Evaluation of Remote Mapping Techniques for Earthquake-Triggered Landslide Inventories in an Urban Subarctic Environment: A Case Study of the 2018 Anchorage, Alaska Earthquake

Earthquake-induced landslide inventories can be generated using field observations but doing so can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to produce landslide inventories, however, is dependent on a variety of factors, such as the extent of coverage, timing, and data quality, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover. With these challenges in mind, we use a combination of field observations and remote sensing data from multispectral, light detection and ranging (lidar), and synthetic aperture radar (SAR) sensors to produce a ground failure inventory for the urban areas affected by the 2018 magnitude (Mw) 7.1 Anchorage, Alaska earthquake. The earthquake occurred during late November at high latitude (∼61°N), and the lack of sunlight, persistent cloud cover, and snow cover that occurred after the earthquake made remote mapping challenging for this event. Despite these challenges, 43 landslides were manually mapped and classified using a combination of the datasets mentioned previously. Using this manually compiled inventory, we investigate the individual performance and reliability of three remote sensing techniques in this environment not typically hospitable to remotely sensed mapping. We found that differencing pre- and post-event normalized difference vegetation index maps and lidar worked best for identifying soil slumps and rapid soil flows, but not as well for small soil slides, soil block slides and rock falls. The SAR-based methods did not work well for identifying any landslide types because of high noise levels likely related to snow. Some landslides, especially those that resulted in minor surface displacement, were identifiable only from the field observations. This work highlights the importance of the rapid collection of field observations and provides guidance for future mappers on which techniques, or combination of techniques, will be most effective at remotely mapping landslides in a subarctic and urban environment.

Geotechnical lessons from the Mw 7.1 2018 Anchorage Alaska earthquake

The 2018 Mw 7.1 Anchorage, Alaska, earthquake is one of the largest earthquakes to strike near a major US city since the 1994 Northridge earthquake. The significance of this event motivated reconnaissance efforts to thoroughly document damage to the built environment. This article presents the spatial variability of ground motion intensity and its correlation with subsurface conditions in Anchorage, the identification of liquefaction triggering in the absence of surficial manifestations (such as sand boils or sediment ejecta), cyclic softening failure in organic soils, and the poor performance of anthropogenic fills subjected to cyclic loading. In addition to lessons from observed ground deformation and geotechnical effects on structures, this article provides case studies documenting the satisfactory behavior of improved ground subjected to cyclic loading and the appropriateness of current design procedures for the estimation of seismically induced sliding displacements of mechanically stabilized earth walls.

AutoCoulomb: An Automated Configurable Program to Calculate Coulomb Stress Changes on Receiver Faults with Any Orientation and its Application to the 2020 Mw 7.8 Simeonof Island, Alaska, Earthquake

Coulomb stress change is the change in resultant force of shear stress and friction imposed on a receiver fault plane. The resulting stress change is often computed using the Coulomb 3.4 and the postseismic Green’s functions and postseismic components (PSGRN-PSCMP) programs. Notwithstanding both preferences, both have incomplete optimally oriented failure planes (OOPs) and are inconvenient to resolve Coulomb stress changes on various fault planes placed in varying depths. Here, we present an alternative program termed AutoCoulomb. It leverages the shell command-line tool to automatically batch-process Coulomb stress changes on all sorts of receiver fault planes. We first validate the program. We then apply it to the 2020 Mw 7.8 Simeonof Island, Alaska, earthquake, as a case study. Our results show that Coulomb stress changes resolved on fixed receiver faults, using the three programs, are in line with each other. So are those resolved on 3D OOPs using the PSGRN–PSCMP and the AutoCoulomb programs. Nevertheless, Coulomb stress changes on 2D OOPs, generated by the AutoCoulomb program, always outweigh those done by the Coulomb 3.4 program, indicating that 2D OOPs constrained by the latter are not the most optimal. Some nonoptimal 2D OOPs result in the reversal of the signs of Coulomb stress changes, posing a risk of misleading stress shadows with negative Coulomb stress changes. For the case study, the 28 July 2020 Mw 6.1 aftershock received a positive coseismic Coulomb stress change of ∼3.5 bars. In contrast, the compounded coseismic Coulomb stress changes at the hypocenters of the 1946 Mw 8.2, the 1948 Mw 7.2, and the 2020 Mw 7.8 earthquakes are within a range from −1.1 to 0.1 bar, suggesting that coseismic Coulomb stress changes promoted by preceding mainshocks alone are not responsible for these mainshocks. Other factors, such as postseismic viscoelastic relaxation, afterslip, and slow slip, may contribute to promoting their occurrence.

Consecutive ruptures on a complex conjugate fault system during the 2018 Gulf of Alaska earthquake

We developed a flexible finite-fault inversion method for teleseismic P waveforms to obtain a detailed rupture process of a complex multiple-fault earthquake. We estimate the distribution of potency-rate density tensors on an assumed model plane to clarify rupture evolution processes, including variations of fault geometry. We applied our method to the 23 January 2018 Gulf of Alaska earthquake by representing slip on a projected horizontal model plane at a depth of 33.6 km to fit the distribution of aftershocks occurring within one week of the mainshock. The obtained source model, which successfully explained the complex teleseismic P waveforms, shows that the 2018 earthquake ruptured a conjugate system of N-S and E-W faults. The spatiotemporal rupture evolution indicates irregular rupture behavior involving a multiple-shock sequence, which is likely associated with discontinuities in the fault geometry that originated from E-W sea-floor fracture zones and N-S plate-bending faults.

Bayesian multiple rupture plane inversion to assess rupture complexity: application to the 2018 Mw 7.9 Alaska earthquake

<p>When the earthquake rupture is complex and ruptures of multiple fault segments contribute to the total energy release, the produced wavefield is the superposition of individual signals produced by single subevents. Resolving source complexity for large, shallow earthquakes can be used to improve ground shaking and surface slip estimations, and thus tsunami models. The 2018 Mw 7.9 Alaska earthquake showed such complexity: according to previous studies, the rupture initiated as a right-lateral strike-slip fault on a N-S oriented fault plane, but then jumped onto a left-lateral strike-slip fault oriented westward. Rupture complexity and presence of multiple subevents may characterize a number of other earthquakes. However, even when individual subevents are spatially and/or temporally separated, it is very difficult to identify them from far field recordings. In order to model complex earthquakes we have implemented a multiple double couple inversion scheme within Grond, a tool devoted to the robust characterization of earthquake source parameters included in the Pyrocko software. Given the large magnitude of the target earthquake, we perform our source inversions using broadband body waves data (P and S phases) at teleseismic distances. Our approach starts with a standard moment tensor inversion, which allows to get more insights about the centroid location and overall moment release. These values can then be used to constrain the double source inversion. We discuss the performance of the inversion for the Alaska earthquake, using synthetic and real data. First, we generated realistic synthetic waveforms for a two-subevents source, assuming double couple sources with the strike-slip mechanisms proposed for the Alaska earthquake. We model the synthetic dataset both using a moment tensor and a double double couple source, and demonstrate the stability of the double double couple inversion, which is able to reconstruct the two focal mechanisms, the moment ratio and the relative centroid locations of the two subevents. Synthetic tests show that the inversion accuracy can be in some cases reduced, in presence of noisy data and when the interevent time between subevents is short. A larger noise addition affects the retrieval of the focal mechanism orientations only in some cases, but in general all the parameters were well retrieved. Then, we test our tool using real data for the earthquake. The single source inversion shows that the centroid is shifted 27 s in time and 40 km towards NE with respect to the original assumed location retrieved from the gCMT catalogue. The following double double couple source inversion resolves two subevents with right-lateral and left-lateral strike-slip focal mechanisms and Mw 7.6 and 7.8 respectively. The subevent centroids are separated by less than 40 km in space and less than 20 s in time.</p>