On December 4, 2014 the PEER Center and EERI Northern California Chapter will host the EERI distinguished lecture “Challenges in Estimating Real-time Earthquake Shaking and Impact” by U.S. Geological Survey (USGS) seismologist Dr. David Wald.
Location: Room 250, Sutardja Dai Hall (CITRIS), UC Berkeley Directions
Time: 3:30 pm – 4:30 pm, Pacific Standard Time
Speaker: Dr. David Wald, U.S. Geological Survey (USGS) and Colorado School of Mines
Who should attend this lecture?
All researchers, engineers, students, seismologists, earth scientists, and those interested in earthquake loss estimates and modeling are encouraged to attend. Consulting firms are encouraged to host this lecture in your office.
How can I attend this lecture?
- – Attend in person at Room 250, Sutardja Dai Hall (CITRIS), University of California, Berkeley. Directions
- – Watch remotely via Webcast live at 3:30 pm on December 4, 2014. Access at  on the day of the event (link active from 3:30pm-4:30pm).
- – A video of this presentation is available on PEER’s YouTube Account for viewing after the event.
The U.S. Geological Survey (USGS) has developed several near-real time earthquake information systems that provide rapid and automated alerting of estimated economic and human impacts following earthquakes. In this talk I describe the four components that rapidly assess an earthquake’s impact. First, earthquakes trigger rapid source characterization; second, these source parameters help inform our estimates of shaking-distribution (ShakeMap). Third, losses are modeled by computing populations exposed per shaking intensity level, and country-specific loss functions are used to provide estimates of economic impact and potential casualties (PAGER). Finally, these uncertain loss estimates are communicated in an appropriate form for actionable decision-making among a variety of users.
Several aspects of our problem cannot yet be adequately solved with purely empirical or solely mechanistic approaches. The “physics-based” model components are essential for informing empirical loss models where they are data-limited, and for providing a framework for better understanding the causative pathways that dominate earthquake losses. In the course of explaining the end-to-end strategies and science/engineering we employ, I describe the pragmatic choices made in balancing the uncertainties in and benefits provided by our empirical and physical models. Recognizing and reconciling the complimentary benefits of data-driven versus theoretical problem solving is at the core of our end-to-end earthquake hazard and loss estimates, as it is for a wide variety of other challenges within the earth and engineering sciences.