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Systems Analysis for Optimal Water Quality ManagementAuthor(s): Ethan T. Smith and Alvin R. MorrisSource: Journal (Water Pollution Control Federation), Vol. 41, No. 9, Annual Conference Issue(Sep., 1969), pp. 1635-1646Published by: Water Environment FederationStable URL: http://www.jstor.org/stable/25039112 .

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SYSTEMSANALYSIS FOROPTIMALWATER QUALITYMANAGEMENT

Ethan T. Smith and Alvin R. MorrisIn late 1961, the Delaware Estuary

Comprehensive Study was undertakenby the Federal Water Pollution ControlAdministration* in cooperation with theDelaware River Basin Commission, theState of Delaware Water PollutionCommission, the New Jersey Department of Health, the Pennsylvania Department of Health, and the City ofPhiladelphia Water Department.The study objectives were:

1. Develop methods of water qualitymanagement, including techniques forforecasting the variations in waterquality caused by natural or man-madecauses.

2. Determine the cause and effectrelationships between pollution fromany source and the present deterioratedquality of water in the estuary.3. Prepare a program for the improvement and maintenance of waterquality in the estuary, including thewaste removal and other control devices necessary to manage the qualityof water in the estuary for municipal,industrial, and agricultural water use,and for fisheries, recreation, and wildlife propagation.

In developing the estuary study, anattempt was made to define strictlycontrols for water pollution, i.e., the

management of man's environmentthrough a set of operational procedures* Its predecessor Agency, the Division ofWater Supply and Pollution Control, U. S.Public Health Service.

Ethan T. Smith and Alvin R. Morris are,respectively, Chief, Program Management Section; and Chief, Planning Branch, Delaware

Estuary Study, Hudson-Delaware Basins Office,Federal Water Pollution Control Administration,Edison, N. J.

(regulating waste discharges, flow regulation, etc.) to achieve a desired wateruse goal in an optimal fashion.The definition obviously requires anexpression of water-use goals?usuallya difficult attainment. A second problem is that the definition presupposesthe existence of a useful description ofthe environment in an engineering orscientific sense. Manipulation of a complex system is impossible withoutknowledge of the major cause and effectrelationships involved. The results ofany actions taken on the various majorcomponents of the physical environment should be able to be predictedwith reasonable confidence. A thirdproblem involves the resolution of thefirst two in an optimal manner. Withdefined goals plus cause and effect relationships in hand, criteria for selectionof a particular program still must bedeveloped, i.e., "optimum" must begiven specific characteristics for thesituation being analyzed.

Mathematical Model of the EstuaryThe initial effort was to embody thecause and effect relationships of the

physical environment in a mathematical model which could be programmedfor a digital computer. One of the mostsignificant cause and effect relationshipsin water pollution control is that between biochemical oxygen demand(BOD) and dissolved oxygen (DO).BOD is a measure of the quantity ofdissolved oxygen removed from the

water by the metabolic activity of microorganisms oxidizing materials in thewater and can be expressed in lb/day(kg/day) of oxygen demanding load.

1635

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1636JOURNAL WPCF September 1969The DO present in the stream oftenis used as an index of water quality.This is because fairly high levels (i.e.,

>4.0 mg/1) of oxygen are required tomaintain a desirable population of organisms, including the aerobic bacteriathat consume waste material in thewater. However, low levels of DO (i.e.,< 1.0 mg/1) mark the transition to anaerobic conditions, which are denotedby odors of hydrogen sulfide, organicsulfides, blackening of the water, anddestruction of the desirable fish speciesand many other aquatic organisms.The large loads imposed on the Delaware Estuary deplete DO resources insome locations to critical levels (i.e.,

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Vol. 41, No. 9 WATER QUALITY MANAGEMENT 1637

J_L_J_l_J_I I I I I I I I I_L_l_I_i ' i t i i i i i t i i i2 4 6 8 10 12 14 16 18 20 22 24 26 28 30MODEL SECTION

FIGURE 1.?Steady-state verification was performed for the June throughAugust 1964 period.

Modeling of all 30 sections yields twosystems of 30 simultaneous equationseach.

The details of this model are described by Thomann (1). In thesteady-state application of this model,a set of transfer functions can be obtained from the equations. The set oftransfer relationships details the transformation of a waste load input in anysection to the stream quality output inany other section. For example, effluent BOD input in one section can betranslated to output DO in another.This constitutes the simulation of theprimary cause-effect relationship.This steady-state mechanism wasformulated as a digital computer program for the CDC 1604 and served asthe basic program on which varioustechniques of load reduction and redistribution were superimposed later.When the appropriate input datawere supplied to the model for thesummer months, it was possible to produce a satisfactory verification of theobserved record. Steady-state verification was performed for the Junethrough August 1964 period (Figure 1).

The verification obtained is inferred tosupport the theoretical approach ofusing a mass-balance model to simulatethe estuary.

Water-Use GoalsThe water-use and water-quality

goals used in developing the estuarypollution control program were ascertained through a technical, quasi-political decision-making process involvingthe community of water users in theregion; appropriate representatives ofthese were organized as the Water Use

Advisory Committee (WUAC). Theywere queried about possible swimmingareas, fishing locations, community desires on water withdrawal from theestuary, and industrial desires on wateruse. Based largely on their response,the many alternatives for improvingwater quality were reduced to five combinations. These were termed "Objective Sets," and gave alternativequality levels starting with "ObjectiveSet V," that is, present water quality,and ranging to "Objective Set I," themaximum feasible enhancement of the

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1638JOURNAL WPCF September 1969Delaware River using present technology. Each obj ective set is composedof 12 water quality parameters, ofwhich DO is the most important.

Control Programs Based on CostAllocation ModelsOnce a set of alternative goals is

specified in terms of DO and the estuary's input-output characteristics canbe reliably specified, the question ofhow a particular goal may be securedoptimally can be asked.Generally speaking, it is possible todetermine the maximum allowable

waste that can be discharged to theestuary under any given objective set.But how should this total quantity ofload, and its associated costs, be allocated among the individual sourceslocated along the length of the river?For example, in the case of objectiveset III, a maximum of 500,000 lb/day(227,000 kg/day) load may be discharged by all sources acting together.One possibility is to require that thelargest sources remove the maximumpossible amount of their load, and thatonly subsequently would smallersources be required to act. This

method, as employed in the past, leavesa great deal to be desired. No cognizance is taken of the relative costs ofremoval between sources, nor is any attempt made to treat sources in anequitable fashion. The problem thatremains is how to select a rational set oftreatment levels for the various sourcesalong the estuary. The selection shouldbalance the apparent equity of thesolution to the individual source, theeconomic cost to the region, and theease of administering the managementprogram. The selected levels also mustresult in attainment of the DO goalswhich are used as an index of overall

water quality.The importance of cost is well illustrated by considering alternative wasteremovals in association with the costfunctions of the sources. For example,even in a simple situation involving only

two sources, the best policy to follow isfar from clear. Because of the influence of tidal hydraulics, the magnitudeof the waste load removals which arerequired depends on the location of thesources on the estuary. However, thecosts of removal depend on the economics of the individual sources whichare extremely variable. Which sourceshould be chosen? Should a solution becompounded of partial abatement ateach source ; if so, how much abatementand at which source?

Facilities to secure various waterquality objectives require large investments for construction, operation, and

maintenance. Thus a careful comparison of the various alternatives is necessary to ensure that the selected program best satisfies the needs and desiresof the region. Comparison of alternative programs on the basis of cost allows two important comparisons :

1. The different costs for obtaining agiven objective set are good criteria onwhich to base decisions as to type ofcontrol to be used in the abatementprogram.2. Comparison of the costs to attaindifferent objective sets are helpful inselecting a final set.

The cost of attaining various waterquality objectives was determined under each of the following allocationprograms :

1. Uniform Treatment?Each sourceto remove identical percentage of itsraw load (i.e., the load before any reduction has taken place).2. Cost Minimization?Using an optimization technique of linear program

ming, a program was formulated whichwould reach the desired quality goals ata minimum cost to the region. It selects effluent modifications based ongreatest waste removal per dollar oftreatment cost and simultaneouslyconsiders where in the estuary waterquality must be improved.3. Zoned Optimization?This solution combines elements of the uniform

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Vol. 41, No. 9 WATEE QUALITY MANAGEMENT 1639and least cost approaches. The estuarywas divided into a series of treatmentor management zones, the treatmentlevel in each zone chosen so as toachieve the water quality goal at minimum overall cost. Several constraintscommon to all three of the above methods are imposed on the various solutions :

(a) In no case will the DO in anyarea be permitted to decrease below itspresent level, even if present levelsexceed the legal standard in the area.(b) No effiuent source may dischargeany load above that discharged at present. When a particular treatment levelis chosen, sources currently treatingtheir wastes to a higher level may notlower the degree of treatment.

Each of these cost allocationprograms now will be examined in turn.Some of the methodology will be described, and the implied efficiency andequity of each program will be pointedout.

The basic computer input data foreach of the programs consisted of thefollowing :

1. The mathematical representationof the physiochemical relationships inthe estuary which are called transferfunctions, or input-output coefficientsfor the estuary.2. The differences between the present DO values in each section and the

DO values defined for each objectiveset.

3. The waste load in lb/day (kg/day) discharged from each of the majorsources.

4. A cost function for each of themajor sources which gives the cost ofremoval as a function of the degree ofremoval.

The Uniform Treatment Cost AllocationModelThe uniform treatment program

requires that an identical percentage ofthe raw oxygen-demanding load fromeach source be removed before dis

charge. Thus it is necessary to find atreatment level that is high enough toachieve the desired DO.The general formulation for a minimization of costs program is as follows :

MMINICi(A).

subject to,ZAiJj> Bi, ? = 1,2,3,..-iV...4

where ; //= Eft.50

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1640JOURNAL WPCF September 1969desired DO improvement in each section. Equation 6 limits the effluentmodification to the maximum amountthe source can remove. Equations 7and 8 test to see if the present fractionof waste removal, Pk, at source k isequal to or greater than the level of uniform treatment being considered. Ifit is, source k is omitted from the solution. If it is not, the contribution fromsource k is described by Equation 7.The approach for solution of thisprogram was a search technique inwhich a low treatment level was chosenand its resulting DO profile calculated.If this did not satisfy the goal, thetreatment level was increased by fivepercent increments until the goal wasreached in all places. Since costs increase with percent removal, the objective of minimum cost is met bychoosing the treatment level that justsatisfies the goal. It should be notedthat the cost of effluent removal at eachsource need not be a linear function ofthe effluent removal. For simplicity incomputing, however, the cost functionwas approximated by a series of linearsegments. The algorithm is not dependent on the cost information given,but rather on the physical environment.A removal level of 85 percent to theeffluent source will cost the same no

matter what flow or temperature conditions exist in the estuary. However,the DO resulting in the estuary after85-percent removal is very much a function of the inherent physical conditionsat any given time.Uniform treatment is the commonlyused approach in existing managementsituations. Its primary advantage isadministrative simplicity; however, itis economically inefficient in accomplishing the goal. Many sources are required to increase treatment in noncritical areas because the goal is not metin the more critical locations. The result is a large surplus of DO in noncritical areas, thus providing a measureof the inefficiency of the solutions.While each source is required to removethe same percent of raw load, no allow

anee ismade for differences in unit costof waste removal from source to source.In spite of apparent equity, the solutionis actually quite inequitable. It at bestcan treat each source identically interms of treatment level without regardfor cost. It does not attempt to equatecosts between sources or to treat sourcessimilarly because of similar locations ortypes of operation. Thus, any gain inadministrative simplicity is offset bythe program's inefficiency and inequityplus its substantially higher costs to thegeneral public.The Cost-Minimization Cost-Allocation

ModelThe basic question answered by costminimization is :What combination of

waste effluent modifications along theestuary should be made to secure desired DO goals at least overall cost forthe region? The key here is that nosource is assumed to act in conjunctionwith any other source. Mathematicallythis can be formulated as a classicallinear programming problem with upper bound constraints. This formulation and its application to the Delaware Estuary originally were accomplished by Thomann and Sobel (2).M

MIN ?&(/*).9subject to,N

E4/i> B{, i= 1,2,3,- -N. .10where ;

//= Efk.h0

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Vol. 41, No. 9 WATER QUALITY MANAGEMENT 1641than its present level of treatment, andrequires that the solution remove onlyup to some maximum level ; in this casethe maximum waste that can be re

moved at the source under presenttechnology.The optimum program consists ofthose values of fk that satisfy the constraint Equations 10, 11, and 12 andminimize the objective function Equation 9. Note that this formulation issimilar to that of uniform treatmentexcept that some constraints have beendropped. Thus a solution to this problem will, at the most, cost the same asthe uniform treatment scheme and for

most cases will.cost much less.The computer solution of the linear

programming problem most often isaccomplished by the "Revised SimplexMethod" which systematically searchesfor the "best" solution, thereby eliminating a complete enumeration of allpossible solutions to find the optimum.The technique is referred to as costminimization because the least costsolution is subject to constraints whichhave associated costs. Thus the finalcost of the program can be altered bychanging the constraints. For example, placing of a lower bound constraint may be considered, with theplan that each discharge must have35-percent minimum of primary treatment. The subsequent least-cost solution with this constraint will be greaterthan the cost without the constraint;,the cost differential is the price for including the additional requirement inthe problem.Because of the nature of the specificproblem of raising water quality bywaste removal, some special modifications had to be made in computing thesolutions to the above formulation ofthe cost minimization problem. Thesecenter around the problem that thecost-of-removal vs. the load-removedrelationship is not linear. An investigation of this relationship shows it isgenerally a convex curve above primarytreatment. A convenient method isavailable for solving convex nonlinear

models by linear programming. It involves approximating the cost curve bya series of linear segments, each ofwhich has a cost per unit and a loadthat may be removed at that unit cost.The algorithm for solving the problemconsiders each segment as a separatesource of effluent. There is no dangerof any segment being taken out of ordersince each segment of the curve for aparticular source has a higher unit costthan the one preceding; the algorithm,in looking for the least cost, will choosethe lowest unit cost available to it.

Least-cost solutions show a number ofinteresting characteristics, aside fromtheir guarantee of an absolute minimuminvestment. The linear programmingmodel considers such items as locationof the source with respect to the lowestpart of the DO profile, the marginalcost to remove additional amounts ofwaste at each source, the maximumamount of waste that could be removed,and the relative proximity of other,cheaper waste loads. Thus the solutions show a number of trade-offs between individual sources. It is not unusual, for example, for the solution toindicate a high degree of removal at onesource while its neighbor is not requiredto increase treatment beyond 35-percent removal.

The least cost solution is very efficient in allocating the treatment levelsto be attained by each source to meet aspecified goal. No unnecessary treatment is called for and only those removals are required which produce anincrement of quality at the lowest cost.The DO surplus, i.e., the amount in excess of the goal, is smaller for thisformulation than for any other.The least-cost solution is equitable inthe sense that a source causing no damage (i.e., not lowering water qualitybelow desired goal) incurs no costs.The solution is likely to be extremelyinequitable in the sense of not treatingindustrial competitors in a like manner.Two dischargers on opposite banks ofthe estuary can be expected to causeequal marginal damages. Yet, if waste

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1642JOURNAL WPCF September 1969treatment costs at one firm are low

while at the other firm they are veryhigh, it is likely that the source with thelow-cost removal capabilities will berequired to treat its waste to extremelyhigh removals and the other dischargerto provide no additional removal at all.This solution would be difficult toimplement administratively. Eachsource would have to be considered individually by a basinwide authorityand waste loads allocated according tothe least cost criterion. Because of theunequal treatment of some dischargerswhich may be alike in many relevantrespects, great antipathy can be anticipated on the part of many sources.

However, the problems are not insoluble.The Zoned-Optimization Cost-AllocationModel

The optimization model for this program is formulated as a combinationof the uniform treatment and the costminimization programs. This resultsin uniform treatment levels for groupsof sources within zones with cost tradeoffs possible between zones that yielda set of levels having minimum cost.This can be expressed as follows :M

MINICt(A).13subject to,

E4ii->fii, ? = 1,2,3,-.. N.. 14

where ;/;= ?/*.15

0

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Vol. 41, No. 9 WATEE QUALITY MANAGEMENT 1643lower and upper levels. Within thisband a search technique is applied thatyields all feasible solutions which satisfythe input DO goal. The techniqueinvolves significantly less effort thancomplete enumeration. It is possibleto compute not only the zone treatmentlevels resulting in the minimum cost,but also other feasible levels that cost

more but might be more desirable administratively. Any number of thesemore costly alternatives can be computed, depending on how much morecostly a result will be accepted.As might be expected, the results ofthis program are intermediate betweenthose of the first two. The great surplus of DO that leads to inefficiencyin the uniform treatment program isavoided. Surplus DO does exist withinzones, but it is smaller than before,since in this case zones are chosen toencompass areas of similar water quality. Four zones are specified in theDelaware Estuary, which cover the areafrom Trenton, New Jersey to the beginning of Delaware Bay.A measure of equity is attained inthat sources located near each other,and adjacent to similar water quality,are treated similarly. Similar typesources also could be treated in equalfashion, although this was not presentlysuperimposed on the geographicalbreakdown. The sort of marginalequity found in the linear programmingapproach is lost here, because themethod does not consider the derivativeof the cost function in selecting sources.The zone approach is looked on witha certain amount of favor from the ad

ministrative viewpoint. It is nearly aseasy to implement as the uniform treatment method, since it requires onlylocating sources within managementzones. In addition, the equities of similar treatment for sources located nearone another tend to reduce the objections of individual dischargers regarding their situation as compared to thatof their neighbors.

Resulting Costs and BenefitsApplying each of the cost allocationmodels to each of the "Objective Sets"yields a complete tabulation of thedifferent methods of attaining a givenwater quality goal.The program costs increase as water

quality increases. The DO objectivefor set I can be reached only by 92- to98-percent removal of all carbonaceouswaste sources plus in-stream aerationand removal of benthic deposits at anestimated cost of $695 mil (Figure 2).Since only experimental plants haveattained such high removals so far,some doubt exists as to whether presenttechnology, in fact, can achieve set Iobjectives on the large scale basis thatwould be necessary.

Many sources would have to makeimprovements to avoid degrading waterquality below present levels, i.e., set V.This alone is estimated to cost $140 milfor the period 1964 through 1975. Thiscost would be incurred through facilitiesconstruction necessary to offset theeffect of regional growth.

Figure 2 presents a breakdown of costby objective set and allocation model.Sets I, II, III, and IV were selected bythe Water Use Advisory Committee tothe Delware Estuary Study. Betweensets II and III, the Delaware RiverBasin Commission (DRBC) defined aset of goals that are intermediate indegree of stringency. For any givenobjective set the cost minimizationmodel yields the smallest cost and theuniform treatment model yields thelargest. This is in agreement with theefficiency concepts discussed earlier foreach of these models. The exceptionto this rule is set I, which stringentlydemands the highest levels of treatmentunder all conditions.

Certain monetary benefits can derivefrom increased use of the estuary, onceits water quality is improved. Numerous benefits are intrinsic in water quality enhancement programs. These arerealized by a more economic utilizationof natural resources, preservation of

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1644JOURNAL WPCF September 1969700

600

500

400

300

200

100

ZONED OPTIMIZATION

ir in DRBc nOBJECTIVE SET

FIGURE 2.?Graphical presentation of the three economic allocation modelsis plotted on the same axes with results of the benefit analysis.

fish and wildlife, and protection of regional health and welfare. One of thebasic aims of the Delaware EstuaryStudy has been to better define andquantify the benefits of enhancingwater quality in the estuary.

Quantification of thebenefits is an

essential part of any feasibility study.However, in the water pollution controlfield, the state of the art is new andmuch methodology currently is beingdeveloped. The Delaware EstuaryStudy proceeded with an analysis ofthe anticipated benefits for severalwater uses under each of the objectivesets. It was not expected that all thebenefits could be quantified. The re

suits included positive benefits for recreation and commercial fisheries basedon the increased use attributable toimproved water quality.A negative (i.e., a cost) benefit wasestimated for some industries along theestuary. This is primarily because ofincreased corrosion rates within circulating water systems caused by higherDO levels in the intake water.

Comparison of program costs andbenefits may be carried out in severalways. Perhaps the most explicit is thesimple graphical presentation (Figure2). Here the costs obtained from thethree economic allocation models areplotted on the same axes along with the

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Vol. 41, No. 9 WATER QUALITY MANAGEMENT 1645results of the benefits analysis. In allcases, the abscissa is only an ordinalscale. Some interesting conclusionscan be reached by comparison of thegraph, benefit/cost ratios (Table I), and

marginal costs vs. benefits (Table II).The benefit/cost (B/C) concept isthat every dollar spent should be offsetby a dollar gained through the benefitsof implementing a particular alternative program. In such a case, a ratio of> 1.0 is desired.

In many of the alternatives a B/Cratio equal to or greater than 1.0 results; however, all ratios decrease forthe higher obj ective sets. This is causedby the occurrence of a benefits''plateau" (Figure 2). Once a particular level of use is reached, no further

gains result from increased waterquality, at least with respect to that use.Therefore, as ever more stringent quality goals are specified, costs increasetremendously while benefits tend tolevel off at a maximum value plateau.Further insight into program choiceis gained by examining the marginalcosts and benefits of each alternative(Table II). In the case examined, theincrements in cost or benefit for each

objective set are somewhat analogousto the slopes of the curves in Figure 2.In theory attempts should be made toproceed to higher objective sets as longas marginal benefits at least equal marginal costs. The functions shown inFigure 2 require a careful interpretation of this rule. The slope of the benefits function is generally greater than

TABLE I.?Total Benefit/Cost RatioObjectiveSet

UniformTreatmentModelZonedOptimizationModel

Cost MinimizationModelI

IIDRBCIIIIVV

.69

.83

.961.05

.891.16

.69

.85

.981.241.111.16

.69

.971.091.391.191.16

that of the cost functions until "Objective Set III" is reached. Comparingthe marginal values in Table II, itcould be argued that set III is the highest level that can be justified using theapproach of incremental returns. Thatis, above set III, values move alongthe benefits plateau, whereas costs continue to increase. In addition, thebenefit/cost ratios for set III are allgreater than one.What reason could be given, then,for seeking yet a higher objective set,specifically the DRBC set? It is ofcourse true that all the benefits couldnot be quantified and hence do not appear in Figure 2 at all. The DRBC setwill obtain more of these intangiblebenefits than will objective set III. Itis emphasized that the ranking of theDRBC set between sets III and II wasbased on cost. The cost resulted fromadditional waste treatment measuresdesigned to facilitate the occurrence ofbenefits, whether or not they could bequantified. In all probability theDRBC objective set represents thatcreature known as a reasonable alterna

TABLE II.?Marginal Costs and Benefits (Million 1964Dollars)

Costs BenefitsMarginal Benefits

Marginal CostsUniformTreatment

186705664179140

ZonedOptimization

2026310470116140

CostMinimization!

26345965398140

62017121121162

UniformTreatment

0.330

0.301.890.681.16

ZonedOptimization

0.310

0.161.731.041.16

CostMinimization

0.240

0.182.281.231.16

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1646JOUENAL WPCF September 1969tive. It possesses some rationale fromthe standpoint of the economic analyst ;note that the benefit/cost ratios areclose to 1.0 for any of the economic allocation models. In the midst of thepowerful conflicting forces that mustbe considered in such a public servicedecision, it probably represents a combination of logic and necessity.

The Decision-Making ProcessThe results of the Delaware Estuary

Study as described here have been presented in the form of a preliminary report (3). The agency utilizing theseresults to the greatest degree has beenthe Delaware River Basin Commission.The DRBC was created in November1961 on enactment of concurrent legislation by congress and by the respectivelegislatures of the states of Delaware,New Jersey, New York, and Pennsyl

vania, as an agency of the federal government and the signatory states. TheCommission consists of the Governorsof the states plus the Secretary of theInterior and has the authority to develop plans, policies, and projectsrelated to the water resources of thebasin.

As the primary decision-makingagency within the basin, the DRBC isresponsible for the selection of waterquality goals which then serve as guidelines for the regulatory agencies of theconstituent states in formulating theirown plans for water quality improve

ment.The DRBC held public hearings onwater quality improvement programsfor the estuary, which culminated in theannual Commissioner's Conference of

March 1967, at which a decision wasreached. At this meeting the fourGovernors and the Secretary of theInterior selected "Objective Set II"as the goal to be sought for the Delaware Estuary. Subsequent adjustments produced the DRBC objectiveset, intermediate between II and III.It was decided to use the zoned approach to estuary management, which

would allow a certain degree of flexibility to be maintained, to meet futureconditions. The water quality standards as selected by the DRBC are nowin the process of being implementedalong with state standards. The selection of a particular objective set andan allocation model has resulted in loadallocations for individual firms and

municipalities. These allocated loadsare the maximum waste discharge loadsthat will be permitted under the givenconditions. If the waste loads aremaintained at their allocated magnitudes, water quality in the estuary willbe maintained at an enhanced level.

This is an example of the way inwhich some of the more recently developed analytical techniques have beenutilized in a real situation. The use ofsystems analysis methods and the advent of the digital computer have madepossible the formulating of rationalalternatives for consideration by policy

making agencies. Seldom are all recommendations of the scientist andengineer accepted. But it is possibleto employ these modern tools so thatthe good and bad points inherent inalternative decisions are readily distinguishable. It thus is possible tominimize illogical and inconsistent actions while attempting to maximize thereturns for necessary expenditures. Ina multi-faceted field such as water resources, optimization may not meangetting the best of all possible worlds;rather it will mean making the bestpossible use of the world as it is.

References1. Thomann, R. V., "Mathematical Model forDissolved Oxygen." Jour. San. Eng.

Div., Proc. Amer. Soc. Civil Engr., 89,SA5 (1963).2. Thomann, R. V., and Sobel, M. J., "Estuarine Water Quality Management andForecasting." Jour. San. Eng. Div.fProc. Amer. Soc. Civil Engr., 90, SA5, 9(1964).3. Delaware Estuary Comprehensive Study,''Preliminary Report and Findings.''U. S. Dept. Interior, Federal WaterPollution Control Administration, Phila

delphia, Pa. (1966).