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Prediction of shoreline–shelf depositional process regime guided by palaeotidal modelling

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Author(s)

  • Daniel S. Collins
  • Alexandros Avdis
  • Martin R. Wells
  • Christopher D. Dean
  • Andrew J. Mitchell
  • Peter A. Allison
  • Howard D. Johnson
  • Gary J. Hampson
  • Jon Hill
  • Matthew D. Piggott

Department/unit(s)

Publication details

JournalEarth-Science Reviews
DateAccepted/In press - 1 Oct 2021
DateE-pub ahead of print (current) - 29 Oct 2021
Volume223
Early online date29/10/21
Original languageEnglish

Abstract

Ancient shoreline–shelf depositional systems are influenced by an unusually wide array of geological, biological and hydrodynamic processes, with sediment transport and deposition primarily determined by the interaction of river, wave (including storm) and tidal processes, and changes in relative sea level. Understanding the impact of these processes on shoreline–shelf morphodynamics and stratigraphic preservation remains challenging. Numerical modelling integrated with traditional facies analysis provides an increasingly viable approach, with the potential to quantify, and thereby improve understanding of, the impact of these complex coastal sedimentary processes. An integrated approach is presented here that focuses on palaeotidal modelling to investigate the controls on ancient tides and their influence on sedimentary deposition and preservation – one of the three cornerstones of the ternary process classification scheme of shoreline-shelf systems. Numerical tidal modelling methodology is reviewed and illustrated in three palaeotidal model case studies of different scales and focus. The results are synthesised in the context of shoreline–shelf processes, including a critique and modification of the process-based classification scheme. The emphasis on tidal processes reflects their global importance throughout Earth's history. Ancient palaeotidal models are able to highlight and quantify the following four controls on tidal processes: (1) the physiography (shape and depth) of oceans (1000s km scale) determines the degree of tidal resonance; (2) the physiography of ocean connections to partly enclosed water bodies (100–1000s km scale) determines the regional-scale flux of tidal energy (inflow versus outflow); (3) the physiography of continental shelves influences shelf tidal resonance potential; and (4) tides in relatively local-scale embayments (typically 1–10s km scale) are influenced by the balance of tidal amplification due to funnelling, shoaling and resonance effects versus frictional damping. In deep time, palaeogeographic and palaeobathymetric uncertainty can be accounted for in palaeotidal models by performing sensitivity analyses to different scenarios, across this range of spatial scales. These tidal process controls are incorporated into an updated predictive decision tree for determining shoreline–shelf process regime in terms of the relative interaction of wave, fluvial and tidal processes. The predictive decision tree considers the effects of basin physiography, shelf width and shoreline morphology on wave, fluvial and tidal processes separately. Uncertainty and ambiguity in applying the widely used three-tier process classification scheme are reduced by using the decision tree in conjunction with a proposed two-tier classification of process regime that is limited to primary and secondary processes. This two-tier classification scheme is illustrated in the three case studies, showing how integration of numerical modelling with facies analysis of the preserved stratigraphic record improves confidence in prediction of tide-influenced shoreline-shelf process regimes. Wider application of this approach will further improve process-based classifications and predictions of modern and ancient shoreline–shelf systems.

Bibliographical note

Funding Information:
The authors acknowledge financial support from Natural Environment Research Council (NERC), Leverhulme Trust, Shell International Ltd , and the Academy of Sciences of the Czech Republic . The authors thank Bob Dalrymple and Zheng Zhou for thorough, constructive reviewers and Jingping Xu for editorial comments. We also acknowledge support of Getech and Imperial College’s Grantham Institute and High-Performance Computing Service . D.M. Hodgson, B.K. Levell, R.B. Ainsworth and B.K. Vakarelov are thanked for valuable comments and discussion.

Publisher Copyright:
© 2021 Elsevier B.V.

    Research areas

  • Delta, Fluvial, Numerical modelling, Palaeotidal, Process regime, Shelf, Shoreline, Tide, Wave

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