Selective mechanisms for benthic water flux generation in coastal waters.

摘要

Benthic water flux (qbf) is the rate of water flow across the bed of a water body, per unit area of bed. It is a component of the hydrologic cycle and a surface water--ground water interaction process. Benthic water flux is an important component of water, pollutant, and other constituent budgets. Several physical, chemical, and biological gradients drive qbf. This work has two objectives: (1) to develop analytical equations for qbf driven by: terrestrial hydraulic gradient (i), with Schwarz-Christoffel mapping and the Poisson integral formula for the half plane (compared with Bokuniewicz [1992]); pressure gradient forced by the ground water tidal prism (DeltaVˆgwtp), with a perturbation solution to a Darcy-based diffusion equation by Nielsen [1990] (compared with Li et al. [1999]); and pressure gradient forced by surface gravity waves, with extension of a boundary value solution by Reid and Kajiura [1957]; and (2) to use these equations to characterize qbf in four case studies: the Indian River Lagoon ( IRL), Florida; Great South Bay (GSB), New York; Lake Sallie, Minnesota; and the South Atlantic Bight (SAB).; The solution forced by i generates estimates that are between 27% and 323% of Bokuniewicz's [1980] observations in the GSB; between 40% and 127% of the observations of Martin et al. [2007] in the IRL; and bounds Lee's [1977] observations in Lake Sallie. The solution forced by DeltaVˆ gwtp explains 26% of Moore's [1996] observations in the SAB; and between 16% and 29% of the observations of Martin et al. [2007] in the IRL, assuming observations were taken during the discharge phase of the DeltaVˆgwtp cycle. The solution forced by surface gravity waves explains between 50% and 75% of the observations of Martin et al. [2002] in the IRL, assuming the Lee-type seepage meter is an asymmetrical device. Deviation of the percent of an observation that is explained by an analytical equation is a function of statistical error in the observational process, abstraction error in the generalization of a physical problem to a soluble mathematical form, and use of a single-process equation in a multi-process application.