Box canyon erosion along the Canterbury coast (New Zealand): A rapid and episodic process controlled by rainfall intensity and substrate variability

Abstract

Abstract. Box canyon formation has been associated to groundwater seepage in unconsolidated sand to gravel sized sediments. Our understanding of box canyon evolution mostly relies on experiments and numerical simulations, and these rarely take into consideration contrasts in lithology and permeability. In addition, process-based observations and detailed instrumental analyses are rare. As a result, we have a poor understanding of the temporal scale of box canyon formation and the influence of geological heterogeneity on their formation. We address these issues along the Canterbury coast of the South Island (New Zealand) by integrating field observations, optically stimulated luminescence dating, multi-temporal Unmanned Aerial Vehicle and satellite data, time-domain electromagnetic data, and slope stability and landscape evolution modelling. We show that box canyon formation is a key process shaping the sandy gravel cliffs of the Canterbury coastline. It is an episodic process associated to groundwater flow that occurs once every 227 days on average, when rainfall intensities exceed 40 mm per day. The majority of the box canyons in a study area SE of Ashburton has undergone erosion, predominantly by elongation, during the last 11 years, with the most recent episode occurring 3 years ago. The two largest box canyons have not been eroded in the last 2 ka, however. Canyons can form at rates of up to 30 m per day via two processes: the formation of alcoves and tunnels by groundwater seepage, followed by retrogressive slope failure due to undermining and a decrease in shear strength driven by excess pore pressure development. The location of box canyons is determined by the occurrence of hydraulically-conductive zones, such as relict braided river channels and possibly tunnels, and of sand lenses exposed across sandy gravel cliff. We also show that box canyon formation is best represented by a linear diffusive model and geometrical scaling.