مرکز منطقه ای اطلاع رساني علوم و فناوري - Statistical characterization of seafloor roughness

Abstract :

The topography of the seabed can strongly affect underwater sound propagation in the ocean. In this regard, seafloor features fall into three overlapping categories according to size: large features that block propagation, intermediate features that act primarily as sloping bottoms, and small-scale features that act as scatterers. In this paper, statistical parameters of bottom topography for the latter two categories are presented. Spatial wavenumber spectra of ocean bottom and subbottom roughness are determined from narrow-beamwidth echosounding and seismic reflection profiling. The spectra are compared to the expression $P(K) = CK^{-b}$ , where $P(K)$ is the power spectral density, $C$ is a proportionality constant, $K$ is the wavenumber, and $b$ is a constant that characterizes the class of roughness. The parameter $b$ is often assumed to be 3; however, the present study shows that $b$ can range from about 1 to 5. Topographic samples were found to have probability density functions which were both non-Ganssian and Gaussian. It is suggested that a first-order roughness data base include hand-limited root mean square (RMS) roughness; $K_{1}$ and $K_{2}$ (the wavenumbers of the estimate); $b$ ; sediment type; physiographic province, water depth, and location.