Geomprphological analysis of seafloor by multifractal

Measurement of seafloor microtopography is rapidly approaching the status as a standardized element of geoacoustic characterization of the sea floor. With the advent of underwater stereo cameras and, recently, multiple-megapixel digital cameras adapted for underwater use, more investigators are measuring seafloor roughness at high resolution for applications to high-frequency acoustic modeling. An assessment of the methodologies used to characterize seafloor roughness, the parameterizations of the characterization of seafloor roughness, and the predictability of seafloor roughness seems appropriate at this time. Use of the roughness power spectrum to characterize seafloor roughness has a wide applicability for acoustic modelers. Currently, the slope and intercept of the regression line through the roughness power spectrum are used to parameterize seafloor roughness for acoustic modeling. Recent availability of digital roughness height datasets allows computation of two-dimensional roughness power spectra at sub-cm resolution. Ideally, these 2-D spectra would make the estimation of 2-D roughness parameters from 1-D roughness parameters unnecessary. Although much seafloor microtopography has been characterized concomitantly with sediment grain size, empirical prediction of roughness from grain size remains problematic. The inherent problem in relating seafloor roughness parameters to grain size is that the sediment-water interface is dynamic. Although seafloor microtopography may be thought to evolve predictably through cycles driven by hydrodynamic and biological processes, the rates of these processes and the resultant bedforms are highly variable. Another aspect of seafloor roughness that needs to be addressed is the character of its power spectrum over several orders of magnitude of spatial dimensions.

Measurement of seafloor microtopography is rapidly approaching the status as a standardized element of geoacoustic characterization of the sea floor. With the advent of underwater stereo cameras and, recently, multiple-megapixel digital cameras adapted for underwater use, more investigators are measuring seafloor roughness at high resolution for applications to high-frequency acoustic modeling. An assessment of the methodologies used to characterize seafloor roughness, the parameterizations of the characterization of seafloor roughness, and the predictability of seafloor roughness seems appropriate at this time.
Use of the roughness power spectrum to characterize seafloor roughness has a wide applicability for acoustic modelers. Currently, the slope and intercept of the regression line through the roughness power spectrum are used to parameterize seafloor roughness for acoustic modeling. Recent availability of digital roughness height datasets allows computation of two-dimensional roughness power spectra at sub-cm resolution. Ideally, these 2-D spectra would make the estimation of 2-D roughness parameters from 1-D roughness parameters unnecessary. Although much seafloor microtopography has been characterized concomitantly with sediment grain size, empirical prediction of roughness from grain size remains problematic. The inherent problem in relating seafloor roughness parameters to grain size is that the sediment-water interface is dynamic. Although seafloor microtopography may be thought to evolve predictably through cycles driven by hydrodynamic and biological processes, the rates of these processes and the resultant bedforms are highly variable. Another aspect of seafloor roughness that needs to be addressed is the character of its power spectrum over several orders of magnitude of spatial dimensions.

Rapid alterations of aquatic ecosystems associated with changing climate and growing anthropogenic stress require the development of effective and low-cost acoustic methods of bottom sediment characterization and mapping. Acoustic reflectance and scattering properties of surface bottom sediment (SBS) were characterized by energetic, statistical, spectral, wavelet, and fractal parameters of single-beam echo envelopes. A common feature of the chosen parameters is indication of energy distribution in the frequency domain and fractal description of the echoenvelope shape. Data collected with a 120-kHz single-beam echosounder along 14 regular transects were used to determine the acoustical properties of SBS, and study their spatial and temporal changes in Lake Kinneret, and their relation to sedimentological characteristics of the bottom. Special post-processing procedures were applied to remove the instability of the acoustical signal (caused by angular movement of the transducer), and the impact of the bottom slope. The influence of changing depth on the shape of the echo signal was corrected by the depth normalization procedure. Sediment grain size in the upper few-centimeter layer was studied based on grab samples. Some acoustical parameters showed close association with granulometric variables and organic matter content in the upper sediments. The observed effect of water level fluctuation on several echo parameters was apparently associated with changes in gas content in the SBS. Spatial distributions of some echo parameters were very stable with time; other parameters showed large changes in the central part of the lake, but were nearly unchanged at the lake periphery. Overall, the suggested approach is a useful tool for investigation of fine modifications of SBS properties in aquatic ecosystems.

Measurement of seafloor microtopography is rapidly approaching the status as a standardized element of geoacoustic characterization of the sea floor. With the advent of underwater stereo cameras and, recently, multiple-megapixel digital cameras adapted for underwater use, more investigators are measuring seafloor roughness at high resolution for applications to high-frequency acoustic modeling. An assessment of the methodologies used to characterize seafloor roughness, the parameterizations of the characterization of seafloor roughness, and the predictability of seafloor roughness seems appropriate at this time. Use of the roughness power spectrum to characterize seafloor roughness has a wide applicability for acoustic modelers. Currently, the slope and intercept of the regression line through the roughness power spectrum are used to parameterize seafloor roughness for acoustic modeling. Recent availability of digital roughness height datasets allows computation of two-dimensional roughness power spectra at sub-cm resolution. Ideally, these 2-D spectra would make the estimation of 2-D roughness parameters from 1-D roughness parameters unnecessary. Although much seafloor microtopography has been characterized concomitantly with sediment grain size, empirical prediction of roughness from grain size remains problematic. The inherent problem in relating seafloor roughness parameters to grain size is that the sediment-water interface is dynamic. Although seafloor microtopography may be thought to evolve predictably through cycles driven by hydrodynamic and biological processes, the rates of these processes and the resultant bedforms are highly variable. Another aspect of seafloor roughness that needs to be addressed is the character of its power spectrum over several orders of magnitude of spatial dimensions.

Rapid alterations of aquatic ecosystems associated with changing climate and growing anthropogenic stress require the development of effective and low-cost acoustic methods of bottom sediment characterization and mapping. Acoustic reflectance and scattering properties of surface bottom sediment (SBS) were characterized by energetic, statistical, spectral, wavelet, and fractal parameters of single-beam echo envelopes. A common feature of the chosen parameters is indication of energy distribution in the frequency domain and fractal description of the echoenvelope shape. Data collected with a 120-kHz single-beam echosounder along 14 regular transects were used to determine the acoustical properties of SBS, and study their spatial and temporal changes in Lake Kinneret, and their relation to sedimentological characteristics of the bottom. Special post-processing procedures were applied to remove the instability of the acoustical signal (caused by angular movement of the transducer), and the impact of the bottom slope. The influence of changing depth on the shape of the echo signal was corrected by the depth normalization procedure. Sediment grain size in the upper few-centimeter layer was studied based on grab samples. Some acoustical parameters showed close association with granulometric variables and organic matter content in the upper sediments. The observed effect of water level fluctuation on several echo parameters was apparently associated with changes in gas content in the SBS. Spatial distributions of some echo parameters were very stable with time; other parameters showed large changes in the central part of the lake, but were nearly unchanged at the lake periphery. Overall, the suggested approach is a useful tool for investigation of fine modifications of SBS properties in aquatic ecosystems.