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<br /> '. <br /> Page 5 <br /> Empirical data from 30 customers show that the typical commercial property e <br /> has a greater area as well as a greater proportion of its area committed <br /> to impervious surfacing than residential lots. The siz~ of the water <br /> meter can be used as an indicator of the size and intensity of use of <br /> a non-residential property for the purposes of assigning storm drainage <br /> costs. On the average, a water meter of a given size serves a commercial pro- <br /> perty with five times the storm water runoff potential as the typical single <br /> fami ly property. Therefore, it is proposed that a commercial customer with a <br /> 5/8" water meter be assessed five times the flat residential rate developed <br /> above (5 X $2.41 = $12.05). Large non-residential properties would be charged <br /> in multiples of the $12.05 depending on the water meter diameter serving that <br /> property. The schedule of charges is shown above. Data to make this charge are <br /> available in the EWES billing file. <br /> A sample of thirteen customers was taken by city staff to test the fairness <br /> of the revised schedule of charges. If data were available for the 4800 <br /> commercial customers, it is generally conceded that impervious surfac~ is the <br /> industry standard for allocation of storm drainage cost responsibility. <br /> Monthly charges to the thirteen customers were plotted on two enclosed <br /> graphs. The horizontal axis shows the amount a customer would be charged IF <br /> we had the data available to calculate the bill based upon area. The <br /> first graph plots the charge on the vertical axis based upon the amount of <br /> fl ow through the water meter. The di stance from the II Li ne of best fi t" <br /> indicates the error in calculating that customer bill. ' The standard error e <br /> in this sample was $176 per month. The second graph plots the charge <br /> based on impervious surface. Within the sample, the standard error is <br /> $61 per month. The average deviation from the ideai monthly bill 'would <br /> be reduced by $ lIS/month by revising the approach for billing. The <br /> improvement is statistically significant and therefore, recommended by the <br /> staff. <br /> - <br />