Time‐Dependent Behavior of a Near‐Trench Slow‐Slip Event at the Hikurangi Subduction Zone

Studying offshore slow‐slip events (SSEs) along subduction zone interfaces is important for constraining the overall slip budget and potential for seismic slip and the relationship with large megathrust earthquakes. Models using only onshore data increasingly lack model resolution the further from the shore the SSE occurs. In this study, we combine data from the Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip seafloor absolute pressure gauge (APG) network with daily position time series from New Zealand's GeoNet to create time‐dependent models of slip during the 2014 Gisborne, New Zealand SSE using the Network Inversion Filter. We compare models assuming heterogeneous versus homogenous elastic properties to explore their influence on our models. The time‐dependent results show that slip uncertainties under the APGs drop by about 23%. We also find that the peak value of slip increases with heterogeneous elastic properties as compared to homogenous models. The inclusion of the offshore APG data in our models places more slip near the trench and detects a more defined migration of slip, especially in the heterogeneous model. These differences are important for interpreting the relationship between the SSE and associated tremor, which occurs after the peak SSE slip rate. Additionally, we use a static “potency bounding” technique in order to gauge the range of models that can fit the data. This analysis demonstrates that the inclusion of offshore data helps to substantially narrow the range of plausible slip models. Plain Language Summary This research focuses on an important aspect of earthquake science called slow‐slip events (SSEs). SSEs are similar to earthquakes but occur more slowly and do not produce damaging seismic energy release. Recently, SSEs have been discovered in areas where large earthquakes happen (the Western United States, Japan, and New Zealand are all examples). The goal of this research is to improve our knowledge of how these events evolve in space and time and their relationship to other seismic phenomena and to quantify the model improvements gained with the addition of seafloor data. Here we investigate a SSE that occurred offshore New Zealand, using both onshore GPS instruments and seafloor instruments that detect centimeter‐level vertical movement of the seafloor. We found that using seafloor instruments helps to better pinpoint the location and evolution of a SSE offshore of New Zealand in 2014. We also found that these