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.

对熔岩流传播进行建模对于确定对当地居民的潜在危害非常重要。诸如PyFLOWGO的热流变模型可跟踪下行流的冷却以及对明渠，冷却受限的流的流变响应。主导的辐射冷却成分部分地由熔岩的发射率决定，而熔岩的发射率是决定辐射效率的材料特性。在冷却模型中，通常将辐射率视为常数，但此处显示辐射率随温度而变化。为了确定温度对发射率的影响，获得了从地幔中注入的小流量的高时空多光谱热红外数据。发现温度和发射率之间存在反相关关系，然后将其整合到PyFLOWGO模型中。结合温度相关的发射率项会导致〜在流动长度增加5％为了评估这种关系的可扩展性，我们将修改后的PyFLOWGO模型应用于模拟了5月27日至6月3日之间发生的2018年下东裂谷裂隙8流动。我们的模型由于降低了约30％的热通量而改善了位置匹配与使用恒定发射率（0.95）进行建模相比，流量增加了约7％。通过精确的与温度相关的发射率项可以实现进入海洋之前长度增加5–7％，这对于开发最准确的未来流量危害评估模型至关重要，尤其是在人口中心位于流量路径中的情况下。