near the data po&nts refer,*to _. . ... ..C"r.J*: .-:. ,. - -.-a _I, . .. .. .s.-:,-: <..;e : ........ '-fibw8' in cfsl recorded at USGS gauging stations,... at the_ .> - 2 ..time .. -.

-. .i- . 

i ... 2...... . - ........ ... 0. _..-c.c-.­

.of-sampling... ...... ,__.*. . . - .. -' IC..

-. .. :. .. .. .. ..t .: . . ---!,;. -;-:-..... ;.,; .......- .-,C,:,C;C. - -?:;%..+ 

. . .....-.~

- . 

.. ­ .. .. 

. 

.. 

I 

\ 

36 
SECTION VI1 

DISCUSSION 

Quality Variations 

Deininger reported that values -+5 WQI are significantly different, and. "WQI is pkobably sensitive down to.a two point 

difference"(16). In discussing the data from this study 

-variations -+5 WQI (A) or WQI (M) are assumed to be significant. 

Mean values for WQI(A) and WQI(M) at all stations over the 

entire period of observation are plotted in Figure 3. Main 

stern stations are connected by a solid line and tributary 

stations are shown as isolated points, as described in the 

legend. From the data in Figure 3, it is apparent that 

quality in the main river showed no significant variation 

over the study period when expressed a5 mean WQI(A) (range 

65-68), and varied only slightly as mean WQI(M) (range 51-58). 

The quality at Willard, Lawrence, and Paxico was significantly 

better than at Eudora or Topeka, and at Willard, it also 

exceeded the quality at the James Street station in Kansas 

City (as WQI(M)) 

The greater range and sensitivity of WQI(M) is further illustrated in--Figures 4 and 5 (mean, high, and low WQI(A) and 

WQI(M), respectively, for main river stations) and Figures 

6 and 7 (mean, high, and low WQI(A) and WQI(M) for tributaries). 

The effect of one or two unusually ''bad" parameters is apparent by visual comparison of the range of WQS values reported for the Delaware River (Figures 6 and 7). This was 

the "best" quality tributary over the period of observation. 

In the sample taken on Sovernber 13th, turbidity and fecal 

coliforms were unusually high - 140 JTU and 2900/100 ml, 

respectively. The highest turbidity level in any other Delaware 

37 
. .. . - -. ~ .. - . -..­

. 

e ­

o 

I.XI x I XI x 

x" 8" 

eo 

0 0 

0 

a 

. 

m 

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VI 

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... . 

38 

. 
.. 

. 

e 
t I

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0 .. I 

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42 

0 
River sample was'40 JTU; the mean for all other samples was 

15.5 (JTU) (Table C-12 Appendix C). Expressed as qi, a 

turbidity of 140 JTU equals 5.00;.a turbidity of 40 JTU 

equals 44.7 (Table D-12, Appendix D) . ' Fecal coliform density'" 

in the Delaware on November 13th was ZSOO/~-O-Oml. The mean . . .. 

of all other samples was 202/100 ml. Expressed -. as qi,

these values are 14.6' and 34.8, respectively... .'Other .. 

unusually high data for -thissample are not '-includedin the 

WQI expression;'e.g., suspended solids and.totalcoliforms. 

Comparison of the range of.WQI values shown in Figures 6 and . .. .

7 for the Delaware River demonstrate the improved sensitivity 

of WQI (31) fur treating unusually bad parameter values. . I 

The maximum is the same in both .figbres,the mean, only 

slightly less for WQI (M), but the low WQI(N) is significantly 

lower than the lowest WQI(A). 

Data from Figures 3, 4 5 6, and 7 are summarized in Table 6. 

Willard, the "best qzality" Kansas River station, is a small 

town (population 94) about midway between Paxico and Topeka. 

Small creeks discharge to the Kansas River between Paxico and 

Willard, but there is no reason to expect any of them to 

contribute significant pollutional loadings. The Willard 

location was sampled principally because of the long distance 

between Paxico and Topeka. 

"Best" tributary quality was recorded from the Delaware and 

Big Blue Rivers, discharging from Perry and Tuttle Creek 

Reservoirs, respectively. Because reservoir retention pro-

* vides time for self purification and sedimentation, the 

quality at these stations was expected to be consistently 

high. 

"Poorest" quality in the main river occurred at the station 

near Eudora; just downstream from Lawrence, and at Topeka. 

"Poorest'~quality in a tributary was observed in Shunganunga 

Creek. Quality variations at the Eudora station result 

43 
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W 

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principally from municipal and separate industrial waste 

discharges in the Lawrence area. (Wastes from Eudora are 

discharged to the Wakarusa River which enters the Kansas 

just downstream from the Eudora station.) Lawrence discnarges 4.57 rngd directly.to the Kansas River from a primary 

slant treating a waste of 45,700 population equivalent, 

with' contributions from at least nine industries including 

-,--organic dyes and inks, blood, and various food processing 

wastes. Industrial wastes discharged directly to the 

Xansas River include: an electric utility (.01 mgd treated 

by extended aeration plus .43 mgd cooling water), an 

industrial and agricultural chemical company (500 gprn of 

untreated process wastes containing phosphates, suspended 

solids, and hexavalent chromium), and a paper and container 

board company (900 gpm of treated wastes containing suspended solids, sulfates, and organics with a mean BOD of 

80 mg/l. 

Topeka is the second largest city in the study area, and 

discharges both municipal and industrial wastes directly 

to the main river. The principal municipal wastewater 

treatment plant is located downstream from the Topeka 

sampling location and would not be expected to have an 

affect on quality at this point. A smaller plant (designed 

for 12,500 -3 P.E. and loaded at approximately 1000 P.E.) upstream from the sampling location discharges its effluent 

along tkle north bank of the river and would likely not be 

well mixed with water in the river .at the referenced .. - sampling point. It may be reasonable to assume that either 

an unidentified direct industrial waste discharge or stokm 

water from Topeka contributed to the relatively low mean 

WQI value observed at the Topeka location. Storm water 

discharge and effluents from the wastewater treatment 

plant serving Forbes Air Force Base may also contribute 

45 
.. . . 

. ._. 

. , . .. , ... signifi.cantly to the observed mean WQI for Shunganunga b 

Creek, which flows through the City of .Topeka.' 

.. 

The main stem station with the widest range'of reported WQI 

was at,Lecompton, just downstream from the point where the 

Delaware River discharges to the Kansas, and downstream from 

Topeka. The Delaware contributes good quality flows to the 

Xansas with discharges from Perry Reservoir: however, it 

appears that the main river may be stratified at the 

Lscom;?ton station and that the stratification line may' 

change as.a function of.relative flows in the two streams. 

Thus samples collected from midstream may'have been in 

differeiit strata at various times of sampling. Least 

variation in main stream stations was observed in Kansas 

City at 7th Street.' 

NOTE: faom Ta'bee 6, it ih appatd that ChaRactetihtich 

obbsaved at any hampling location wme. Xhe hame. whethet 

ca2cutationh..&eke additive. ok mul2iplicative in iotmat. 

- . .-.' : 

Despite--fhe brevity of the field phase of this study, quality 

in the Ransas. 'River and its tributaries generally improved 

over .the period'of observation. Initial and final WQI (A) 

values for each sampling location are plotted in Figure 8. 

At a ievei'of -+5 WQI units, all main river stations except 

Gansas City 'at'7th Street, DeSoto, Lawrence, and Ft. Riley, .* 

and all tributary stations except the Delaware River, Soldier 

Creek, and Clark Creek, showed significant improvement. This . .. * effect can likely be attributed to normal seasonal variation 

associased -with the colder weather. .1 . 

. . 

46 .. 
U 

.A 

c 

H 

47 
Although no significant variation in quality expressed as 

i * mean WQI (A) is demonstrated in the main river. over the entire sampling period, short term variations are apparent 

from the figures in Appendices F and G. WQI(A) versus time 

is plotted for each station in Figures F-1 through F-26 

(Appendix F) I and profiles, WQI(A) versus distance, are 

shown for each sampling day in'Figures G-1 through G-36 

(Appendix G) . In Appendix- G, main stem stations are connected by solid lines, tributary stations are shown as 

isolated points, and flow, from USGS gauging stations, by 

numbers (as cfs) near the quality designations. 

In general, the quality of tributaries is better than that 

in the main stream (Appendix G); however, Mill and Shunganunga Creeks are frequent exceptions. (Two "Mill" Creek 

sampling stations are included in the study. These were 

on two separate creeks, one considerably east (upstream) 

of the other. Reference to "Mill Creek" quality in the 

previous statement relates to the creek to the east, near 

Kansas City.) Bridge construction near the Mill Creek 

. 

station may have affected the data acquired at this location. 

From the figures in Appendix F, it is apparent that quality 

in rivers and tributaries does vary between.sampling periods, 

and thgt these variations can be expressed as WQI. This 

single number expression of nine important water quality 

parameters is much more meaningful than similar plots of 

single parameter values, and' provides a sound basis for .. water quality management decision making. 

Short term variations at individual stations are shown in the 

data plotted in Appendix F. The quality changed significantly ? 

(+5 - WQI units) from sample to sample six times in the main

river at 'Kansas City-James Street (10-14116, 10-20/22, 

10-22/24, 11-07/09, 11-11/13, 11-15/17), and nine times at 

48 
Lecompton (10-02/04, 11-11/13, 11-15/17, 11-19/21, 11;23/25, 

11-27/29, 11-29/12-02, 12-02/03, 12-03/05). Lecompton was 

. the high frequency station previously reported (Table 6) to 

be "most variable" on the main river. Most of the variation 

occurred late -in the study: Every other sample from 

November 09-23? and every sample from November 23-December OS 

was significantly different from the sample taken either 

just before - or just after -I or both, Four individual 

parameters .- POqr tbtal solids, turbidity, and BODS - varied 

appreciably during this period. 

. . Data from Kansas river stations at Topeka and Lecompton and 

from tributary stations discharging between these two main 

river stations - Soldier Creek (which receives industrial 

wastes from a rubber company), Shunganunga Creek, and 

the Delaware River - are plotted in Figure 9. Data only 

from days on which all stations were sampled are included. 

The upstream station, Topeka, is shown in the open circle, 

solid line format, and the downstream station, Lecompton, 

in the closed circle, solid lhe format. The ability 

of WQI to reflect the effect of tributary contributions 

on overall quality of the main stream is demonstrated 

in this figure. During the period 09-26 to 10-04, 

downstream quality was significantly xltered by the relatively poor quality discharged from Shunganunga Creek. Flow 

in the creek was so low at the time of sampling on 10-04 that 

tne sample--*aepthwas two inches (routinely two feet), thus 

temperature was high; percent DO saturation, low; fecal 

coliform density, high; etc. Flow in the main stream was 

also relatively low during this period, thus the apparent 

effect of the tributary contribution was dramatic. Downstream 

quality improved on 10-12, apparently as a result of rainfall 

that provided dilution, and the release of high quality water 

-! from Perry Reservoir, and peaked on 10-20 with good quality 

contributions from all tributary sources. Conversely, 

49 
.. 

.. 

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.... 

. -. .- I ...._ . -.. .. .. . .. . 

. . , 

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\ --.- .

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\ * . * 

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quality dropped in all the tributaries on 11-13, and 

downstream quality again reflected these changes. Flow on 

this date was relatively high at all. stations - from1800 cfs 

on 11-05 at Topeka to 4000 cfs on 11-13; 150 cfs on 11-05 on 

the Delaware River to 500 on 11-13; 40 cfs on Soldier Creek 

to 3000 cfs; and 2600 cfs to 5200 cfs at Lecompton. It 

would appear .that these flows had a scouring effect on the 

streams which reflectea in calculated values of WQI. Flows 

recorded for Topeka, the Delaware River, and Lecompton 

between the intervals shown in Figuxe 9 continued to increase, 

then became relatively consistent for Lecompton; e. g. , 

11-15, 12,000 cfs; 11-17, 10,000 cfs; 11-19, 9600 Cfs; 

11-21, 8000 cfst 11-23, 7400 cfs; 11-25, 7400 cfs; 11-27, 

7700 cfs (from Table C-llf Appendix Cl - until peak quality 

was observed on 11-29. With some basic knowledge of.the 

sampling sites, fiow characteristics, etc., it is possible 

to explain the apparent trends in Figure 9, and to use this 

information to.predict future effects of changes in quality 

at these locations. WQI provides an ideal method for 

presenting overall quality variations as a function of 

time and distance. No single parameter data could be used 

in achieving similar objectives. ..-. 

.' Frequency of Sampling, Computing, and Reporting WQI 

4 In determining optimum sampling frequency, "true mean" and 

"true standard deviation" were computed for the largest data 

base available; i.e.,- WQI values for the nine high frequency 

stations. For every station {i) in this groupf there were 

i thirty-seven WQI values [Wi'1' 'i,2, 'i,3***, 'i,37 I which 

refer to every other sampling day (1, 3, '5, 7..., 37) during 

51 
- 

the study. 

\ - , -. .. - I_ ­ \ 

-.-. .-,The data recurd was then divided in half by ..

arranging _. . . the

- :WQS's into two sets. Consecutive values in each set now . .. refer to samples taken four days (d) apart; - _--i.e. , .I.' ,'-

I .. 11.

'**dl '*Id 2 

d3 d4 

ds ds 

Mean (Mi, and M. 

12 

1 and percent deviation (PDi, and PD. ) 1 2

from the mean were calculated for each of.these two sets. 

To estimate deviation from .. the true mean if samples were taken .. every fourth rather than every second day,' average percent 

deviation was calculated. The steps are summarized as 

follows: 

[Wl rl I Wir2?Wit3..., Wit3,1 3 TMi and TSDi (3 1 

where --. i = station 1, 2, 3,...9 

W = WQIl ...WQf37 at station i 

TM =, true mean \ 

TSD = ' true standard deviation ... -

(TMi-Mi- )

r l - x 100 (4 1 s 

TMi 

52 
and 

(TMi -Mi ) I2 

3) iSDi.= PDi = 1/2 {PDi + PDi ) rl r2 

Tnis process was continued for three through 19 ssks 

of sub records; i.e., percent deviation of mean WQI was 

estimated for samples taken every fourth, sixth, eighth. . . fortieth day versus the "true mean" experienced with sampling 

every second day. Using this approach, the lowest-percent 

deviation from the true mean occurred for samples taken every 

sixth day for six of the nine stations. 

For all nine stations, twenty-day sampling frequencies 

provided WQI values with less than (<) 2% average deviation 

from the mean. If this is sufficient accuracy for routine 

.surveillance programs in the study area, the every twentyday sampling scheme should be adopted. Results of this 

analysis -are-"shownin Table 7. 

The practice of calculating WQI each time data for all niiie 

parameters are available is recommended. With calculators 

and computers generally available, calculation bf WQI is a 

simple "next step" in processing water quality data. Hand 

calculation, though more tedious is also manageable. 

f 

The optimum frequency for reporting WQI is a function of 

variations in data which may occur as a result of local 
noc '(c r) I 

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54 
conditions. The duration of the field sampling phase of this 

study was too short to reflect seasonal variations, and improperly timed to be coincident with high temperature, low 

flow conditions. A firm recommendation for frequency of 

reporting WQI should be made only when these additional data 

are available for consideration. Review of statistical data 

(Appendix E) from the period of observation suggests that 

reporting only once every three months or more is sufficient 

to indicate water quality conditions during the fall months. 

By applying least squares regression, four parameters were 

shown to account for more than 90% of the variance in 

WQI over the period of observation. Results of these 

analyses are summarized in Table 8. The summary is grouped 

to include 1) all data and 2) all main stem river stations. 

. Although tne same four parameters are indicated in both 

groups of data, variation in their relative importances is 

noted. By difference, it is apparent that fecal coliform 

density accounts for most of the variance in quality at 

tributary stations but is a considerably less importact 

parameter at river stations. Although there is no adequate 

substitute. �or adopting a uniform method of reporting water 

quality, this information, when related to costs for laboratory analysis of- - .. 

each parameter, is useful in planning 

routine data acquisition programs. In reporting WQX all 

nine parameters in the expression must be measured. However, 

more frequent analysis of fewer parameters may be used to 

show intermittent trends in stream quality, particularly at 

critical locations. 

. 

55 
-- 

.. 

"C . - . .1..' , .. . .'. : 

. . . * . 

- . . .. . .. .. 

.. .... . ­ . Table 8.. 'XEGRESSION- ANhYSIS OF WQI PARAMETERS - . 

' BY FORWARD SELECTION 

All Data - (From Quality Ratings) 

Parameter 

Fecal coliforms. 

BOD 

Turbidity 

p04 

DO (% Sat) 

Total solids 

PH 

R2 

.524 

' -726 

.826 

.916 

.956 

.987 

0997 

NO3 C NO2 .1.000 

All River Stations 

(From qi) 

Parameter R2 

BODj .407 

Turbidity -718 

p04 . ,843 

Fecal coliforms .904 

Total solids -938 

DO (% Sat) 0 973 

PH .994 

NO3 + NO2 1.000 

-. 

I 

56 
.. . 

.. . 

SECTION VI11 . 4 

SPECIAL STUDIES 

Parameter Correlations 

In field application of WQI, the feasibility of parameter 

substitution is frequently discussed. To establish the. 

effect of modifying parameters., as well as reducing the 

number of total parameters in the index expression, laboratory analysis in.this study was extended to include 15 

parameters for all samples, and 17 parameters on 11 predetermined sampling days. Analytical data for all samples 

included the following measurements: 

- all nine parameters in WQI, plus I

- -. conductivity, pmhos/cm 

- suspended solids, mg/l 

- amonia, mg/l NH~-N 

- chlorides, mg/l 

- total coliform density, #/lo0 ml 

- fecal streptococci, #/lo0 ml 

Analytical data for samples collected on 9-28, 10-6, 10-10, 

10-18, 10-26, 11-3, 11-11, 11-15, 11-19, 11-27, and 12-5 

included two additional parameters : 

- chemical oxygen demand' (COD) 8 mg/l and 

-' total organic carbon (TOC) I mg/l. 

Correlation coefficients for eight selected pairs of parameters are shown in Table 9: total solids versus conductivity, total solids versus suspended solids, turbidity 

versus suspended solids, fecal coliforms versus total coliforms,' and fecal coliforms versus fecal streptococci. 

57 
-- 

.. ­ - .. . 

, .. - Table 9. CORRELATION COEFFICIENTS FOR . 

SELECTED PARAMETERS 

All Data All River Stations 

R @ 95. = .083 R @ 95. = .094 

Parameters R @ 99. = .lo9 R @ 99. = .123 

Total solids versus .385 . . Conductivity 

Total solids versus .742 

Suspended solids 

.Turbidity versus ,932 

Suspended solids 

' Fecal coliforms versus ,855 

Total coliforms 

Fecal coliforms versus ,165 

Fecal streptococci ".-* 

.456 

.575 

.937 

.849 

,131 

58 
In each pair, the parameter in WQI is listed first; the 

.% related parameter follows. 

Data.are grouped to include all data, and all main river 

stations, with correlation coefficients -expressed at 95 and 

99 percent levels of confidence. 

The degree of correlation at 95 and 99 percent confidence 

levels was determined for each individual station included 

in the study. These data are summarized in Table 10. Re-

. ': sults of individual station correlation are shown in 

Appendix H. From the sumnary (Table 10) it is apparent 

that suspended solids can be substituted for turbidity 

measurements, and total coliforms for fecal coliforms with 

a high level of confidence. Other parameters were not I 

shown to be closely related. 

Hoilrly Variations 

One twenty-four-hour study was undertaken on November 6, ' 

1972 from the 7th Street Bridge in Kansas City. Samples 

. were taken every two hours and brought to the laboratory 

for measurement of the nine parameters in WQI. Data 

for each individual parameter and the WQI'S are listed 

in Table 11;. No significant variations in WQI occurred 

during this period: however, the data may have been 

affected by heavy rainfall at 1000, 1200, and 1400 hours 

and light rain at 1600 and 1800 hours. Flow rate was not 

measured, thus actual effects of the rainfall are not 

determined. It is entirely possible that flow patterns 

for storm water discharge followed the banks too closely 

for detection at midstream, where samples for this study 

59 

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were obtained. There is no reason to assume that 

sampling or analytical errors contributed to the .uniform 

quality reflected in reported WQI. .-

Transverse and Vertical Variations 

On December 5 and 8, 1972, sampl.es were taken .from a boat to 

reflect transverse and vertical variations in Kansas River 

1 . 

quality at the Kansas City-7th Street sampling station. A 

profile of the stream at this station is shown in Figure 10. 

Sampling sites for both studies are indicated on the profile. 

Points 1, 3, and 5 are’two feet below the water surface. 

Point 2 is six feet, Point 4 is seven feet, and Point 6 is 

eight feet below the surface. 

On December 5th, beginning at 0830 hours, samples were taken 

in sequence from each of the six points indicated in Figure 10. 

A single bottle Dunker sampler, flamed at the inlet tube and 

in the chamber with a propane torch, was used for sampling. 

Sampling was repeated at each point in sequence beginning 

at 1000 hours and again at 1100 hours. Microbiological data 

obtained from this study are reported in Table 12; 

-_. 

In a similar study on December 8th, two se-ts of samples 

were taken at -approximately three hour intervals from the 

same six points, beginning at about 1000 hours. These 

samples were analyzed for the nine parameters in WQI. 

Samples for fecal coliforms were taken with a flamed 

Dunker sampler. Samples for all other parameters were 

obtained in a Kenunerer sampler and transported to the 

laboratory in cubitainers. Data from this study are shown 

in Table 13. Little if any significant change is apparent 

over the period of observation. 

62 
c 

.. 

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. 

0

s+ 
. . . 

Table 12. RESULTS OF MICROBIOLOGICAL STUDY 

KANSAS RIVER AT KANSAS CITY-7TH STREET 

December'5, 1972 

Total 

Time Pt. No. Coliforms 

Fecal Fecal 

Coliforms Streptococci 

0830 1 . 

, 2 

3 

4 . . -

3 

6 

1OGO 1 

2 

3 

4 

3 

5 

6 

1100 . 1 

2 

3 

4 

5 

6 

(1) flaximum 

(2) Minimum 

45,000 

62,000 (1) 

46 ,000 

41,000 

49,000 

38,000 

40,000 

59,000 

40,000 

35,000 

31,000 

35,000 

55,000 

48,000 

35,000 

40,000 

33,000 

28,000 (2) 

64 

3 ,700 

4,100 

. 2,800 

3,500 

3 ,600 

3 ,600 

5,700 (1) 

4,600 

3,800 

3 ,400 

3,200 

3,100 

5,600 

3,800 

4,300 

5,300 

2,900 

2,600 (2) 

2,300 

2,600 

1,900 

1,200 

1,300 

1,700 

1,500 

1,900 

1,700. 

1,500 

1,700 

1,400 

2,800 (1) 

2,300 

2,200 

1,400 

1,400 

1,100 (2) 
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65 
Biological Sampling 

At the outset of this project, it seemed desirable to attempt 

to relate biological data to WQI by installing rock filled 

sampling baskets at various locations in the stream and. 

observing the diversity of species which collected on the 

rocks over a period of six weeks. On October 17, 1972, five 

sets (two each) of.baskets were installed: one set in the 

Kansas River at Lecompton, one at Willard, two at Fort Riley, 

. and one in Soldier Creek. Within the first week, all but 

two sets, at Lecornpton and Willard, were vandalized. These 

two sets remained intact and were retrieved on November 28th. 

The organisms which persisted are identified in Appendix I. 

Tne sample size was too small for statistical analysis of 

species diversity, richness, evenness, redundancy, dominance, 

etc,; however, the taxa identified can be said to represent 

a stable community composed of predators, filter feeders, 

grazers, and other omnivores. The d'iversity of this 

community ana its food and feeding habits would characterize 

* 

1 

the following conditions of its aquatic environment: 

Fairly rapidly'rnoving water (0.6-1.5 ft/sec, 1. 

which contains phytoplanlcton, detached algae , 

and other suspended materials, 

Bottom composed mostly of rubble, gravel, 

and some sand which is covered with 

periphyton (attached algae) and aquatic 

moss , 

Oxygen levels usually above 80% saturation. 

This is.'particularly true of water at 

Willard where three species of stoneflies 

(Plecoptera) were found. (This group 

. 
-- 

-- 

usually .'is the first to\, be eliminated. . 

.-. .-. --J-. -e*;,- . _. ... - -. -. ,- 7.. 

. .=$.-., -Y s .... c ­ ** . when oxygen.c0ncentfation"i.s 'decre'a'skd. )- ' -.. . _-. * ~ -_-I . .~. -..- 4) -Turbidity (silt, shifting sand) 'rela- . . . .. ...-' tively. low at Willard dGing this 

period of observation. Stoneflies . 

(Plecoptera) and mayflies (Ephemeroptera) are well represented. 

. .­ 5) A more stable community at Willard 

than that at Lecompton, suggesting 

better water quality at Willard. This 

-observation is supported by WQI (MI 

calculation reported in Table 6. 

. , ....: .. .. .. 
-M .-

SECTION IX 

REFERENCES 

1. "Restoring the Quality of Our Environment," Report Of the 

Envirokntal Pollution Panel, President's Science 

Advisory Committee, The White House, Washington, Do C. 

(1965). 

8.2. Institutions for Effective Management of the Envikonment, , 

Report of the Environmental Study Group, Environmental 

Board, National Academy of Sciences, National Academy of 

Engineering, Washington, D. C. (1970). 

3. "The Case for National Environmental Laboratories,If Report by Ad Hoc EEL Concept Committee, Oak Ridge National . 

Laboratory for the Senate Committee on Public Works, 

U.S.G.P.O., Washington, D. C. 41970). 

4. Environmental Quality, the Third Annual Report of the 

Council on EnvironmentaS Quality,. Washington, D. C. , 

(1972). 

5. Train, Russell E., "Management for the Future.'I Presented 

at the National Conference on Managing the Environment, 

Washington, D. C. (May 1973). 

6. Dal-key,N. C., DELPHI. The Rand Corporation (1968). 

7. Public Health Service Drinkins -Water Standards. United

States Department of Health, Education, and Welfare, 

Public Health Service, (1962). 

8. Brown, R.. M., McClelland, N. I.t Deininger, R. A., and 

Tozer, R. G., "A Water Quality Index - Do We Dare?" 

Presented at National Symposium on Data and Instrumentation for Water Quality Management, Madison, Wisconsin, 

(1970) and published in Water -& Sewage Works, (1970). 

c 

68 

I 

> 
-- ---- 

--- 

--- 

c 

9. Brown, R. M., McClelland, N.. .I., Deininger, R. A., and 

\

Landwehr, J. M., "Validating the WQI." Presented at-the 

National Meeting of the American Society of Civil 

-. Engineers, Washington, D. C. (1973). 

10. "WQI Field Validation Report to Participating Agencies" 

(unpublished). (1973). 

11. O'Connor, M. F. I "The Application of Multi-Attribute . 

Scaling Procedures to the Development of Iniices of'Water 

Quality." Ph.D. dissertation, University of Michigzn 

(1971). 

12. Interim Basin-Planfor Kansas River Basin, Kansas, Prepared by Kansas State Department of Health,,Division of .. 

Environmental Health, Topeka, Kansas (1971). 

13. Standard Methods for the Examination of Water li Wastawater, 13th Edition, Published and Prepared by American 

Public Health Association, American Water Works Association, and Water Pollution Control Federation (1971). 

14. Methods -

for Chemical Analysis of Water and Wastes, Manual

of-.EnvironmentalProtection Agency, Water Quality Office, 

Cincinnati, Ohio (1971). 

.. 

.15. Handbook -

for Analytical Quality Control in Water and

Wastewater Laboratories, Analytical Quality Control .. 

Laboratory, National Environmental Research Center, 

Cincinnati, Ohio (1972) 

16. Deininger, R. A,, Landwehr, J:M., "A Water Quality Index 

for Public Water Supplies." Department of Environmental 

and Industrial Health, The University of Michigan (1971). 

69 
. -.- -. .- - . 

.. # .. .: -APPENDICES . t . _. :: . . . 

-.A-.. Water -Quality C.uryes , .. 

B, Sampling Scheme 

. .. 

C. Sample Data 

D. Quality Ratings .and WQI 

I 

.-_ 

E. Summary Statistics 

..- . 

F. Water Quality Index 

G. Water Quality Index Profiles 

--.-

H. Parameter Correlations 

.. ... 

I. Biological Organisms 

. . Page 

71 .­

80 

81 

107 

133 

159 , 

185 

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..-.. 

APPENDIX B 

OVERALL SAMPLING SCHEME 

I’ANSAS RIVER STUnY 

Sampler Stationed 

in Kansas City 

H: High Frequency 

Stations Every 2nd 

day 

L -. 

14: Medium Frequency 

.Stations Every 

4tn day 

L: Low Frequency 

Stations Every 

8th day 

(~16s1 extra day) 

On west to east 

days: 

16, 20,-24 

6, 10, 12 

7, 9 

80 

Sampler Stationed 

in Topeka 

On east to west 

days :. 

#1, 3, 5, 8, 11,

14, 16, 20, 24 

#18, 21, 22, 25, 

26 

C13, 15, 17, 19, 

23