7910

• UCREFRP Catalog Number: 7910
• Author: Bovee, K. D. and R. T. Milhous.
• Title: Hydraulic Simulation In Instream Flow Studies
• USFW Year: 1978.
• USFW - Doc Type: Theory And Techniques, Instream Flow Information Paper No. 5.
• Copyright Material: NO

1 of flow, cover, bottom type, water movement, turbulence, etc) into things
he cannot see, namely, the attractiveness of those parameters from a
fish's viewpoint. Thus, a "mental model" of the stream reach has been
constructed, requiring certain data inputs (visual stimuli), data
manipulations (pretending one is a fish), and interpretations (whether
alternate stream flows would provide good habitat or not). Mental models
based upon an understanding of certain processes are very useful for
formulating a professional opinion when predicting the outcome of
alternative situations. They are not very useful for communicating flow
assessments from one person to another, particularly between individuals
of different disciplines. Nor are they very useful when extrapolated.
beyond the range of experience of the observer.
In order to increase its transferability and predictive ability, a
mental model may be expressed in written narrative form or in mathematical
terms. This process allows a large, complex system to be broken down into
a sequence of smaller, more predictable parts, which are then connected by
a train of logic.
The primary differences between the mathematical model and a word
model are that the complex. interactions and relationships have been
expressed as a variety of implicit or explicit functions, preferably
explicit, and the logic train is clearly stated and exposed for examin-
ation. If the logic of a model (i.e. , assumptions required to connect the
parts) does not-reflect the real world situation, it can be replaced by
logic that does, or at least with logic which is a=epted as approximating
the real world si tuati on.
The mathematical simulation model serves as the laboratory world in
which the scientist.can conduct experiments to test various hypotheses.
Once the model has been built and verified, an inexhaustible number of
management alternatives. can be simulated and the relative difference
between project impacts determined. There are several advantages to
conducting experiments in this way. For example, one might wish to
determine the change in depth and velocity of a river with changes in
discharge. These changes could be measured directly over many flows, and
an empirical relationship made for each variable. This process might take
as long as a year or two to complete, and there would still be some flows
which lie above- and- below the end points of the observations. These. same
parameters could be modeled in a much- shorter time period, and the results
extrapolated beyond the range of observation. Thus, modeling has the
advantages of time efficiency and extrapolative capability.
Perhaps a value or some relationship used in the model is not known
with any certainty, or perhaps a relationship is well documented, but its
importance to the system is uncertain. Various trials can be made with
the model, using different values for an uncertain parameter. If the
output of the model changes drastically, the uncertain perameter is
important to the system. If the uncertain parameter is not important to
the system, manipulation of that parameter will not greatly influence the
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