Zum Hauptinhalt springen

PhD-Project I6 by Shubham Sharma (UP): Detecting time-depending forcing of seismicity

Timescale: Oct.2018 – Sept.2021

Supervisors:

Dr. Sebastian Hainzl, GFZ Potsdam

Prof. Dr. Matthias Holschneider, University of Potsdam

PD Dr. Gert Zöller, University of Potsdam

Background

While standard seismic hazard assessments assume time-independence of earthquakes, observations clearly show that the earthquake activity changes significantly in time and space. Besides earthquake interactions leading to aftershock occurrences, aseismic sources contribute to the observed transients such as fluid injections, slow slip events, fault creep or accelerated slip initiating upcoming mainshocks. Often the seismicity data are the best or even the solely information about these processes. For the purpose of process understanding and seismic hazard estimations, it is thus essential to detect the underlying transients in the seismicity data. We aim to utilize purely statistical as well as physics-based seismicity models to invert for the stressing signal in a statistically robust way. The method will be tested and applied for synthetic data and observed seismicity on local, regional and global scale.

Objectives and Methods

We will use the rate- and state-dependent friction (RS) model, which is based on laboratory-derived friction laws and predicts rate changes of the seismicity as function of a time-dependent stressing history. This model has been already demonstrated to reproduce the main features of the observed seismicity. The same model can also be applied to estimate the stressing history given the observed seismicity. However, this estimation requires smoothing of the seismicity data and fixing the input parameters of the seismicity model. So far, this hampers the application of this model for the inversion of the spatiotemporal stressing history. In this project, we will apply and test appropriate smoothing methods (e.g. splines, wavelets, and others) and will account for the parameter uncertainties in a Bayesian framework.

 

Publications within NatRiskChange:

SHARMA, S., Hainzl, S., Zöeller, G., & Holschneider, M. (2020): Is Coulomb stress the best choice for aftershock forecasting? Journal of Geophysical Research,Solid Earth, 125, e2020JB019553. https://doi.org/10.1029/2020JB019553

Powali, D., SHARMA, S., Mandal, R., Mitra, S. (2020): A reappraisal of the 2005 Kashmir (Mw 7.6) earthquake and its aftershocks: Seismotectonics of NW Himalaya, Tectonophysics, 228501.