, Volume 27, Issue 1, pp 141–148 | Cite as

Mangrove stilt root morphology modeling for estimating hydraulic drag in tsunami inundation simulation

  • Wataru Ohira
  • Kiyoshi Honda
  • Masahiko Nagai
  • Anuchit Ratanasuwan
Original Paper


The submerged tree volume and the projection area of mangroves play a significant role in damping tsunami inundation flow with a distinct root formation above ground. We modeled the stilt root morphology of the Rhizophora sp., especially to incorporate into a hydraulic drag of tsunami inundation simulation. The equivalent Manning’s roughness coefficient has been used as the hydraulic drag of mangroves for the computation of inundation flow [Yanagisawa et al. (Coast Shelf Sci 81: 27–37, 2009)], but it could not elucidate the effectiveness under different tree conditions. The field data from 18 sample trees in Ranong Province, Thailand, were measured. The total number of primary roots, the root height at trunk, and the root-spread distance, the root diameter, and the vertical root angle from trunk could be estimated with the diameter of the breast height. The quadratic equation expressed the root curve of the primary stilt root, and functions to estimate root volume and projected area were derived by the integration of the equation that will be used to calculate drag force in tsunami simulation.


Mangrove Stilt root Morphology Tsunami inundation Hydraulic drag 



We thank Mr. Sukrid Krataichan, Chief of Laem Son National Park, Ranong, Department of National Park, wildlife and Plant, Thailand, for his assistance in the field survey.


  1. Dahdouh-Guebas F, Jayatissa LP, Di Nitto D, Bosire JO, Lo Seen D, Koedam N (2005) How effective were mangroves as a defence against the recent tsunami? Curr Biol: CB 15(12):R443–R447PubMedCrossRefGoogle Scholar
  2. Giesen W, Wulffraa MZ, Scholten L (2007) Mangrove guidebook for southeast Asia. FAO, Weltlands International, RomeGoogle Scholar
  3. Gill AM, Tomlinson PB (1977) Studies on the growth of red mangrove (Rhizophora mangle L.) 4. Adult root system. Biotropica 9(3):145–155CrossRefGoogle Scholar
  4. Harada K, Imamura F (2005) Effects of coastal forest on tsunami hazard mitigation—a preliminary investigation. In: Advances in natural and technological hazards research, vol 23. Springer, Netherlands, p 279–292. doi: 10.1007/1-4020-3331-1_17
  5. Kathiresan K, Rajendran N (2005) Coastal mangrove forests mitigated tsunami. Estuar Coast Shelf Sci 65(3):601–606CrossRefGoogle Scholar
  6. Mazda Y, Wolanski E, King B, Sase A, Ohtsuka D, Magi M (1997) Drag force due to vegetation in mangrove swamps. Mangroves Salt Marshes 1:193–1999CrossRefGoogle Scholar
  7. Ohira W, Honda K, Harada K (2012) Reduction of tsunami inundation by coastal forests in Yogyakarta, Indonesia: a numerical study. Nat Hazards Earth Syst Sci 12(1):85–95. doi: 10.5194/nhess-12-85-2012 CrossRefGoogle Scholar
  8. Ong JE, Gong WK, Wong CH (2004) Allometry and partitioning of the mangrove, Rhizophora apiculata. For Ecol Manag 188(1–3):395–408CrossRefGoogle Scholar
  9. Proisy C, Couteron P, Fo Fromard (2007) Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images. Remote Sens Environ 109(3):379–392CrossRefGoogle Scholar
  10. Prusinkiewicz P, Lindenmayer A (1990) The algorithmic beauty of plants, vol The virtual laboratory. Springer, New YorkCrossRefGoogle Scholar
  11. Running SW, Nemani RR, Peterson DL, Band LE, Potts DF, Pierce LL, Spanner MA (1989) Mapping regional forest evapotranspiration and photosynthesis by coupling satellite data with ecosystem simulation. Ecology 70(4):1090–1101CrossRefGoogle Scholar
  12. Sato K (1978) Studies on the protective functions of the mangrove forest against erosion and destruction (I). The morphological characteristics of the root system of Yaeyama hirugi (Rhizophora mucronata LAMK). Sci Bull Coll Agric, University Ryukyus 25:615–630Google Scholar
  13. Soares MLG, Schaeffer-Novelli Y (2005) Above-ground biomass of mangrove species. I. Analysis of models. Estuar Coast Shelf Sci 65:1–18Google Scholar
  14. Tomlinson PB (1986) The botany of mangrove. Cambridge University Press, New YorkGoogle Scholar
  15. Yanagisawa HKS, Goto K, Miyagi T, Imamura F, Ruangrassamee A, Tanavud C (2009) The reduction effects of mangrove forest on a tsunami based on field surveys at Pakarang Cape, Thailand and numerical analysis Estuarine. Coast Shelf Sci 81:27–37CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Wataru Ohira
    • 1
  • Kiyoshi Honda
    • 2
  • Masahiko Nagai
    • 3
  • Anuchit Ratanasuwan
    • 4
  1. 1.Remote Sensing and GIS, School of Engineering and TechnologyAsian Institute of TechnologyPathumthaniThailand
  2. 2.International Digital Earth Applied Science Research CenterChubu UniversityKasugaiJapan
  3. 3.Geoinformatics CenterAsian Institute of TechnologyPathumthaniThailand
  4. 4.Geo-Infomatics Division, Department of National ParkWildlife and Plant ConservationBangkokThailand

Personalised recommendations