Search for: All records

Abstract Landslides pose a significant hazard worldwide. Despite advances in landslide monitoring, predicting their size, timing, and location remains a major challenge. We revisit the 2017 Mud Creek landslide in California using radar interferometry, pixel tracking, and elevation change measurements from satellite and airborne radar, lidar, and optical data. Our analysis shows that pixel tracking of optical imagery captured the transition from slow motion to runaway acceleration starting ~ 1 month before catastrophic failure—an acceleration undetected by satellite InSAR alone. Strain rate maps revealed a new slip surface formed within the landslide body during acceleration, likely a key weakening mechanism. Failure forecast analysis indicates the acceleration followed a hyperbolic trend, suggesting failure time could have been predicted at least 6 days in advance. We also inverted for the landslide thickness during the slow-moving phase and found variations from < 1 to 36 m. While thickness inversions provide important first-order information on landslide size, more work is needed to better understand how landslide subsurface properties and deforming volumes may evolve during the transition from slow-to-fast motion. Our findings underscore the need for integrated remote sensing techniques to improve landslide monitoring and forecasting. Future advancements in operational monitoring systems and big data analysis will be critical for tracking slope instability and improving regional-scale failure predictions. 

Abstract. pyTopoComplexity is a Python package designed for efficient and customizable quantification of topographic complexity using four advanced methods: two-dimensional continuous wavelet transform analysis, fractal dimension estimation, rugosity index, and terrain position index calculations. This package addresses the lack of open-source software for these advanced terrain analysis techniques essential for modern geomorphology and geohazard research, enhancing data comparison and reproducibility. By assessing topographic complexity across multiple spatial scales, pyTopoComplexity allows users to identify characteristic morphological scales of studied landforms. The software repository also includes a Jupyter Notebook that integrates components from the surface-process modeling platform Landlab (Hobley et al., 2017), facilitating the exploration of how terrestrial processes, such as hillslope diffusion and stream power incision, drive the evolution of topographic complexity over time. When these complexity metrics are calibrated with absolute age dating, they offer a means to estimate in situ hillslope diffusivity and fluvial erodibility, which are critical factors in determining the efficiency of landscape recovery after significant geomorphic disturbances such as landslides. By integrating these features, pyTopoComplexity expands the analytical toolkit for measuring and simulating the time-dependent persistence of geomorphic signatures against environmental and geological forces. 

Abstract The grounding zone of a marine-terminating glacier, where ice begins to float, is a key control on glacier stability and ice discharge. Seismic deployments are a powerful means of studying both the geometry and processes of grounding zones; however, these regions are frequently inaccessible and dangerous for field work, and as a result are underrepresented in field studies. We report new data sets acquired at Eastwind Glacier, Antarctica, a relatively accessible grounding zone near McMurdo Station and Scott Base, as part of the Eastwind Glacier Geophysical Surveys on Top of an Antarctic Ice Shelf Transition, EGGS on TOAST, project. These data sets comprise a deployment of three-component seismic nodes and distributed acoustic sensing. The nodal deployment consisted of 330 nodes crossing the grounding zone, with all 330 nodes continuously recording for at least nine days, and 150 nodes recording for 19 days, in the austral summer of 2022/2023. Hammer-and-plate sources were recorded, with densely spaced shots along flow through the center of the array and shots located at every node. In 2023/2024, a 2.2 km fiber-optic cable was deployed for active source imaging by distributed acoustic sensing along and across flow, immediately downstream of the grounding line, for a period of 2 hr. Analysis of active source data recorded by the nodal array locates the point of flotation within the grounding zone and provides ice thickness estimates. We present initial analyses of passive source data, including icequake detection and location, and ambient noise analysis. We expect this data set to be of significant value to provide insight into fundamental grounding zone processes and as an event-rich cryoseismological data set on which to test novel methods of seismic analysis. 

Regional‐scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics‐based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three‐dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad‐scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km2) using 3D, limit‐equilibrium (LE)‐based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back‐calculated from inventoried landslides using 3D LE‐based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA. 

This Review synthesizes progress and outlines a new framework for understanding how land surface hazards interact and propagate as sediment cascades across Earth’s surface, influenced by interactions among the atmosphere, biosphere, hydrosphere, and solid Earth. Recent research highlights a gap in understanding these interactions on human timescales, given rapid climatic change and urban expansion into hazard-prone zones. We review how surface processes such as coseismic landslides and post-fire debris flows form a complex sequence of events that exacerbate hazard susceptibility. Moreover, innovations in modeling, remote sensing, and critical zone science can offer new opportunities for quantifying cascading hazards. Looking forward, societal resilience can increase by transforming our understanding of cascading hazards through advances in integrating data into comprehensive models that link across Earth systems. 

Abstract We construct a high‐resolution shear‐wave velocity (V_S) model for the uppermost 100 m using ambient noise tomography near the West Antarctic Ice Sheet Divide camp. This is achieved via joint inversion of Rayleigh wave phase velocity and H/V ratio, whose signal‐to‐noise ratios are boosted by three‐station interferometry and phase‐matched filtering, respectively. The V_Sshows a steep increase (0.04–0.9 km/s) in the top 5 m, with sharp interfaces at ∼8–12 m, followed by a gradual increase (1.2–1.8 km/s) between 10 and 45 m depth, and to 2 km/s at ∼65 m. The compressional‐wave velocity and empirically‐obtained density profile compares well with the results from Herglotz–Wiechert inversion of diving waves in active‐source shot experiments and ice core analysis. Our approach offers a tool to characterize high‐resolution properties of the firn and shallow ice column, which helps to infer the physical properties of deeper ice sheets, thereby contributes to improved understanding of Earth's cryosphere. 

Basal conditions that facilitate fast ice flow are still poorly understood and their parameterization in ice‐flow models results in high uncertainties in ice‐flow and consequent sea‐level rise projections. Direct observations of basal conditions beneath modern ice streams are limited due to the inaccessibility of the bed. One approach to understanding basal conditions is through investigating the basal landscape of ice streams and glaciers, which has been shaped by ice flow over the underlying substrate. Bedform variation together with observations of ice‐flow properties can reveal glaciological and geological conditions present during bedform formation. Here we map the subglacial landscape and identify basal conditions of Rutford Ice Stream (West Antarctica) using different visualization techniques on novel high‐resolution 3D radar data. This novel approach highlights small‐scale features and details of bedforms that would otherwise be invisible in conventional radar grids. Our data reveal bedforms of <300 m in length, surrounded by bedforms of >10 km in length. We correlate variations in bedform dimensions and spacing to different glaciological and geological factors. We find no significant correlation between local (<3 × 3 km) variations in bedform dimensions and variations in ice‐flow speed and (surface or basal) topography. We present a new model of subglacial sediment discharge, which proposes that variations in bedform dimensions are primarily driven by spatial variation in sediment properties and effective pressure. This work highlights the small‐scale spatial variability of basal conditions and its implications for basal slip. This is critical for more reliable parameterization of basal friction of ice streams in numerical models. 

ABSTRACT Earthquake-induced landslides can record information about the seismic shaking that generated them. In this study, we present new mapping, Light Detection and Ranging-derived roughness dating, and analysis of over 1000 deep-seated landslides from the Puget Lowlands of Washington, U.S.A., to probe the landscape for past Seattle fault earthquake information. With this new landslide inventory, we observe spatial and temporal evidence of landsliding related to the last major earthquake on the Seattle fault ∼1100 yr before present. We find spatial clusters of landslides that correlate with ground motions from recent 3D kinematic models of Seattle fault earthquakes. We also find temporal patterns in the landslide inventory that suggest earthquake-driven increases in landsliding. We compare the spatial and temporal landslide data with scenario-based ground motion models and find stronger evidence of the last major Seattle fault earthquake from this combined analysis than from spatial or temporal patterns alone. We also compare the landslide inventory with ground motions from different Seattle fault earthquake scenarios to determine the ground motion distributions that are most consistent with the landslide record. We find that earthquake scenarios that best match the clustering of ∼1100-year-old landslides produce the strongest shaking within a band that stretches from west to east across central Seattle as well as along the bluffs bordering the broader Puget Sound. Finally, we identify other landslide clusters (at 4.6–4.2 ka, 4.0–3.8 ka, 2.8–2.6 ka, and 2.2–2.0 ka) in the inventory which let us infer potential ground motions that may correspond to older Seattle fault earthquakes. Our method, which combines hindcasting of the surface response to the last major Seattle fault earthquake, using a roughness-aged landslide inventory with forecasts of modeled ground shaking from 3D seismic scenarios, showcases a powerful new approach to gleaning paleoseismic information from landscapes. 

Abstract Seismic imaging in 3-D holds great potential for improving our understanding of ice sheet structure and dynamics. Conducting 3-D imaging in remote areas is simplified by using lightweight and logistically straightforward sources. We report results from controlled seismic source tests carried out near the West Antarctic Ice Sheet Divide investigating the characteristics of two types of surface seismic sources, Poulter shots and detonating cord, for use in both 2-D and 3-D seismic surveys on glaciers. Both source types produced strong basal P-wave and S-wave reflections and multiples recorded in three components. The Poulter shots had a higher amplitude for low frequencies (<10 Hz) and comparable amplitude at high frequencies (>50 Hz) relative to the detonating cord. Amplitudes, frequencies, speed of source set-up, and cost all suggested Poulter shots to be the preferred surface source compared to detonating cord for future 2-D and 3-D seismic surveys on glaciers.