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<br />001204 <br /> <br />7 <br /> <br />With the availability of better data and improved simulation <br />algorithms, the relative capabilities of response prediction may change. <br />Intuitively, the detailed Physically-based models should be able to <br />better simulate the runoff response if adequate verification and <br />calibration data are available. The advantage of this improved pre-, <br />dictive capability is taken for granted. It is believed that drainage <br />facility analysis improves as the accuracy of response prediction <br />increases. Just how important is prediction accuracy? <br />The writers answer this question by examining the economic <br />sensitivity of poor discharge prediction. The examination revealed that <br />the cost of urban drainage and flood control facilities generally <br />follows the "two-thirds power rule", and is not very sensitive to poor <br />predictions of discharge. Project analyses such as Benefit Cost <br />analysis and Minimum Cost analysis, on the other hand, are quite <br />sensitive to errors in discharge prediction. This sensitivity was <br />determined by estimating project benefits using damage frequency curves <br />for various distributions of flood discharge. <br />The writers note, however, that the sensitivity of these project <br />analysis techniques may not be as important as one might think. If a <br />community uses a single rainfall-runoff prediction tool for evaluating' <br />all basins within that community, the analyses for each project will <br />have a consistent basis, That is, the predicted benefit-cost ratio for <br />each project may not be accurate, but it will precisely define the <br />relative economic merits of each project. In the urban drainage and <br />flood control area, where the benefit-cost ratios for politically <br />justified projects are not always greater than one, this relative con- <br />sistency can be more important than truly accurate benefit-cost ratios. <br /> <br />,/ <br />