BOARD02064

• Board Meeting Date: 3/21/2002
• Description: OWC Section - Drought and Water Supply Assessment
• Board Meetings - Doc Type: Memo

Section 4
Project Approach (RFP Section 4.6)

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Summarizing this information on a regional scale will then provide a "picture" of the drought
resistance capabilities for individual water users and opportunities for reallocation throughout
the State.

Additional statistical analysis that will be performed will include Factor and! or Cluster
Analysis [in concert with correlation analysis] to identify homogeneous segments, subject to
response size. Factor analysis is one of several multivariate -statistical tools that attempt to
identify underlying patterns in the data -
homogeneous' relationships. : Factor analysis
isolates variables, or factors, that explain the
,patte~n of correlations withiri a set of observed
variables. Factor analysis is often used in data
reduction to identify a small number of factors that
explain most of the, variance observed in a much
largljr number of manifest variables. Factor
analysis can also be used to generate hypotheses
regarding causal mechanisms or'to, sC,reen .variables
for' subsequent analysis (for example, to identify
collinearity prior to performing a linear regression
analysis). '

It is important to frame the report within the
understanding of the term "drought", since its
meaning can be varied to different water user~ and providers. To some it may simply be a
period when stream flows are significantly belotv average, or when an individual water .right is
not capable of meeting a specific demand. To o1ihers it can be much more complex, particularly
where demands vary seasonally and water supplies are derived from a combination of surface
and ground water diversions, combined with sforage, and in many cases transbasin diversions.
"Drought protection" can also have different meanings, where some p~oviders~ ~y consi~er
drought protectiol;l. to be sufficient if their system is projected to proVlde suffiCIent supplies
measured against some baseline condition (such as the 1950's drought or the 1977 drought),

A non-technical analogy for Factor
[analysis:
A mother sees various bumps and
shapes under a blanket at the bottom
of a bed. When one shape moves
toward the top of the bed, allihe other
bumps and shapes move toward the
top also, so the mother concludes that
what is under fhablanket is a single
thing, most likely her child, Similarly,
factor analysis takes as input a
number of measures and tests,
analogous to the bumps and shapes.
Those that move together are
considered a single thing, which it
labels a factor. That is, in factor
analysis the researcher is assuming
that there is a "child" out there in the
form of an underlying factor, and he or
she takes simultaneous movement
(correlation) as evidence of its
existence. If correlation is spurious for
some reason, this inference will be
mistaken, of course, so it is important
when conducting factor analysis that
possible variables that might
introduce spuriousness, such as
anteceding causes, be included in the
analysis.

Usillg the analytical techniques above, the team can
ti:anslate 'the data collec,ted ill this project into
information that can be used to identify the
pop\llation of water users and providers that
would benefit from the teclmical and financial
services offered by CWCB, in areas of wise water
use,' water conservation practices, and water
project identification' and development. In
addition, ,.opportunities will' be identified for
coo~dination among water users and providers,
thrdugh such means as interruptible supply
agreements, water 1:>anking, water conservation,
and! other measures identified during the course of
the ~tudy.

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Section 4, Page 22