Scale invariant characteristics of the Storegga Slide and implications for large-scale submarine mass movements

This study documents the fractal characteristics of submarine mass movement statistics and morphology within the Storegga Slide. Geomorphometric mapping is used to identify one hundred and fifteen mass movements from within the Storegga Slide scar and to extract morphological information about their headwalls. Analyses of this morphological information reveal the occurrence of spatial scale invariance within the Storegga Slide. Non-cumulative frequency-area distribution of mass movements within the Storegga Slide satisfies an inverse power law with an exponent of 1.52. The headwalls exhibit geometric similarity at a wide range of scales and the lengths of headwalls scale with mass movement areas. Composite headwalls are self-similar. One of the explanations of the observed spatial scale invariance is that the Storegga Slide is a geomorphological system that may exhibit self-organized criticality. In such a system, the input of sediment is in the form of hemipelagic sedimentation and glacial sediment deposition, and the output is represented by mass movements that are spatially scale invariant. In comparison to subaerial mass movements, the aggregate behavior of the Storegga Slide mass movements is more comparable to that of the theoretical ‘sandpile’ model. The origin of spatial scale invariance may also be linked to the retrogressive nature of the Storegga Slide. The geometric similarity in headwall morphology implies that the slope failure processes are active on a range of scales, and that modeling of slope failures and geohazard assessment can extrapolate the properties of small landslides to those of larger landslides, within the limits of power law behavior. The results also have implications for the morphological classification of submarine mass movements, because headwall shape can be used as a proxy for the type of mass movement, which can otherwise only be detected with very high resolution acoustic data that are not commonly available. © 2007 Elsevier B.V. All rights reserved.