Nonlinear Science issues in the dynamics of unstable rock slopes: new tools for rock fall risk assessment and early warnings
Jiří Zvelebil, Milan Paluš, Dagmar Novotná, 2006. "Nonlinear Science issues in the dynamics of unstable rock slopes: new tools for rock fall risk assessment and early warnings", Fractal Analysis for Natural Hazards, G. Cello, B. D. Malamud
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Time series of displacement data from unstable rock slopes contain ‘hidden’ information about the dynamics of slope failure. This information cannot be found when using the current linearly causal paradigm based on analytical methods, but is revealed when numerical and graphical methods from the toolbox of the Nonlinear Sciences are applied. The occurrence of fractal patterns, which suggests a qualitative difference between intrinsic slope movement dynamics of time series from the near-to-equilibrium and the far-from-equilibrium dynamical states of slope failure systems, is an example of such a ‘hidden’, diagnostically important indicator. It helps to identify the stage of immediate danger of rock fall occurrence, just in time to launch an efficient early warning. Phase portrait and correlograms of time series proved to be suitable for earlier revelation of transitions from the near-to-equilibrium to the far-from-equilibrium dynamical states, as well as for helping to distinguish between intrinsic slope movement dynamics and climatically driven reversible deformation activity.
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Fractal Analysis for Natural Hazards
In the Earth sciences, the concept of fractals and scale invariance is well recognized in many natural objects. However, the use of fractals for spatial and temporal analyses of natural hazards has been less used (and accepted) in the Earth sciences. This book brings together 12 contributions that emphasize the role of fractal analyses in natural hazard research, including andslides, wildfires, floods, catastrophic rock fractures and earthquakes. A wide variety of spatial and temporal fractal-related approaches and techniques are applied to ‘natural’ data, experimental data and computer simulations. These approaches include probabilistic hazard analysis, cellular-automata models, spatial analyses, temporal variability, prediction and self-organizing behaviour. The main aims of this volume are (a) to present current research on fractal analyses as applied to natural hazards and (b) to stimulate the curiosity of advanced Earth science students and researchers in the use of fractals analyses for the better understanding of natural hazards.