In the last two decades, New Zealand (NZ) has experienced significant earthquakes, including the 2010 M 7.2 Darfield, 2011 M 6.2 Christchurch, and 2016 M 7.8 Kaikōura events. Amongst these large events, tens of thousands of smaller earthquakes have occurred. While previous event and ground-motion databases have analyzed these events, many events below M 4 have gone undetected. The goal of this study is to expand on previous databases, particularly for small magnitude (M<4) and low-amplitude ground motions. This new database enables a greater understanding of regional variations within NZ and contributes to the validity of internationally developed ground-motion models. The database includes event locations and magnitude estimates with uncertainty considerations, and tectonic type assessed in a hierarchical manner. Ground motions are extracted from the GeoNet FDSN server and assessed for quality using a neural network classification approach. A deep neural network approach is also utilized for picking P and S phases for determination of event hypocentres. Relative hypocentres are further improved by double-difference relocation and will contribute toward developing shallow (< 50 km) seismic tomography models. Analysis of the resulting database is compared with previous studies for discussion of implications toward national hazard prediction models.
This study investigates the uncertainty of simulated earthquake ground motions for smallmagnitude events (Mw 3.5 – 5) in Canterbury, New Zealand. 148 events were simulated with specified uncertainties in: event magnitude, hypocentre location, focal mechanism, high frequency rupture velocity, Brune stress parameter, the site 30-m time-averaged shear wave velocity (Vs30), anelastic attenuation (Q) and high frequency path duration. In order to capture these uncertainties, 25 realisations for each event were generated using the Graves and Pitarka (2015) hybrid broadband simulation approach. Monte-Carlo realisations were drawn from distributions for each uncertainty, to generate a suite of simulation realisations for each event and site. The fit of the multiple simulation realisations to observations were assessed using linear mixed effects regression to generate the systematic source, path and site effects components across all ground motion intensity measure residuals. Findings show that additional uncertainties are required in each of the three source, path, and site components, however the level of output uncertainty is promising considering the input uncertainties included.
The University of Canterbury’s RECOVER project (Reef Ecology and Coastal Values, Earthquake Recovery) is a research programme funded by the Ministry of Business, Innovation and Employment (MBIE), and supported by the Ministry of Primary Industries (MPI). It has been evaluating recovery from the 7.8 Mw Kaikōura earthquake in the coastal environment between Oaro in the south and Marfells Beach in the north. The project has documented a wide range of biological and physical impacts in the coastal environment over the past four years. These include the widespread mortality of habitat-forming species that support characteristic ecosystems and natural resources on the coast (Alestra et al. 2021; Schiel et al. 2019; Tait et al. 2021). Due to the popularity of the coast for recreational use, interactions between people and the recovering environment are an important influence on recovery processes. These interactions may include threats to the natural environment but also the potential for positive interventions that could help to restore natural ecosystems and resources – including those that have been degraded in the past. Physical effects of uplift at the coastline include the seaward movement of shorelines and creation of new land above the reach of the tide, leading to a widening of beaches (Orchard et al. 2020; Orchard et al. in press). This has also provided a greater opportunity for off-road vehicle access to sections of the coast previously protected by headlands that were impassable at high tide (Marlborough District Council 2019; Orchard 2020). MDC management responses have included the development of a proposed bylaw to reduce the impacts of motor vehicle use in the area (Marlborough District Council 2021). Changes in the position of the sea-level on the landscape also affect the location of characteristic ecosystems such as sand dunes and storm beaches as they recover to a new norm. Notable changes include the establishment of new dunes closer to the sea which could potentially lead to the degradation of old dune systems that may experience reduced sand supply as a result. Wildlife habitat has also been affected by these uplift and re-assembly effects although the specific impacts remain largely unknown. This report contributes to a collaborative project between the Marlborough District Council (MDC) and University of Canterbury (UC) which aims to help protect and promote the recovery of native dune systems on the Marlborough coast. It is centred around the mapping of dune vegetation and identification of dune protection zones for old-growth seed sources of the native sand-binders spinifex (Spinifex sericeus) and pīngao (Ficinia spiralis). Both are key habitat-formers associated with nationally threatened dune ecosystems (Holdaway et al. 2012), and pīngao is an important weaving resource and Ngāi Tahu taonga species. The primary goal is to protect existing seed sources that are vital for natural regeneration following major disturbances such as the earthquake event. Several additional protection zones are also identified for areas where new dunes are successfully regenerating, including areas being actively restored in the Beach Aid project that is assisting new native dunes to become established where there is available space.
