Earthquake Risk of Gas Pipelines in the Conterminous United States and Its Sources of Uncertainty

Abstract

Relatively little research has been conducted to systematically quantify the nationwide earthquake risk of gas pipelines in the US; simultaneously, national guidance is limited for operators across the country to consistently evaluate the earthquake risk of their assets. Furthermore, many challenges and uncertainties exist in a comprehensive seismic risk assessment of gas pipelines. As a first stage in a systematic nationwide assessment, we quantify the earthquake risk of gas transmission pipelines in the conterminous US due to strong ground shaking, including the associated uncertainties. Specifically, we integrate the US Geological Survey 2018 National Seismic Hazard Model, a logic tree-based exposure model, three different vulnerability models, and a consequence model. The results enable comparison against other risk assessment efforts, encourage more transparent deliberation regarding alternative approaches, and facilitate decisions on potentially assessing localized risks due to ground failures that require site-specific data. Based on the uncertainties approximated herein, the resulting sensitivity analyses suggest that the vulnerability model is the most influential source of uncertainty. Finally, we highlight research needs such as (1) developing more vulnerability models for regional seismic risk assessment of gas pipelines; (2) identifying, prioritizing, and measuring input pipeline attributes that are important for estimating seismic damage; and (3) better quantifying seismic hazards with their uncertainties at the national scale, for both ground failures and ground shaking.

Uses of epistemic uncertainties in the USGS National Seismic Hazard Models

“…In contrast, for mean AFEs smaller than 1 3 10 25 , linear extrapolation in semi-log space is used. These approximations are shown as orange curves in Figure 4, along with the approximate relation for SA(1.0) in solid blue by Kwong et al (2022).…”

“…First, the trend of increasing s ln l for decreasing mean AFE is again observed independently in this study. Furthermore, the relation between l and s ln l from Kwong et al (2022) is closer to that of Hawaii than that of California. This observation makes sense because the model therein was intended for hazard curves at locations throughout the conterminous United States (CONUS) that are less well studied than those from California.…”

“…In the study by Kwong et al (2022), a relatively crude model for generating approximate fractile hazard curves was developed to understand the influence of various sources of uncertainty within a nationwide seismic risk assessment of gas transmission pipelines. Although that study had a different goal than this study, comparison of the approximate models in Figure 4b yields several observations.…”

“…Figure 13 presents results from repeating the sensitivity analyses that were described by Kwong et al (2022) but with different input fractile hazard curves. Specifically, Figure 13a presents the tornado diagram resulting from replacing the input fractile hazard curves with those generated from standard deviations for California shown in Table 3.…”

Theoretical Framework of Supply Chain Uncertainties

“…There has been no effort to advance theory in this area by recognizing the many uncertainty sources and the potential connections to management strategies for enhancing supply chain performance. Kinet [11], nonetheless, has purposed to present the ideology of the SCM scheme, supply chain risk, or specific types of uncertainty, such as demand and supply uncertainty. This study aims to help fill that void by offering both a literature assessment (in which gaps in the research are noted) and a theoretical framework for further research into the effects of uncertainty on supply networks.…”