Search USGS⌕ Search

USGS · 70033388

Distribution of tsunami interevent times

Abstract

The distribution of tsunami interevent times is analyzed using global and site-specific (Hilo, Hawaii) tsunami catalogs. An empirical probability density distribution is determined by binning the observed interevent times during a period in which the observation rate is approximately constant. The empirical distributions for both catalogs exhibit non-Poissonian behavior in which there is an abundance of short interevent times compared to an exponential distribution. Two types of statistical distributions are used to model this clustering behavior: (1) long-term clustering described by a universal scaling law, and (2) Omori law decay of aftershocks and triggered sources. The empirical and theoretical distributions all imply an increased hazard rate after a tsunami, followed by a gradual decrease with time approaching a constant hazard rate. Examination of tsunami sources suggests that many of the short interevent times are caused by triggered earthquakes, though the triggered events are not necessarily on the same fault.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E.L. Geist, T. Parsons. 2008-01-26. Distribution of tsunami interevent times. https://doi.org/10.1029/2007gl032690

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Evolution of summit magma pressure during the 2018 caldera collapse at Kılauea volcano

We utilized geodetic data from the 16 May to 4 August 2018 caldera collapse sequence to refine the geometries and pressure evolution of two summit reservoirs at Kīlauea volcano: the shallower Halema‘uma‘u (HMM) and deeper South Caldera (SC) reservoirs. We modeled magma reservoirs as pressurized spheroidal cavities and constrained reservoir geometries with Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar displacements. Inverting high-rate GPS and borehole tilt time series recovered time-dependent reservoir pressure changes and caldera ring fault shear stress. During the collapse sequence, the HMM reservoir accommodated episodic, co-collapse pressure increases of 1.9 MPa (median) and a net 5.8 MPa (median) decrease. Simultaneously, the SC reservoir underwent monotonic depressurization of 6.7 MPa (median). Negligible co-collapse pressure changes in the SC reservoir imply it was not exclusively supplying magma to the eruption vent. These results provide a coherent view of magma reservoir pressure evolution during the 2018 eruption.

Hawaii↗

EMIT reveals elevated calcite signatures in shorelines of Lake Powell and Lake Mead exposed by drought and Colorado River management

Nearly half of Earth’s seasonal freshwater storage variability occurs in human-managed reservoirs, resulting in large areas of reservoir-bed that are episodically inundated or subaerially exposed. Here we use hyperspectral data from NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) mission to map calcite mineral assemblages across exposed surfaces in two large U.S. reservoirs, Lake Mead and Lake Powell. Results show distinct patterns in the occurrence of carbonate, clay, and mica minerals. Reservoir-deposited sediments exhibited significantly higher calcite proportions than adjacent, lithologically similar, non-inundated terrestrial surfaces. These differences likely reflect hydrologically-driven calcite precipitation, wherein warm, clear, productive reservoir waters drive calcium carbonate out of solution. We also detect reductions in calcite proportions in areas of the shoreline disturbed by human recreation. EMIT's imaging capabilities enable rapid, high-resolution mineralogical inventories across vast areas where field sampling is infeasible. We find EMIT is a scalable tool for monitoring geochemical changes associated with large water level fluctuations.

Arizona, Nevada, Utah↗

First application of a coastal-dune model (AeoLiS) to simulate fluvial-aeolian morphodynamics

Quantifying aeolian processes is important to decision-making in river management and for optimizing strategies for ecosystem conservation, natural resource management, and recreation. We applied the AeoLiS aeolian transport model, originally developed for coastal environments, to a dryland river corridor to evaluate its ability to simulate sediment dynamics in a fluvial-aeolian system. The model reproduced spatial and temporal patterns of geomorphic change at a Grand Canyon sandbar, including aeolian dune formation, observed in field data. The model effectively captured trends in observed sediment movement in the spring and summer months. Thus, despite assuming a single grain-size, static vegetation, and not directly accounting for variable sediment supply from fluvial sources, the model performs well at capturing aeolian processes in a complex fluvial-aeolian system. AeoLiS demonstrates strong potential for dryland river applications and management, due to its flexibility and compatibility with coupled modeling frameworks.

Arizona↗