TY - JOUR

T1 - A note on two alternative probabilistic methods to address parametric uncertainty in magnitude frequency distribution (MFD) logic trees (BEEE-D-22-00704)

AU - Akkar, Sinan

AU - Yazgan, Ufuk

AU - Eroğlu Azak, Tuba

N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature B.V. 2023.

PY - 2024/3

Y1 - 2024/3

N2 - The magnitude frequency distributions (MFDs) are one of the most important components of seismic source modeling in probabilistic seismic hazard analysis (PSHA). They describe the annual occurrence rates of ruptures that are expected to occur in the seismic source. Eventually, the occurrence rates (or probabilities) of ruptures affect the exceedance rate (or probability) and the amplitude of the target ground-motion intensity metric, which is the essential product in PSHA. To this connection, proper portrayal of parametric uncertainty in MFDs entails justifiable ground-motion amplitude exceedance distributions. In this paper, we propose two alternative approaches to account for the parametric uncertainties in the modeling of MFDs. Both approaches treat MFD model parameters as random variables and describe their conditional probability distributions conditioned on seismic source activity. Although both approaches are tailored to structure a proper MFD logic-tree, they differ in the way they handle the conditional probabilities to delineate the parametric uncertainty associated with each MFD model parameter. We first explain the theoretical background of the alternative methods, and then discuss their similarities (and differences) from a case study.

AB - The magnitude frequency distributions (MFDs) are one of the most important components of seismic source modeling in probabilistic seismic hazard analysis (PSHA). They describe the annual occurrence rates of ruptures that are expected to occur in the seismic source. Eventually, the occurrence rates (or probabilities) of ruptures affect the exceedance rate (or probability) and the amplitude of the target ground-motion intensity metric, which is the essential product in PSHA. To this connection, proper portrayal of parametric uncertainty in MFDs entails justifiable ground-motion amplitude exceedance distributions. In this paper, we propose two alternative approaches to account for the parametric uncertainties in the modeling of MFDs. Both approaches treat MFD model parameters as random variables and describe their conditional probability distributions conditioned on seismic source activity. Although both approaches are tailored to structure a proper MFD logic-tree, they differ in the way they handle the conditional probabilities to delineate the parametric uncertainty associated with each MFD model parameter. We first explain the theoretical background of the alternative methods, and then discuss their similarities (and differences) from a case study.

KW - Logic-tree framework for magnitude frequencydistributions

KW - Magnitude frequency distributions

KW - Parametric uncertainty

KW - Probabilistic seismic hazard analysis

UR - http://www.scopus.com/inward/record.url?scp=85180182946&partnerID=8YFLogxK

U2 - 10.1007/s10518-023-01811-x

DO - 10.1007/s10518-023-01811-x

M3 - Article

AN - SCOPUS:85180182946

SN - 1570-761X

VL - 22

SP - 1581

EP - 1604

JO - Bulletin of Earthquake Engineering

JF - Bulletin of Earthquake Engineering

IS - 4

ER -