WATER & SOIL - These are not the droids you are looking for.
WATER & SOIL - These are not the droids you are looking for.
WATER & SOIL - These are not the droids you are looking for.
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In <strong>the</strong> first test <strong>the</strong> GEV method was often affected in<br />
this manner, producing many curves that fitted <strong>the</strong> data<br />
very well but giving 100-year flood peak estimates that were<br />
<strong>not</strong> always sensible. For example, <strong>the</strong> trend in <strong>the</strong> lower<br />
half of <strong>the</strong> series would cause <strong>the</strong> GEV curve to flatten off<br />
at <strong>the</strong> top end, impþing that <strong>the</strong>re was a limit to flood<br />
peaks of about twice <strong>the</strong> mean annual flood. While <strong>the</strong>re<br />
may be an upper limit to flood magnitude, it is certainly<br />
more than <strong>the</strong> figure implied (see Tables 3.3 and 3.6).<br />
In comparison, <strong>the</strong> straight-line fits of <strong>the</strong> Gumbel and<br />
EVI methods were often a good approximation to <strong>the</strong> data<br />
and gave more sensible 100-year flood peak estimates.<br />
However, this better per<strong>for</strong>mance by <strong>the</strong> t$'o-pa¡ameter<br />
methods can be attributed to <strong>the</strong> small samples used<br />
(NERC 1975; pp. 159-60). The fact that <strong>the</strong> Gumbel<br />
method still per<strong>for</strong>med better than <strong>the</strong> GEV method in <strong>the</strong><br />
second test suggests that <strong>the</strong> samples in this test may also<br />
have been small. However, it is also likely that <strong>the</strong> leastsquÍues<br />
fitting technique of <strong>the</strong> Gumbel method influenced<br />
<strong>the</strong> evaluation test in <strong>the</strong> method's favour.<br />
The two-parameter log-Normal method also gave good<br />
approximations to <strong>the</strong> data at times, producing a reasonable<br />
proportion of good fits. However, <strong>the</strong> method assumes<br />
that <strong>the</strong>re is no skew in <strong>the</strong> logarithms of <strong>the</strong> series, an<br />
assumption which was r<strong>are</strong>ly true. Hence <strong>the</strong> method did<br />
<strong>not</strong> per<strong>for</strong>m as well as o<strong>the</strong>rs in <strong>the</strong> test, including its p<strong>are</strong>nt<br />
method, <strong>the</strong> three-parameter LP3.<br />
A.4.5 Gonclusions<br />
The evaluations in <strong>the</strong> two tests involved a good deal of<br />
subjective judgement, but this typifies <strong>the</strong> present situation,<br />
with <strong>the</strong> objective goodness-of-fit indices <strong>not</strong> providing rigorous<br />
enough criteria <strong>for</strong> discriminating between different<br />
frequency analysis methods.<br />
From <strong>the</strong> findings of <strong>the</strong> tests, <strong>the</strong> following conclusions<br />
were reached:<br />
(¡) <strong>the</strong> Jenkinson method was <strong>the</strong> superior method in both<br />
tests and should be used in flood frequency analysis,<br />
especially when <strong>the</strong> sample is small;<br />
(iÐ <strong>the</strong> Gumbel method improved in per<strong>for</strong>mance with increase<br />
in sample size, and should be a satisfactory alternative<br />
to <strong>the</strong> Jenkinson method on <strong>the</strong> larger sam-<br />
Ples;<br />
(ii¡) <strong>the</strong> GEV and LP3 methods were more flexible than <strong>the</strong><br />
two-parameter methods, with <strong>the</strong>ir frequency curves<br />
geneially following <strong>the</strong> trend in <strong>the</strong> data extremeiy<br />
well;<br />
(iv) on small samples, in particular, <strong>the</strong> straight-line fits<br />
from <strong>the</strong> two-parameter methods can give good approximations<br />
to <strong>the</strong> data and sometimes more sensible<br />
results than those obtained from <strong>the</strong>ir p<strong>are</strong>nt threeparameter<br />
methods;<br />
(v) on small samples <strong>the</strong> LP3 method appears to per<strong>for</strong>m<br />
better than <strong>the</strong> GEV method, being influenced less by<br />
<strong>the</strong> trend in <strong>the</strong> lower part of a series;<br />
(vi) on larger samples <strong>the</strong> GEV and LP3 methods can produce<br />
similar shaped curves and give a comparable per<strong>for</strong>mance.<br />
<strong>These</strong> conclusions apply <strong>for</strong> individual records and up to<br />
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9l