Publications

Devastating hot ash clouds (Pyroclastic density currents - PDCs) can run over hills and ridges crossing significant topographic obstacles. The processes that govern the interaction of PDCs with obstacles remain poorly understood leaving uncertainty in hazard planning and mitigation. Here, we report the results of large-scale experimental PDCs comprising hot volcanic particles and gas propagating across ridge-shaped obstacles.

Observations from high-speed video and measurements of the velocity, density and temperature structure of the flows are used to identify the flow processes that occur when PDCs propagate across and become partially blocked by hill-shaped topographic obstacles; and how these characteristics are recorded in PDC deposits. The facies architecture of experimental deposits across ridges resembles those of natural PDC deposits from Te Maari and Taupo¯ volcanoes (New Zealand). The findings of this study can guide the interpretation of PDC deposits or be taken into consideration in numerical models simulating the propagation of PDCs across complex topography for hazard forecast.

Infrastructure network modelling to identify elements of a system that are most vulnerable, and support risk mitigation strategies, and examine restoration plans.
Network models have been previously proposed for spatial cascades of natural hazard events. These have generally not taken time into account, with the cascade of events effectively assumed to occur instantaneously. This study introduces a dynamic, network-based stochastic model developed as a virtual testbed to simulate complex multihazard interactions between multiple temporal processes, often occurring on different time scales. 

We exemplify our methodology by investigating impacts of volcanic ashfall on river flow dynamics in the Rangitaiki and Tarawera river systems in New Zealand, simulating hydrological processes over a 365-day period with a volcanic eruption. Our results demonstrate how testbeds can be use to explore ‘‘what-if’’ cascading impacts scenarios, by providing a flexible, computationally efficient framework, offering crucial support for Disaster Risk Management (DRM) in volcanic regions.