Interactive Water Resources Modeling and Model Use: …

WATER RESOURCES RESEARCH, VOL. 21, NO. 2, PAGES 95-102, FEBRUARY 1985

InteractiveWater ResourcesModeling and Model Use' An Overview

DANIEL P. LOUCKS

Schoool f CivilandEnvironmentaElngineeringC,ornellUniversityI,thaca,New York

JANUSZ KINDLER

Instituteof EnvironmentaElngineeringW, arsawTechnicalUniversityP, oland

KURT FEDRA

InternationalInstitutefor AppliedSystemsAnalysis,Laxenburg,Austria

This servesasan introductionfor the followingsequenceof fivepaperson interactivewaterresources and environmentaml anagemenpt,olicymodelinga, nd modeluse.We reviewsomeimportantshortcomingsof manymanagemenatnd policymodelsand arguefor improvedhuman-computer-model interaction and communication. This interaction can lead to more effective model use which in turn shouldfacilitatethe explorationa,nalysisa,nd synthesiosf alternativedesignsp,lans,and policiesby thosedirectlyinvolvedin theplanningm, anagemenot,r policymakingprocessP.otentiaal dvantageosf interactivme odelingandmodelusea, swellassomeproblemasndresearcnheedsa,rediscussed.

INTRODUCTION

We recentlyconductedan informal survey.We askedmany of our acquaintancesin governmentagenciesconcernedwith water resourcesand environmentalprotection what their biggest problems seemedto be. All of their responsescould be summarized as keeping ahead of the increasing number of water- and environmental-related"crises."Efforts spent in reducing each current crisis seemsonly to result in the emergenceof seeminglymore difficultones.

In spiteof all that hasbeendone to reducethe everreoccurring cycle of floods and droughts and their accompanying damages,these eventsstill occur, and their damagesare increasing.On top of theseand other reocurring problemsit seems,suddenly,we have a host of new problems. Increasingly, various toxic wastesdischargedon or under the ground are contaminating groundwater supplies and occasionally oozing up to the surfaceto create health hazards for those living on it. Our urban water distribution systems,many that havefunctionedwell beyondtheir designlife, havecollectively, it seems,decided to call for help. The control of nonpoint source pollution is becoming a major challenge to surface water quality managers.Increasingly,acid rain, in a variety of wet and dry forms, is adversely altering aquatic and forest ecosystemson regional scales.The potential for more Three Mile Island nuclear accidentsis becomingincreasinglyapparent, and so on. Any reading of major daily newspaperscould lead one to ,concludethat we are not yet very effectivemanagersof our water and other natural environmentalresources. We ought to be able to do better,and we can if we have the

will.

What is to be discussedin this and the following sequence of papersis not going to solveall of our current water and environmentalproblems.However, we believeit can provide some help toward that end. It seemsto us that managers, planners,and policy makerscould benefitfrom having avail-

Copyright 1985by the AmericanGeophysicalUnion.

Paper number 4W0977. 0043-1397/85/004W-0977505.00

able, when they needit, someeasy-to-usetools to help them identify, explore, analyze, and synthesizeeffective resource managementplansand policies.

The developmentand applicationof managementor policyorientedmodelsfor helpingwater and environmentalresource managershavebeentaking placefor severaldecadesthrough-

out much of the world. The extent to which this effort has

been as useful as it could have been. is in some doubt. A

comprehensivestudy of the use of modelsfor water resource management,planning, and policy in the United Stateswas recently completed by the Office of Technology Assessment (OTA) of the U.S. Congress[Friedman et al., 1982]. This report emphasizesthe potential of currently existingmodels for improving the accuracy and effectivenessof informaton available to managers,decisionmakers, and scientists.It also documentsthe needfor modelsin meetingthe requirementsof a wide variety of Federal and State laws in the United States concerningresourcemanagement and environmental protection. However, the primary focusof the report is on the constraints to effectivemodel use. Among these constraintsare the lack of information about available models, lack of training in model use and interpretation,lack of communication between model users and developers,and lack of required support services.

'Some constraintsto model usecan only be reducedby actions taken by potential useragenciesor groups.Much of the OTA report is directedtoward this issueand suggestspossible coursesof action that resourcemanagementagenciescould take to increasethe benefitsthey can obtain from model use. However, there are other constraints that we as modelers and analystscan help to reduce.It is this need and opportunity that motivatesthe discussionin this and the followingpapers.

Many of the constraintsfor effective model use that confront us today are the same that Little [1970] identified well over a decadeago. Not every proposedmodel is appropriate in all contexts.A very good model for one problem and institutional setting may not be as good, or oven applicable, in

another. Unless model builders are familiar with both the

problemand the institutionalsettingin which the problemis

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LOUCKSET AL..'INTERACTIVEMODELINGOVERVIEW

to be addressedi,t is unlikelyany modelingwork will be very quencesof particular actionstaken to help solve or reduceit

effective.Good model parameterizationand validation is rare. [Little, 1970]. It may also assistin the resolution of conflicts

Modelsmust be madecredibleto the potentialusers.Regard- by providing negotiators with a "face-saving" excuse for

lessof whether or not the usersfully understandthe model or changingtheir positions,i.e., for compromise[Sebenius,1981?

models, the outcome must be believable. It must conform to Strausand Clark, 1980; Lara and Sachs,1978].

the user'sperceptionof the world or at least that part of it

Before discussingour proposed interactive approach to

beingmodeled.Finally, the model must be complete.It must modeling and model use it seemsappropriate to first briefly

include the capability of examining all of the issuesdeemed discussin a general way how much of water resourcesand

important by the user,and the resultinginformationmust be environmental policy making seemsto take place. This dis-

easyto understand.How to make our modelsmore flexible or cussionprovidesa contextfor comparingwhat we are propos-

adaptable to alternative paths of exploration and how to ing with somepast approachesto policy modelingthat placed

designan interfacefor more effectivecommunicationbetween little if any emphasison human-model-computerinteraction

the user and the model are continuing challengesto model and communication.

builders.

Our thesis,in short,is asfollows.Modeling,if it attemptsto

SOME CHARACTERISTICS OF PLANNING AND POLICY MAKING

describemorethan somemicroaspectosf physicalsystemsb,y Water resourcesand environmental planning and policy

necessityinvolves a strong subjectiveand value-dominated making are commonly characterized by their breadth of

human element which defiesa formal representationin any impact, uncertainty,scarcityof causal evidenceon which to

generallyacceptableway. At the same time, any acceptable basea plan or policy,and by their multiobjectiveand multiin-

formal model must be compatible with the set of mental stitutional involvement. Many individuals, interest groups,

modelsand the cognitivestylesof their users.We argue that and organizationsare affectedand concernedabout water and

widespreadmodel acceptanceand use can only stem from the environment.We are not very good at predicting future

direct user involvementat various phasesof the modeling economicconditions,costs,and benefits,or estimatingfuture

processi,ncludingdefinitionof basicassumptionsand the con- socialor political impactsof current decisionsp, lans,or poli-

trol of output formats. Interactive methods which give the cies.We must use considerablesubjectivejudgment to sup-

user an appropriate role in controlling model calibration, plement what meagerevidencemight exist to help us predict

model use, and output display requires new ways of man- even the physical, biological, or chemical impacts of alter-

machineinteraction.The role of modelsthus changesfrom a native decisions.Finally, water and environmental problems

product-orientedfunctionwheremodelsare productsof a usu- tend to be heavily value-laden,and objectivesand institutions

ally external modeling processand produce solutionswhich are very much a part of the problem.

the end-userdoes or does not accept,to a process-oriented As a consequenceof all this apparent confusionand uncer-

function.In a process-orientedfunction,modelingand model tainty, water resourcesand environmental problem-solving

useare the important elementsof a learningprocesswhich in tendsto be an iterative, explorative,learning processthat re-

turn facilitatesthe policyand decision-makingprocess.

definesthe problems as much as it seekssolutions to them.

This paper, and thosethat follow, presentsomeideasand Any review of the U.S. water pollution control policiesover

general approachesfor model builders to consideras they the past severaldecades,for example, will provide ample evi-

work toward improving the effectivenessof their models to dence of this.

managers,planners,and policy makers.Given the increasing The very nature of this iterative, recursive,learning, and

number and complexity of today's water and environmental decision-making process usually requires subjective evalu-

managementproblemsand those that are likely to emergein ationsand considerablecompromisesamong conflictinggoals.

the future, it follows that the potential utility of modelsde- The processis typicallymore political than analyticalor scien-

signedto helpstudytheseproblemsis alsoincreasingC. learly, tific. The direct involvement of various interest groups is

the demand for information that can and should be derived common.Their goalsand behaviorare not easilymodeledin

from models exists;it is only a questionof how well we as any acceptable way. What model builders may assumeas

model builders can meet it [Brown, 1982]. We will need, and rational cannot be assumedW. hat is rational to one may not

we will develop,bettermodels,of course,as our knowledgeof be to another,and for reasonsthat may not ever be revealed.

the systemswe model increases.However, equally important, Values and beliefs,and the resulting objectivesthat shape

we must devote some attention to the interface between the policies, are the result of dynamic human and institutional

model user and the models being used. More effectivecom- interactions.While one could suggestt,herefore,that "planners

munication is essential for increased effectiveness in model use. must design from the beginning for the complete range of

Many gaps betweenmodel availability and model use can objectives"[Kahn, 1960], sucha task may be difficult to ac-

be reducedby the developmentof a more user-friendlyinter- complish.Objectivesand values are usually conflictingand

action betweenthe model and its user. Facilitating human- changing.They are dependenton the choicesgiven,i.e.,on the

model-computerinteraction will not necessarilyincreasethe status of the learning process.Values may very well be un-

likelihoodthat any oneor moremodelsolutionswill beimple- known to those who have them; i.e., one may not be able to

mented. Rather, it should, we believe, increase the likelihood make them explicit when asked. Yet the same person will

of the modelsproducinginformationusefulin any debateover usually be able to select preferred plans or policies from

what to do, who will be affected,how they will be affected,and amongalternatives.

how much they will care.

Values and priorities may also depend on the possibilities

Models,if and whenusedin the planningor policymaking and tradeoffs in a bargaining situation. Such situations are

process,are used becausethey provide and organize infor- typical in multiple objective decision making exercisesthat

mation that togetherhelp in the understandingof the prob- characterizewater resourcesand environmental planning and

lemsbeingaddressedO. ften this "additional"informationmay policy making. Goals may changeand unknown constraints

simply better define the problem and the possible conse- may emergeduring suchprocesses.

LOUCKSET AL.: INTERACTIVEMODELING OVERVIEW

97

To include thesecomplex and uncertain behavioral characteristicsof planning and policy making within one or more models becomesimpossible,but to exclude them from consideration during the developmentof policy models invites a high chance of model failure or rejection. So, what to do? First, we suggest,is to includewithin modelsonly thoseparts of the problem under studywhich can be modeledwith credibility. That which cannot, i.e., most human or institutional behavior,must be left outsidethe model. This then requires that the modelsbe capableof directly and interactivelyinvolving humans,i.e., the managers,plannersor policy makers,or their staffs,who must supply the crucial behavioral elements. This capability requires, in turn, that the model or models mustfit into the managing,planning,and policy-makingprocessesT. hey must be appropriate for the institutions in which suchprocessestake placeand for the individualswithin those institutionsinvolvedin managing,planning,or policy making.

Inadequate data of the kinds most needed is another

troublesome characteristic of most water and environmental

planning or policy-making exercisesE. ach discipline involved in such multidisciplinary exercisestends to collect data in its own traditional way. Data compatibility can be a major constraint.Temporal and spatial resolution,and the resultingstatisticalquality as well as the appropriatenessof the data differ widely when considering,for example, ecological, geographical, or economicand fiscaldata related to a given problem.

Some data in some casesmay be available in large quantities. Meteorological and hydrological records and data resultingfor remote sensorsmay be available with considerable temporal and spatialcoverage.In suchsituations,data-related problemsare often thoseof data reduction,aggregation,and interpretation. Data on causalrelationships,however,are usually scarce. This is particularly so when the phenomena of interestare the long-term and synergisticimpactsof a particular plan or policy pertaining to, for example, public health, economicdevelopment,and ecologicalsystems.Once again, decisionsin the absenceof adequate evidence of causal relationshipswill be largelybasedon subjectivejudgments.

How can these and other troublesome features of water

resourcesand environmentalmanagementand policy making be reduced by those who develop models? We believe there needsto be a changein the manner we approach such problems.Before discussingtheseproposedchangesa brief review of our view of how most modelshave been developedin the pastmay serveas a basisfor comparison.

TRADITIONAL APPROACHES TO POLICY MODELING

Many modelershave, perhapsuntil relatively recently,been followinga modelingapproachthat hasfocusedmainly on the analysisof alternativesand lessso on the generation,exploration, and synthesisof alternatives.Many of thesemodelshave been designedfor use outsideof the planning, management, and policy-makingprocess.They were designedfor use by policy model builders and analysts to provide quantitative solutions to specific problems. This information has occasionallyended up in one or more reports.Very often these quantitative solutionshave been based on the assumptionof rational economicbehaviorfor lack of any better assumption. Multiobjective modelshave been usedto attempt to eliminate from further consideration solutions that were not efficient i.e., that were inferior with respectto the objectivesconsideredin the models.The trouble is that rational behavior of any kind is not likely to be the same among different individuals and

that unspecifiedp, erhapsunknownand unquantifiableo, bjectives and constraints also apply.

The difficultiesin identifyingappropriatepolicy objectivesis increasinglybeing recognized.Many models found in the literatureassumethe existenceof one or more fixed objectives. In the caseof prespecifiedmultiple objectives,one can resort to multiobjectiveor multicriteria modelingto generatesetsof "efficient," "noninferior," or "Pareto-optimal" solutions [Cohon,1978;Zeleny, 1981a,b; Goicoecheaet al., 1982]. However,solvinglarge multiobjectivemodelsmany timesto generate even a small subsetof noninferior solutionshas proven to be an expensiveand time-consumingeffort. Moreover, thereis increasingrealization that individuals may want to consider an apparently inferior solution (with respectto those objectives being modeled) as well as noninferior ones. So-called inferior solutionsmay not be inferior at all when considering additional objectives.Rarely, if ever,can all relevantobjectives be explicitly consideredin multiobjectivemodels.Hence there are legitimate needs to focus on more than only the set of noninferior or efficient solutionsgeneratedby multiobjective

models.

Perhapsone of the biggestreasonsfor model solutionrejection, even as a basisfor discussionin the managing,planning, or policy-makingprocess,has been the lack of model understandingor confidence,and the lack of adequatecommunication betweenthe analystsand their clients.Throughout the managing,planning, or policy-makingprocess,analystsrarely can addressthe right questionsthat managers,planners,and policy makers want answeredunlessthey are aware of these questionsA. lso, individualsoftendo not know what questions they want answersfor before someexploration and comprehensionof the impacts of some of their ideas for plans and policies.The outcome of this exploration will lead to new questionsand the needfor additional exploration.

Another tendency in the past, and to some extent even today, has been to concentrate on the development of fairly complex and comprehensivemodels. This is natural. Most water and environmentalproblemsand their impactsare complex and involve a wide variety of individuals,interestgroups, and institutions. The trend toward bigger and more comprehensivemodelswhich simultaneouslytry to describeas many relevant aspectsof the problem as can be put into the computer has coincided with the growth in computer speed and capacity,and in the developmentof more efficientalgorithms for solving a variety of mathematical models. Large complex models,however,are not only more difficult to develop and maintain; they tend to require more input data, and this can be expensiveto obtain. They also tend to producelarge quantities of output, much of which can be a challenge to comprehend.

Figure 1 is an admittedly very simplified illustration of many past and even some current attempts of comprehensive model building and application. The heart of the modeling processrevolvesaround the analysts(model builder and user) and the comprehensivesimulationand/or optimization model. The potential client, the potential user of model information, is only weakly involved, usually through reports the analysts may preparebasedon information derivedfrom the model.

Typical of many resourcemanagementand policy-modeling applications,the analystshave someinitial contact with those needinginformation to be obtained from models, e.g., managers,planners,and policy makers or their staffs.They also have some contact with them at the very end when some reasonableresultsfrom the modelsare available. During most

98

LOUCKSET AL.' INTERACTIVEMODELING OVERVIEW

DataBasJe

and softwaremakesthis approachmuch more feasibletoday than it was even severalyearsago. The current revolutionin

the development of mini- and microcomputers,interactive

software,and color graphicsis making it possiblefor eachof

JAnsatsly

Comprehensive Model

us, as individuals or as members of an organization, to have accessto fast, cheap, interactive (flexible) computing power, supplementedincreasinglyby graphical or pictorial display

I

capabilitiesif desired[Weger, 1981; Whitted, 1982]. We are

I I

Managers,

convincedthis technologicaldevelopment cannot but have a profoundeffecton how we all approachpolicymodelbuilding

Policy Makers and Staffs and use in the future. Other articles [Fedra and Loucks,this

Fig. 1. Typical relationshipsamongmanagersand policymakers, analysts,their model, and their data, indicatingweak or nonexisting links betweenpotential usersof model information and the models and thosewho developthem.

issue;Loucks et al., this issue] discussthis subject in more

detail.

For managementp, lanning,and policy studies,analystsare increasingly beginning to develop systems of interrelated smaller models rather than single large and more complex

models [Walker, 1982]. Current trends in managementand

of the intervening time, however, the analysts and potential policymodelingseemto bedirectedtoward the interactiveuse

userstend to go their separateways. Once somemodel results of relativelysmallerinterrelatedmodelsdesignedto be adapt-

are available, the original resourceuseconflicts,management ive and responsiveto a wide variety of questionsthat policy

questions,policy objectives,and sometimeseven the man- makers and thoseaffectedby a policy may want to ask. Even

agers,planners,or policy makersare often quite differentthan if each of the smallermodelscan only addressa few questions,

when the modelingwork began.All too often,too little atten- togetherthey can be usedto study the more complexstruc-

tion hasbeendevotedto building the modelsinto the dynamic tured aspectsof a resourcemanagement problem. The re-

management, planning, or policy-making process [Walker, sulting information together with policy makers' experience

1982; Lara and Sachs, 1978]. This has made it difficult for andjudgmentabout the lessstructuredaspectsof the problem

anyone but analyststo usemodelsto explore their own ideas, can assistin the processof making more informeddecisions.

obtain information about the impacts of new policy options, This has to be done within the time and budget available and

and indeed,to synthesizeas well as to analyzealternatives.

without the need to identify and argue over explicit manage-

The fact that many of our past models were complex and ment or policy objectives[Quade and Miser, 1983; McClure,

relatively comprehensivedid not necessarilyhave to mean 1981; House and McLeod, 1977; Hadden, 1982].

that they were also lesscomprehendableor lesscredibleto a

Collections of interactively linked models for impact ex-

potential user.That this has tended to be the rule rather than ploration,synthesisa,nd evaluationare oftentermeddecision-

the exception indicates only that in many casesnot enough supportor decision-aidingsystemsor modelmanagementsys-

attention has been placed on model managementand model tems [Spragueand Carlson,1982]. Figure 2 illustrateshow a

use. The challengefor the future is to learn how to model model managementor decision-supporst ystemapproachdif-

complexsystemsso that the models,or more likely a system fers from the approachillustratedin Figure 1. The focusis

of more comprehendablemodels, and the interface between broader and includesnot only modelsand policy analysts,but

the modelsand the usersbecomesmore intelligible,manage- reflectsalsothe interactivepolicymaking processA. dmittedly,

able, useful,and reliable [-Quadeand Miser, 1983]. Too little Figure2 is oversimplifieda,sis Figure 1, but theircomparison

attention has been devoted to building models into the dy- demonstratesthe changein modelingphilosophynow becom-

namic management,planning, and policy-making processes, ing evident.

i.e.,model and implentationand communication.

Figure 2 emphasizesthe interactionof managers,planners,

AN APPROACH TO MODEL IMPLEMENTATION AND COMMUNICATION

and policymakers(or their staffs)with a varietyof impactpredictionmodelslinked togetherto their appropriatedata bases.An essentialfeature is the human interaction through a

Any approach to overcomingmany of the difficultiesand "command"programinterface.This givesmanagersp, lanners,

limitations of many of our past modelsjust discussedmust andpolicymake'rsor theirstaffstheabilityto easilyexplore,

recognizethe needto involve representativesfrom eachappro- define,and synthesizea variety of managementor policy op-

priate level of decisionmaking in the modeling process.In- tions at any time, includingduring the time when the nego-

volvementof plannersand the staffsof policy makers,rather tiations over the relative merits of these options are taking

than analysts trying to guess and model their objectives, place.

values,and behavior, is the only way we seehow models are This new modeling philosophy recognizes that policy

going to become more effective as tools for exploring and making typically involvesa number of actorsand interests,

understandingkey issuesand for identifyingpossiblemanage- conflictingperceptionsof nature, contradictoryrationalities,

ment or policy options and their probable impacts.This in- and divergentadvocaciesP. olicymakingand planningare not

volvement of nonmodelers in model use, if not also model a static phenomena,but dynamic historicalprocessesC. om-

building, will only happen if the interface between the com- plexity, goal ambiguity,contradictoryuncertaintiesc, onflict,

puter, the models,and the model usersmakesmodelseasyto risk, institutional inertia, and temporal change are not rare

use and their results easy to obtain and understand.This characteristicsof policy making or planning environments;

interfacemust permit easyinteractionbetweenthe model user they are their essentialfeatures.

and the model or modelsbeingused.It must make data input High-levelmanagersp, olicymakers,and seniorbureaucrats

and editing easy to perform and make data output easy to are usuallywherethey are becauseof stronglyfelt, or at least

manageand comprehend.

effectivelyarticulated,beliefsabout certain issues.Existing

Increasing availability of interactive computer hardware policiesb, asedon thosebeliefsa, re identifiedwith thoseindi-

LOUCKS ET AL..' INTERACTIVE MODELING OVERVIEW

99

DatBa as]e

PolicAynastlsy

Decision/Impa ct-

Prediction

Models

Interactive Command Program

Managers, Policy Makers and Staffs

Fig. 2. Interactiverelationshipsamongpolicy makers,policy analysts,their models,and their data, showingstrong link betweenmodel users,model builders,and thosebenefitingfrom the useof models.

viduals.Analystsgivinginformationor providingtoolsyield- The appropriateprocedurethusis also a heuristicone: start-

ing resultsthat questionthosebeliefsand existingpoliciesare ing from expertknowledgeand problemperception,guidedby

not likely to have an audience.The problem is to resistthe strict parsimonyand whatevertheoreticalframework may be

urge to ignore thesefeaturesof political life and insteadto applicable,models are built to satisfytheir users'needsfor

adapt our thinking and modelingto this fact. Political con- information and enhancedunderstandingon the planning or

siderationsmay permit, at best, incrementalor transitional policy levels.They shouldnot be built, necessarilyt,o reliably

policiesthat not only preservereputationsbut also provide predict, becausehow could that be establishedother than in

feedbackprior to more significantmanagementor' policy hindsight?

shifts.We believethat only when modelersinclude thesecon- Model credibility is also a very subjectivenotion. A model

siderations in their models will their contributions be con- is or is not credibleonly in the eyeof the beholderor modeler.

sideredrelevantby thoseindividualsand institutionsinvolved Planningor policy modelingis as much an attempt to depict

in the processof managing,planning,or policymaking.

realityasit is an attemptto formalizeand guideour subjective

Any shift in an approach to modeling complex resource perceptionand understandingof reality. The only remaining

management problems brings with it new research op- criterion(givena certain professionaal nd scientificstandard)

portunities.Certainly this is true for the developmentof sys- is user satisfaction.

temsof interlinkedimpact predictionmodelsimplementedon Each of the remainingfive papersin this seriesaddresses

readily accessiblecomputerwork stations[Fedra and Loucks, this issue further. The conclusion to be drawn from this admit-

this issue] possiblycoupled to graphical and pictorial input tedly limited sample of experiencesand opinions is that the

and display devices[Loucks et al., this issue]. Some of the answerto the abovequestionis yes.However,it remainsto be

morechallengingof theseresearchneedsare asfollows.

seen how this can best be done.

1. Can proceduresbe developedfor deriving systemsof 2. How can a systemof interlinked modelsbe developed

simplified, yet sufficiently realistic and reliable predictive and used so that it contributes not only to increasing the

models for use in the planning or policy making process? efficiencyof any proposedplan or policy or decision(i.e.,

What is the appropriatelink betweenthesesimplifiedmodels doing thingsright) but also to the effectivenessof the policy

and the more comprehensivemodelsthat are designedto en- making process(i.e., helpingmanagers,planners,and policy

hanceour scientificunderstandingof various natural, techno- makersdecidewhat are the appropriatequestionsto ask and

logical, or social systems?How can systemsof relatively the right thingsto do)? Relatedto this is the needto evaluate

simple predictivemodels representinga complex systembe a wide variety of impactsassociatedwith a large number of

designedto be solvedrelatively quickly on a small computer objectivesor measuresof systemperformance,especiallywhen

and remain credible ?

someof those typesof impactsand objectivesare not known

One way of looking at this problem is to realize that all or thought of until well along in the planning or policy

planning or policy models,and especiallythe more sophisti- making process.

cated ones, are largely determined by their underlying as- At the heart of this questionis the problem of complexity,

sumptions: what to include and what to leave out, how to of everythingaffectingeverythingelse.It involvesthe problem

describea given process,which parameter value to choose, of not knowing what one wants to do, or knowing what will

how to interpret and prepare empirical data for inputs, etc. be consideredimportant, until one knows what can be done,

Models are thus at least partly based on subjectivefounda- or what impactswill result and how they will affect others.In

tions. In other words, models rely heavily on expert knowl- our view, the appropriate approach is a modular one made

edge.It is their heuristicvalue rather than any degreeof preci- from numerousmore general building blocks in a problem-

sionthat makesthem helpfulin planningand policymaking. specificframework.Also, the preconditionfor sucha mode of

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