The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction. Issue 1 (February 2022)

• Record Type: Journal Article
• Authors: Allstadt, Kate E; Thompson, Eric M; Jibson, Randall W; Wald, David J; Hearne, Michael; Hunter, Edward J; Fee, Jeremy; Schovanec, Heather; Slosky, Daniel; Haynie, Kirstie L
• Is Part Of: Earthquake spectra. Volume 38:Issue 1(2022)
• Page Start: 5
• Page End: 36
• Publication Date: 2022-02
• Subjects: Earthquake -- landslides -- liquefaction -- ground failure -- earthquake hazard -- earthquake losses -- near-real time; Earthquake engineering -- Periodicals; Earthquake engineering; Periodicals; 624.1762
• DOI: 10.1177/87552930211032685
• Languages: English
• ISSNs: 8755-2930

Abstract

Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.