Characterization of a landslide-triggered debris flow at a rainforest-covered mountain region in Brazil
Victor Carvalho Cabral, Fábio Augusto Gomes Vieira Reis, Fernando Mazo D’Affonseca, Ana Lúcia, Claudia Vanessa dos Santos Corrêa, Vinícius Queiroz Veloso, Marcelo Fischer Gramani, Agostinho Tadashi Ogura, Andréa Fregolente Lazaretti, Felipe Vemado, Augusto José Pereira Filho, Cláudia Cristina dos Santos, Eymar Silva Sampaio Lopes, Lis Maria Reoni Rabaco, Lucília do Carmo Giordano, Christiane Zarfl
Abstract
Abstract Debris flows represent great hazard to humans due to their high destructive power. Understanding their hydrogeomorphic dynamics is fundamental in hazard assessment studies, especially in subtropical and tropical regions where debris flows have scarcely been studied when compared to other mass-wasting processes. Thus, this study aims at systematically analyzing the meteorological and geomorphological factors that characterize a landslide-triggered debris flow at the Pedra Branca catchment (Serra do Mar, Brazil), to quantify the debris flow’s magnitude, peak discharge and velocity. A magnitude comparison with empirical equations (Italian Alps, Taiwan, Serra do Mar) is also conducted. The meteorological analysis is based on satellite data and rain gauge measurements, while the geomorphological characterization is based on terrestrial and aerial investigations, with high spatial resolution. The results indicate that it was a large-sized stony debris flow, with a total magnitude of 120,195 m 3 , a peak discharge of 2146.7 m 3 s −1 and a peak velocity of 26.5 m s −1 . The debris flow was triggered by a 188-mm rainfall in 3 h (maximum intensity of 128 mm h −1 ), with an estimated return period of 15 to 20 years, which, combined with the intense accumulation of on-channel debris (ca. 37,000 m 3 ), indicates that new high-magnitude debris flows in the catchment and the region are likely to occur within the next two decades. The knowledge of the potential frequency and magnitude ( F – M ) can support the creation of F – M relationships for Serra do Mar, a prerequisite for reliable hazard management and monitoring programs.