scholarly journals Rapid and Quantitative Uncertainty Estimation of Coseismic Slip Distribution for Large Interplate Earthquakes Using Real-time GNSS Data and Its Application to Tsunami Inundation Prediction

2021 ◽  
Author(s):  
Keitaro Ohno ◽  
Yusaku Ohta ◽  
Ryota Hino ◽  
Shunichi Koshimura ◽  
Akihiro Musa ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Real Time ◽  
Uncertainty Estimation ◽  
Slip Distribution ◽  
Fault Models ◽  
Coseismic Slip ◽  
Plate Interface ◽  
Tsunami Inundation ◽  
Gnss Data

Abstract This study proposes a new method for the uncertainty estimation of coseismic slip distribution on the plate interface deduced from real-time global navigation satellite system (GNSS) data and explores its application for tsunami inundation prediction. Jointly developed by the Geospatial Information Authority of Japan and Tohoku University, REGARD (REal-time GEONET Analysis system for Rapid Deformation monitoring) estimates coseismic fault models (a single rectangular fault model and slip distribution model) in real time to support tsunami prediction. The estimated results are adopted as part of the Disaster Information System, which is used by the Cabinet Office of the Government of Japan to assess tsunami inundation and damage. However, the REGARD system currently struggles to estimate the quantitative uncertainty of the estimated result, although the obtained result should contain both observation and modeling errors caused by the model settings. Understanding such quantitative uncertainties based on the input data is essential for utilizing this resource for disaster response. We developed an algorithm that estimates the coseismic slip distribution and its uncertainties using Markov chain Monte Carlo methods. We focused on the Nankai Trough of southwest Japan, where megathrust earthquakes have repeatedly occurred, and used simulation data to assume a Hoei-type earthquake. We divided the 2951 rectangular subfaults on the plate interface and designed a multistage sampling flow with stepwise perturbation groups. As a result, we successfully estimated the slip distribution and its uncertainty at the 95% confidence interval of the posterior probability density function. Furthermore, we developed a new visualization procedure that shows the risk of tsunami inundation and the probability on a map. Under the algorithm, we regarded the Markov chain Monte Carlo samples as individual fault models and clustered them using the k-means approach to obtain different tsunami source scenarios. We then calculated the parallel tsunami inundations and integrated the results on the map. This map, which expresses the uncertainties of tsunami inundation caused by uncertainties in the coseismic fault estimation, offers quantitative and real time insights into possible worst-case scenarios.

scholarly journals Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling

2008 ◽  
Vol 31 (4) ◽  
pp. 630-648 ◽  
Author(s):  
Roberta-Serena Blasone ◽  
Jasper A. Vrugt ◽  
Henrik Madsen ◽  
Dan Rosbjerg ◽  
Bruce A. Robinson ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Monte Carlo Sampling ◽  
Uncertainty Estimation ◽  
Generalized Likelihood Uncertainty Estimation

Mechanics-based scenarios for great thrust earthquakes in subduction zones using GNSS data analysis: Released strain energy and dissipated energy

2020 ◽  
Author(s):  
Akemi Noda ◽  
Tatsuhiko Saito ◽  
Eiichi Fukuyama ◽  
Yumi Urata
Keyword(s):  
Shear Stress ◽  
Dynamic Modeling ◽  
Strain Energy ◽  
Recurrence Time ◽  
Dissipated Energy ◽  
Fault Rupture ◽  
Coseismic Slip ◽  
Plate Interface ◽  
Slip Deficit ◽  
Gnss Data

<p>Owing to developments of geodetic observation using satellite systems such as GNSS, we can now estimate slip-deficit rate distribution at plate interfaces. There are roughly two types of attempts to predict possible scenarios for future megathrust earthquakes based on the estimated slip deficit rates. One is kinematic modeling, in which coseismic slip distribution is modeled by multiplying the estimated slip deficit rates by the recurrence time (e.g., Baranes et al. 2018 GRL; Watanabe et al, 2018 JGR). The rupture area and seismic moment can be easily modeled, but the model is not always consistent with the mechanics of fault rupture. The other is dynamic modeling, in which source models are obtained via dynamic rupture simulations using shear stress calculated from the slip deficit rates and assuming frictional parameters (e.g., Hok et al., 2011 JGR; Lozos et al., 2015 GRL; Yang et al., 2019 JGR). The method reasonably predicts the rupture processes based on the mechanics of fault rupture, but generally needs a lot of computing resources for parametric studies of the frictional parameters because of the difficulty to estimate them. In this study, we propose a mechanics-based method to bridge the gap between the kinematic and dynamic modeling. The method predicts possible static slip models with a small computational load, and then examines whether each model actually happens from the viewpoint of the mechanics of fault rupture.</p><p>First, we calculated shear stress change rates at the plate interface from the slip-deficit rate distribution estimated from GNSS data (Noda et al., 2018 JGR). In each scenario, we assumed a rupture region and obtained stress drop distribution by multiplying the shear stress change rates in the region by accumulation period. The coseismic slip distribution of each scenario was estimated from the assumed stress drop distribution by using an inversion method. We created scenarios for various rupture regions and various accumulation periods. Next, we investigated the possibility that the scenario happens based on the conservation law of energy. Fault rupture releases shear strain energy accumulated in the lithosphere and the released strain energy is consumed as the radiated energy and the dissipated energy. We assumed some plausible frictional constitutive relations for the plate interface to evaluate the dissipated energy for each case. We calculated the strain energy released by shear faulting in each scenario and compared it with the dissipated energy considering that the released strain energy is necessarily larger than the dissipated energy in earthquake occurrence. If the released strain energy is smaller than the dissipated energy, we find that the scenario will not happen in terms of earthquake mechanics.</p><p>We applied this method to the subduction zone along the Nankai trough, southwest Japan, where great thrust earthquakes have repeatedly occurred with a recurrence time of about 100 years. Based on possible scenarios predicted in this region, we discussed the necessary condition of fault strength and accumulation period for earthquake generation.</p>

Real-Time Tsunami Inundation Forecast for a Recurrence of 17thCentury Great Hokkaido Earthquake in Japan

2014 ◽  
Vol 9 (3) ◽  
pp. 358-364 ◽  
Author(s):  
Yuichiro Tanioka ◽  
◽  
Aditya Riadi Gusman ◽  
Kei Ioki ◽  
Yugo Nakamura
Keyword(s):  
Real Time ◽  
Pacific Coast ◽  
Great Earthquake ◽  
Tsunami Deposit ◽  
Fault Models ◽  
Fine Grid ◽  
Tsunami Inundation ◽  
Inundation Area ◽  
The Pacific ◽  
Tsunami Waveforms

Paleotsunami studies have shown that several large tsunamis hit the Pacific coast. Many tsunami deposit data were available for the 17thcentury tsunami. The most recent tsunami deposit study in 2013 indicated that the large slip of about 25 m along the plate interface near the Kurile trench would be necessary and the seismic moment of this 17thcentury earthquake was 1.7 × 1022Nm. If a great earthquake like the 17thcentury earthquake occurs off the Pacific coast of Hokkaido, the devastating disaster along the coast is expected. To minimize the tsunami disaster, a development of the real-time forecast of a tsunami inundation area is necessary. Estimating a tsunami inundation area requires tsunami numerical simulation with a very fine grid system of less than 1 arcsecond. There is not enough time to compute the tsunami inundation area after a large earthquake occurs. In this study, we develop a real-time tsunami inundation forecast method using a database including many tsunami inundation areas previously computed using various fault models. After great earthquakes, tsunamis are computed using linear long-wave equations for fault models estimated in real time. Simulating such tsunamis takes only 1-3 minutes on a typical PC, so it is potentially useful for forecasting tsunamis. Tsunami inundation areas computed numerically using various fault models and tsunami waveforms at several locations near the inundation area are stored in a database. Those computed tsunami waveforms are used to choose the most appropriate tsunami inundation area by comparing them to the tsunami waveforms computed in real time. This method is tested at Kushiro, a city in Hokkaido. We found that the method worked well enough to forecast the Kushiro’s tsunami inundation area.

Quasi-real-time on-fault heterogeneous slip distributions for tsunami early warning purposes

2020 ◽  
Author(s):  
Alberto Armigliato ◽  
Enrico Baglione ◽  
Stefano Tinti
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Fault Plane ◽  
Near Field ◽  
Slip Distribution ◽  
Slip Model ◽  
Fault Models ◽  
Tsunami Early Warning ◽  
Finite Fault ◽  
Run Up

<p><span>The study presented here takes the move from two well-known premises in tsunami science: the slip distribution on earthquake faults is heterogeneous and, in the case of tsunamigenic earthquakes, slip heterogeneity influences significantly the distribution of tsunami run-ups, especially for near-field areas. In the perspective of tsunami early warning, a crucial issue is to obtain a reasonable slip distribution within a time significantly shorter than the time taken by the waves to impact the nearest coastlines.</span></p><p><span>When an earthquake occurs, the only information that becomes available after a few minutes concerns the location of the earthquake and its magnitude. The first finite-fault models (FFM), based on seismic/geodetic data inversion, become available several hours or even days after the earthquake origin time. In the case of tsunamigenic earthquakes, tsunami waveforms useful for inversion become available after the tsunami passage at the recording stations. From the warning perspective, the time to get FFM representations is therefore too long for the near-source coastal areas. </span></p><p><span>We propose and describe a strategy whose goal is to derive in quasi-real-time a reasonable representation of the heterogeneous slip distribution on the fault responsible for a given tsunamigenic earthquake and to forecast the run-up distribution along the nearest coastlines. The strategy is illustrated in its application to the 16 September 2015 Illapel (Chile) tsunamigenic earthquake.</span></p><p><span>Realistically, the hypocentre location and the magnitude of the event can be available within two-three minutes. Knowing the hypocentre location permits us to place the fault plane in a definite geographical reference, while the knowledge of magnitude allows to derive the fault dimension and the slip model. A key point here is that we can derive slip models only knowing the magnitude and the location of the hypocenter. Among these models, we adopt simple 2D Gaussian Distributions (GDs), representing the main asperity, whose parameters can be deduced from properly defined regression laws. The 2D-GD simple representation takes a very short time to be derived. To complete the characterization of the tsunamigenic source, focal parameters can be safely derived from seismological databases, while the position of the fault represents a trickier point, as the fault plane is not necessarily centered at the earthquake hypocentre. To take this uncertainty into account, as a first approach three faults for each slip model are considered: 1) a plane centered on the hypocentre, 2) a fault shifted northwards, 3) a fault shifted southwards. </span></p><p><span>We run tsunami simulations for each adopted slip distribution and for each fault position, and compare the results against the available observed tide-gauge and run-up data in the near-field. We compare the performance of our 2D-GD models with respect to the finite-fault models retrieved from inversion procedures, published months after the 2015 event. We demonstrate that the 2D-GD method performs very satisfactorily in comparison to more refined, non-real-time published FFMs and hence permits to produce reliable real-time tsunami simulations very quickly and can be used as an experimental procedure in the frame of operational tsunami warning systems. </span></p>

scholarly journals Uncertainty Estimation of HEC-HMS Flood Simulation Model using Markov Chain Monte Carlo Algorithm

2017 ◽  
Vol 8 (15) ◽  
pp. 235-249
Author(s):  
مه روز نورعلی ◽  
بیژن قهرمان ◽  
محسن پوررضا بیلندی ◽  
کامران داوری ◽  
◽  
...  
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Simulation Model ◽  
Uncertainty Estimation ◽  
Monte Carlo Algorithm ◽  
Flood Simulation

Role of Real-Time GNSS in Near-Field Tsunami Forecasting

2018 ◽  
Vol 13 (3) ◽  
pp. 453-459 ◽  
Author(s):  
Yusaku Ohta ◽  
Takuya Inoue ◽  
Shunichi Koshimura ◽  
Satoshi Kawamoto ◽  
Ryota Hino ◽  
...  
Keyword(s):  
Real Time ◽  
Near Field ◽  
Satellite System ◽  
Fault Model ◽  
Short Paper ◽  
Tsunami Inundation ◽  
Tsunami Forecasting ◽  
Finite Fault ◽  
Gnss Data

This short paper reviews the role of real-time global navigation satellite system (GNSS) in near-field tsunami forecasting. Recent efforts highlight that coseismic fault model estimation based on real-time GNSS has contributed substantially to our understanding of large magnitude earthquakes and their fault expansions. We briefly introduce the history of use of real-time GNSS processing in the rapid estimation of the coseismic finite fault model. Additionally, we discuss our recent trials on the estimation of quasi real-time tsunami inundation based on real-time GNSS data. Obtained results clearly suggest the effectiveness of real-time GNSS for tsunami inundation estimation as the GNSS can capture fault expansion and its slip amount in a relatively accurate manner within a short time period. We also discuss the future prospects of using real-time GNSS data for tsunami warning including effective combination of different methods for more reliable forecasting.

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