Challenges and opportunities in New Zealand seismic hazard and risk modeling using OpenQuake

Abbott, Elizabeth; Horspool, Nick; Gerstenberger, Matt; Huso, Rand; Houtte, Chris Van; McVerry, Graeme H.; Canessa, Silvia

doi:10.1177/8755293020966338

Cited by 5 publications

(1 citation statement)

References 15 publications

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“…Since there is no epistemic uncertainty in the earthquake rates, and fault source rupture magnitudes and locations, the hazard model therefore represents a lower bound (Gerstenberger et al, 2017(Gerstenberger et al, , 2020. Seismic hazard calculations were carried out using the OpenQuake engine (Pagani et al, 2014;Silva et al, 2014) with New Zealand-specific configurations (Abbott et al, 2020).…”

Section: Seismic Hazard Modelmentioning

confidence: 99%

Risk-targeted hazard for seismic design in New Zealand considering individual and societal risk targets

et al. 2023

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The promotion of risk-targeted hazard as the basis of seismic design internationally has increased over the past decade. Risk-targeted hazard estimates are derived through convolution of hazard curves with representative fragility functions and provide a means to target uniform risk across a region. Using risk targets also enables performance objectives of building codes that are consistent with other life risks and can include societal input into the expected performance of structures. Current design procedures using a uniform-hazard spectrum are unable to provide equal risk across the country due to variation in the shapes of hazard curves in different locations and uncertainty in structural response. In this article a framework is proposed, which can be used with national seismic hazard models, to produce risk-targeted hazard spectra for seismic design. This study extends the risk-targeted hazard framework through full quantification of epistemic uncertainty in seismic hazard and includes multiple risk targets for individual and societal risk at the building and city scales. The article describes a framework that can be used to adjust current seismic design force levels in New Zealand standards to target uniform seismic risk for buildings considering both the performance of individual buildings and the performance of cities.

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Section: Seismic Hazard Modelmentioning

confidence: 99%

Risk-targeted hazard for seismic design in New Zealand considering individual and societal risk targets

et al. 2023

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Global building exposure model for earthquake risk assessment

Yepes-Estrada,

Calderon,

Costa

et al. 2023

Earthquake Spectra

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The global building exposure model is a mosaic of local and regional models with information regarding the residential, commercial, and industrial building stock at the smallest available administrative division of each country and includes details about the number of buildings, number of occupants, vulnerability characteristics, average built-up area, and average replacement cost. We aimed for a bottom-up approach at the global scale, using national statistics, socio-economic data, and local datasets. This model allows the identification of the most common types of construction worldwide, regions with large fractions of informal construction, and areas prone to earthquakes with a high concentration of population and building stock. The mosaic of exposure models presented herein can be used for the assessment of probabilistic seismic risk and earthquake scenarios. Information at the global, regional, and national levels is available through a public repository ( https://github.com/gem/global_exposure_model ), which will be used to maintain, update and improve the models.

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Capturing Directivity in Probabilistic Seismic Hazard Analysis for New Zealand: Challenges, Implications, and a Machine Learning Approach for Implementation

Weatherill,

Lilienkamp

2023

Bulletin of the Seismological Society of America

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The proximity of fast-slipping crustal faults to urban areas may result in pulse-like ground motions from rupture directivity, which can contribute to increased levels of damage even for engineered structures. Systematic modeling of directivity within probabilistic seismic hazard analysis (PSHA) remains challenging to implement at the regional scale, despite the availability of directivity models in the literature. In the process of developing the 2022 National Seismic Hazard Model for New Zealand (2022 NSHM), we explored the feasibility and impact of modeling directivity for PSHA at a national scale using the previous generation 2010 NSHM. The results of this analysis allowed us to quantify the impact of directivity on the resulting seismic hazard maps for New Zealand and gain insights into the factors that contribute to the expected increases (and decreases) in ground-motion level. For the 2022 NSHM, the earthquake rupture forecast (ERF) seismogenic source models introduced enormous challenges for directivity modeling due to the abundance of large multisegment or multifault ruptures with complex geometries. To overcome these challenges, we applied a machine learning-based strategy to “overfit” an artificial neural network to capture the distributions of directivity amplification and its variability for each unique rupture in the earthquake rupture forecast. This produces a compact representation of the spatial fields of amplification that are computationally efficient to generate within a complete PSHA calculation for the 2022 NSHM. This flexible and reproducible framework facilitates the implementation of directivity in PSHA at a regional scale for complex ERF source models and opens up the possibility of more complex characterization of epistemic uncertainties for near-source ground motion in practice.

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Challenges and opportunities in New Zealand seismic hazard and risk modeling using OpenQuake

Cited by 5 publications

References 15 publications

Risk-targeted hazard for seismic design in New Zealand considering individual and societal risk targets

Risk-targeted hazard for seismic design in New Zealand considering individual and societal risk targets

Global building exposure model for earthquake risk assessment

Capturing Directivity in Probabilistic Seismic Hazard Analysis for New Zealand: Challenges, Implications, and a Machine Learning Approach for Implementation

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