measurement estimates the total rainfall over the area

The number of gages required depends on local

!

represented by that gage. For example, if the raingage

conditions. Areas of higher rainfall variability gener-

accurately measures rainfall at a point but that measurement

ally require higher numbers of gages to estimate rain-

is an inconsistent estimator of areal rainfall, the gage has

fall over a watershed adequately. Mountainous areas

little value. However, if the rain gage measurement

require more gages than flat lands. Areas subject to

consistently estimates areal rainfall, the measurements are

convective storms require more gages than areas

highly valuable, even if the point measurement is inaccurate.

subject to frontal type storms.

As long as any point measurement inaccuracies are

consistently biased in one direction, the forecasts can be

National Weather Service guidelines recommend a

!

quantitatively or qualitatively calibrated to account for the

minimum of three raingages and often use the follow-

bias.

ing relationship between the minimum number of

gages required (N) and the watershed area (A) in

(a) Number of gages. he number of raingages installed

square miles (Schaake 1980).

in a data collection system directly effects the quality of the

data and the performance of hydrologic forecast models. The

(4-1)

(*N *> 3)

density of required raingages is based on the ability to provide

an accurate estimate of the mean areal precipitation for the

Equation 4-1 is shown graphically in Figure 4-1 and illustrates

watershed. The minimum number is usually considered to be

how the minimum number of gages increases rapidly for areas

three gages. The maximum number is generally governed by

#129.5 sq km (50 sq miles).

the resources available and whether additional increases in flood

warning time and reliability can be realistically achieved by

increasing the gage density. Additional gages are often

implemented in stages as more is learned about the system.