WSP01635

• File Number: 8200.400
• Description: Colorado River Basin - Briefing Documents-History-Correspondence
• State: CO
• Basin: Colorado Mainstem
• Water Division: 5
• Date: 10/1/1961
• Author: CSU Civil Engineerin
• Title: Analysis of Precipitation Data in the Upper Colorado River Basin
• Water Supply Pro - Doc Type: Report/Study

000435

6

II. FREQUENCY ANALYSES

One of the objectives of the study was to
determine the frequency distribution of precipita-
tion during various periods of time. The results
of these frequency analyses are given in Figures
3 - 32 which are presented in this section. The
inclusive dates for which meteorological data were
used are presented in Figure 1.

In Figures 3 - 15 and Figures 19 - 30. the
frequency analyses are presented by giving the
mean, standard deviation, and coefficient of varia-
tion. As pointed out later in this report (see
especially section II B below) the precipitation data
are not normally distributed and usually are posi-
tively skewed. In spite of this fact, for convenience
the standard deviation is presented with the mean
to give an estimate of the probability of occurrence
of the event.

For normally distributed data the mean :t
one standard deviation should include about two-
thirds of the cases; the mean :t two standard
deviations should include about 95 per cent of all
the cases; and the mean :t three standard devia-
tions should include about 99 per cent of all the
cases. To illustrate, from Figure 3 we note that
the mean annual precipitation at Gunnison is 10.54
inches. with a standard deviation of 2. 21 inches.
Thus, approximately two-thirds of all years should
fall approximately within the limit of 10.54 :t. 2.21
inches. etc.

It should be emphasized that these frequen-
cies are approximate only, since most of the data
are positively skewed and do not follow a normal
distribution.

The coefficient of variation, defined as the
standard deviation divided by the mean, gives a
measure of the relative variability of the data.

A. ANNUAL PRECIPITATION

t. Observed Annual Precipitation

Figure 3 shows that marked differences in
annual precipitation occur at stations which are
relatively close together. For example. Silver-
ton, Colorado (elevation 9400 feet), has the highest
annual precipitation with 24.60 inches per year,
while Montrose (elevation 5830 feet). geographical-
ly nearby, but on the opposite side of a ridge of
high terrain. has a much lower value of 9.75 inches
per year. The coefficient of variation is higher for
stations in the southern part of the Upper Colorado
River Basin. The values vary from O. 3 for

stations in southern Colorado and Utah to a value
of about 0.2 for stations in northern Colorado and
Wyoming .

2. Number of Storms Occurring
During a Water Year

One storm period consists of a number of
G:onsecutive days with precipitation greater than a
trace in any 24 hour period.

Figure 4 shows that the variations in the
number of storms are similar to the variations in
mean annual precipitation. High-altitude stations
such as Silverton and Telluride receive more
storms during the year than nearby low-altitude
stations such as Delta and Grand Junction. A
greater number of storms per year occur at sta-
tions in the northern part of the basin such as
Kendall and Bedford than in southern stations such
as Durango and pagosa Springs.

3. Annual Precipitation Contributing to Runoff

a. Adjustin,g- Actual Precipitation Data To
IlPrecipitation Contributing To Runoff" Data -
Basically there is a very direct relationship bet-
ween precipitation and runoff. Large amounts of
precipitation are required to produce large amounts
of runoff. However. the range of errors sustained
in working with total known precipitation records
to derive co-related runoff indicates considerable
room for refinement. One very large source of
error comes from the assumption that one particu-
lar rain gage with a cross sectional catchment area
of less than one square foot can represent the true
measurement of precipitation for an area of
seveTIIlthousancrsqu<I!""Fmil~1:i .

A second cause for error is the wide varia-
tion in precipitation timing. One storm which
produces four inches of rain on one day can deliver
far more runoff than 40 storms on 40 different days
each producing. 10 inch.

With the advent of computer facilities it is
believed possible to reduce the second cause of
error by adjusting actual precipitation records to
give resultant values which are more directly re-
lated to runoff. Small storms which will contribute
little or no runoff can be eliminated from the ad-
justed precipitation record. A large part of the
rainfall from large storms returns to the atmos-
phere by evapotranspiration, and only the balance
moves to the streams as runoff.

The quantities to be deducted from individual
storm totals to account for evaporation losses