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Regional scale assessments of future chronic coastal hazard impacts are critical tools for adaptation planning under a changing climate. Probabilistic simulations of hazard impacts can improve these assessments by explicitly attempting to quantify uncertainty and by better simulating dependence between complex multivariate drivers of hazards. In this study, probabilistic future timeseries of total water levels (TWLs) are generated from a stochastic climate emulator (TESLA; Anderson et al., 2019) for the Cascadia region, USA for use in a chronic hazard impact assessment. This assessment focuses on three hazard metrics: collision, overtopping, and beach safety, and also introduces a novel hotspot indicator to identify areas that may experience dramatic changes in hazard impacts compared to present day conditions. Results are presented for a subset of the Cascadia region (Rockaway Beach Littoral Cell, Oregon) to demonstrate the power of the probabilistic impact assessment approach. The results highlight how useful spatially varying, scenario-based hazard impacts assessments and hotspot indicators are for identifying which areas and types of hazards may require increased adaptation support. This approach enables us to piece apart the relative uncertainty of hazards as driven by SLR versus natural variability (caused by variation in climate, weather, and hydrodynamic drivers).
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Workflows for Construction of Spatio-Temporal Probabilistic Maps for Volcanic Hazard Assessment
Probabilistic hazard assessments for studying overland pyroclastic flows or atmospheric ash clouds under short timelines of an evolving crisis, require using the best science available unhampered by complicated and slow manual workflows. Although deterministic mathematical models are available, in most cases, parameters and initial conditions for the equations are usually only known within a prescribed range of uncertainty. For the construction of probabilistic hazard assessments, accurate outputs and propagation of the inherent input uncertainty to quantities of interest are needed to estimate necessary probabilities based on numerous runs of the underlying deterministic model. Characterizing the uncertainty in system states due to parametric and input uncertainty, simultaneously, requires using ensemble based methods to explore the full parameter and input spaces. Complex tasks, such as running thousands of instances of a deterministic model with parameter and input uncertainty require a High Performance Computing infrastructure and skilled personnel that may not be readily available to the policy makers responsible for making informed risk mitigation decisions. For efficiency, programming tasks required for executing ensemble simulations need to run in parallel, leading to twin computational challenges of managing large amounts of data and performing CPU intensive processing. The resulting flow of work requires complex sequences of tasks, interactions, and exchanges of data, hence the automatic management of these workflows are essential. Here we discuss a computer infrastructure, methodology and tools which enable scientists and other members of the volcanology research community to develop workflows for construction of probabilistic hazard maps using remotely accessed computing through a web portal.
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- Award ID(s):
- 2004302
- PAR ID:
- 10482141
- Publisher / Repository:
- Frontiers
- Date Published:
- Journal Name:
- Frontiers in Earth Science
- Volume:
- 9
- ISSN:
- 2296-6463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Probabilistic assessments of the potential impact of earthquakes on infrastructure entails the consideration of smaller magnitude events than those generally considered in deterministic hazard and risk assessments. In this context, it is useful to establish if there is a magnitude threshold below which the possibility of triggering liquefaction can be discounted because such a lower bound is required for probabilistic liquefaction hazard analyses. Based on field observations and a simple parametric study, we conclude that earthquakes as small as moment magnitude 4.5 can trigger liquefaction in extremely susceptible soil deposits. However, for soil profiles that are suitable for building structures, the minimum earthquake magnitude for the triggering of liquefaction is about 5. We therefore propose that in liquefaction hazard assessments of building sites, magnitude 5.0 be adopted as the minimum earthquake size considered, while magnitudes as low as 4.5 may be appropriate for some other types of infrastructure.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/feart.2021.744655
