In the dissertation, a Monte Carlo approach, that combines stochastic and deterministic modeling approaches, is used to analyze the hydrological control on shallow landslide triggering. In particular, an integrated stochastic rainfall and deterministic landslide simulator has been developed for the purpose. The simulator is composed by the following components: (i) a seasonal NeymanScott Rectangular Pulses (NRSP) model to generate synthetic hourly point rainfall data; (ii) a module for rainfall event identification and separation from dry intervals; (iii) the Transient Rainfall Infiltration and GridBased Regional SlopeStability (TRIGRS) model, version 2 (Baum et al., 2008, 2010) to simulate landslide triggering by rainfall infiltration, combined with a water table recession (WTR) model that computes the initial water table height to consider in simulating rainfall events with TRIGRS. The Monte Carlo simulator has been applied to the Loco catchment in the Peloritani Mountains in northeastern Sicily of Italy, an area with high landslide risk, as recently demonstrated by the regional debrisflow event that occurred on 1 October 2009, which caused 37 casualties and millions of euros of damage. The Monte Carlo approach has been applied for estimation of return periods of shallow landslide triggering and for the evaluation of the most commonlyused types of empirical rainfall threshold. Use of the Monte Carlo approach for estimation of the return period of landsling, represents an advance to approaches based on rainfall IntensityDurationFrequency (IDF) curves, applied by several different researchers, for two reasons. Firstly because the response of an hillslope to hyetographs of rectangular (or any other predifined) shape may be significantly different from that to a reallike stochastically variable hyetograph. Secondly, and more importantly, the use of the Monte Carlo approach, in which water table depths at the beginning of each rainfall event are determined in response to antecedent rainfall time history, enables to avoid the drawback of assuming an arbitrary initial water table depth (for instance equal to zero), which has a probability to occur that should be taken into account in estimating the return period. In fact, IDFbased return period estimation is in principle flawed by the fact that in estimating return period the conditional probability of the rainfall event, given the assumed initial water table height, should be considered. Monte Carlo simulations have allowed to map return period of landslide triggering on the casestudy catchment. Simulation results have been analyzed to evaluate from a theoretical perspective the IntensityDuration empirical model paradigm, i.e. to understand if the stochastic nature of rainfall combined with the physical processes of soilwater movement provide a theoretical justification to this most widely used empirical model. In fact, in spite of its consolidated use, no particular theoretical justification for the use of the IntensityDuration empirical model exists. The paradigm is that a rainfall threshold for landslide triggering assumes a straight line in a bilogarithmic rainfall (mean) Intensity  Duration plane. The obtained results allow to state that, actually, stochastic structure of real rainfall events combined with the infiltration response reveal in a certain sense a theoretical justification to the I  D relationship. Isoporepressure points, in the bilogarithmic rainfall (mean) Intensity  Duration plane, lay, with relatively low scattering, around a straight line, in the cases that initial water table height is negligible. This means that the ID model represents a valid model to interpret data in the case that memory of pore pressures is negligible. In the opposite, most likely, case, the ID model should be coupled with an antecedent rainfall model.
THE HYDROLOGIC CONTROL ON SHALLOW LANDSLIDE TRIGGERING: EMPIRICAL AND MONTE CARLO PYSICALLYBASED APPROACHES / Peres, DAVID JOHNNY.  (2012 Dec 10).
THE HYDROLOGIC CONTROL ON SHALLOW LANDSLIDE TRIGGERING: EMPIRICAL AND MONTE CARLO PYSICALLYBASED APPROACHES
PERES, DAVID JOHNNY
20121210
Abstract
In the dissertation, a Monte Carlo approach, that combines stochastic and deterministic modeling approaches, is used to analyze the hydrological control on shallow landslide triggering. In particular, an integrated stochastic rainfall and deterministic landslide simulator has been developed for the purpose. The simulator is composed by the following components: (i) a seasonal NeymanScott Rectangular Pulses (NRSP) model to generate synthetic hourly point rainfall data; (ii) a module for rainfall event identification and separation from dry intervals; (iii) the Transient Rainfall Infiltration and GridBased Regional SlopeStability (TRIGRS) model, version 2 (Baum et al., 2008, 2010) to simulate landslide triggering by rainfall infiltration, combined with a water table recession (WTR) model that computes the initial water table height to consider in simulating rainfall events with TRIGRS. The Monte Carlo simulator has been applied to the Loco catchment in the Peloritani Mountains in northeastern Sicily of Italy, an area with high landslide risk, as recently demonstrated by the regional debrisflow event that occurred on 1 October 2009, which caused 37 casualties and millions of euros of damage. The Monte Carlo approach has been applied for estimation of return periods of shallow landslide triggering and for the evaluation of the most commonlyused types of empirical rainfall threshold. Use of the Monte Carlo approach for estimation of the return period of landsling, represents an advance to approaches based on rainfall IntensityDurationFrequency (IDF) curves, applied by several different researchers, for two reasons. Firstly because the response of an hillslope to hyetographs of rectangular (or any other predifined) shape may be significantly different from that to a reallike stochastically variable hyetograph. Secondly, and more importantly, the use of the Monte Carlo approach, in which water table depths at the beginning of each rainfall event are determined in response to antecedent rainfall time history, enables to avoid the drawback of assuming an arbitrary initial water table depth (for instance equal to zero), which has a probability to occur that should be taken into account in estimating the return period. In fact, IDFbased return period estimation is in principle flawed by the fact that in estimating return period the conditional probability of the rainfall event, given the assumed initial water table height, should be considered. Monte Carlo simulations have allowed to map return period of landslide triggering on the casestudy catchment. Simulation results have been analyzed to evaluate from a theoretical perspective the IntensityDuration empirical model paradigm, i.e. to understand if the stochastic nature of rainfall combined with the physical processes of soilwater movement provide a theoretical justification to this most widely used empirical model. In fact, in spite of its consolidated use, no particular theoretical justification for the use of the IntensityDuration empirical model exists. The paradigm is that a rainfall threshold for landslide triggering assumes a straight line in a bilogarithmic rainfall (mean) Intensity  Duration plane. The obtained results allow to state that, actually, stochastic structure of real rainfall events combined with the infiltration response reveal in a certain sense a theoretical justification to the I  D relationship. Isoporepressure points, in the bilogarithmic rainfall (mean) Intensity  Duration plane, lay, with relatively low scattering, around a straight line, in the cases that initial water table height is negligible. This means that the ID model represents a valid model to interpret data in the case that memory of pore pressures is negligible. In the opposite, most likely, case, the ID model should be coupled with an antecedent rainfall model.File  Dimensione  Formato  

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