Volcano growth versus deformation by strike-slip faults: Morphometric characterization through analogue modelling

Volcanoes display diverse morphologies as a result of the complex interplay of several constructive and destructive processes. Scaled analogue models offer a tool to isolate and characterize the different processes. Here, we investigate the interplay between volcano growth and deformation caused by an underlying strike-slip fault through simple analogue models. In particular, we analyze the morphometry of analogue volcanoes resulting from different growth-to-deformation ratios. Deformation elongates the volcano edifice at an angle of 10-45 degrees from the fault trace along the extensional quadrants and generates a summit graben structure oriented perpendicular to the edifice elongation. The overall steepness of the edifice decreases, but steep slopes are preserved or increased on the lower compressional flanks, commonly related to small avalanches. Growth can partially to totally mask these features depending on the growth rate to strike-slip velocity ratio. The summit graben is easily masked even by low growth rates, whereas edifice elongation has the best preservation potential. Scaling of the experiments suggests that at volcanoes with growth rate (km(3)/yr) to strike-slip velocity (km/yr) ratios <= 3.8 km(3)/km, deformation features should be clearly preserved, whereas at volcanoes with ratios >= 15 km(3)/km, deformation features should be completely masked. The typical growth rates of volcanoes (0.01 to 1 km(3)/ka) and the typical velocities of strike-slip faults (1 to 20 mm/yr) suggest that in nature, growth rate to strike-slip velocity ratios can range over 3 orders of magnitude, spanning both types of end-members. Using examples of both active and inactive volcanoes located on strike-slip faults with variable elongation intensities and orientations, we highlight that the analogue models account for some of the morphometric variability observed at volcanoes in nature, although the role of vent distribution can be a key factor.