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Article Dans Une Revue Natural Hazards and Earth System Sciences Année : 2022

A modeling methodology to study the tributary-junction alluvial fan connectivity during a debris flow event

Alex Garcés
  • Fonction : Auteur
Gerardo Zegers
  • Fonction : Auteur
Germán Aguilar
  • Fonction : Auteur
Aldo Tamburrino
  • Fonction : Auteur
Santiago Montserrat
  • Fonction : Auteur

Résumé

Traditionally, interactions between tributary alluvial fans and the main river have been studied in the field and in the laboratory, giving rise to different conceptual models that explain their role in the sediment cascade. On the other hand, numerical modeling of these complex interactions is still limited because the broad debris flow transport regimes are associated with different sediment transport models. Even though sophisticated models capable of simulating many transport mechanisms simultaneously exist, they are restricted to research purposes due to their high computational cost. In this article, we propose a workflow to model the response of the Crucecita Alta alluvial fan in the Huasco Valley, located in the Atacama Desert, Chile, during an extreme storm event. Five different deposits were identified and associated with four debris flow surges for this alluvial fan. Using a commercial software application, our workflow concatenates these surges into one model. This study depicts the significance of the mechanical classification of debris flows to reproduce how an alluvial fan controls the tributary-river junction connectivity. Once our model is calibrated, we use our workflow to test if a channel is large enough to mitigate the impacts of these flows and the effects on the tributary-river junction connectivity.
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insu-03619989 , version 1 (25-03-2022)

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Alex Garcés, Gerardo Zegers, Albert Cabré, Germán Aguilar, Aldo Tamburrino, et al.. A modeling methodology to study the tributary-junction alluvial fan connectivity during a debris flow event. Natural Hazards and Earth System Sciences, 2022, 22, pp.377-393. ⟨10.5194/nhess-22-377-2022⟩. ⟨insu-03619989⟩
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