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Field measurement and prediction of drag in a planted Rhizophora mangrove forest
  • +7
  • Masaya Yoshikai,
  • Takashi Nakamura,
  • Dominic M Bautista,
  • Eugene C Herrera,
  • Alvin Baloloy,
  • Rempei Suwa,
  • Ryan Basina,
  • Yasmin H Primavera-Tirol,
  • Ariel Blanco,
  • Kazuo Nadaoka
Masaya Yoshikai
Tokyo Institute of Technology

Corresponding Author:[email protected]

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Takashi Nakamura
Tokyo Institute of Technology
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Dominic M Bautista
University of the Philippines, Diliman
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Eugene C Herrera
University of the Philippines, Diliman
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Alvin Baloloy
University of the Philippines, Diliman
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Rempei Suwa
Japan International Research Center for Agricultural Sciences
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Ryan Basina
Aklan State University
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Yasmin H Primavera-Tirol
Aklan State University
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Ariel Blanco
University of the Phili[[ines
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Kazuo Nadaoka
Tokyo Institute of Technology
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Abstract

Mangrove forests with complex root systems contribute to increased coastal protection through drag effects. Previous flume studies proposed a predictive model of drag in Rhizophora mangrove forests based on quadratic drag law. However, its general applicability on mangrove forests in the field has not been tested. To fill this knowledge gap, this study quantified drag in a 17-year-old planted Rhizophora mangrove forest using a comprehensive measurement of hydrodynamics and vegetation morphology. The vegetation projected area density, a, showed an approximate exponential increase towards the bed, mainly due to root branching. This vertical variation led to enhanced vegetation drag per unit water volume relative to velocity with decreasing water depth. Alternatively, the drag per vegetation projected area solely depended on the square of velocity, indicating association with the quadratic drag law. The derived drag coefficient (CD) was 1.0 ± 0.2 for tide-driven currents, consistent with previous flume studies. By using the mean value of derived CD (1.0), it was confirmed that the quadratic drag model expresses well the field-measured drag. We also presented a method for predicting a value for a, another unknown parameter in the drag model, using an empirical Rhizophora root model, and confirmed a successful prediction of a and drag. Therefore, the drag in a Rhizophora mangrove forest can be accurately predicted only using the input parameters of the Rhizophora root model – stem diameter and tree density. This provides insights into effectively implementing the drag model in hydrodynamic models for better representation of mangroves’ coastal protection function.