Title: Models As A Viable Management Tool
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Title: Models As A Viable Management Tool
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Abstract: Richard Hamann's Collection - Models As A Viable Management Tool
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Full Text

Computer Models as Viable Management Tools

Brian W. Mar, M.ASCE1


There should be no question whether models are being used to support
analysis of environmental issues, nor whether such efforts should continue. I
will focus my comments on identifying the types of models currently in use and
the actions that are required to increase the role models can play in
environmental decision making. My observations are based on three major
assessment, efforts that I have participated in. These were an NSF sponsored
study of large scale interdisciplinary research efforts (1), an NSF/RANN
sponsored study on regional environmental modeling projects (2), and a SCOPE
(Scientific Committee on the Protection of the Environment) sponsored effort
on environmental modeling and decision making in the United States (3). Since
all these studies have been published, I will only briefly summarize the findings
and synthesize a response to the questions of improved use of models in
environmental decision making.

Current Model Usage

The SCOPE study of environmental modelling and decision making (3)

1. Conventional decision making in the United States tends to be
subject to a wide variety of constraints, including political pressures and
limited resources of money, time, and personnel. Furthermore, decision
makers may be susceptible to apprehensions involving the risk in using
such a novel or unfamiliar tool as modeling, the large investment costs,
and the lack of adequate scientific knowledge to support particularly the
large, interdisciplinary models. Modelling, however, involves an an
attempt to gain knowledge about environmental systems and generally
does not focus on the particular needs and characteristics of decision
making. These differing circumstances and objectives entail that model
application in environmental decision making may be difficult.

2. The application of environmental modeling to decision making is
most advanced in those areas requiring relatively simple operations
models for day-to-day or short-term decision making. As more complex
and unpredictable environmental systems are studied, the number of users
increases. The interactions among modelers, decision makers, and various
interest groups become more complex and model application thus becomes
more difficult.

Associate Dean, College
University of Washington, Seattle, WA 98195


3. Models which are descriptive and developed with the intent of
classifying a system may not raise false expectations in decision makers
because such models do not purport to provide answers or solutions.
Prescriptive models, which attempt to indicate or recommend a particular
solution or course of action depend on accurate, descriptive models.
These models also make greater demands on data and theory, and
consequently their ability to provide accurate predictions are subject to
these constraints.

4. Modeling undertaken in an application-oriented, integrative
context (i.e., the synthesis and integration of current knowledge) has a
better chance of facilitating decision making than modeling undertaken as
basic research. This is not to belittle the role of basic scientific research,
but to suggest that modeling applied to environmental management must
be undertaken with different and perhaps more pragmatic objectives.

5. A significant factor in successful model application is the extent
of interaction between modeler and decision maker. This interaction is
difficult to foster because modelers and decision makers often have
differing perspectives, goals, methodologies, and reward systems. Never-
theless, with viable user involvement in the modeling process, model
specifications and objectives can be defined, resulting in models which can
address the particular needs of the decision maker.

6. The most successful users of models tend to be the modelers
themselves. This is due to their familiarity with and confidence in the
modeling effort. Thus modeling may contribute most successfully to
decision making when it is used by decision makers who were once
modelers, or who at least have a fairly sophisticated knowledge of
technical modeling matters and systems analysis methodology.

7. Interaction between modelers and decision makers may be
enhanced through the involvement of an intermediary or "policy analyst."
The policy analyst is often conversant with both technical modeling
matters and the pragmatic realities of decision making. He thus has the
capacity to translate the goals and constraints of decision making into tan-
gible modeling specifications.

8. Modeler-decision maker interaction may also be improved by
bringing modelers and decision makers closer together. One approach has
been the development of software systems such as graphic displays which
present model output in a form likely to be understandable to the client.
These systems are, however, relatively costly to develop and maintain.
Another promising technique is that of gaming-simulations specifically
designed to develop a language common to both decision makers and

9. Another mechanism which facilitates interaction or information
exchange between modeler and user is adequate documentation. Com-
plete documentation should include an explanation of the conceptual basis,
assumptions, and limitations of the model, along with basic information on
computer programs and operating instructions. Documentation is fre-
quently inadequate because few incentives exist and inadequate resources
are provided for this aspect of model development. Furthermore,


recognized and widely accepted documentation standards do not exist.

An important contribution of the SCOPE analysis was to suggest a
framework for analysis of models used in problem solving context. Models must
be designed to address a particular type of decision since operating decisions
are so different from planning design. Each have particular data and resolution
criteria which are difficult to satisfy with a single model. Table 1 presents the
suggested types of system theory that are used to support such models. Notice
that systems that can be treated as complete known systems can still require
large-scale and complex models in some cases. Most important is the
recognition that it is unlikely that one model can meet the demands of all
decision makers. Notice that models that fall on the diagonal from upper left
to lower right corner of the table have found the most acceptance. For
example, day to day operations use simple but predictable models more than
highly complex and unpredictable models, while long range planning decisions
use just the opposite.

The SCOPE study also argues for an intermediate agent between the
decision making process and the university. The agent can be an analyst who
can translate between group or a gaming process which provides a forum where
both groups can merge. The yardstick for utility should examine the simplicity
and strength of the bridge between the University researchers and those in the
decision making processes. In most cases this bridge is only one way (from
University to decision process) without feedback and fails to be responsive to
the needs of the decision makers. If the bridge is not crossed until after the
research is completed, the research are often the right answer to the wrong

While the SCOPE study found broad usage of operational models that were
developed by a modeler in a particular discipline for professionals trained in
that same discipline, it identified a need for models in planning and
management decisions that contains concepts from more than one discipline.

Table 1. The System-Decision Matrix


TYPE OF Simple and Complex but Simple but Highly Complex
DECISION Predictable Predictable Unpredictable and Unpredictable

Day-to-day traffic light moon flight models for models of economic
Operations models models police response to
deployment tax change
based on

Short-term highway flood control system urban planning
Decision design models responses to models

Long-term usually not models for models of models of
Planning- applicable updating government global
Policy pollution budgets or environmental
control consumer policy
strategies preference


Interdisciplinary Environmental Models

The NSF/RANN assessment (2) examined 18 large scale interdisciplinary
modeling efforts (2-3 years and 0.5-1.5 million dollars) to develop models of
economic, engineering and ecological aspects of regions ranging in size from a
city to multistate areas.

The findings of the evaluation of the RES projects (2, 4, 8) indicate that a
major investment is required to develop the data to support intensive large-
scale modeling efforts, whether they are micro-models demanding detailed
cellular data or macro-models demanding extensive time series data for
parameter identification. If the trend toward the scientific/reductionist
approach is to be continued, extensive investments to support data bases will be
necessary (5). It may be several decades in the future before such data bases
will be supported by Federal, State or Local units of government. In the
meantime, large-scale prototype models could pioneer the exploration of the
use of such regional data bases. An alternative strategy is to decompose the
large-scale model products into subroutines that can utilize partial data bases
or respond to specific user needs. This would be compatible with existing
diversity of users, but would ignore the holistic concerns of the "spaceship
economy" expressed by Boulding (5).

The experiments in user involvement revealed a large gap between
available knowledge and methods and those used in the decision making arena.
A very practical model usage strategy would be to limit the next generation of
large-scale modeling projects to consulting activities that emphasize the
applications of existing tools to recognized problems. Since such a program
would have immediate impact and the warehouse of existing knowledge seems
large, such a program can have high impact, but also high resistance from the
scientific community that searches for new knowledge.

A third alternative is to seek to develop a new kind of science based not
on full knowledge, but on the ability to cope with the unknown. Holling (7) has
argued for the need to be able to fail safely rather than to develop fail safe
systems. The latter assumes full knowledge and the ability to design systems
with this luxury. The former acknowledges partial knowledge and the need to
be responsive and correct errors rapidly. The ability to anticipate surprises is
not well developed, but catastrophe theory, fuzzy sets, and surprise theory
provide evidence of new alternatives to the classical data intensive reductional-
ist strategies. Exploration of the uncertainty and development of strategies for
responsiveness and ability to perceive early warnings appears to be a fruitful
area for exploration, as an alternative to large-scale models.

Past large scale modeling efforts have presented exciting challenges to
modelers and scientist, but disappointing results for decision makers. Modelers
have modeled the known and ignored the unknown. Many of the national
problems that have been studied by models are abstracted into non problems.
The omission of factors is a major pitfall of models. Bridges fail because some
factors are ignored rather than improper modeling of factors that are included.
The yardstick for effectiveness should include completeness as a criteria to
determine if the information contained in models ignore important interactions,
or are limited by crippling assumptions.


The transfer and application of a large-scale interdisciplinary models
appear to involve four steps: (1) the development of the models and the
demonstration of the ability of the model to address a specific client's problem,
(2) the modification, documentation and generalization of the model for use by
a broad set of clients, (3) physical transfer of the model from one computer to
another, or the establishment of an agency to operate the model for prospective
clients, and (4) the widespread acceptance of the models as a routine element in
regional environmental decision making processes.

The cost and difficulty of the transfer and application of a computer
model appears to be a function of the complexity, size, and philosophy
underlying the models. Those models based on conventional analytical methods
that address one particular problem such as employment, water supply, resource
consumption can be transferred at relatively small costs. Complex models that
interrelate economic activities, technological development, resource consump-
tion and environmental quality in unique and novel ways face very high costs of
transfer until existing agencies recognize the need to use these tools and more
effort is made to develop a cost effective approach for the four step transfer

Interdisciplinary Modeling

The third assessment effort examined the ability of interdisciplinary
teams in universities to produce models or other useful results. The university
structure stimulates the individual faculty member to conduct research.
Similarly most scientific organizations mirror this discipline and individual
structure. If a national problem requires such an individual input it can usually
be obtained. However, if the problems require the integration of several
faculties or disciplines the empiricial evidence seems to suggest that the
university has not been effective and many faculty suggest that such research
does not even belong on campus.

While the observations presented here are speculative and subjective, a
major thrust of our project on the management of interdisciplinary research is
to provide quantitative insight. A three-pronged attack to identify issues and
experiences of university administrators, center and institute directors, and
interdisciplinary project teams at many universities across the nation was
completed. Many of these projects use models as one of their tools of analysis.
Data were collected from extensive on-site interviews and formal question-
naires. Based on a preliminary assessment of these data we suggest the
following hypotheses:

University administrators generally do not differentiate between the
costs or problems of interdisciplinary research projects and disciplinary
research efforts. Some faculties are expected to develop interdisciplinary
efforts with no more help than that provided disciplinary efforts; much of this
cost is passed on to the funding agency in terms of less productive research in
the first few years.--Interdisciplinary research is not nurtured on campuses.

While a center or institute can provide an umbrella and a voice for
faculty wishing to pursue interdisciplinary research, experience has shown that
such units work hard to obtain a firm base of financial support. Once such


funding is achieved the interdisciplinary zeal slowly fades because the
participating faculty work hard to exclude new members to avoid further
division of existing resources.--Centers do not stimulate interdisciplinary
research in many cases.

Management strategies affect interdisciplinary research team perform-
ance. No one strategy has been able to create the commitment and
cohesiveness necessary in a successful team. But the more types of integrating
mechanisms a group uses (such as workshops, seminars, continual documenta-
tion) the more interdisciplinary it becomes.--Interdisciplinary research is not a
stable grouping.

Since faculty members tend to concentrate on the frontiers of their
disciplines, and interdisciplinary research requires the whole breadth of
knowledge in a discipline, it may not be necessary to have a team solely
comprised of basic researchers. A balance of applied and pure research will
always be necessary.--Interdisciplinary teams of only faculty members are most

Quality control presents a challenge for any interdisciplinary research on
campuses as peer review is difficult to develop.--Most faculty will not consider
interdisciplinary research to be scholarly. One major observation is that the

One major observations is that the academic status structure is a major
deterrent to interdisciplinary research efforts. An assistant professor has a low
probability of successfully manage a group of professors of higher rank nor can
a professor from a lesser discipline (engineering) successfully lead a team that
has disciplines of higher stature (medicine, economics, etc.).

The disciplines tend to pride themselves in their self importance, they
encourage their faculty and students to look with disdain on members of other
disciplines and require others to learn their language rather than attempt to
present their concepts in terms understandable to all. The problems of learning
to work together towards a common cause is not addressed in universities.
Discipline bigotry is reinforced and transferred to non academic research
institution to an extent that almost all interdisciplinary efforts suffer from the
inability to communicate with other disciplines. The Universities may not be
alone with this problem, but they may be the epitome! If large scale modeling
or problem solving is to be effective the universities must be one of the
yardsticks used to determine if sciences can address national problems. A
project that requires most of its resources to organize and establish effective
communication will not produce much more than a training grant. Most
interdisciplinary projects have provided training in the process of interdisciplin-
ary research at fairly high cost.

The large complex interdisciplinary models are not accepted because of
the disciplinary biases of user groups. In the future a major educational effort
will be required to gain acceptance of these complex models. Until disciplinary
barriers are lowered, the operational disciplinary model will be the only type of
model in common use.



The role of models in solving national problems may be indirect rather than
direct. Faculty members in universities seem to be unable to form teams to
address interdisciplinary issues, but they could permit and encourage their
students to do so. Individual faculty could also develop teams of post doctoral
fellows, students, and staff to address such problem with high probability of
success. The problem appears to be the lack of a mechanism to bridge between
the to results of faculty efforts to construct models on perceived national
problems and the demands of the decision making process created by real
national problems.

The gap between most participants in the decision making process and
large-scale model developers is very wide. Rather than forcing those involving
in decision making and those in large-scale modeling to leap across the gap it is
suggested that a sequence of steps be established across this gap. Such steps
could be gaming to condition those in decision making to expand the complexity
or their analysis as well as those in modeling to simplify their models. A forum
to encourage communication between those that understand the decision making
process and those that study the causality of factors affected by decisions must
be constructed. The forum must stress the outer boundaries of the system in
question and avoid rapidly focusing on a few easily identified variables.

Universities must build these bridges to solve national problems, since the
style of university problem solving is in fact a major cause of our national
problem. Disciplines tend to have inherent myopic views which prevent frac-
tions of the university from considering problems of interest to the decision
making process.

This research was funded by the National Science Foundation grant
ENV76-04273. The findings and conclusions do not necessarily represent
views of the National Science Foundation or the University of Washington.



1. Mar, B.W., W.T. Newell and B.O. Saxberg, "Interdisciplinary Research
in the University Setting," Environmental Science and Technology 10
#7, 50-653, 1976.

2. Mar,B.W., "RANN Models of Regional Environmental Systems," Working
Proceedings, March 1, 1978, University of Washington.

3. "Environmental Modeling and Decision Making," a report by the Holcomb
Research Institute for SCOPE, Praeger Publishers, New York, 1976.

4. Mar, B.W., "Problems Encountered in Multidisciplinary Sources and
Environmental Simulation Models Development," Journal of Environmental
Management 2, 83-100, 1974.

5. Weaver, W., American Scientist 36, No. 4, 1948.

6. Boulding, K.E., "The Economics of the Coming Spaceship Earth," in
H. Jarret, Ed., Environmental Quality in a Growing Economy, John Hopkins
Press or RFF, 1966.

7. Holling, C.S., in "Ecological and Resilience Indications for Management,"
R. Yorque, Ed., Inst. of Resource Ecology, University British Columbia,

8. Mar, B.W., "Assessment of Selected RANN Regional Environmental
Systems Modeling Projects: Transfer and Comparaility Testing," Final
Report, March 1, 1978, University of Washington.


Donald E. Overton, Member1


Agreeing to address this subject would imply that the author knows
the secret of effective communication. As a modeler or a technocrat I
feel that I have had some successes in communication and I also know
that I have had my share of disappointments and setbacks in this area.
If I could be so bold as to attempt a generalization of these experi-
ences, I would say that the successes resulted when I concentrated
heavily upon understanding the problems of the institution I was addres-
sing and placed a minimum of concern upon the intricacies of the
technological solution in issue. My disappointments resulted when my
concerns on these matters were inverted. Although I cherish success
and loath disappointments as much as the next modeler, I would be much
happier with a middle ground or trade-off between humanistic concerns
and technologic detail.

I have no crystal ball for arriving at a global solution to such
a profound and crucial problem as achieving effective communication.
What I will offer, however, is a commentary on why effective communica-
tion is so difficult and elusive and some suggestions as to what can be
done within institutions (universities in particular) to promote the
development of communication skills of technocrats.

Development of technology has never been a problem for the United
States. The problem has been technology transfer or in other words
closing the gap between theory and practice. It is a serious problem
and stems from the assumptions underlying our attempts to provide educa-
tion principally through schooling and the ensuing certification pro-
cess. With little emphasis placed upon much needed humanistic develop-
ment and an overemphasis placed upon mastering voluminous and intricate
technicaldetails it is easy for us to become caught up in our own
technology so much so that it becomes a way of life. Ideas, notions,
and technical detail slightly outside our narrow band of technology
can easily be passed off as generalities. Hence, in the interest of
problem solution it is essential that our newly developed technology be
placed in a humanistic context, otherwise the gap between theory and
practice shall grow wider, problems will not get solved and we shall
grow more frustrated and be understood less.
Further discussion of the ideas presented in this paper can be
found in the reference.

Department of Civil Engineering, The University of Tennessee,
Knoxville, Tennessee 37916.



Our schooling systems have operated upon the concept of training
technocrats for firing up the industrial-military machine and little
emphasis has been placed upon the development of human values. Yet,
our failures have not been in the training and developing of technology
and technocrats, but rather we have clearly failed in our attempts to
narrow the gap between theory and practice such that the needed tech-
nology is applied to solution of environmental and socioeconomic prob-
lems. The failure, therefore, has been in the area of human relations
and in our inability to confine our proliferating technology within
the bounds of a much needed humanistic perspective.

I truly believe that we can achieve beyond certification.

It is true that the number of years of schooling of the populace
is highly correlated with the GNP, likewise it is correlated equally as
well with the increase in many environmental, social and economic prob-
lems. Hence, there must be something about our schooling that is help-
ing us along our way towards oblivion. Indeed, there is .

The schooling movement was given great impetus by the pursuit of
a great dream by Americans: to pull themselves out of one socio-econo-
mic class into the next higher or even higher class. But an inherent
value judgement was made by those who pursued a higher socio-economic
class standing, and, it was that the production lines wpuld continue,
but someone would simply take their place. Further, those who left
the declining small farm or the production lines and joined the new
class of technocrats decided that the real satisfaction in living would
be to attain position and wealth rather than eradicating poverty, big-
otry and oppression. In essence; the Great American Dream was.the
attainment of self gratification. There was, however, a great hope
that the spin off of these efforts would gradually improve the lot of
those left behind.

Our blind spot in equating schooling with education is so complete
and so subtle that we find ourselves thinking that we are educated but
at the same time unable to solve or in many cases, cope with our prob-
lems. Clearly, we are not educated nor for that matter are we even
knowledgeable; instead, we have schooled ourselves into passiveness.
We have consistently overlooked the fact that schooling has inherent
morality which generally reflects the culture of the ruling class.

Lack of a definitive obtainable goal for schooling, although hard
to comprehend, is indeed almost self evident. In fact, leading educa-
tors define education as what goes on in schools and they generally
feel that even a discussion of the ends of schooling would prove futile.
This definition of education necessarily blocks any attempt to ask what
the goals of education should be.

In schools, young people are subjected to a structured curriculum
with a resulting alienation between work and leisure. They soon sense
that there is an expected response to give to the teacher. When a
child responds to a given question in a prescribed way, he is said to


be learning. Ultimate evaluation of performance is based on test
scores. The atmosphere of certainty is generated in such ways as re-
presenting science as a series.of controlled experiments, history as
a series of uncorrelated facts, and language is represented as correctly
spelled words placed out of context of familiar usage. These repre-
sentations facilitate ease in presentation and testing and free the
teachers from having to think. If acceptable scores are not made on
the tests, the conclusion is made that one is not learning and there-
fore there must be something wrong with him. One not learning in school
is construed to mean that one cannot learn at all.

But structured learning by testing does not stop here for the
pupil is further evaluated by I.Q. tests which are given because they
allegedly measure intelligence. An I.Q. test must be perforce struc-
tured after someone's concept of intelligence. Proponents of the use
of I.Q. tests themselves have never defined intelligence coherently,
and for that matter few have even been bold enough to try. Some who
use I.Q. tests who have not attempted a definition of intelligence hold
the view that the results of the test is a sample of personality. Ad-
ministration of I.Q. tests is an institutionalization of intelligence
and morality. The testors set themselves up as intelligent and the
decision is final. Yet, their alleged scientific approach is tainted
by their inability to define what they are attempting to measure. Fur-
ther, credibility of the results of the tests are seriously jeopardized
by holding such strong predilictions as to what the outcome should be.

Teachers are being required to bring the I.Q. scores of their
students up to some prescribed level (probably the national average).
The nonsense of this gesture overpowers the imagination. In the first
place, I.Q. tests, like most all tests; are devised on the theory that
a bell shaped distribution will result. Actually, it is the other
way around: the tests are devised to induce a bell shaped curve. In
any event the grading is based heavily on the norm, and consequently
the scores have a marked scale effect. As long as the scale effect is
left in, there will always be states who fall above and below the 50th
percentile on the I.Q. quota. Thus, after a two or three year trial
period as many as 50% of the teachers could be subject to dismissal on
grounds of incompetence. Secondly, further teacher pressure on stu-
dents can only widen the gap between those who score high on tests
(generally the middle class) and those who score low on tests (generally
children from low socio-economic homes). Such intensification on
forced learning would only lead to a greater number of psychological
referrals to special learning classes, dropouts and an overall deeper
sense of frustration for all students. Neurotic and psychotic dis-
orders are increasing at an alarming rate already. It clearly follows
that further pressure on teachers to raise the I.Q. of their students
cannot succeed on a national basis because test scores are all scaled
and therefore relative. In addition, further pressure can only widen
the spread between high and low scores and the net effect is that
teachers will be considered to have failed to a greater extent. This
whole idiotic preoccupation with raising I.Q. scores is likened to a
tournament where there is always a winner and a loser, and it is just
a matter of playing until all but one is undefeated--everyone else is
a loser. We might as well conduct a tournament and expect everyone to
finish first.


The richest 10% of parents can afford private schooling and educational
experiences for their children which help them considerably in winning
scholarships and grants. These richer children also obtain ten times
more the amount of public expenditures than do children from the poorest
ten percent. As Ivan Illich has clearly pointed out, this disparity is
gigantic in Latin America where the amount of public money spent on each
graduate is between 350 and 1,500 times the amount spent on the median
citizen. To correct this injustice in the United States the NEA seeks
an appropriation for the poorer schools which will permit them to
raise their effectiveness to those of the richer schools. Their well
intended approach toward social injustice is to create equal educational
opportunity for all by making the whole world into a classroom. The
main problems encountered with this approach are, first, that it would
take a yearly appropriation of one-hundred billion dollars to do what
is utterly impossible; second, the Coleman report, and others, have
shown that the damaging effect of an unhappy home life cannot be over-
come with additional school facilities, services, and new teaching
methods; and third, as long as I.Q. and other tests are used in evalua-
tion of the intelligence (whatever that is) there will always be 50
percent who do not measure up to the norm (this is the tournament
effect mentioned earlier). The motives of the NEA are above reproach,
but it is the religious adherence to their concepts of intelligence
and learning plus the impossibility of all students scoring above the
average on I.Q. and regular classroom tests which spell failure for
their approach. Unless they realize that they have built in failure
in their concepts and procedures, they will forever make frantic pleas
for additional resources to transform the below average learner into an
average learner and an average learner into a bright or gifted learner.

Our contemporary schooling has produced a youth which is deeply
skeptical and distrustful of established values and order. Even though
they may nurture an intense dislike for the system, they choose the
safe course of conformity. Thus, the seed of schizophrenia is sown.
Because they feel outcast from the community of free speech and
sense that they are being exploited for the good of the economy or
their parents' ego; they fall back into their own exclusiveness of
language, sex, and drugs as a shield against the octopus of adult mid-
dle class culture. The perniciousness of contemporary schooling is
solidified by the mindlessness of standardized testing. Defining and
judging intelligence on the basis of predelictions of a few self-
styled intellectuals who have never been out of school is deleterious
to the maintenance of a healthy democratic state. In clear view of the
social and economic polarization which results from "the tournament"
of mass testing, it is a tragic irony that the tests are supposedly
structured to judge the ability of young people.

Research on campus has added greatly to the wealth of institutions
of higher learning. They are tax exempt and are not required to make
public disclosures of their holdings; and few make such disclosures.
University officials are to be found on the board of directors of
about 50 percent of the largest corporations in America, and the dis-
tinction between federal government and industry is becoming tenuous.
Many top federal executives now move from universities and after a
spell they tend to be hired back by universities or land top executive
positions with big industrial concerns.




The university is no longer a community of scholars--if it ever
was. There is little if any concern about education, only preoccupa-
tion with attainment of position and accumulation of wealth. The huge
sums of money that the university takes in as research grants evidently
greatly hinders their prescribed role as teachers. The university is
hardly a center of independent thought and introspection but is a na-
tionalized industry which consumes two percent of the GNP and operates
primarily as a certification mill.

We must realize that a college degree is not a guarantee of charac-
ter nor is it an index of creativity or innovation. We should realize
or remind ourselves that learning is a combination of work and play;
and, therefore, forcing our youth to sit silently for decades listening
to someone lecture, is little reason to believe that anyone in school
is really learning anything of value. We should remind ourselves also
that it takes talent and courage to be successful and if the spark is
not there it is doubtful that sitting and listening to lectures will
change our inner fiber.

Converting the whole world into a classroom is not the solution to
narrowing the technological gap. Besides, many middle class Americans
have lost their confidence in our schooling system, perhaps because the
schools have not fulfilled our impossible expectations. Some educators
fear the death knell for public schools. Even if we were committed to
raising the standards of poor schools to that of rich schools we would
have to decide who would pay for it.

We really do not know how to measure the effectiveness of school
systems because we still have not decided what our goals are in society.
We pay far too much attention to the "education" of our children rather
than providing them with a worthwhile adult world to grow up in. Con-
tinual study in pursuit of technology leaves no time to experience,
meditation or for leisure. On our present path the drastic changes
which have come and which will come to our schools have not and will
not be practical or orderly.

Well, where do we go from here? Alistair Cooke commented that he
sees the U.S. in a race between vitality and decadence. He wrote:

"Every other country scorns American materialism while
striving to match it. Envy obviously has something to do with
it, but there is a true basis for this debate and it is whether
America is in its ascendance or its decline.

I myself think I recognize several of the symptoms that
Edward Gibbon saw so acutely in the decline of Rome, which arise
not from external enemies but from inside the country itself:
A love of show and luxury; a widening gap between the very rich
and the very poor; the exercise of military might in places
remote from the centers of power; an obsession with sex; freak-
ishness in the arts masquerading as originality, and enthusiasm
pretending to creativeness; and a general desire to live off the
state, whether it's a junkie on welfare or a government-subsidized



In a word, the idea that Wasington--Big Daddy--will provide.

Yet I have tried to show that the original institutions of
this country still have great vitality. Much of the turmoil
here springs from the energy of people who are trying to apply
those institutions to forgotten minorities.

Now, as for our rage to believe that we've found the secret
of liberty in general permissiveness from the cradle on, I can
only recall the saying of a wise Frenchman, "Liberty is the
luxury of self-discipline." And historically those people who
did not discipline themselves had it thrust on them from the

That's why the usual cycle of great nations has been:
First, a powerful tyranny broken by revolt; the introduction
to liberty, the abuse of liberty, and back to tyranny again.

As I see it in this country, a land of the most persistent
idealism and blandest cynicism, the race is on between its
decadence and its vitality. ."

If we wish to improve humankind we must have some notion of what
we are, because if we have none, we can have no idea of what is good or
bad for us. Humans tend to be moral and spiritual beings. Improvement
of humankind means improvement of their powers. Humans need not agree
with one another, but it is essential that they understand one another.
Without such effective communication, the technological gap grows,
oligarchies rise, unhealthiness continues and we edge closer to obli-
vion--confused, sick, desperate. Hence, we should temper the learning
of technical skills with a liberal education.

A liberal education should aim at the development of the powers
of understanding and judgment. The object of a liberal education for
our youth is to teach them subjects that cannot be understood without
experience in practical real world situations. These subjects should
not be taught by those who are without that experience. Hence, there
is a strong need for pragmatism with the teachers and in the learning
process. But we must remember that important things can be learned
only in adult life. This educational process should be dialectual.

But we must be realistic in our expectations of schools and
teachers. School cannot and should not take over the role of the
family. The ultimate responsibility for the supervision of the educa-
tion of the children must rest with their parents.

It is realistic to expect that our schooling systems shall move in
a direction to develop a consistent and clear philosophy of education
including measurable objectives. If that philosophy includes the gene-
ration of an "intellectual elite" in a democratic republic, it is
realistic to expect the schooling systems to clarify this apparent
inconsistency. Schooling should include a significant element of prag-
matism, and it is their responsibility to insure that it exists in and


is practiced and professed by its teachers.

Universities have transcended from innocent forums of academic
pursuit into tax exempt businesses where their product is newly deve-
loped, highly complex technicalogical solutions to research problems
funded principally by federal tax revenues. Nevertheless, the last
vestige of freedom is entrenched in universities and they have been
given the responsibility of educating our young, and preparing them for
the uncertainties of the world.


If we are ever to improve our record in social and economic jus-
tice, as well as in communications we must provide a mechanism for
permitting and encouraging us to achieve beyond certification. Certain
evils associated with taking academic certificates too seriously have
been discussed herein, but I am assuming that the certification process
will continue. I would like to suggest mechanisms which we may under-
take for using the certification process much more to our advantage
rather than have it work against the best in interests of our general
health and welfare. To better utilize the certification process it is
imperative that we undergo a drastic change in our attitudes toward
certificates and the certification process.

To achieve beyond certification, we must revitalize and replenish
our declining universities and schooling systems at large on the way to
Controlling technology and our destiny. The timing is right because
our schooling systems (as well as the environment), are in big trouble.
They are in a steady state of decline as often pointed out by the
National Education Association (NEA). The problems in public schools
are but a symptom of the underlying problems which are deeply imbeded
in our culture.

Universities and colleges are facing serious problems also. On
the surface the problems appear to be essentially financial, yet this
too is only the tip of the iceberg. Institutions of higher learning
-are without clearly defined objectives and their financial problems are
principally due to a lack of planning and to poor management. During
the past few years, the courts have exhibited an increasing tendency
to review academic decisions about students. Fears have been expressed
that the tendency will accelerate. If this be true, it appears to be
the result of several forces: increased sophistication and curiosity
of students, the decline of the doctrine of in loco parents, higher
education regarded as both a social necessity and an individual right,
Sthe expansion of civil rights protection by public authority, and the
developing notion that state universities are simply another state
agency of state government to be policed, regulated, and whipped into
a bureaucratic mold. In short, if the universities do not get their
house in order the courts are going to intervene into their tradition-
ally unscrutinized affairs and to an extent supervise them.

Further, a blue-ribbon task force on education for HEW in 1973
recommended that higher education be more responsive to the needs of
today's students and be made to prove its worth in real terms. This
sounds like a need for "managing by objectives." Although universities


are endowed to foster education, they are steadily developing corpora-
tion-type problems.

In order to implement a program for developing schools into human-
istic educational institutions, we must first begin with specific ad-
justments which must be made in the universities. Some adjustments
should be made in the area of administrative policy, and some adjust-
ments should be made in the attitudes of the faculty.


The university should focus in discourse on problems of contem-
porary society. Thinking is hard work. Development of a coherent
philosophy of education is difficult and an ungrateful task. This may
result in the need to re-educate (not necessarily re-school) educators.
This is a very difficult task. University administrators should de-
escalate their lobbying of state legislatures for increased funding for
expansions and take on an aggressive role in negotiating with the
Federal government over the ability and availability of the universities
to participate in the temporary solutions of crises. The university
is in an excellent position to take a fresh look at our society and to
formulate a "pecking order" of priorities, concentrating on the most
serious problems first. Administrations should look at their tenured
faculty for input. This effort should not be taken on as an additional
work load, but because of the critical nature of this mission lower
priorities should fall away.
Hiring and promotional practices must change in order to provide
a reward and review process for implementing this program. The empha-
sis shall be placed upon demonstrated ability and willingness to solve
problems in a professional style and in a pragmatic fashion. A person
holding any kind of a doctorate with no real world experience either
in or outside of the university should not be considered to be qualify
to hold a tenured faculty position.

In hiring new faculty, heavy consideration should be given the
candidate's ability and experience to solve problems and to be able to
effectively relate to people.

The biggest single attidutinal change which university adminis-
trations must make is to discard their aloofness, and get into the
spirit of community and of world involvement and cooperation. The
world will welcome such a gesture, but to be effective, it must be
backed up by affirmative action.


The biggest single adjustment for university faculty will be to
come to grips with their technology. Unfortunately, many seldom rea-
lize that the technology associated with the most minute topic is
actually infinite and unbounded, and that the only sane approach to
coming to grips with technology is to utilize the technology needed to
solve problems. This would be the cut-off point until the next prob-
lem is attacked. They must begin to realize that the answer to serious
contemporary problems is not to be found in the library, that the


technology which they learned in school may not be applicable to the
problems of today, and that, if necessary they may have to become in-
novative and develop a new technology for solivng the problems at hand.

Fostering disciplines rather than fostering the solution of prob-
lems in a pragmatic fashion leads one to chase technology as a way of
life--world without end, amen. Hence, an attitudinal change of faculty
and perhaps all technocrats would be necessary before technology could
be controlled.

With these attitudinal changes, university professors would there-
by have an incentive to test for competence rather than intelligence
since the classroom work would be linked directly with the attempted
problem solution rather than with a discipline, per se. The class-
room would become one of the main mechanisms for development of a new
breed of humanistic, pragmatic technocrats who hopefully can communicate
with hierarchies. This is intended to serve as the main example of
how education may be achieved through schooling.

These attitudinal changes must come about, and if the universities
do not take on roles as aggressive problem solvers and cease prolifera-
ting technology, per se, to the exclusion of the development of human-
istic qualities we can only expect our general health to worsen,
i.e. vitality will yield to decadence and effective communication will
be stifled.


1. Overton, Don, Doctoritis, Vantage Press, Inc., New York; 1978
(in press).



By Thomas N. Debo, M. ASCE and Gerald N. Day, A.M. ASCE

Columbus, Georgia is typical of many communities throughout the
country which are being plagued by flooding and drainage problems re-
sulting from urban development. Columbus is located in Muscogee County
in Southwest Georgia, on the fall line separating the sandy soils of the
coastal plain from the sandy-clay soils of the Piedmont (Figure 1). The
topography in the County ranges from very hilly areas in the north to
flat plains in the south. The area receives approximately 50 inches of
rainfall annually which is fairly uniformly spread throughout the year.
Approximately 40 percent of the County is within the Fort Benning
Military Reservation which is not included in the following discussions
since it is not under local control.
Columbus and Muscogee County are governed by a consolidated city/
county government. The Departments of Community Development, Engineering
and Public Works have the primary jurisdiction over flooding and drainage
matters. The Department of Community Development is the lead agency for
the Columbus Storm Water Management Program (SWMP) which is the subject
of this paper.

Columbus Storm Water Management Program (SWMP)
In 1975, the Columbus Department of Community Development obtained
funds from the HUD Comprehensive Planning Assistance Program (701) to
initiate Phase I of a comprehensive Storm Water Management Program.
When completed the program will span over five years with implementation
proceeding into the 1980's (Figure 2). One of the basic elements of thel
Columbus SWMP is the development and implementation of a hydrologic
computer model. The emphasis of this paper is to discuss the role of
the model as the key factor in the development of the Columbus SWMP.

Hydrologic Model
Traditional engineering design procedures are adequate for analysis
of small development sites and design of individual drainage facilities.
If the interrelationships between drainage facilities or the complex
dynamics involved in the hydrologic-hydraulic characteristics of complex

*Respectively, Senior Water Resources Planner with Hydrocomp Inc.,
and Assistant Professor, City Planning Program, Georgia Institute of
Technology; and Associate Hydrologist, Hydrocomp Inc., Atlanta, Georgia.|




i ..,Di "-IJ / DE L WAL TON


\ !- 1 JONES \BALDWI< \


-L I,- _RWIN7 L




Phase I Phase II
1975-76 1976-77

U.S. Soil U.S. Geological Hydrocomp
Conservation Survey

Phase III


user's manual)



urban drainage systems are to be analyzed, traditional procedures will
be either very cumbersome and time consuming or inadequate to do the
analysis. The hydrologic model developed for Columbus is a computer
program which simulates the rainfall-runoff processes of the hydrologic
cycle. The model has the capability of simulating runoff to and routing
the runoff through complex urban drainage systems, including both natural
and man-made drainage facilities. The model also has several other major
capabilities and advantages over traditional procedures:

Use of the model will result in uniform procedures being used
for all drainage design in the County.
Because of its speed in evaluation, the model will save countless
hours of engineering analysis time which can be used for problem
solving and analysis of alternative designs.
Interrelationships between drainage systems and components of
individual systems can be analyzed and evaluated.
SThe Columbus model also has the capability of evaluating the
economic consequences of flooding and the effects of implementing
flood mitigation measures.

Role of the Model in the SWMP

The hydrologic model is the key to the development and success of
the Columbus SWMP. Consideration of the model's needs and capabilities
influenced the planning and development of all elements of the program.
The following discussions describe the role and function of the hydro-
logic model with respect to the different elements shown in Figure 2.

Soils Inventory and Analysis

In the first phase of the program, the U.S. Soil Conservation
Service contracted to prepare detailed soil surveys for Muscogee County.
The information gained from these surveys will be used for many purposes
in the County (e.g., identifying sites suitable for development, deline-
ating those areas where erosion and sedimentation might cause problems,
aiding in making decisions concerning areas to be preserved for open
space and wildlife habitats). One major consideration in the design of
the soil surveys was to provide the data needed for the hydrologic model-
ing. It was necessary to distinguish the different soil types and their
rainfall-runoff characteristics in order to determine if separate evalu-
ations by the hydrologic model were necessary. Thus, the soil surveys
provided the data necessary to make several important hydrologic related
decisions (e.g., location of stream gauging sites, and evaluation charac-
teristics of the hydrologic model).

Hydrologic Data Collection To insure that a hydrologic model is
correctly simulating the local hydrology, it should be calibrated and
verified using rainfall and streamflow data from the local area. Cali-
bration is the process where simulated flows are compared with observed
flows and parameters are adjusted until a good "fit" is obtained. A
review of the available data in the Columbus area indicated the need for
several types of data.


(1) None of the existing stream gauges in the area were located
on small drainage basins (under 10 sq. mi.).
(2) There were no streamflow data available on urban or suburban
watersheds in the area.
(3) The few existing stream gauges were located in only one of the
two physiographic regions in the County.

To fill in these gaps of missing data, a stream gauging network was
designed, and the U.S. Geological Survey contracted to install the
gauges, maintain them, and process the measured data. Figure 3 shows
the location of four gauges which were installed during the Fall of
1976. It is anticipated that data will be collected from these gauges
for the next five years. The hydrologic model will be calibrated using
the first year of record from the gauges and other data available from
nearby counties, and then recalibrated once the five years of data are
available. The development of a good hydrologic data base is essential
for a good calibration, and the model can only be as good as its cali-

Sediment and Erosion Control Ordinance

Ordinances and regulations are a very important part of any storm
water management program, and provisions of such ordinances must be
supported by the other elements of the program. Provisions must not
require designs that are beyond the enforcement capabilities of the

On April 24, 1975, the State of Georgia passed the Erosion and
Sedimentation Act of 1975. The Act requires that each county and munici
pality of the State adopt a comprehensive erosion and sediment control
program by April 24, 1977. In response to this mandate, a sediment and
erosion control ordinance was drafted and adopted by the Columbus City
Council. Figure 4 lists the basic provisions included in the ordinance
Although this ordinance is not directly impacted by the development of
the hydrologic model, it is planned that other drainage and flood con-
trol regulations will be adopted to incorporate the capabilities of the
model. These ordinances will then constitute the written documents
describing the policies of the community related to storm water manage-

Storm Water Management Handbook

The storm water management handbook was developed to provide engi-
neering design guidance to:

local agencies responsible for implementing the Columbus Storm
Water Management Program
Engineers responsible for the design of storm water management
developers involved in site planning and design
Others involved in storm water management at various levels who
may find the handbook useful as a technical reference to define
and illustrate engineering design techniques.





Figure 4
Sediment and Erosion Control Ordinance Provisions

Section 1. Title
Section 2. Statement of Purpose
Section 3. Definitions
Section 4. Scope and Exclusions
Section 5. Application Procedure
Section 6. General Design Principles
Section 7. Implementation and Maintenance
Section 8. Inspection and Enforcement
Section 9. Administrative Appeal and
Judicial Review
Section 10. Penalties
Section 11. Validity and Liability
Section 12. Effective Date

Design procedures and criteria are presented for the estimation of storm
runoff; design of culverts, storm sewers, open channels, storm water
inlets, and detention storage facilities; suitable methods of flood
proofing; and allocation of drainage facility costs. Application of the
procedures and criteria should contribute toward the effective and
economical solution of local drainage problems in the region so that
development in one area will not have detrimental effects on another
area, either upstream or downstream. Figure 5 shows the major areas
covered in the handbook.

Throughout the handbook, areas where the hydrologic model should be
used are identified. Examples include the design of storage facilities
and closed conduits where routing flows and calculating flood frequencies
at several points in the drainage system are an essential part of the
engineering design. Thus, the availability of a hydrologic model en-
hances and expands the scope and accuracy of standard engineering designs
and allows for the evaluation of complex designs which are necessary in
order to solve many urban drainage problems. This allows the SWMP to
have a much greater impact on storm water management than would be
possible without the use of a model.

Urban Flood Simulation Model

Phase III of the SWMP concentrated on the development of the hydro-
logic simulation model. Other publications discuss the details of the
model which will not be repeated here (Lumb and James, 1976, Debo and
Ulrich, 1977). Figure 6 shows the essential steps in the development of
the hydrologic model. Figure 7 is a schematic of the economic model
which is used with the hydrologic model. What is important for this
discussion is how this model becomes the focus for all of the elements


Figure 5

Storm Water Management Handbook

Chapter 1. Hydrologic Design
Discussion of the Rational Method
Application of the Rational Method

Chapter 2. Determination of Culvert Sizes
Culvert Hydraulics
Drainage Inlets
Design of Culverts and Inlets

Chapter 3. Closed Conduit System Design
Design Procedures
Hydraulic Design

Chapter 4. Open Channel
Basic Design Methods
Rectangular, Triangular,and Trapezoidal
Channel Design
Grassed Channel Design
Erosion Control

Chapter 5. Storm Water Inlets
Types of Inlets
Design of Curb Opening Inlets
Design of Grate Inlets
Design of Combination Inlets
Inlet Location and Spacing

Chapter 6. Storm Water Detention Storage
Types of Storage Facilities
Downstream Storage
Upstream Storage
Storage Facility

Chapter 7. Flood Proofing
Types of Flood Proofing
Engineering Aspects
Flood Proofing Operations

Chapter 8. Cost Allocation of Drainage Improvements
On-Site Improvements
Off-Site Improvements
Combined Facilities


Figure 6






Source: Lumb and James, 1976


Figure 7



of the SWMP. The first two phases of the program provide the data base
necessary to calibrate and verify the model for the Columbus area.
Phase III will help prepare the local engineers to use the model by in-
cluding workshops and training programs.

The hydrologic simulation model is a complex engineering tool with
which the local engineer must become familiar. There is always some
initial resistance to the acceptance of new methods and procedures which
can limit their impact and possibly even their use. Once familiarity is
gained, using the model will not be much more difficult than the methods
presently being used in the Columbus area. The user's manual provides
the bridge between the present methods and procedures and the acceptance
of the model. Design and evaluation areas are identified where the
model can be used to augment and/or replace other design methods in order
to obtain more accurate results and broaden the scope of the analysis.
In areas where the model's use is not necessary standard procedures are

Although still in the final phases of calibration and verification,
preliminary model output is available to demonstrate the type of infor-
mation that can be obtained from model simulations.

Hydrology Model The hydrology model can be used to analyze and
calculate several characteristics of flooding in channels and storage
facilities (e.g., maximum flood levels and peak flows at selected points
in the drainage system, inflow-outflow data for storage facilities, flow
velocities). However, what is usually of most interest for storm water
management studies is flow-frequency data. Figures 8 and 9 illustrate
the type of flow-frequency data which are calculated by the model. These
data give the simulated flows and stages for given return periods which
can be directly used for drainage facility design. Also, different
drainage facility designs can be simulated by the model and the effects
will be seen by comparing the changes in flow-frequency data.

Economic Model The economic model analyzes the costs and benefits
(flood damage reduction) associated with different flood mitigation
measures. Figure 10 shows the type of data available from the model.
For each land use parcel (defined as an area of uniform land use) and
flood return period, the stage and total flood damages are calculated.
A damage-frequency curve can then be established from the damages calcu-
lated for a series of return periods. The area under the damage-
frequency curve is equal to the average annual damages given in Figure
10. The base average annual damages are calculated using existing con-
ditions where no flood mitigation measures are considered. The gross
benefits are equal to the base average annual damages minus the average
annual damages after implementing some flood mitigation measure (base
damages minus residual flooding damages). The final column in Figure 10
gives the cost for the flood mitigation measure being used.

The above five elements complete the development phase of the
Columbus SWMP. The task now is to implement the program in a systematic
and efficient manner. Three small studies are being undertaken as an
initial part of the implementation phase.


Figure 8

Peak Flow Frequency Table

Flood Frequency Analysis for Segment 4

UROS Test Run

Computed Flow Stage Probability Return Period

205. 6.0 0.005 200.
186. 5.7 0.010 100.
166. 5.4 0.020 50.
146. 5.1 0.040 25.
119. 4.6 0.100 10.
98. 4.2 0.200 5.
66. 3.5 0.500 2.

Drainage Problem Categorization Study

In the past, drainage problems were undertaken using a crisis
criteria. Those drainage problems which affected vocal citizens or
politically active groups got priority action. There was no systematic
criteria used to evaluate all problems and give priority rating to the
most critical. Sensing the need to establish some priorities for appli-
cation of the SWMP, a drainage problem categorization study was under-
taken. This study involves several major tasks:

(1) Develop standards and criteria for identifying and categorizing
the types and severity of drainage and flooding problems in the
Columbus area.
(2) Develop a procedure to integrate into the methodology, input
from the Department of Community Development, Department of
Engineering, City Managers Office, elected politicians, local
professionals, professional organizations, and concerned
citizens. The goal of this task is to involve active partici-
pation by individuals concerned with storm water management in
(3) Prioritize and rank all drainage problems in the Columbus area
for funding purposes.

The results of the Drainage Problem Categorization Study will enable
the City of Columbus to allocate its limited resources to those areas
where the need is the greatest. The results will also indicate where
the most severe problems are and the spatial interrelationships between
these problems. Thus, small watersheds with major drainage problems
will be identified for analysis by the hydrologic model.

Interdepartment Coordination Study

It has been Hydrocomp's experience in the development and implemen-
tation of storm water management programs that interdepartment coordi-
nation problems can severely limit the impact of the program. In some
areas the engineering and public works departments become quite active


Figure 9


Flood Frequency Plot for Segment 4

UROS Test Run

0 = Annual peaks simulated this run
X = Peaks computed by frequency distribution
Ordinate = Logarithmic scale
Abscissa = Normal (Gaussian) probability scale

Flow (cfs)

I I 1 1 I I I 1 1 1 I I I
I1 I I I I I I I0 I I I
I I I I I I I I 1 I I
100-..------..---- --....---------......................................---....................
I I I I I I I I I I 1 1 1


50 ... ... ... ... ... .. ... ... ... ... .. ... ... ... ... .. ... ... ... ... ... ........... ......
II I I I I I I I I I 1
I I I I 1 I I I I I
I I I I 1 I I I 1 I I I
I I I I 1 I 1 1 1 I I 1
I I I I I I I I 01 I I I I
I I I I I 1 1 1 1 1 I 1 1
I I I I I I I I 0000 1 I I I I
I I I I I I I 0010 I I I I I
I I I II I 1 00 I I I I I I
I I I I I I 1000 I I I I I I
I I I I I I 00X I I I i I I
I I I I I 00 I I I I I I00
1 I I I I 100 1 I I I I I I
I I I I I 0010 I I I I I I I
I I I I I 00 I I I 1 1 I I I
I I I I I 00 I I I I I I I I
I I I I X 0 I I I I I I I I
I I I I 10 I I I I I I I I'
I I I I 0 I I I I I 1 I 1
I I X I 0 I I I I I I I I I
1.001 1.31.01 1.--------------------------- 1.11 1.43 2.0 3.33 10.0 33.3 100 3331000
1.001 1.003 1.01 1.03 1.11 1.43 2.0 3.33 10.0 33.3 100 333 1000

Return Period (Years)


Figure 10

(all values in dollars)

Parcel Land Use

(Acres) Flood Damages
Return Period
100 50 25 15 10

Average Average
Annual Annual Gross Annual
Damags damages Benefits Costs
(X103) (X103) (X103) (X10')

5 2

3 Single-Family
4 Mobile Homes
5 Apartments
6 Mobile Homes

3 Single-Family
4 Mobile Homes
5 Apartments
6 Mobile Homes

Existing Conditions No Flood Mitigation Measures Used
83 10.3 9.3 7.7 6.7 5.9 4.5 2.6 2.5
53 85.1 79.6 70.5 63.6 54.5 38.4 14.2 20.7
103 60.3 53.6 42.7 34.6 31.0 24.7 15.2 14.3
150 198.2 179.4 148.7 125.5 100.9 68.2 23.5 38.8 -
353.9 321.9 269.6 230.4 192.3 .135.8 55.5 76.3 0

Channelize Segment 80

0 0

4.9 4.2 3.6 3.1 2.8 1.4 0 .8 2.5 1.7
43.1 34.9 26.7 20.5 15.6 8.4 1.1 5.4 20.7 15.3
26.5 23.3 20.1 17.8 15.7 9.8 1.3 5.0 14.3 9.3
76.7 61.7 46.5 35.2 26.1 12.1 1.6 8.7 38.8 30.1 -
152.1 124.1 96.9 76.6 60.2 31.7 4.0 19.9 76.3 56.4 30


in the program but lack of participation by the planning department
limits the benefits realized. In other areas the opposite has been

In anticipation of these potential problems an Interdepartment
Coordination Study has been included in the Columbus SWMP. This study
will include:

(1) A study of the existing work loads and functions of all de-
partments whose work relates to drainage and flooding problems.
(2) From the experience of storm water management programs in other
cities and counties, their implementation procedures, staff and
budget requirements, and interdepartment coordination procedures
will be documented.
(3) Conduct personal interviews with personnel from the city de-
partments involved, city manager, city council members, and
representatives from professional and citizen associations in
the Columbus area to determine their opinions and ideas on how
best to mobilize the resources within the City to insure the
maximum use and benefits from the SWMP and the hydrologic model.
(4) Using the information from Tasks 1-3, develop procedures and
recommendations aimed at efficiently coordinating the imple-
mentation of the SWMP and the use of the hydrologic model.

Interdepartment coordination will be a key element in the success of
the Columbus SWMP. In particular, if the use of the hydrologic model is
to reach its potential in helping the City to analyze and control
drainage and flooding problems, all aspects of the local engineering and
planning community must become involved in its use. The results of this
study will provide the procedures necessary to insure this coordination.

Pilot Basin Study

To complete the first year of the implementation phase of the
Columbus SWMP, a pilot basin study will be done. This study will demon-
strate the use of the hydrologic model on a small watershed which is
experiencing drainage problems. Based on the results of the drainage
problem categorization study, a small watershed (2-4 square miles) will
be selected for analysis. The hydrologic model will be used to evaluate
the hydrologic and economic problems existing within the area and the
effect of constructing and/or implementing different flood mitigation

The results of the study will be a drainage plan and cost estimate
for the pilot basin. This study will be used as the prototype for
future drainage studies in the Columbus area. It is anticipated by the
Department of Community Development that the pilot study will demon-
strate to the citizens and professional community in Columbus that the
many years of time and effort devoted to the SWMP have been beneficial
in the struggle to deal with urban drainage and flooding problems in



Columbus, Georgia is spending five years and over $200,000 to develop
a comprehensive storm water management program. At the heart of this
program is a hydrologic model which represents the "state of the art" in
flood and drainage analysis and evaluation. This program will not solve
all of the present and future drainage and flooding problems in Columbus,
but will provide the framework needed to deal with these problems.


1. Debo, Thomas N. and Bruno 0. Ulrich, "Storm Water Management Program
is Model for Others," PUBLIC WORKS, July 1977, pp. 60-62.

2. Lumb, Alan M. and L. Douglas James, "Runoff Files for Flood Hydro-
October 1976, pp. 1515-1531.


By Harry C. Torno,1 M. ASCE


Modeling in EPA (and its predecessor organizations) goes back a
number of years. The first extensive practical uses were probably
Streeter-Phelps model applications as tools in determining the impact
on receiving streams of treatment plant discharges. Since then, many
factors have caused modeling programs to expand rapidly. First, of
course, have been the recent advances in the capabilities of digital
computers, and the associated increases in user skills. Second, has
been the increasing acknowledgement of the major influence of diffuse
(non-point) sources on water quality. Third, is the recognition that
traditional, steady-state analyses are not adequate to predict water
quality over time. Fourth, there is the ever-increasing array of
pollutants of concern, and the complexity of the interactions of these
pollutants with each other and with the environment. Finally, there
is the recognition that we cannot simply set uniform discharge criteria
and expect improved water quality. In addition, there wdre sections
of PL 92-500 which required the development and application of point
and non-point loading models and in-stream water quality models in
order to make appropriate assessments. The most notable of these were
sections 303(e), which required that means be developed to allocate
loadings in river basins, and 208, which mandated areawide wastewater
management studies.

The results of a recent study, conducted by Hydrocomp, Inc., for
the Office of Water Research and Technology (OWRT), U.S. Department of
the Interior (1), graphically demonstrate how model usage has expanded.

In this study, 1716 questionnaires were sent to urban planning and
public works agencies with a jurisdictional population of 50,000 or
more, including all 208 agencies. Of the 349 respondents, 167 (48%)
reported using models in 220 separate applications. Of these, 77%
were planning agencies, and 23% were public works agencies.

Respondents were asked to rate models with regard to their useful-
ness. Virtually all found them useful, and 50% found them more useful
than alternative methods. 52% reported that the modeling analyses had
an impact on the plan or policy which was ultimately adopted, and of
this group, 72% reported that the impacts were critical or significant.

1Staff Engineer, United States Environmental Protection Agency (RD-682)
Washington, D.C. 20460


The model uses reported by respondents are interesting.

Model Use % Reporting

Water Quality 40%

Storm Drainage 27%

Water Supply 22%

Flood Control 20%

Other 3%

HYDROCOMP concluded that the predominance of water quality modeling
applications reflected attempts by users to substitute modeling results
for data (which was generally unavailable).


The last five years have witnessed a virtual explosion in the
number and variety of planning and design applications of computer-based
mathematical models in the U.S. and Canada, and, to a lesser degree,
elsewhere. The vast majority of the 208 agencies (88% of the respond-
ents in the OWRT study previously mentioned) use models in some form,
in spite of the fact that early EPA guidance (2) discouraged data
collection and modeling. Few, if any, major urban drainage projects,
particularly where analyses of existing systems must be performed,
are now undertaken without some sort of model study, and frequently
these studies are very large. The following examples will demonstrate
the variety and complexity of urban drainage problems to which models
have been applied:

1. Chicago The Tunnel and Reservoir Plan (TARP), now under
construction, is a $2.8 billion project to control combined sewer
overflows and to alleviate local flooding due to inadequate sewer
capacity. In essence, Chicago's existing combined sewer overflows
will be intercepted with surface structures and drop shafts and
led to large tunnels which will temporarily store a portion
of the overflows and carry larger overflows to large reservoirs.
When rainfall stops, stored combined sewage will be pumped out
and routed to treatment plants. Computer simulation models were
developed by City engineers and used for the determination of
system component sizes, waterway improvements and waterway quality
for each plan alternative. The EPA Stormwater Management Model
(SWMM) (3) was used to supplement and compare results obtained
from the City's models.

2. San Francisco The City of San Francisco is implementing what
is perhaps the most comprehensive and thorough master plan for
the control of combined sewer overflows. The basic concept is to
use a sophisticated system of outfall consolidation structures
plus storage basins to store wet weather flows and to regulate


the rate at which combined wastewaters enter a large storage-
transport system interconnecting wet and dry weather treatment
facilities. An extensive monitoring and data collection program
has collected rainfall, runoff and quality data for over ten
years, and is developing a program for real-time automatic con-
trol of the system. Computer models were extensively used in the
formulation of the plan, and continue to be used as the plan is
revised. STORM (4), a model now being distributed by the
Hydrologic Engineering Center, iU.S. Army Corps of Engineers, was
originally developed for San Francisco's use in the preliminary
planning phase. A revised version of SWMM, which includes the
capability of modeling flow in surcharged systems, was also
developed for San Francisco, though it is now being distributed
by EPA.
On a larger scale, the Association of Bay Area Governments has
sponsored the application of a Macroscopic Planning Model (MAC)
and SWMM in a regional surface runoff modeling program (5) in the
San Francisco Bay Area. This work is part of the area's ongoing
208 planning effort to control and abate point and non-point
waste sources.
3. Washington, D.C. The Metropolitan Washington Council of
Governments (MWCOG) has developed the most comprehensive water
resources planning model now in use. It links component computer
models which test alternative future community development
patterns by small area, estimate water demands by usage cate-
gories, calculate sewage flows based on water demands and add
infiltration/inflow, simulate stormwater runoff, test application
of alternative waste treatment management systems, and simulate
the quality response of the region's major water body (Figure 1).
This effort has been well documented in two EPA Reports (6,7),
which describe the model and its components, and provide program
documentation for users of the model.

These are but a few examples. It is of particular interest that
extensive modeling work is now being done for facility planning and
design under EPA's Construction Grant (201) program, and that in some
cases, such as San Francisco, the hydraulic complexity of the facilities
is such that thorough analyses are possible only if models are
The situation is much the same in Canada. Figure 2 indicates some
typical projects, involving the use of models, that have been completed
in Canada.



Figure 1. MWCOG Framework Water Resources Planning Model



(4500 acr


(a. 200
(b. 2800

Port Credit

St. Catherii



Toronto Int

(4500 acr


Transport Ca



Master Drainage SWMMS*
e combined) Study, Relief

a) Retention/Detention ILLUDAS**
b) Airport Storm Water SWMM/STORM

acre) a) Relief Study SWMMS/STORM
acre) b) Combined Sewer Storage

Outfalls, Relief

nes Assess Combined Flows SWMM/STORM

Assess Combined Systems, DORSCH HVM***
Provide Relief

Assess Combined Systems, DORSCH HVM
Provide Relief

ernational a) Assess Environmental SWMM/STORM
b) Design Relief Sewer SWMMS

Master Drainage Plan SWMM

a) Combined Sewer Relief SWMMS
b) Airport Storm Water
Management SWMM/STORM

anada Storm Water Management SWMM,STORM,IL

SWMMS = SWMM with Surcharged Flow Routines
** ILLUDAS = Illinois Urban Drainage Area Simulator
*** DORSCH-HVM = Hydrograph-Volume Method

Figure 2. CANADIAN MODEL APPLICATIONS (from a paper by A. R. Perks,
presented at the SWMM Users Group Meeting, Gainesville,
Florida, 4-5 April, 1977)



One Canadian activity bears special mention. Environment Canada
and the Ontario Ministry of the Environment, in a joint project of the
Urban Drainage Subcommittee of the Canada-Ontario Agreement on Great
Lakes Water Quality, are developing an Urban Drainage Policy Document
for the Province of Ontario. This pioneering effort, which includes
guidance on the use of models in planning and design, is nearing
completion and should provide a firm base for urban drainage policy

The number of models available to the potential user runs into the
hundreds. Very few of them, however, receive wide use. Hydrocomp (1)
cited nine models which predominated in urban wastewater management
planning in their survey, and their findings were corroborated in a
study conducted by EPA's Water Planning Division of State and Areawide
208 agencies. Figure 3 is a list of the most frequently used models.
Interestingly, all but one (HSP) are in the public domain, and
available "free" to users. One might be tempted to say that the
government has exerted undue influence. However, the fact remains that
the primary reasons for their continued use are that they have
demonstrated their usefulness, are well-documented and, in most cases,
are being modified or corrected as necessary on a continuing basis.


In spite of the wide use of models, and a general conviction that
they are useful tools, some significant problems exist. The VERTEX
Corporation, in a recent report to EPA (8) on an analysis of planning
for advanced waste treatment (AWT), noted that even sophisticated,
well-documented models give questionable answers. In a study of the
San Jose-Santa Clara AWT facility, a model of San Francisco Bay was used
which showed AWT was necessary. A later version of the same model
indicated that AWT was not necessary. In both cases, adequate
measurements of the Bay and the marshes near the south end of the Bay
were not taken, and there was no way to verify the assumptions made by
the model developers. VERTEX reported similar problems on other
studies. Users of EPA's Stormwater Management Model and other surface
runoff models have had the same sorts of difficulty reproducing observed
water quality data. We really know very little about many water quality
processes and our models reflect this lack of knowledge.This is perhaps
our most pressing problem in the modeling area. Other significant
problems which have been noted include:

1. Models are frequently selected before the problem is adequately
defined. As a result, the incorrect model is used.

2. Model complexity often exceeds the users' ability to master
such tools. Related to this is a tendency to view models as a "black
box", and to place undue reliance on modeling .results. There are
modeling failures blamed on poor models which are more properly
attributed to improper use.

3. There is a tendency to use a single "representative" criterion
having little or no relationship to actual occurrences (such as a
"design storm", 7-day, 10-year low flow, etc.), in defining system


STORM Storage, Treatment, Overflow
Runoff Model

SWMM Stormwater Management Model

HSP Hydrocomp Simulation Program

ILLUDAS Illinois Urban Drainage Area

TR-20 Project Formulation Hydrology

QUAL (I,II,III) Instream Water Quality

RECEIV (RECEIVE Receiving Water Module of

U.S. Army Corps
Of Engineers


Hydrocomp, Inc.

Illinois State
Water Survey

U.S. Soil
Conservation Service

Texas Water Development
Board et al.

EPA et al.

Figure 3. Models most frequently used in Urban Wastewater Management


I~ __ ~__*_______*______~____~_~


performance, as opposed to using actual long-term data as a reference,
to developing frequency criteria for levels of protection, and to
testing a range of conditions in arriving at the final plan or design.


Models play an important part in EPA planning programs, and will
continue to do so. There is ample evidence that consulting engineers
and planners consider them an important part of their arsenal of tools.
Consider the following list of advantages of model use:

1. They provide the ability to test alternative futures.

2. They provide better understanding of system performance.

3. They help to clarify the relationships between land-use
projections, mitigative actions and costs.

4. They provide a means for conjunctive evaluation of flood con-
trol and wastewater management alternatives.

5. They allow easy updating of projects if planning assumptions
are revised.

6. They allow joint consideration of water quantity and quality.

7. They aid in identifying deficiencies in existing facilities
and/or management programs.

It should be apparent that models are planning tools with
formidable power. At the same time, their application requires con-
siderable skill and judgement if they are to be correctly used,
* and if their results are to be correctly interpreted.


1. HYDROCOMP, INC., "Evaluating the Use of Models in Urban Water
Management," Simulation Network Newsletter, Vol. 9, No. 5, Palo
Alto, California, September-October 1977.

2. L, S. Environmental Protection Agency, "Water Quality Analysis and
Modeling, Waste Load Estimation, and Data Collection in Designated
Areas," Program Guidance Memorandum AM-8, Water Planning Division,
Washington, D.C., May 1976.

3. Huber, W.C., et al., "Storm Water Management Model User's Manual,
Version II," EPA-670/2-75-017, Environmental Protection Agency,
Cincinnati, Ohio, March 1975.

4. Hydrologic Engineering Center, Corps of Engineers, "Storage,
Treatment, Overflow, Runoff Model (STORM), Users' Manual," Computer
Program 723-S8-L7520, 609 2nd Street, Davis, California 95616,
170 pp., July 1976.


5. Association of Bay Area Governments, "SURFACE RUNOFF MANAGEMENT
REPORT NO. 2, Berkeley, California 94705, February 28, 1977.

6. Spooner, C.S., Promise, J., and Graham, P.H., "A DEMONSTRATION OF
mental Protection Agency, Washington, D.C., April 1978.

7. U.S. Environmental Protection Agency, "A DEMONSTRATION OF AREAWIDE
Washington, D.C., April 1978.

July 1977.


I *1

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