4.3 Article

Benchmarking a new 2.5D shallow water model for lava flows

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DOI: 10.1016/j.jvolgeores.2023.107935

Keywords

Lava flows modelling; Heat transfer modelling; Temperature -dependent viscosity; Viscoplastic viscosity model; Depth -averaged model; Velocity and temperature profiles

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This study presents a new depth-averaged model for accurately modelling lava flows associated with volcanic eruptions, allowing for precise prediction of potential paths of destruction. The model incorporates enhancements to capture the vertical variations in velocity, thermal gradients, and viscosity of the flowing lava. Benchmark tests show that the modified model accurately reproduces essential flow features with short execution times.
Lava flows associated with effusive volcanic eruptions require accurate modelling in order to forecast potential paths of destruction. This study presents a new depth-averaged model that overcomes the classical shallow water hypothesis by incorporating several enhancements, allowing for a more precise representation of the flow dynamics and behaviour: (i) a parabolic profile which captures the vertical variations in velocity within the flow; (ii) a nonconstant vertical profile for temperature, enabling a more realistic representation of thermal gradients within the flowing lava; (iii) a viscoplastic temperature-dependent viscosity model to account for the non-Newtonian behaviour of lava; (iv) a transport equation for temperature accounting for the thermal heat exchanges with the environment and the soil. The first two modifications allow us to describe, under reasonable assumptions, the vertical structure of the flow, and for this reason, we put our model in the class of 2.5D models.To assess the performance of our modified model, comprehensive benchmark tests are conducted using both laboratory experiments and real-world lava flow data related to the 2014-2015 Pico do Fogo, Cape Verde, effusive eruption. The benchmarking analysis demonstrates that this model accurately reproduces, with short execution times, essential flow features such as flow front advancement and cooling processes.

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