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AbstractCommunity recovery from a disaster is a complex process, in which the importance of different types of infrastructure functionality can change over time. Most of the myriad of metrics available for measuring disaster resilience do not capture the dynamic importance of functionality explicitly, however. This means that very different recovery trajectories of a given infrastructure can correspond to the same resilience value, regardless of variations in its utility over time. While some efforts have been made to integrate features of time dependency into individual facility resilience quantification, the resulting metrics either capture only a limited set of temporal instances throughout the post‐disaster phase or do not offer a way to prioritize time steps in line with variations in the importance of facility functionality. This study proposes a novel, straightforward metric for component‐level post‐disaster resilience quantification that overcomes the aforementioned limitations. The metric involves a dynamic weighting component that enables stakeholders to place varying emphasis on different temporal points throughout the recovery process. The end‐user–centered approach to resilience quantification facilitated by the metric allows for flexible, context‐specific interpretations of infrastructure functionality importance that may vary across different communities. The metric is demonstrated through a hypothetical case study of infrastructure facilities with varying degrees of importance across the post‐disaster recovery period, which showcases its versatility relative to a previously well‐established measurement of component‐level resilience. The proposed metric has significant potential for use in stakeholder‐driven approaches to decision making on critical infrastructure (as well as other types of built environment) recovery and resilience.

Abstract. We propose a novel framework for assessing the risk associated with seismicity induced by hydraulic fracturing, which has been a notable source of recent public concern. The framework combines statistical forecast models for injection-induced seismicity, ground motion prediction equations, and exposure models for affected areas, to quantitatively link the volume of fluid injected during operations with the potential for nuisance felt ground motions. Such (relatively small) motions are expected to be more aligned with the public tolerance threshold for induced seismicity than larger ground shaking that could cause structural damage. This proactive type of framework, which facilitates control of the injection volume ahead of time for risk mitigation, has significant advantages over reactive-type magnitude and ground-motion-based systems typically used for induced seismicity management. The framework is applied to the region surrounding the Preston New Road shale gas site in North West England. A notable finding is that the calculations are particularly sensitive to assumptions of the seismicity forecast model used, i.e. whether it limits the cumulative seismic moment released for a given volume or assumes seismicity is consistent with the Gutenberg–Richter distribution for tectonic events. Finally, we discuss how the framework can be used to inform relevant policy.

Abstract. Flood risk is expected to increase in many regions
worldwide due to rapid urbanization and climate change if adequate
risk-mitigation (or climate-change-adaptation) measures are not implemented. However, the exact benefits of these measures remain unknown or inadequately quantified for potential future events in some flood-prone areas such as Kathmandu Valley, Nepal, which this paper addresses. This study examines the present (2021) and future (2031) flood risk in Kathmandu Valley, considering two flood occurrence cases (with 100-year and 1000-year mean return periods) and using four residential exposure inventories representing the current urban system (Scenario A) or near-future development trajectories (Scenarios B, C, D) that Kathmandu Valley could experience. The findings reveal
substantial mean absolute financial losses (EUR 473 million and
775 million in repair and reconstruction costs) and mean loss ratios
(2.8 % and 4.5 %) for the respective flood occurrence cases in current times if the building stock's quality is assumed to have remained the same as in 2011 (Scenario A). Under a "no change" pathway for 2031 (Scenario B), where the vulnerability of the expanding building stock remains the same as in 2011, mean absolute financial losses would increase by 14 %–16 % over those of Scenario A. However, a minimum (0.20 m) elevation of existing
residential buildings located in the floodplains and the implementation of
flood-hazard-informed land-use planning for 2031 (Scenario C) could decrease the mean absolute financial losses of the flooding occurrences by
9 %–13 % and the corresponding mean loss ratios by 23 %–27 %,
relative to those of Scenario A. Moreover, an additional improvement of the
building stock's vulnerability that accounts for the multi-hazard-prone
nature of the valley (by means of structural retrofitting and building code
enforcement) for 2031 (Scenario D) could further decrease the mean loss
ratios by 24 %–28 % relative to those of Scenario A. The largest mean loss ratios computed in the four scenarios are consistently associated with populations of the highest incomes, which are largely located in the
floodplains. In contrast, the most significant benefits of risk mitigation
(i.e., largest reduction in mean absolute financial losses or mean loss
ratios between scenarios) are experienced by populations of the lowest
incomes. This paper's main findings can inform decision makers about the
benefits of investing in forward-looking multi-hazard risk-mitigation
efforts.