Parameterization of Mangrove Root Structure of Rhizophora stylosa in Coastal Hydrodynamic Model

Nobuhito Mori,Che-Wei Chang,Tomomi Inoue,Sotaro Mori,Miho Miyauchi,Takuya Miyashita,Ryosuke Suganuma,Yasuaki Akaji,Audrius Sabunas,Shigeyuki Baba,Ko Hinokidani,Masashi Takagi,Hironoshin Koike,Tomoya Shimura

doi:10.3389/fbuil.2021.782219

Abstract

Mangroves are able to attenuate tsunamis, storm surges, and waves. Their protective function against wave disasters is gaining increasing attention as a typical example of the green infrastructure/Eco-DRR (Ecosystem-based Disaster Risk Reduction) in coastal regions. Hydrodynamic models commonly employed additional friction or a drag forcing term to represent mangrove-induced energy dissipation for simplicity. The well-known Morison-type formula (Morison et al. 1950) has been considered appropriate to model vegetation-induced resistance in which the information of the geometric properties of mangroves, including the root system, is needed. However, idealized vegetation configurations mainly were applied in the existing numerical models, and only a few field observations provided the empirical parameterization of the complex mangrove root structures. In this study, we conducted field surveys on the Iriomote Island of Okinawa, Japan, and Tarawa, Kiribati. We measured the representative parameters for the geometric properties of mangroves, Rhizophora stylosa, and their root system. By analyzing the data, significant correlations for hydrodynamic modeling were found among the key parameters such as the trunk diameter at breast height (DBH), the tree height H, the height of prop roots, and the projected areas of the root system. We also discussed the correlation of these representative factors with the tree age. These empirical relationships are summarized for numerical modeling at the end.

Highlights

Green infrastructure, known as ecosystem-based disaster risk reduction (Eco-DRR), has become popular in the context of coastal flooding reduction following the Intergovernmental Panel on Climate Change Fifth Assessment Report, AR5 (Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report—Working Group II, 2014) and the Sendai Framework for Disaster Risk Reduction 2015–2030 (UNISDR,2015)
Targeting at the parameterization of mangrove root structure, we collected the representative characteristics of mangrove geometry in fields, such as the tree height, the height of the root system, the spanning width of mangrove roots, the trunk diameter, and the frontal projected area
By analyzing the field data, we aimed to find out empirical formulas among the characteristic parameters of mangrove root geometry which are critical for the implementation of mangrove effects in numerical models for wave propagation

Summary

Introduction

Known as ecosystem-based disaster risk reduction (Eco-DRR), has become popular in the context of coastal flooding reduction following the Intergovernmental Panel on Climate Change Fifth Assessment Report, AR5 (Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report—Working Group II, 2014) and the Sendai Framework for Disaster Risk Reduction 2015–2030 (UNISDR,2015). Based on several reports of the 2011 Tohoku Earthquake Tsunami (e.g., Tanaka 2012), coastal pines can be critical in attenuating wave energy under small-to medium-sized tsunamis Another major type of coastal vegetation, mangroves were identified as useful buffers in the tropics and subtropics during the 2004 Indian Ocean Earthquake Tsunami (e.g., Danielsen et al, 2005) and other major natural disasters (e.g., Goda et al, 2019). In addition to their protective function against coastal disasters, afforestation and reforestation of mangroves have been adopted in Southeast Asia and the Pacific islands to improve the capacity for carbon storage and environmental recovery as a measure of climate change mitigation. The vegetation effects were integrated as enhanced bottom friction in some studies (e.g., Augustin et al, 2009; Yang et al, 2015), while the Morison-type formula (Morison et al, 1950) has recently been considered more straightforward to parameterize vegetation-induced resistance (e.g., Huang et al, 2011; Chakrabarti et al, 2017; Alagan Chella et al, 2020)

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