Importance of the Assumption of Independence or Dependence among Multiple Flood Sources.

At any location, flood magnitudes can result from multiple causes (e.g., riverine flooding, tidal surges, snowmelt runoff, pluvial flooding, etc.) that occur simultaneously or independently. Analyzing flood data that resulted from simultaneous occurrences but treating the individual magnitudes as independent factors can lead to inaccurate estimates of flood depths, probability, and risk. While the assumption of independence is computationally convenient, it can be hydrologically incorrect. A method of joint flood frequency analysis that is based on copulas is proposed to address cases where the assumption of independence does not apply. For example, flooding at a coastal site can be the result of high riverine flows that simultaneously happen with high storm surges. The individual flood records would not adequately describe flood depths where both flood types occurred. The proposed method can be applied with two or more causes of flooding. The method is demonstrated using data from a site in coastal Florida, with the results showing that differences in flood estimates can be significant when independence is assumed for cases when a dependency exists. [ABSTRACT FROM AUTHOR]