Engineering With Nature : the role of mangroves in coastal protection

Tomiczek, Tori; Wargula, Anna; Hurst, Nia; Bryant, Duncan B.; Provost, Leigh A.

doi:10.21079/11681/42420

Cited by 4 publications

(5 citation statements)

References 68 publications

(93 reference statements)

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“…Tree density is calculated by counting the number of individual trees in a plot and dividing by plot area. The density of trees in a mangrove forest has a significant influence on wave attenuation models (Novitzky 2010;Ohira et al 2013;Tomiczek et al 2021). Tree density (N) is calculated as follows:…”

Section: Appendix A: Mangrove Field Methodsmentioning

confidence: 99%

“…To date, most publications investigating NNBF to reduce flood risk have focused on wetlands, dunes, and beaches. However, there is growing interest in the application of mangroves to contribute to flood risk reduction (Tomiczek et al 2021). Observations and hindcast modeling of mangrove forests suggest they offer significant protection during tsunami and shorter-duration surge events by restricting the flow of water (Kathiresan and Rajendran 2005;Krauss et al 2009;Montgomery et al 2019), and field observations have highlighted their capacity to attenuate wave energy under low-energy conditions (Horstman et al 2014).…”

Section: Figures and Tablesmentioning

confidence: 99%

“…Appendix A: Mangrove Field Methods contains an overview of common mangrove field measurements and techniques. The target species used to develop the model was the North American red mangrove (Rhizophora mangle [R. mangle]), a native species found in Florida (Tomiczek et al 2021).…”

Section: Mangrove Forest Modelmentioning

confidence: 99%

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Wave attenuation of coastal mangroves at a near-prototype scale

Bryant¹,

Bryant²,

Provost³

et al. 2022

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A physical model study investigating the dissipation of wave energy by a 1:2.1 scale North American red mangrove forest was performed in a large-scale flume. The objectives were to measure the amount of wave attenuation afforded by mangroves, identify key hydrodynamic parameters influencing wave attenuation, and provide methodologies for application. Seventy-two hydrodynamic conditions, comprising irregular and regular waves, were tested. The analysis related the dissipation to three formulations that can provide estimates of wave attenuation for flood risk management projects considering mangroves: damping coefficient β, drag coefficient C𝐷, and Manning’s roughness coefficient 𝑛. The attenuation of the incident wave height through the 15.12 m long, 1:2.1 scale mangrove forest was exponential in form and varied from 13%–77%. Water depth and incident wave height strongly influenced the amount of wave attenuation. Accounting for differences in water depth using the sub-merged volume fraction resulted in a common fit of the damping coefficient as a function of relative wave height and wave steepness. The drag coefficient demonstrated a stronger relationship with the Keulegan–Carpenter number than the Reynolds number. The linear relationship between relative depth and Manning’s 𝑛 was stronger than that between Manning’s 𝑛 and either relative wave height or wave steepness.

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Section: Appendix A: Mangrove Field Methodsmentioning

confidence: 99%

Section: Figures and Tablesmentioning

confidence: 99%

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Wave attenuation of coastal mangroves at a near-prototype scale

Bryant¹,

Bryant²,

Provost³

et al. 2022

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“…Methods have been proposed to parameterize emergent vegetation including wetland plants (Feagin et al, 2011;Liu et al, 2021;Niazi et al, 2021) and specifically the trunk-prop root system of the Rhizophora genus (Ohira et al, 2013;Niazi et al, 2021). The model of Ohira et al (2013) was used as the basis of the design of the idealized mangrove tree for this study because it was the basis of previous laboratory studies (Maza et al, 2017(Maza et al, , 2019Tomiczek et al, 2020b) and an ongoing study at another laboratory (Tomiczek et al, 2021) and would facilitate comparisons of the results. Commercially available polyvinyl chloride (PVC) pipe with an outside diameter of 0.1143 m was used for the trunk, resulting in D BH = 0.1143 m. Following Ohira et al (2013) yielded a representative model tree with 14 roots and a mean root diameter, D Root , of 0.0286 m with the tallest root, H Rmax , located 1.35 m from the ground.…”

Section: Mangrove Specimenmentioning

confidence: 99%

Prototype-Scale Physical Model of Wave Attenuation Through a Mangrove Forest of Moderate Cross-Shore Thickness: LiDAR-Based Characterization and Reynolds Scaling for Engineering With Nature

et al. 2022

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This study investigates the potential of a Rhizophora mangrove forest of moderate cross-shore thickness to attenuate wave heights using an idealized prototype-scale physical model constructed in a 104 m long wave flume. An 18 m long cross-shore transect of an idealized red mangrove forest based on the trunk-prop root system was constructed in the flume. Two cases with forest densities of 0.75 and 0.375 stems/m2 and a third baseline case with no mangroves were considered. LiDAR was used to quantify the projected area per unit height and to estimate the effective diameter of the system. The methodology was accurate to within 2% of the known stem diameters and 10% of the known prop root diameters. Random and regular wave conditions seaward, throughout, and inland of the forest were measured to determine wave height decay rates and drag coefficients for relative water depths ranging 0.36 to 1.44. Wave height decay rates ranged 0.008–0.021 m–1 for the high-density cases and 0.004–0.010 m–1 for the low-density cases and were found to be a function of water depth. Doubling the forest density increased the decay rate by a factor two, consistent with previous studies for other types of emergent vegetation. Drag coefficients ranged 0.4–3.8, and were found to be dependent on the Reynolds number. Uncertainty in the estimates of the drag coefficient due to the measured projected area and measured wave attenuation was quantified and found to have average combined standard deviations of 0.58 and 0.56 for random and regular waves, respectively. Two previous reduced-scale studies of wave attenuation by mangroves compared well with the present study when their Reynolds numbers were re-scaled by λ3/2 where λ is the prototype-to-model geometric scale ratio. Using the combined data sets, an equation is proposed to estimate the drag coefficient for a Rhizophora mangrove forest: CD = 0.6 + 3e04/ReDBH with an uncertainty of 0.69 over the range 5e03 < ReDBH < 1.9e05, where ReDBH is based on the tree diameter at breast height. These results may improve engineering guidance for the use of mangroves and other emergent vegetation in coastal wave attenuation.

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“…It also has a salt excretion mechanism that helps the tree to tolerate the high salinity. L. racemosa, which is typically situated at higher elevations than the other two species and is rarely flooded, may not have visible roots but can produce prop roots if flooded for prolonged periods or subjected to anaerobic soil conditions (Tomlinson, 2016;Tomiczek et al, 2021). R. mangle presents thinner stems with higher mechanical resistance when compared with A. germinans, a tree species with wide girth and flare at the base (Méndez-Alonzo et al, 2015), while L. racemosa possesses a flexible and adaptive biomechanical structure that enables it to withstand strong winds (Spatz et al, 1987).…”

Section: Introductionmentioning

confidence: 99%