Insights into the nature of coastal cliff rockfall from constant 4D monitoring
Intervenant : Nick Rosser
Durham University, UK
Understanding the nature of rockfalls and those conditions which promote collapse relies upon detailed monitoring, ideally before, during and immediately after failure. With standard repeat surveys it is rarely the case that surveys are contemporaneous with the event itself so gaining insight into the controls on failure and the timescales over which precursors operate remains difficult to establish. As a result, establishing direct links between environmental conditions and rock-falls, or sequences of events prior to rockfall, remain difficult to define. We present an analysis of a high-frequency long-term dataset captured with a permanently installed 3D laser scanning system developed to constantly monitor an actively failing coastal rock slope. The system is based around a Riegl VZ-1000, integrated with and remotely controlled. The system captured data at 0.1 m spacing across > 22,000 m3 at 30 minute intervals for 9 months. Data is streamed to a server that conducts a rolling analysis of change. In parallel to the development of the hardware, we present a new set of algorithms for differencing that trade temporal resolution against spatial resolution to enhance the precision of change detection, allowing both deformation and detachments to be identified. From this dataset we present rockfall volume frequency distributions based upon short-interval surveys, the presence and/or absence of precursors, a near-realtime volumetric measurement of rock face erosion, and rockslope response to individual storm events. The results hold implications for understanding of rockfall mechanics and what controls how coastal cliffs erode, but also for the interpretation of data captured using much lower frequency surveys.