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ORIGINAL RESEARCH article

Front. Earth Sci.
Sec. Hydrosphere
Volume 12 - 2024 | doi: 10.3389/feart.2024.1421265

A Multi-algorithm Approach for Modeling Coastal Wetland Ecogeomorphology

Provisionally accepted
Zeli Tan Zeli Tan 1*L. Ruby Leung L. Ruby Leung 1Chang Liao Chang Liao 1Luca Carniello Luca Carniello 2José F. Rodríguez José F. Rodríguez 3Patricia M. Saco Patricia M. Saco 4Steven G. Sandi Steven G. Sandi 5
  • 1 Pacific Northwest National Laboratory (DOE), Richland, United States
  • 2 Department of Civil, Architectural and Environmental Engineering, School of Engineering, University of Padua, Padua, Veneto, Italy
  • 3 School of Engineering, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, Australia
  • 4 School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, New South Wales, Australia
  • 5 Deakin University, Geelong, Australia

The final, formatted version of the article will be published soon.

    Coastal wetlands play an important role in the global water and biogeochemical cycles. Climate change is making them more difficult to adapt to the fluctuation of sea levels and other environment changes. Given the importance of eco-geomorphological processes for coastal wetland resilience, many eco-geomorphology models differing in complexity and numerical schemes have been developed in recent decades. But their divergent estimates on the response of coastal wetlands to climate change indicate that substantial structural uncertainties exist in these models. To investigate the structural uncertainty of coastal wetland eco-geomorphology models, we developed a multi-algorithm model framework of eco-geomorphological processes, such as mineral accretion and organic matter accretion, within a single hydrodynamics model. The framework is designed to explore possible ways to represent coastal wetland eco-geomorphology in Earth system models and reduce the related uncertainties in global applications. We tested this model framework at three representative coastal wetland sites: two saltmarsh wetland (Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter Estuary). Through the model-data comparison, we showed the importance to use a multi-algorithm ensemble approach for more robust predictions of the evolution of coastal wetlands. We also find that more observations of mineral and organic matter accretion at different elevations of coastal wetlands and evaluation of the coastal wetland models at different sites of diverse environments can help reduce the model uncertainty.

    Keywords: Coastal wetland, Eco-geomorphology, model uncertainty, Mineral accretion, organic matter accretion

    Received: 22 Apr 2024; Accepted: 02 Jul 2024.

    Copyright: © 2024 Tan, Leung, Liao, Carniello, Rodríguez, Saco and Sandi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Zeli Tan, Pacific Northwest National Laboratory (DOE), Richland, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.