Modeling lava flow propagation is important to determine potential hazards to local populations. Thermo-rheological models such as PyFLOWGO track downflow cooling and rheological responses for open-channel, cooling-limited flows. The dominant radiative cooling component is governed partly by the lava emissivity, which is a material property that governs the radiative efficiency. Emissivity is commonly treated as a constant in cooling models, but is shown here to vary with temperature. To establish the effect of temperature on emissivity, high spatiotemporal, multispectral thermal infrared data were acquired of a small flow emplaced from a tumulus. An inverse correlation between temperature and emissivity was found, which was then integrated into the PyFLOWGO model. Incorporating a temperature-dependent emissivity term results in a ∼5% increase in flow length and < 75% lower total cumulative heat flux for the small flow. To evaluate the scalability of this relationship, we applied the modified PyFLOWGO model to simulations of the 2018 Lower East Rift Zone fissure 8 flow, emplaced between May 27 and June 3. Our model improves the emplacement match because of the ~ 30% lower heat flux resulting in a ∼7% longer flow compared to modeling using a constant emissivity (0.95). This 5–7% increase in length prior to ocean entry, realized by an accurate temperature-dependent emissivity term, is critical for developing the most accurate model of future flow hazard assessments, particularly if population centers lie in the flow’s path.
80NSSC17K0445
