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Abstract Four decades of seismic reflection, onshore‐offshore and ocean‐bottom seismic data are integrated to constrain a high‐resolution 3‐D P‐wave velocity model of the Hikurangi subduction zone. Our model shows wavespeeds in the offshore forearc to be 0.5–1 km/s higher in south Hikurangi than in the central and northern segments (V_P ≤ 4.5 km/s). Correlation with onshore geology and seismic reflection data sets suggest wavespeed variability in the overthrusting plate reflects the spatial distribution of Late Jurassic basement terranes. The crustal backstop is 25–35 km from the deformation front in south Hikurangi, but this distance abruptly increases to ∼105 km near Cape Turnagain. This change in backstop position coincides with the southern extent of shallow slow‐slip, most of which occurs updip of the backstop along the central and northern margin. These relationships suggest the crustal backstop may impact the down‐dip extent of shallow conditional stability on the megathrust and imply a high likelihood of near/trench‐breaching rupture in south Hikurangi. North of Cape Turnagain, the more landward position of the backstop, in conjunction with a possible reduction in the depth of the brittle ductile transition, reduces the down‐dip width of frictional locking between the southern (∼100 km) and central Hikurangi margin by up‐to 50%. Abrupt transitions in overthrusting plate structure are resolved near Cook Strait, Gisborne and across the northern Raukumara Peninsula, and appear related to tectonic inheritance and the evolution of the Hikurangi margin. Extremely low forearc wavespeeds resolved north of Gisborne played a key role in producing long durations of long‐period earthquake ground motions. 

Abstract Marine multichannel and wide‐angle seismic data constrain the distribution of seamounts, sediment cover sequence and crustal structure along a 460 km margin‐parallel transect of the Hikurangi Plateau. Seismic reflection data reveals five seamount up‐to 4.5 km high and 35–75 km wide, with heterogeneous internal velocity structure. Sediment cover decreases south‐to‐north from ∼4.5 km to ∼1–2 km. The Hikurangi Plateau crust (V_P5.5–7.5 km/s) is 11 ± 1 km thick in the south, but thins by 3–4 km further north (∼7–8 km). Gravity models constructed along two seismic lines show the reduction in crustal thickness persists further east, coinciding with a bathymetric scarp. Gravity data suggest the transition in crustal thickness may reflect spatial variability in deformation and lithospheric extension associated with plateau breakup. Variability in the thickness of subducting crust may contribute to differences in megathrust geometry, upper‐plate stress state and high‐rates of contraction and uplift along the southern Hikurangi margin. 

Abstract Models of bathymetry derived from satellite radar altimetry are essential for modeling many marine processes. They are affected by uncertainties which require quantification. We propose an uncertainty model that assumes errors are caused by the lack of high‐wavenumber content within the altimetry data. The model is then applied to a tsunami hazard assessment. We build a bathymetry uncertainty model for northern Chile. Statistical properties of the altimetry‐predicted bathymetry error are obtained using multibeam data. We find that a Von Karman correlation function and a Laplacian marginal distribution can be used to define an uncertainty model based on a random field. We also propose a method for generating synthetic bathymetry samples conditional to shipboard measurements. The method is further extended to account for interpolation uncertainties, when bathymetry data resolution is finer than∼10 km. We illustrate the usefulness of the method by quantifying the bathymetry‐induced uncertainty of a tsunami hazard estimate. We demonstrate that tsunami leading wave predictions at middle/near field tide gauges and buoys are insensitive to bathymetry uncertainties in Chile. This result implies that tsunami early warning approaches can take full advantage of altimetry‐predicted bathymetry in numerical simulations. Finally, we evaluate the feasibility of modeling uncertainties in regions without multibeam data by assessing the bathymetry error statistics of 15 globally distributed regions. We find that a general Von Karman correlation and a Laplacian marginal distribution can serve as a first‐order approximation. The standard deviation of the uncertainty random field model varies regionally and is estimated from a proposed scaling law.