Universal scaling between precursory duration and event size across mechanically driven geohazards

Abstract

Many catastrophic events, including landslides, rockbursts, glacier breakoffs, and volcanic eruptions, are preceded by an observable acceleration phase that offers a critical window for early warning and hazard mitigation; however, the duration of this precursory phase remains poorly constrained across sites, scales, and hazard types. This limitation arises because the onset of acceleration is often identified using heuristic thresholds or empirical criteria. Here, we introduce a physics-based framework that objectively constrains the precursory duration from accelerating dynamics, without prescribing the onset a priori or being tied to any specific observable. We analyse a global dataset of 109 geohazard events across seven continents over the past century, quantifying their precursory durations in a consistent manner. For mechanically driven instabilities, we identify a robust scaling between precursory duration and failure volume spanning more than ten orders of magnitude. When expressed in terms of a characteristic system size, this relationship is close to linear, consistent with finite-size scaling near a dynamical critical point. This behaviour indicates that precursory duration reflects the progressive growth of correlated deformation up to system-spanning scales, rather than local rupture kinetics. The resulting universality points to common organising mechanisms governing the approach to catastrophic failure across mechanically driven geohazards.

Figures (6)

• Figure 1: Representative examples of precursory dynamics and onset identification across geohazards. In each subfigure, the upper panel shows the monitoring data (grey symbols) together with the corresponding LPPLS model fit (blue line), while the lower panel shows the normalised regularised cost function $\tilde{\chi}^{2}$ as a function of the calibration window start time $\tau$. Vertical dashed lines indicate the identified onset time $\tau^{*}$ of precursory acceleration, vertical dotted lines mark the latest time of the $\tau$-scanning interval, and shaded regions highlight the inferred precursory phase. The examples include: (a) slope surface displacement (daily aggregation) prior to the catastrophic landslide on 5 September 2019, at Veslemannen, Norway; (b) tunnel roof displacement (hourly aggregation) prior to a violent rockburst on 4 June 2004, in an underground coal mine in New South Wales, Australia; (c) glacier surface displacement (daily aggregation) prior to rapid breakoffs in late September 2014, at the Grandes Jorasses glacier, Italy; and (d) seafloor uplift (weekly aggregation) prior to the volcanic eruption on 6 April 2011, at Axial Seamount, Pacific Ocean.
• Figure 2: Global distribution of 109 historical geohazard events. The dataset includes 49 landslides, 11 rockbursts, 17 glacier breakoffs, and 32 volcanic eruptions. Colours indicate hazard type and symbol size scales with the cube root of failure volume.
• Figure 3: Scaling relationship between precursory duration $T$ and failure volume $V$ for mechanically driven geohazards. Symbols indicate hazard type, the solid black line shows the best-fit power law regression $T \propto V^{0.35\pm0.05}$, and dashed lines mark the 95% confidence interval.
• Figure : Extended Data Fig. 1 | Precursory dynamics and onset identification for the Veslemannen landslides based on different radar point measurements. In each subfigure, the upper panel shows the monitoring data (grey symbols) together with the corresponding LPPLS fit (blue line), while the lower panel shows the normalised regularised cost function $\tilde{\chi}^{2}$ as a function of the calibration window start time $\tau$. Vertical dashed lines indicate the identified onset time $\tau^{*}$ of the precursory phase, vertical dotted lines mark the latest time of the $\tau$-scanning interval, and shaded regions highlight the inferred precursory phase.
• Figure : Extended Data Fig. 2 | Temporal evolution of the inferred onset time of precursory phase. The inferred onset time $\tau$ is shown as a function of the end time of the calibration window used for LPPLS fitting. Panels show examples for (a) the Veslemannen landslide, (b) the New South Wales rockburst, (c) the Grandes Jorasses glacier, and (d) the Axial Seamount volcano.