Channel networks within lava flows: Formation, evolution, and implications for flow behavior

Abstract

New high-resolution maps of Hawaiian lava flows highlight complex topographically controlled channel networks. Network geometries range from distributary systems dominated by branching around local obstacles, to tributary systems constricted by topography. We combine 2-D network analysis tools developed for river systems and neural networks with 3-D lidar morphologic analysis and historical records of flow emplacement to investigate both the origins of channel networks and their influence on flow morphology and behavior. We find that network complexity is a function of underlying slope and that the degree of flow branching, network connectivity, and longevity of individual channels all influence the final flow morphology (flow and channel widths and levee heights). Furthermore, because channel networks govern the distribution of lava supply within a flow, changes in the channel topology can dramatically alter the effective volumetric flux in any one branch, which affects both flow length and advance rate. Specifically, branching will slow and shorten flows, while merging can accelerate and lengthen them. Consideration of channel networks is thus important for predicting lava flow behavior and mitigating flow hazards with diversion barriers. Observed relationships between network geometry, flow parameters, and morphology also offer insight into the interpretation of these features elsewhere on Earth and other terrestrial planets.

Benchmarking computational fluid dynamics models of lava flow simulation for hazard assessment, forecasting, and risk management

“…3; Dietterich et al, 2015). For simulations of flow into topographic obstacles, including artificial diversion structures (Scifoni et al, 2010;Fujita et al, 2009) or abrupt confining topography (Dietterich and Cashman, 2014), our results suggest that the 2D VolcFlow and COMSOL models consistently underestimate flow thickening at obstacles. It may therefore be more appropriate to use fully 3D models such as OpenFOAM or FLOW-3D to determine if a flow may overtop an obstacle.…”

“…Lava flows are ultimately controlled by topography, thus accurately incorporating ways in which flows interact with that topography is critical for modeling lava flow advance (Dietterich and Cashman, 2014). Additionally, lava flows are one of the few volcanic hazards that may be mitigated through engineering (e.g., Barberi and Carapezza, 2004).…”

“…Cooling, however, leads to the growth of a surface crust (Griffiths and Fink, 1993) and to lava crystallization, which introduces non-Newtonian rheology (Hulme, 1974;Lyman et al, 2005;Soule and Cashman, 2005;Castruccio et al 2013). Topography also exerts a major control on flow behavior, as the underlying slope drives advance rates, while topographic features may split and slow flows or confine and lengthen them (Dietterich and Cashman, 2014;Dietterich et al, 2015).…”

Tube coalescence in the Jingfudong lava tube and implications for lava flow hazard of Tengchong Volcanism

“…It was small in scale and fully developed, but almost totally intruded into the main tube. Dietterich & Cashman (2014) proposed that braiding index had a positive correlation with underlying slope and channel width, and flow thickness had a negative correlation with slope. Jingfudong lava tube provides a case for applying their model to the vertical case.…”

“…Harris & Rowland (2009) reasserted this view and emphasized that cooling rates play an important role in lava flow length. Dietterich & Cashman (2014) summarized that the emplacement of lava flow was controlled primarily by effusion rate, underlying slope and rheology of lava (e.g., Dragoni et al 2002Dragoni et al , 2008Honda, 2004), and proposed that the effusion rate at the vent could not record the lava supply to the flow front in accuracy. Furthermore, the branching, merging and slope also played important roles in lava emplacement and are affected strongly by topography.…”