A new fluid-dynamic model is developed to numerically simulate the non-equilibrium dynamics of polydisperse gas–particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model, valid for low-concentration regimes (particle volume fraction less than 10⁻³) and particle Stokes number (St – i.e., the ratio between relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capability to describe gas–particle non-equilibrium effects. Direct Numerical Simulation accurately reproduces the dynamics of isotropic, compressible turbulence in subsonic regimes. For gas–particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of high-Reynolds number and high-temperature regimes in the presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to reproduce the averaged and instantaneous flow properties. In particular, the self-similar Gaussian radial profile and the development of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of the important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal and maximum plume height. For very fine particles (St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and preferentially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas–particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.

Destructive tsunamis are most often generated by large earthquakes occurring at subduction interfaces, but also other “atypical” sources—defined as crustal earthquakes and non-seismic sources altogether—may cause significant tsunami threats. Tsunamis may indeed be generated by different sources, such as earthquakes, submarine or coastal landslides, volcano-related phenomena, and atmospheric perturbations. The consideration of atypical sources is important worldwide, but it is especially prominent in complex tectonic settings such as the Mediterranean, the Caribbean, or the Indonesian archipelago. The recent disasters in Indonesia in 2018, caused by the Palu-Sulawesi magnitude Mw 7.5 crustal earthquake and by the collapse of the Anak-Krakatau volcano, recall the importance of such sources. Dealing with atypical sources represents a scientific, technical, and computational challenge, which depends on the capability of quantifying and managing uncertainty efficiently and of reducing it with accurate physical modelling. Here, we first introduce the general framework in which tsunami threats are treated, and then we review the current status and the expected future development of tsunami hazard quantifications and of the tsunami warning systems in Italy, with a specific focus on the treatment of atypical sources. In Italy, where the memory of historical atypical events like the 1908 Messina earthquake or the relatively recent 2002 Stromboli tsunami is still vivid, specific attention has been indeed dedicated to the progressive development of innovative strategies to deal with such atypical sources. More specifically, we review the (national) hazard analyses and their application for coastal planning, as well as the two operating tsunami warning systems: the national warning system for seismically generated tsunamis (SiAM), whose upstream component—the CAT-INGV—is also a Tsunami Service Provider of the North-eastern Atlantic, the Mediterranean and connected seas Tsunami Warning System (NEAMTWS) coordinated by the Intergovernmental Coordination Group established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO, and the local warning system for tsunamis generated by volcanic slides along the Sciara del Fuoco of Stromboli volcano. Finally, we review the state of knowledge about other potential tsunami sources that may generate significant tsunamis for the Italian coasts, but that are not presently considered in existing tsunami warning systems. This may be considered the first step towards their inclusion in the national tsunami hazard and warning programs.

We present a benchmark study aimed at identifying the most effective modeling approach for tsunami generation, propagation, and hazard in an active volcanic context, such as the island of Stromboli (Italy). We take as a reference scenario the 2002 landslide-generated tsunami event at Stromboli simulated to assess the relative sensitivity of numerical predictions to the landslide and the wave models, with our analysis limited to the submarine landslide case. Two numerical codes, at different levels of approximation, have been compared in this study: the NHWAVE three-dimensional non-hydrostatic model in sigma-coordinates and the Multilayer-HySEA model. In particular, different instances of Multilayer-HySEA with one or more vertical discretization layers, in hydrostatic and non-hydrostatic formulation and with different landslide models have been tested. Model results have been compared for the maximum runup along the shores of Stromboli village, and the waveform sampled at four proximal sites (two of them corresponding to the locations of the monitoring gauges, offshore the Sciara del Fuoco). Both rigid and deformable (granular) submarine landslide models, with volumes ranging from 7 to 25 million of cubic meters, have been used to trigger the water waves, with different physical descriptions of the mass movement. Close to the source, the maximum surface elevation and the resulting runup at the Stromboli village shores obtained with hydrostatic and non-hydrostatic models are similar. However, hydrostatic models overestimate (with respect to non-hydrostatic ones) the amplitude of the initial positive wave crest, whose height increases with the distance. Moreover, as expected, results indicate significant differences between the waveforms produced by the different models at proximal locations. The accurate modeling of near-field waveforms is particularly critical at Stromboli in the perspective of using the installed proximal sea-level gauges, together with numerical simulations, to characterize tsunami source in an early-warning system. We show that the use of non-hydrostatic models, coupled with a multilayer approach, allows a better description of the waveforms. However, the source description remains the most sensitive (and uncertain) aspect of the modeling. We finally show that non-hydrostatic models, such as Multilayer-HySEA, solved on accelerated GPU architectures, exhibit the optimal trade-off between accuracy and computational requirements, at least for the envisaged problem size and for what concerns the proximal wave field of tsunamis generated by volcano landslides. Their application and future developments are opening new avenues to tsunami early warning at Stromboli.