DIFFERENCE EQUATION-BASED ESTUARINE FLUSHING MODEL APPLICATION TO US GULF-OF-MEXICO ESTUARIES

Estuarine flushing is conceptually simple. However, the use of simple ''ratio type'' estuarine flushing estimators generates estimates that are often inadequate and unverifiable. Obviously, estuarine flushing e stimators that address more of the complexities of the flushing proces ses are needed. Difference equations lend themselves to modeling compl ex systems by virtue of their mathematical stability and ability to be linked into long complex inter-connecting series. With the above in m ind, a simple to use model based on difference equations was developed for the explicit purpose of generating more realistic estuarine flush ing estimates. The model and its application to a series of US Gulf of Mexico estuaries are presented in this paper. Estuarine oceanographer s will recognize the relationships driving the model. However, an in-d epth knowledge of estuarine oceanography is not required to understand or operate the model. Average estuary volume and average intertidal v olume are used to drive the model as it tracks freshwater retention an d flushing via tidal cycles. The configuration of the model accommodat es vertically homogeneous and stratified salinity/flushing regimes. Ap plication of the model to a series of U.S. Gulf of Mexico estuaries yi elds a 79% agreement between the model's freshwater input estimates an d empirically derived freshwater input estimates. Linear regression an alysis of the freshwater estimates of the model versus the empirically derived freshwater estimates, yields a r(2) of 0.98 for the estuaries modeled. The empirically derived freshwater estimates were used to ap proximate the salt-content of the estuaries as a check of their approp riateness for use in verifying the model. Comparison of the ''empirica lly derived freshwater based salt-content approximations'' versus ''sa lt-content approximations based on the observed salinities of the estu aries'' yields a 74% agreement, while linear regression yields a r(2) of 0.81 for the estuaries modeled. This generic model can be applied t o estuaries with known low tide estuary volumes, intertidal volumes, a nd salinity characterizations. Electronic copies of the programming of the model are available from the author.