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  • Probabilistic seismic damage and loss assessment methodology for wastewater network incorporating modeling uncertainty and damage correlations
Title: Probabilistic seismic damage and loss assessment methodology for wastewater network incorporating modeling uncertainty and damage correlations
Maintaining the functionality of wastewater networks is critical to individual well-being, business continuity, public health, and safety. However, seismic damage and loss assessments of wastewater networks traditionally use fragility functions based on median repair rates without considering relevant sources of uncertainty and correlations of damage when estimating potential damage states and pipe repairs. This study presents a probabilistic methodology to incorporate modeling uncertainty (e.g. model parameter and model class uncertainty) and spatial correlations (e.g. spatial auto- and cross-correlation) of pipe repairs. The methodology was applied to a case study backbone system of a wastewater network in Portland, OR, using the expected hazard intensity maps for multiple deterministic earthquake scenarios, including a moment magnitude M6.8 Portland Hills Fault and M8.1, M8.4, M8.7, and M9.0 Cascadia Subduction Zone (CSZ) events. As spatial-correlation models of pipeline damage were non-existent in the literature and local information on costs to repair the pipes was limited at the time of this study, correlation methods and repair costs were proposed to estimate lower and upper bounds of pipe damage and loss. The results show how the consideration of different levels of uncertainty and spatial correlation for pipe repair rate could lead to different probabilistic estimates of damage and loss at the system level of the wastewater network, even though the point estimates, such as the mean and median, remain essentially unaltered.  more » « less
Award ID(s):
2103713
PAR ID:
10579264
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
Earthquake Spectra
Date Published:
Journal Name:
Earthquake Spectra
Volume:
39
Issue:
3
ISSN:
8755-2930
Page Range / eLocation ID:
1435 to 1472
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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