Estimating the Maximum Possible Earthquake Magnitude Using Extreme Value Methodology: The Groningen Case

CentER Discussion Paper Series No. 2017-050

30 Pages Posted: 21 Dec 2017

See all articles by Jan Beirlant

Jan Beirlant

Catholic University of Leuven (KUL)

Andrzej Kijko

University of Pretoria

Tom Reynkens

KU Leuven - Department of Mathematics

John H. J. Einmahl

Tilburg University - Department of Econometrics & Operations Research

Date Written: December 6, 2017

Abstract

The area-characteristic, maximum possible earthquake magnitude TM is required by the earthquake engineering community, disaster management agencies and the insurance industry. The Gutenberg-Richter law predicts that earthquake magnitudes M follow a truncated exponential distribution. In the geophysical literature several estimation procedures were proposed, see for instance Kijko and Singh (Acta Geophys., 2011) and the references therein. Estimation of TM is of course an extreme value problem to which the classical methods for endpoint estimation could be applied. We argue that recent methods on truncated tails at high levels (Beirlant et al., Extremes, 2016; Electron. J. Stat., 2017) constitute a more appropriate setting for this estimation problem. We present upper confidence bounds to quantify uncertainty of the point estimates. We also compare methods from the extreme value and geophysical literature through simulations. Finally, the different methods are applied to the magnitude data for the earthquakes induced by gas extraction in the Groningen province of the Netherlands.

Keywords: anthropogenic seismicity, endpoint estimation, extreme value

JEL Classification: C13, C14

Suggested Citation

Beirlant, Jan and Kijko, Andrzej and Reynkens, Tom and Einmahl, John H. J., Estimating the Maximum Possible Earthquake Magnitude Using Extreme Value Methodology: The Groningen Case (December 6, 2017). CentER Discussion Paper Series No. 2017-050. Available at SSRN: https://ssrn.com/abstract=3089547 or http://dx.doi.org/10.2139/ssrn.3089547

Jan Beirlant (Contact Author)

Catholic University of Leuven (KUL) ( email )

W. de Croylaan 54
Leuven, B-3001
Belgium

Andrzej Kijko

University of Pretoria ( email )

Physical Address Economic and Management Sciences
Pretoria, Gauteng 0002
South Africa

Tom Reynkens

KU Leuven - Department of Mathematics ( email )

Celestijnenlaan 200 B
Leuven, B-3001
Belgium

John H. J. Einmahl

Tilburg University - Department of Econometrics & Operations Research ( email )

P.O. Box 90153
5000 LE Tilburg
Netherlands

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