Willy Aspinall

Oklahoma's induced seismicity strongly linked to wastewater injection depth

Injection depth matters for induced earthquakes Wastewater injection has induced earthquakes in Oklahoma, but the relative importance of operational and geologic parameters in triggering such earthquakes is unclear. Hincks et al. developed an advanced Bayesian network to determine the interplay between these parameters in Oklahoma. The injection depth above the crystalline basement was the most important parameter when considering the potential for release of seismic energy. This modeling strategy may provide a way to improve forecasts of the impact of proposed regulatory changes on induced seismicity. Science, this issue p. 1251 A Bayesian network approach implicates well depth as the most important operational factor for induced earthquakes. The sharp rise in Oklahoma seismicity since 2009 is due to wastewater injection. The role of injection depth is an open, complex issue, yet critical for hazard assessment and regulation. We developed an advanced Bayesian network to model joint conditional dependencies between spatial, operational, and seismicity parameters. We found that injection depth relative to crystalline basement most strongly correlates with seismic moment release. The joint effects of depth and volume are critical, as injection rate becomes more influential near the basement interface. Restricting injection depths to 200 to 500 meters above basement could reduce annual seismic moment release by a factor of 1.4 to 2.8. Our approach enables identification of subregions where targeted regulation may mitigate effects of induced earthquakes, aiding operators and regulators in wastewater disposal regions.

Assessing future vent opening locations at the Somma‐Vesuvio volcanic complex: 2. Probability maps of the caldera for a future Plinian/sub‐Plinian event with uncertainty quantification

In this study, we combine reconstructions of volcanological data sets and inputs from a structured expert judgment to produce a first long-term probability map for vent opening location for the next Plinian or sub-Plinian eruption of Somma-Vesuvio. In the past, the volcano has exhibited significant spatial variability in vent location; this can exert a significant control on where hazards materialize (particularly of pyroclastic density currents). The new vent opening probability mapping has been performed through (i) development of spatial probability density maps with Gaussian kernel functions for different data sets and (ii) weighted linear combination of these spatial density maps. The epistemic uncertainties affecting these data sets were quantified explicitly with expert judgments and implemented following a doubly stochastic approach. Various elicitation pooling metrics and subgroupings of experts and target questions were tested to evaluate the robustness of outcomes. Our findings indicate that (a) Somma-Vesuvio vent opening probabilities are distributed inside the whole caldera, with a peak corresponding to the area of the present crater, but with more than 50% probability that the next vent could open elsewhere within the caldera; (b) there is a mean probability of about 30% that the next vent will open west of the present edifice; (c) there is a mean probability of about 9.5% that the next medium-large eruption will enlarge the present Somma-Vesuvio caldera, and (d) there is a nonnegligible probability (mean value of 6–10%) that the next Plinian or sub-Plinian eruption will have its initial vent opening outside the present Somma-Vesuvio caldera.

Expert judgment-based fragility assessment of reinforced concrete buildings exposed to fire

•The fire fragility of a generic modern, mid-rise, RC office building is assessed.•Fragility curves for its slabs and columns are constructed by expert elicitation.•The expert elicitation also used to construct a suitable fire damage scale.•The significance of spalling in the two RC elements is identified.

Elicitation in the Classical Model

The Classical Model (CM) is a performance-based approach for mathematically aggregating judgements from multiple experts, when reasoning about target questions under uncertainty. Individual expert performance is assessed against a set of seed questions, items from their field, for which the analyst knows or will know the true values, but the experts do not; the experts are, however, expected to provide accurate and informative distributional judgements that capture these values reliably. Performance is measured according to metrics for each expert’s statistical accuracy and informativeness, and the two metrics are convolved to determine a weight for each expert, with which to modulate their contribution when pooling them together for a final combined assessment of the desired target values. This chapter provides mathematical and practical details of the CM, including describing the method for measuring expert performance and discussing approaches for devising good seed questions.

Volcanic Unrest Simulation Exercises: Checklists and Guidance Notes

When a volcano emerges from dormancy into a phase of unrest, the civil protection authorities charged with managing societal risks have the unenviable responsibility of making difficult decisions balancing numerous competing societal, political and economic considerations. A volcano that is threatening to erupt requires sound risk assessments incorporating trusted hazard assessments that are timely, relevant and comprehensible. Foreseeable challenges arise when the inevitable uncertainties of hazard assessment and communication meet societal and political demands for certitude. In some regions that host volcanic hazards, it would be both realistic and prudent to adopt three working assumptions. The complex legal and administrative infrastructures of risk governance will be largely untested and possibly inadequate. Many volcano observatory scientists, and probably even more risk managers and at-risk individuals/communities, will have inadequate recent experience of the challenges of hazard communication during a period of unrest. And lastly, the scientists may also have inadequate practical experience of the needs and management capacities of the risk-mitigation decision makers with whom they must communicate. “Practice doesn’t make perfect. Practice reduces the imperfection.” (Beta 2011). If this statement is correct, volcanic unrest simulation exercises (VUSE) have a vital role to play within the complex processes of volcanic risk governance. Consistent with the broad approach of the Sendai Framework for Risk Reduction 2015–30, this chapter argues that practical knowledge of VUSE can and should be analysed and recorded so that key lessons can be shared for the widest possible benefit. This chapter investigates five recent simulation exercises and presents six complementary checklists based upon data, insights and practice pointers derived from those exercises. The use of checklists, supported by guidance notes, is commended as a pragmatic way to create, test and develop acceptable standards of governance practice. It is argued here that well planned and executed simulation exercises are capable of informing and motivating a wide range of risk governance stakeholders. They can identify process and individual shortcomings that can be mitigated. Simulation exercises can and should play a vital role in reducing volcanic risks.

Expert judgment elicitation

Abstract Two project case histories for geological disposal of nuclear waste are discussed in this and a companion contribution ( Chapter 21 ) with emphasis on the application of formalized treatments of scientific uncertainties in siting considerations. In this chapter, a decision support approach is described, governed by a formalized basis for eliciting and aggregating expert judgments in a rational and auditable way when reasoning under scientific uncertainties. The Classical Model for structured expert judgment elicitation is the theme common to both case histories, serving as a means for determining inputs to a logic tree assessment of the potential evolution of multiple tectonic hazards over extended future periods in the present case history, and providing a way for characterizing potential impacts of climate change on repository performance in the second case history. This chapter first notes the emerging role of structured expert judgment in radioactive waste management and geological disposal facility siting decisions, and describes the properties and attributes of the elicitation method adopted for both case histories. The first, discussed here, is a contribution to a major geological disposal facility siting program in Japan, where expert judgments were elicited in a pioneering approach for parameterizing a logic tree assessment of site-specific impacts due to hazards arising from different long-term tectonic evolution scenarios. Some generic insights on expert elicitation are summarized in the context of facility siting considerations, and suggestions made for further applications, research and methodology developments.