Submarine landslide deposits of the historical lateral collapse of Ritter Island, Papua New Guinea

摘要

The March 13th 1888 collapse of Ritter Island in Papua New Guinea is the largest known sector collapse of an island volcano in historical times. One single event removed most of the island and its western submarine flank, and produced a landslide deposit that extends at least 70 km from the headwall of the collapse scar. We have mapped and described the deposits of the debris avalanche left by the collapse using full-coverage multibeam bathymetry, side-scan sonar backscatter intensity mapping, chirp seismic-reflection profiles, TowCam photographs of the seafloor and samples from a single dredge. Applying concepts originally developed on the 1980 Mount St. Helens collapse landslide deposits, we find that the Ritter landslide deposits show three distinct morphological facies: large block debris avalanche, matrix-rich debris avalanche and distal debris flow facies. Restoring the island's land and submarine topography we obtained a volume of 4.2 km(3) for the initial collapse, about 75% of which is now forming the large block facies at distances less than 12 km from the collapse scar. The matrix-rich facies volume is unknown, but large scale erosion of the marine sediment substrate yielded a minimum total volume of 6.4 km(3) in the distal debris flow and/or turbidite deposits, highlighting the efficiency of substrate erosion during the later history of the landslide movement. Although studying submarine landslide deposits we can never have the same confidence that subaerial observations provide, our analysis shows that well-exposed submarine landslide deposits can be interpreted in a similar way to subaerial volcano collapse deposits, and that they can in turn be used to interpret older, incompletely exposed submarine landslide deposits. Studying the deposits from a fades perspective provides the basis for reconstructing the kinematics of a collapse event landslide; understanding the mechanisms involved in its movement and deposition; and so providing key inputs to tsunami models. (C) 2015 Elsevier Ltd. All rights reserved.