How do sea-level curves influence modeled marine terrace sequences? - Corinth Rift Laboratory Access content directly
Journal Articles Quaternary Science Reviews Year : 2020

How do sea-level curves influence modeled marine terrace sequences?

Abstract

Sequences of uplifted marine terraces are widespread and reflect the interaction between climatic and tectonic processes at multiple scales, yet their analysis is typically biased by the chosen sea-level (SL) curve. Here we explore the influence of Quaternary SL curves on the geometry of marine terrace sequences using landscape evolution models (LEMs). First, we modeled the young, rapidly uplifting sequence at Xylokastro (Corinth Rift; <240 ka; ∼1.5 mm/yr), which allowed us to constrain terrace ages, model parameters, and best-fitting SL curves. Models that better reproduced the terraced topography used a glacio-isostatically adjusted SL curve based on coral data (for ∼125 ka), and a eustatic SL curve based on ice-sheet models (for ∼240 ka). Second, we explored the opposite end-member of older, slower uplifting sequences (2.6 Ma; 0.1–0.2 mm/yr). We find that cliff diffusion is important to model terrace sequence morphology, and that a hydraulic-model based SL curve reproduced observed terrace morphologies best. Third, we modeled the effect of SL noise with various amplitudes and wavelengths on our interpretations, finding that younger, faster uplifting sequences are less noise-sensitive and thus generally more promising for LEM studies. Our results emphasize the importance of testing a variety of SL-curves within marine terrace studies, and highlight that accurate modeling through LEMs may provide valuable insight on climatic and tectonic forcing to Quaternary coastal evolution.
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Dates and versions

insu-02436871 , version 1 (16-11-2020)

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Gino de Gelder, Julius Jara-Muñoz, Daniel Melnick, David Fernández-Blanco, Hélène Rouby, et al.. How do sea-level curves influence modeled marine terrace sequences?. Quaternary Science Reviews, 2020, 229, pp.106132. ⟨10.1016/j.quascirev.2019.106132⟩. ⟨insu-02436871⟩
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