Comparative granulometric study of epiclastic deposits in volcanic environments
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Keywords

granulometric distribution
density countered plot
epiclastic deposits
debris avalanches
cohesive debris flows
non-cohesive debris flows
till.

How to Cite

Carreras-Soriano, L. M., & Capra-Pedol, L. (2018). Comparative granulometric study of epiclastic deposits in volcanic environments. Revista Mexicana De Ciencias Geológicas, 25(1), 97–114. Retrieved from https://rmcg.unam.mx/index.php/rmcg/article/view/674

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Abstract

The epiclastic deposits related to volcanic slope instability and erosion include matrix facies of debris avalanche, cohesive debris flow, non-cohesive debris flow and tills. Because of their similarity in textural features, a granulometric approach is here presented in attempt to compare these four types of epiclastic deposits and discuss they similarities or difference on the basis of their origin, transport and sedimentary processes. We compared the granulometric distribution of 337 samples on the basis of density diagrams, where mean and standard deviation are compared. Main achievements are: best sorted deposits are non-cohesive debris flows, whereas the poorest sorted are cohesive debris flows; till deposits are the coarsest, whereas non-cohesive debris flows are the finest. By looking only at the granulometric distribution of the matrix (<-1f), better sorting corresponds to higher content of sand respect to silt and clay fraction. These results show that particles transported by debris avalanches, debris flows and glaciers do no suffer fragmentation or significant grain segregation during transport. In contrast, non-cohesive debris flow particles are easily segregated and yield better sorting. Finally, the granulometric distribution of these four types of epiclastic deposits associated to volcanic aprons (cones, edifices) depends more on the granulometry of the source material than on transport and depositional processes. This work shows that the granulometric characteristics of epiclastic deposits should be supported by additional textural information to better constrain their classification.

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