Evaluation of landslide risk based on synchronization of nonlinear motions in observed data

This work proposes an approach to evaluate the landslide risk from observed data by means of synchronization effects of nonlinear motions, forming a judgment on the linkage between two physical phenomena, slope failure and synchronization motion. Phase synchronization of spatial motion is an essential prerequisite for the landslide occurrence, and the connection between phase synchronization behaviors associated with the triggering factor at different points, as a definite mark, constitutes the sufficient criterion to forecast the coming of the landslide risk. Both of them can be obtained through phase synchronization analysis based on the method of empirical mode decomposition, Hilbert transform and order parameter description of phase synchronization. Direct action of the triggering factor can cause a generalized synchronization behavior, and otherwise the connection between different synchronization behaviors must be searched from three movement patterns as follows: damage spread up the slope, damage spread down the slope and damage spread up and down the slope. The first one shows orderly appearing of the peak phase values at different points up the slope, the second has a connection that the phase lock values vary in the same rhythm for a longer time period, and the last is the combination of the first two cases. Investigations of Vaiont landslide occurred on October 9, 1963, in Italy, and Xintan landslide occurred on June 12, 1985, in China, examined the effectiveness of the proposed approach, and also, as examples, provided a possible principle and effective measures to put it into practice for the early warning of landslide.

[1]  Aniruddha Sengupta,et al.  Rainfall thresholds for the initiation of landslide at Lanta Khola in north Sikkim, India , 2010 .

[2]  S. Boccaletti,et al.  On the intrinsic time scales involved in synchronization: a data-driven approach. , 2005, Chaos.

[3]  Eduardo Alonso,et al.  Criteria for rapid sliding I. A review of Vaiont case , 2010 .

[4]  William Murphy,et al.  Patterns of movement in rotational and translational landslides , 2002 .

[5]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[6]  Slawomir J. Nasuto,et al.  A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition , 2007, Journal of Computational Neuroscience.

[7]  Ervin Nonveiller,et al.  The Vajont reservoir slope failure , 1987 .

[8]  M. Soldati,et al.  Recent advances in landslide investigation: Issues and perspectives , 2010 .

[9]  Rex L. Baum,et al.  Estimating the timing and location of shallow rainfall‐induced landslides using a model for transient, unsaturated infiltration , 2010 .

[10]  Denys Brunsden,et al.  Some mudslide movement patterns , 1990 .

[11]  E. Aharonov,et al.  On the stability of landslides: A thermo-poro-elastic approach , 2009 .

[12]  Fawu Wang,et al.  Progress in Landslide Science , 2007 .

[13]  Zhang Li-ning.  Prediction of landslide displacements through multimode support vector machine model , 2011 .

[14]  José M. Matías,et al.  Partially linear support vector machines applied to the prediction of mine slope movements , 2010, Math. Comput. Model..

[15]  Jordi Corominas,et al.  Prediction of ground displacements and velocities from groundwater level changes at the Vallcebre landslide (Eastern Pyrenees, Spain) , 2005 .

[16]  Alexander F. Vakakis,et al.  Physics-Based Foundation for Empirical Mode Decomposition , 2009 .

[17]  Shangqing Wang.  Time Prediction of the Xintan Landslide in Xiling Gorge, the Yangtze River , 2009 .

[18]  David P. Nicholls,et al.  Assessing instantaneous synchrony of nonlinear nonstationary oscillators in the brain , 2010, Journal of Neuroscience Methods.

[19]  D. V. Griffiths,et al.  SLOPE STABILITY ANALYSIS BY FINITE ELEMENTS , 1999 .

[20]  Sijing Wang,et al.  A nonlinear dynamical model of landslide evolution , 2002 .

[21]  Jyh-Jong Liao,et al.  Logistic regression model for predicting the failure probability of a landslide dam , 2011 .

[22]  J. Godt,et al.  Early warning of rainfall-induced shallow landslides and debris flows in the USA , 2010 .

[23]  H. W. Veen,et al.  Handbook of Biological Physics , 1996 .

[24]  Jürgen Kurths,et al.  Synchronization - A Universal Concept in Nonlinear Sciences , 2001, Cambridge Nonlinear Science Series.

[25]  D. Savić,et al.  A symbolic data-driven technique based on evolutionary polynomial regression , 2006 .

[26]  Young-Kwang Yeon,et al.  Landslide susceptibility mapping in Injae, Korea, using a decision tree , 2010 .

[27]  John A. Hudson,et al.  Specifying the information required for rock mechanics modelling and rock engineering design , 2010 .

[28]  Eduardo Alonso,et al.  Criteria for rapid sliding II.: Thermo-hydro-mechanical and scale effects in Vaiont case , 2010 .

[29]  R. Sidle,et al.  Landslides: Processes, Prediction, and Land Use , 2006 .

[30]  K. Sassa.  Landslide Science as a New Scientific Discipline , 2007 .

[31]  F. Mantovani,et al.  The use of surface monitoring data for the interpretation of landslide movement patterns , 2005 .

[32]  P. Landa.  Nonlinear Oscillations and Waves in Dynamical Systems , 1996 .

[33]  Tamotsu Matsui,et al.  Finite element slope stability analysis by shear strength reduction technique , 1992 .

[34]  J. Kurths,et al.  Phase synchronization: from theory to data analysis , 2003 .

[35]  Stéphane Garambois,et al.  Characterization and comparison of landslide triggering in different tectonic and climatic settings , 2010 .

[36]  A J Hendron,et al.  The Vaiont Slide: A Geotechnical Analysis Based on New Geologic Observations of the Failure Surface, Volume 1: Main Text , 1985 .

[37]  Davide Tiranti,et al.  Application of the MoniFLaIR early warning system for rainfall-induced landslides in Piedmont region (Italy) , 2010 .

[38]  M. Paluš,et al.  Fractal rock slope dynamics anticipating a collapse. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[39]  V. V. Geppener,et al.  Applications of empirical mode decomposition for processing nonstationary signals , 2008, Pattern Recognition and Image Analysis.

[40]  L.P.H. van Beek,et al.  A view on some hydrological triggering systems in landslides , 1999 .

[41]  Da-Chao Lin,et al.  Elimination of end effects in empirical mode decomposition by mirror image coupled with support vector regression , 2012 .

[42]  Andreas Hördt,et al.  Landslide monitoring with high resolution tilt measurements at the Dollendorfer Hardt landslide, Germany , 2010 .

[43]  Sijing Wang,et al.  A nonlinear catastrophe model of instability of planar-slip slope and chaotic dynamical mechanisms of its evolutionary process , 2001 .

[44]  Thom Bogaard,et al.  Problems in predicting the mobility of slow-moving landslides , 2007 .

[45]  A. Pikovsky,et al.  Synchronization: Theory and Application , 2003 .

[46]  John Coggan,et al.  Developments in the characterization of complex rock slope deformation and failure using numerical modelling techniques , 2006 .

[47]  Peter Lehmann,et al.  Spatial statistical modeling of shallow landslides—Validating predictions for different landslide inventories and rainfall events , 2011 .

[48]  Wei Hu,et al.  Nonlinear Time Series Predication of Slope Displacement based on Smoothing Filtered Data , 2009 .

[49]  Malcolm G. Anderson,et al.  An integrated hydrological model for rain‐induced landslide prediction , 2002 .

[50]  Angelo Doglioni,et al.  Evolutionary polynomial regression to alert rainfall-triggered landslide reactivation , 2012, Landslides.

[51]  M. Paluš,et al.  Complex system approach to interpretation of monitoring time series: two case histories from NW Bohemia , 2011 .

[52]  F. Mayoraz,et al.  Neural Networks for Slope Movement Prediction , 2002 .

[53]  Nii O. Attoh-Okine,et al.  The Hilbert-Huang Transform in Engineering , 2005 .

[54]  Simon M. Mudd,et al.  The mobilization of debris flows from shallow landslides , 2006 .

[55]  Henk J. M. Bos,et al.  Christiaan Huygens' the pendulum clock, or, Geometrical demonstrations concerning the motion of pendula as applied to clocks , 1986 .