Exciting news! We're transitioning to the Statewide California Earthquake Center. Our new website is under construction, but we'll continue using this website for SCEC business in the meantime. We're also archiving the Southern Center site to preserve its rich history. A new and improved platform is coming soon!

Current State of New Zealand’s Operational Earthquake Forecasting (OEF)

Kenny Graham, Annemarie Christophersen, Matthew C. Gerstenberger, & David A. Rhoades

Submitted September 11, 2022, SCEC Contribution #12440, 2022 SCEC Annual Meeting Poster #209

In New Zealand, GNS Science through the GeoNet programme is the official provider of earthquake forecast information to help communities understand how earthquake sequences might evolve and aid recovery and future resilience planning. Such information has been available since the September 2010 Darfield earthquake. Until recently, the requirement for human input in the production of forecasts limited the speed at which initial forecasts were produced and the frequency with which they were updated. Here, we present the current state of the earthquake forecasting tool and the proposed future development. We have developed a robust and an automated tool (Hybrid Forecast Tool, HFT) that can produce forecasts quickly, regularly, and systematically for future responses to large earthquakes and regular forecast updates. The HFT combines forecast models that cover three different timescales; short-term (from hours to a few years, which are constrained by earthquake-clustering statistics and mainly describe aftershock decay), medium-term (from years to decades, which captures the increase of seismicity prior to large earthquakes) and long-term (from decades to centuries, which smooth out the spatial distribution of earthquake occurrence and can include information on faults and strain-rate). A significant difference with the HFT models and other recent OEF models around the world is the usage of the EEPAS medium-term clustering model, and the use of the overall hybrid modelling framework. To sidestep the technical challenges such as incompatibility of different software libraries, the HFT utilizes a Docker container to enable all the individual models developed with different software programming languages (Fortran, Java, and R) to run on a single computing environment. Moreover, to ensure that the forecast information provided are useful and usable, we have established an on-going engagement with stakeholders to ascertain their information needs and how best to communicate the information. Plans are also in place to revitalize regional earthquake testing center in New Zealand.

Key Words
OEF, New Zealand, Hybrid forecast Models

Citation
Graham, K., Christophersen, A., Gerstenberger, M. C., & Rhoades, D. A. (2022, 09). Current State of New Zealand’s Operational Earthquake Forecasting (OEF). Poster Presentation at 2022 SCEC Annual Meeting.


Related Projects & Working Groups
Earthquake Forecasting and Predictability (EFP)