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Keith A. Porter

Publications and source records attributed to Keith A. Porter.

9 recordsLinked to original sources

Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast

We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.

California↗

The HayWired earthquake scenario—We can outsmart disaster

The HayWired earthquake scenario, led by the U.S. Geological Survey (USGS), anticipates the impacts of a hypothetical magnitude-7.0 earthquake on the Hayward Fault. The fault is along the east side of California’s San Francisco Bay and is among the most active and dangerous in the United States, because it runs through a densely urbanized and interconnected region. One way to learn about a large earthquake without experiencing it is to conduct a scientifically realistic scenario. The USGS and its partners in the HayWired Coalition and the HayWired Campaign are working to energize residents and businesses to engage in ongoing and new efforts to prepare the region for such a future earthquake.

California↗

Get your science used—Six guidelines to improve your products

Introduction Natural scientists, like many other experts, face challenges when communicating to people outside their fields of expertise. This is especially true when they try to communicate to those whose background, knowledge, and experience are far distant from that field of expertise. At a recent workshop, experts in risk communication offered insights into the communication challenges of probabilistic hazard products, suggested tips, and shared their strategies for making products that a targeted audience can understand and use. Although the workshop was held to broaden the understanding and use of the U.S. Geological Survey (USGS) National Seismic Hazard Maps (NSHM), the workshop outcomes presented in this report can benefit anyone who develops products based on technical information. On the basis of research and practice into how people think, use tools, make decisions, and understand scientific/technical information, the social and behavioral scientists, marketers, and social-impact designers at the NSHM workshop provided remarkably consistent guidelines to develop successful science products, such as text, maps, and other products. In this report the guidelines are numbered for clarity, but they can be applied repeatedly, piecemeal, or out of order to fit each project and your resources.

Circular↗

The SAFRR tsunami scenario: Improving resilience for California

On March 11, 2011, the Tohoku earthquake and the resulting tsunami devastated Japan with a disaster of unfathomable proportions. Five thousand miles away, the waves from Tohoku caused $50 to 100 million in damages in California. Although this pales in comparison to the loss of lives and property in Japan, the U.S. Government must ask whether California, and the national economy, will someday face worse consequences from other distant-source tsunamis. Unfortunately, the answer is “yes.”

California↗

SAFRR (Science Application for Risk Reduction) Tsunami Scenario--Executive Summary and Introduction: Chapter A in The SAFRR (Science Application for Risk Reduction) Tsunami Scenario

The Science Application for Risk Reduction (SAFRR) tsunami scenario depicts a hypothetical but plausible tsunami created by an earthquake offshore from the Alaska Peninsula and its impacts on the California coast. The tsunami scenario is a collaboration between the U.S. Geological Survey (USGS), the California Geological Survey, the California Governor’s Office of Emergency Services (Cal OES), the National Oceanic and Atmospheric Administration (NOAA), other Federal, State, County, and local agencies, private companies, and academic and other institutions. This document presents evidence for past tsunamis, the scientific basis for the source, likely inundation areas, current velocities in key ports and harbors, physical damage and repair costs, economic consequences, environmental and ecological impacts, social vulnerability, emergency management and evacuation challenges, and policy implications for California associated with this hypothetical tsunami. We also discuss ongoing mitigation efforts by the State of California and new communication products. The intended users are those who need to make mitigation decisions before future tsunamis, and those who will need to make rapid decisions during tsunami events. The results of the tsunami scenario will help managers understand the context and consequences of their decisions and how they may improve preparedness and response. An evaluation component will assess the effectiveness of the scenario process for target stakeholders in a separate report to improve similar efforts in the future.

California↗

Trimming the UCERF2 hazard logic tree

The Uniform California Earthquake Rupture Forecast 2 (UCERF2) is a fully time‐dependent earthquake rupture forecast developed with sponsorship of the California Earthquake Authority (Working Group on California Earthquake Probabilities [WGCEP], 2007; Field et al., 2009). UCERF2 contains 480 logic‐tree branches reflecting choices among nine modeling uncertainties in the earthquake rate model shown in Figure 1. For seismic hazard analysis, it is also necessary to choose a ground‐motion‐prediction equation (GMPE) and set its parameters. Choosing among four next‐generation attenuation (NGA) relationships results in a total of 1920 hazard calculations per site. The present work is motivated by a desire to reduce the computational effort involved in a hazard analysis without understating uncertainty. We set out to assess which branching points of the UCERF2 logic tree contribute most to overall uncertainty, and which might be safely ignored (set to only one branch) without significantly biasing results or affecting some useful measure of uncertainty. The trimmed logic tree will have all of the original choices from the branching points that contribute significantly to uncertainty, but only one arbitrarily selected choice from the branching points that do not.

Seismological Research Letters↗

On the contribution of reconstruction labor wages and material prices to demand surge

Demand surge is understood to be a socio-economic phenomenon of large-scale natural disasters, most commonly explained by higher repair costs (after a large- versus small-scale disaster) resulting from higher material prices and labor wages. This study tests this explanation by developing quantitative models for the cost change of sets, or "baskets," of repairs to damage caused by Atlantic hurricanes making landfall on the mainland United States. We define six such baskets, representing the total repair cost, and material and labor components, each for a typical residential or commercial property. We collect cost data from the leading provider of these data to insurance claims adjusters in the United States, and we calculate the cost changes from July to January for nine Atlantic hurricane seasons at fifty-two cities on the Atlantic and Gulf Coasts. The data show that: changes in labor costs drive the changes in total repair costs; cost changes can vary significantly by geographic region and year; and cost changes for the residential basket of repairs are more volatile than the cost changes for the commercial basket. We then propose a series of multilevel regression models to predict the cost changes by considering several combinations of the following explanatory variables: the largest gradient wind speed at a city in a hurricane season; the number of tropical storms in a hurricane season whose center passes within 200 km of a city; and cost changes in the first two quarters of the year. We also allow the coefficients of the regression model to be stochastic, varying across groups defined by region of the Southeastern United States and year. Our best models predict that, for any city on the Gulf or Atlantic Coasts in any hurricane season, the residential total repair cost changes vary from 0.01 to 0.25, depending on the wind speed and number of storms, with an uncertainty of 0.1 (two standard errors of prediction) given the wind speed and number of storms. The commercial total repair cost changes vary from 0.005 to 0.15 with an uncertainty of 0.08. Our models including wind speed, the number of storms affecting a city, and cost changes in the first half of the year explain roughly half of the observed variability in cost changes. Additional explanatory variables that we have not considered may account for the remaining variability. Given these models, however, there is still considerable uncertainty in their predictions. This uncertainty arises from variations between groups defined by region and year, not from variations within a given region and year.

SESM↗

Earthquake casualty models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system

Since the launch of the USGS’s Prompt Assessment of Global Earthquakes for Response (PAGER) system in fall of 2007, the time needed for the U.S. Geological Survey (USGS) to determine and comprehend the scope of any major earthquake disaster anywhere in the world has been dramatically reduced to less than 30 min. PAGER alerts consist of estimated shaking hazard from the ShakeMap system, estimates of population exposure at various shaking intensities, and a list of the most severely shaken cities in the epicentral area. These estimates help government, scientific, and relief agencies to guide their responses in the immediate aftermath of a significant earthquake. To account for wide variability and uncertainty associated with inventory, structural vulnerability and casualty data, PAGER employs three different global earthquake fatality/loss computation models. This article describes the development of the models and demonstrates the loss estimation capability for earthquakes that have occurred since 2007. The empirical model relies on country-specific earthquake loss data from past earthquakes and makes use of calibrated casualty rates for future prediction. The semi-empirical and analytical models are engineering-based and rely on complex datasets including building inventories, time-dependent population distributions within different occupancies, the vulnerability of regional building stocks, and casualty rates given structural collapse.

Book chapter↗

The Loma Prieta, California, earthquake of October, 17, 1989: Marina District

During the earthquake, a total land area of about 4,300 km2 was shaken with seismic intensities that can cause significant damage to structures. The area of the Marina District of San Francisco is only 4.0 km2--less than 0.1 percent of the area most strongly affected by the earthquake--but its significance with respect to engineering, seismology, and planning far outstrips its proportion of shaken terrain and makes it a centerpiece for lessons learned from the earthquake. The Marina District provides perhaps the most comprehensive case history of seismic effects at a specific site developed for any earthquake. The reports assembled in this chapter, which provide an account of these seismic effects, constitute a unique collection of studies on site, as well as infrastructure and societal, response that cover virtually all aspects of the earthquake, ranging from incoming ground waves to the outgoing airwaves used for emergency communication. The Marina District encompasses the area bounded by San Francisco Bay on the north, the Presidio on the west, and Lombard Street and Van Ness Avenue on the south and east, respectively. Nearly all of the earthquake damage in the Marina District, however, occurred within a considerably smaller area of about 0.75 km2, bounded by San Francisco Bay and Baker, Chestnut, and Buchanan Streets. At least five major aspects of earthquake response in the Marina District are covered by the reports in this chapter: (1) dynamic site response, (2) soil liquefaction, (3) lifeline performance, (4) building performance, and (5) emergency services.

California↗