Geoscience Reference
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between altitude and rainfall is linear, which is not
always the case and warrants exploration before
using this technique.
An additional piece of information that can be
gained from interpolated rainfall surfaces is the
likely rainfall at a particular point within the catch-
ment. This may be more useful information than
total rainfall over an area, particularly when needed
for numerical simulation of hydrological processes.
The difficulty in moving from the point measure-
ment to a spatially distributed average is a prime
example of the problem of scale that besets
hydrology. The scale of measurement (i.e. the rain
gauge surface area) is far smaller than the catchment
area that is frequently our concern. Is it feasible
to simply scale up our measurement from point
sources to the overall catchment? Or should there
be some form of scaling factor to acknowledge the
large discrepancy? There is no easy answer to these
questions and they are the type of problem that
research in hydrology will be investigating in the
twenty-first century.
Isohyetal and other smoothed
surface techniques
Where there is a large number of gauges within a
catchment the most obvious weighting to apply on
a mean is based on measured rainfall distribution
rather than on surrogate measures as described
above. In this case a map of the catchment rainfall
distribution can be drawn by interpolating between
the rainfall values, creating a smoothed rainfall
surface. The traditional isohyetal method involved
drawing isohyets (lines of equal rainfall) on the map
and calculating the area between each isohyet. The
spatial average could then be calculated by equation
2.3
n
= = 1
ra
A
(2.3)
ii
R
RAINFALL INTENSITY AND STORM
DURATION
i
where a i is the area between each isohyet and r i is
the average rainfall between the isohyets. This
technique is analogous to Figure 2.13, except in this
case the contours will be of rainfall rather than
elevation.
With the advent of GIS the interpolating and
drawing of isohyets can be done relatively easily,
although there are several different ways of carrying
out the interpolation. The interpolation subdivides
the catchment into small grid cells and then assigns
a rainfall value for each grid cell (this is the
smoothed rainfall surface). The simplest method of
interpolation is to use a nearest neighbour analysis,
where the assigned rainfall value for a grid square
is proportional to the nearest rain gauges. A more
complicated technique is to use kriging , where the
interpolated value for each cell is derived with
knowledge on how closely related the nearby gauges
are to each other in terms of their co-variance. A
fuller explanation of these techniques is provided by
Bailey and Gatrell (1995).
Water depth is not the only rainfall measure of
interest in hydrology; also of importance is the rain-
fall intensity and storm duration . These are
simple to obtain from an analysis of rainfall records
using frequency analysis. The rainfall needs to be
recorded at a short time interval (i.e. an hour or
less) to provide meaningful data.
Figure 2.15 shows the rainfall intensity for a rain
gauge at Bradwell-on-Sea, Essex, UK. It is evident
from the diagram that the majority of rain falls
at very low intensity: 0.4 mm per hour is considered
as light rain. This may be misleading as the rain
gauge recorded rainfall every hour and the small
amount of rain may have fallen during a shorter
period than an hour i.e. a higher intensity but last-
ing for less than an hour. During the period of
measurement there were recorded rainfall intensities
greater than 4.4 mm/hr (maximum 6.8 mm/hr) but
they were so few as to not show up on the histogram
scale used in Figure 2.15. This may be a reflection
of only two years of records being analysed, which
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