Laserfiche WebLink
<br />explaining variation in the dependent variable, percent damage. The <br /> <br />advantages of this approach are that it is easy and quick; water height <br /> <br />has always been believed to have the most influence on physical damage; <br /> <br /> <br />and the effect of outliers can still be limited by setting reasonable <br /> <br /> <br />limits on the values to be used in the calculations. <br /> <br /> <br />Regression analysis can measure the effects of several variables on <br /> <br />percent damage. The strength of anyone variable can be estimated along <br /> <br />with the strength of the entire model in explaining the variance of <br /> <br />percent damage. Regression analysis with depth-damage data is difficult <br /> <br />because of the problems in obtaining good measurements of all the <br /> <br />important variables that influence percent damage. <br /> <br />STEP SEVEN: CALCUIATE DAHAGE-REQUENCY RElATIONSHIPS <br />Definition: The damage-frequency relationship is a simple <br />relationship that is represented by the probability that could be <br />associated with any level of flood damage. This relationship is derived <br />from stage-damage, stage-discharge, and discharge-frequency relationships. <br /> <br />Use: The damage-frequency relationship is the last step in the <br /> <br />process before computing average annual damages. By applying a frequency <br /> <br />interval to each level, a weighted average for each of these events can be <br /> <br />computed. Damage-frequency relationships are basically an interim step <br /> <br />used in computing average annual damages. However, the breakdown of <br /> <br />information by damage reach is particularly useful for identifying the <br />areas of most severe economic damage. <br /> <br />Categories: Damage-frequency relationships are aggregated for <br /> <br />display by damage category and reach. Major land use categories can <br /> <br />V-46 <br />