FLOOD00764

• County: Statewide
• Community: Nationwide
• Title: Use of Extreme Value Theory in Estimating Flood Peaks from Mixed Populations
• Date: 2/1/1980
• Prepared By: Utah State University Water Research Laboratory
• Floodplain - Doc Type: Educational/Technical/Reference Information

has two or possibly three nonhomogeneous
sources. The Oder River (Figure 25) has two
components, however the definition is not
sharp. The Vanerngota River (Figure 26) has
well defined components and the Neva River
(Figure 27) appears to be homogeneous. The
Assiniboine River (Figure 28) and the
Red River (Figure 29) have sharply defined
components.

The goodness-of-fit for the first ten
stations is excellent. The fit for the Red

Table 11. Computed flood flows Q(T) (in m3,s)
for selected return periods.

T in Years
No. 2 5 10 20 50 100
1 4754 6112 6961 7740 8699 9382
2 2347 2526 2617 2688 2760 2803
3 6153 7303 8015 8664 9455 10015
4 1699 2364 2796 3212 3779 4278
5 448 546 589 619 646 660
6 694 829 913 990 1084 1150
7 1351 1988 2407 2772 3192 3470
8 617 725 787 840 901 941
9 3290 3727 3976 4190 4433 4594
10 151 262 413 542 618 644
11 552 902 1174 1622 2546 2852

River is not as good although it does fit
well the Weibull method of observed flood
discharges. Perhaps the largest maximum
yearly flood is an outlier (see Figure 29) as
it is much larger than any other flood on
record. Alternatively, it might be the only
observation from a particular source popula-
t ion. It is impossible to achieve a good
est imate of the parameters of a populat ion
with only one observation.

Table 12. Goodness-af-fit statistics.

Mean of the Mean of the
Absolute Quadratic
Deviations Deviations
No. Hazen Chegodayev Weibull Hazen Chegodayev Weibull
1 1.9 2.2 2.9 6.3 7.9 11.0
2 1.4 1.4 0.9 2.7 2.7 1.0
3 3.0 3.0 3.3 10.6 11. 1 13.4
4 2.3 3.0 3.5 9.2 11. 0 22.0
5 0.9 0.9 0.9 1.2 1.2 1.2
6 3.4 3.5 3.6 16.1 16.0 16.0
7 3.4 3.0 3.9 18.8 20.5 31. 0
8 1.8 1.8 2.1 5.3 4.7 5.8
9 1.1 1.0 0.8 1.6 1.2 1.0
10 3.1 3.1 2.8 17.9 13.6 7.8
11 8.6 7.1 4.8 97.9 57.9 35.8

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