We estimate slip rates on major active faults in southern California using a block model constrained by Global Positioning System measurements of interseismic deformation. The block model includes the effects of block rotation and elastic strain accumulation consistent with a simple model of the earthquake cycle. Our estimates of the right‐lateral strike‐slip rate on the San Andreas fault vary by at least a factor of 5, from a high of 35.9 ± 0.5 mm/yr in the Carrizo Plain to a low of 5.1 ± 1.5 mm/yr through the San Bernadino segment. Shortening across the Puente Hills Thrust and left‐lateral slip on the Raymond Hill fault are consistent with both thickening and escape tectonics in the Los Angeles Basin. Discrepancies between geodetic and geologic slip rate estimates along the San Andreas and San Jacinto faults, as well as in the Eastern California Shear Zone, may be explained by a temporal change in fault system behavior. We find no substantial evidence for long‐term postseismic relaxation and infer that the viscosity of the lower crust/upper mantle may be relatively high (η > 1019 Pa s).

[1] Interseismic deformation in Japan results from the combined effects of tectonic processes including rotation of crustal blocks and the earthquake cycle process of elastic strain accumulation about upper plate faults and subduction zone interfaces. We use spherical linear block theory constrained by geodetic observations from densely spaced Global Positioning System (GPS) stations to estimate plate motions, fault slip rates, and spatially variable interplate coupling on the Japan-Kuril, Sagami, and Nankai subduction zones. The reference model developed in this paper consists of 20 blocks, produces a mean residual velocity magnitude of 1.84 mm/yr at 950 stations, and accounts for 96% of the observed interseismic deformation signal. We estimate fault slip rates in excess of 15 mm/yr along the Niigata-Kobe Tectonic Zone and Itoigawa-Shizuoka Tectonic Line through central Japan, confirming their hypothesized roles as major tectonic boundaries. Oblique convergence across the Nankai Trough is partitioned, with 3/4 of the $30 mm/yr of trench-parallel motion accommodated by strike-slip motion on the subduction interface and the remaining 1/4 accommodated by right-lateral slip on the Median Tectonic Line. In contrast, our models suggest negligible slip partitioning in eastern Hokkaido, where oblique slip on the Japan-Kuril subduction interface accommodates all of the trench-parallel component of relative plate motion. Inferred spatial variations in the rake and magnitude of slip deficit on subduction zone interfaces reflect the influences of megathrust geometry and earthquake cycle processes such as enhanced elastic strain accumulation about seismic asperities and coseismic sense fault motion indicative of silent slip events or afterslip following large earthquakes.

The collision of the Indian subcontinent with Asia drives the growth and evolution of the greater Tibetan Plateau region. Fault slip rates resulting from the relative motion between crustal blocks can provide a kinematic description of the distribution of presentday deformation. I construct a three-dimensional, regional-scale elastic block model of the India-Asia collision zone that is consistent with geodetic observations of interseismic deforma tion, mapped fault system geometry, historical seismicity, and the mechanics of the earthquake cycle. This mechanical model of the elastic upper crust yields a set of kinematically consistent fault slip rates and block motions that may serve to constrain dynamic models of continental crustal dynamics.

We model the geodetically observed secular velocity field in northwestern Turkey with a block model that accounts for recoverable elastic-strain accumulation. The block model allows us to estimate internally consistent fault slip rates and locking depths. The northern strand of the North Anatolian fault zone (NAFZ) carries approximately four times as much right-lateral motion (ϳ24 mm/yr) as does the southern strand. In the Marmara Sea region, the data show strain accumulation to be highly localized. We find that a straight fault geometry with a shallow locking depth of 6-7 km fits the observed Global Positioning System velocities better than does a stepped fault geometry that follows the northern and eastern edges of the sea. This shallow locking depth suggests that the moment release associated with an earthquake on these faults should be smaller, by a factor of 2.3, than previously inferred assuming a locking depth of 15 km.Online material: an updated version of velocity-field data.

[1] Imaging the extent to which the rupture areas of great earthquakes coincide with regions of pre-seismic interplate coupling is central to understanding patterns of strain accumulation and release through the earthquake cycle. Both geodetic and seismic estimates of the coseismic rupture extent for the March 11, 2011 M W = 8.9-9.0 earthquake Tohoku-oki earthquake may be spatially correlated (0.26 ± 0.05 to 0.82 ± 0.05) with a region estimated to be partially to fully coupled in the interseismic period preceding the earthquake, though there is substantial variation in the estimated distribution and magnitude of coseismic slip. The ∼400 km-long region estimated to have slipped ≥4 m corresponds to an area of the subduction zone interface that was coupled at ≥30% of long-term plate convergence rate, with peak slip near a region coupled ≥80%. The northern termination of rupture is collocated with a region of relatively low (<20%) interseismic coupling near the epicenter of the 1994 M W = 7.6 Sanriku-oki earthquake, and near a region of potential longterm low coupling or ongoing slow slip. Slip on the subduction interface beneath the coastline (40-50 km depth) is best constrained by the land-based GPS data and least constrained on the shallowest portion of the plate interface due to the ∼230 km distance between geodetic observations and the Japan trench. Citation: Loveless, J. P., and B. J. Meade (2011), Spatial correlation of interseismic coupling and coseismic rupture extent of the 2011 M W = 9.0 Tohoku-oki earthquake,

Many important insights regarding the coupling among climate, erosion, and tectonics have come from numerical simulations using coupled tectonic and surface process models. However, analyses to date have left the strength of the coupling between climate and tectonics uncertain and many questions unanswered. We present an approximate analytical solution for two‐sided orogenic wedges obeying a frictional rheology, and in a condition of flux steady state, that makes explicit the nature and sensitivity of the coupling between climate and deformation. We make the simplifying assumption that the wedge grows in a self‐similar fashion consistent with Airy isostasy such that topographic taper is invariant with orogen width, tectonic influx rate, and climate. We illustrate first how and why the form of the erosion rule matters to orogen evolution and then derive a physically based orogen‐scale erosion rule. We show that steady state orogen width, crest elevation, and crustal thickness are controlled by the ratio of accretionary flux to erosional efficiency to a power dictated by the erosion process. Remarkably, we show that for most combinations of parameters in the erosion law, rock uplift rate is more strongly controlled by erosional efficiency than it is by the accretionary flux. Further, assuming frontal accretion with no underplating, the spatial distribution of erosional efficiency dictates the relative rock uplift rates on the pro‐wedge and retro‐wedge and the time‐averaged trajectories of rocks through the orogen. The restriction to invariant frictional properties is conservative in these respects; systems subject to positive feedback between erosion and rheology will exhibit even stronger coupling among climate, erosion, and deformation than shown here.

This article provides an overview of current applications of machine learning (ML) in seismology. ML techniques are becoming increasingly widespread in seismology, with applications ranging from identifying unseen signals and patterns to extracting features that might improve our physical understanding. The survey of the applications in seismology presented here serves as a catalyst for further use of ML. Five research areas in seismology are surveyed in which ML classification, regression, clustering algorithms show promise: earthquake detection and phase picking, earthquake early warning (EEW), ground-motion prediction, seismic tomography, and earthquake geodesy. We conclude by discussing the need for a hybrid approach combining data-driven ML with traditional physical modeling.

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