Mangroves as a coastal protection from waves in the Tong King Delta, Vietnam
Abstract
The wave reduction (wave period; 5–8 sec.) was investigated in amangrove reforestation area (Kandelia candel) close toaquaculture ponds in the Tong King delta, Vietnam.
On one site where only young mangrove trees grew, the wavereduction due to the drag force on the trees was hardlyeffective. On the other site where mangrove trees weresufficiently tall, the rate of wave reduction per 100 m was aslarge as 20%. Due to the high density of vegetation distributedthroughout the whole water depth, the effect of wave reductionwas large even when the water depth increased. These resultsdemonstrate the usefulness of mangrove reforestation for coastalprotection.
Full-text (PDF)
Available from: Yoshihiro Mazda, Mar 10, 2015
- CitationsCitations160
- ReferencesReferences13
- "The mangrove forest biome, commonly referred to as " mangroves " collectively, is the most important ecosystem within coastal inter-tidal zones in many tropical and semitropical regions. It plays a vital role in reducing damage from tsunamis (Danielsen et al. 2005), protecting land from erosion, and mitigating the effects of typhoons (Mazda et al. 1997). In addition, this ecosystem can act as a highly efficient carbon sink in the tropics (Donato et al. 2011), because mangroves can sequester carbon in both above and below-ground biomass as well as within sediment (Kauffman et al. 2014). "
[Show abstract] [Hide abstract] ABSTRACT: This study tested the use of machine learning techniques for the estimation of above-ground biomass (AGB) of Sonneratia caseolaris in a coastal area of Hai Phong city, Vietnam. We employed a GIS database and multi-layer perceptron neural networks (MLPNN) to build and verify an AGB model, drawing upon data from a survey of 1508 mangrove trees in 18 sampling plots and ALOS-2 PALSAR imagery. We assessed the model's performance using root-mean-square error, mean absolute error, coefficient of determination (R 2), and leave-one-out cross-validation. We also compared the model's usability with four machine learning techniques: support vector regression, radial basis function neural networks, Gaussian process, and random forest. The MLPNN model performed well and outperformed the machine learning techniques. The MLPNN model-estimated AGB ranged between 2.78 and 298.95 Mg ha −1 (average = 55.8 Mg ha −1); below-ground biomass ranged between 4.06 and 436.47 Mg ha −1 (average = 81.47 Mg ha −1), and total carbon stock ranged between 3.22 and 345.65 Mg C ha −1 (average = 64.52 Mg C ha −1). We conclude that ALOS-2 PALSAR data can be accurately used with MLPNN models for estimating mangrove forest biomass in tropical areas.- "The mangrove forest biome, commonly referred to as " mangroves " collectively, is the most important ecosystem within coastal inter-tidal zones in many tropical and semitropical regions. It plays a vital role in reducing damage from tsunamis (Danielsen et al. 2005), protecting land from erosion, and mitigating the effects of typhoons (Mazda et al. 1997). In addition, this ecosystem can act as a highly efficient carbon sink in the tropics (Donato et al. 2011), because mangroves can sequester carbon in both above and below-ground biomass as well as within sediment (Kauffman et al. 2014). "
ĐỘ DÀY RỪNG NGẬP MẶN ĐÁP ỨNG KHẢ NĂNG LÀM GIẢM TÁC ĐỘNG CỦA SÓNG TRIỀU ĐẾN VÙNG VEN BỜ TỈNH BẠC LIÊU
- "Một trong những giải pháp giảm thiểu tác động của sóng triều đến vùng bờ biển là phát triển hệ sinh thái rừng ngập mặn (Quỳnh, V.V., 2007; Marcel Marchand, 2008). Rừng ngập mặn có khả năng giúp giảm nhẹ năng lượng sóng, hạn chế tác động đến vùng ven bờ (Mazda et al, 1997Mazda et al, , 2006 Thampanya et al, 2006). Tuy nhiên, khả năng giảm sóng biển sẽ hạn chế khi các khu rừng ngập mặn ven biển bị suy giảm về độ dày và cấu trúc (Phan Nguyên Hồng và ctv, 2007). "
[Show abstract] [Hide abstract] ABSTRACT: Mangroves play an important role as natural levee system to protect the coast given impacts of tidal-wave and this ability would change according to thickness of mangrove. The study was done to determine the thickness of mangroves to meet the potential to reduce the impact of tidal - wave on the Bac Lieu coastal zone. The standard-plots with the distance of 20 m mangrove were set for each transect, ranging from the edge facing the sea to further inland of 100m and there were three transects to ensure the representation of the study area. The wave reduction coefficient of the mangroves with thickness from 20 m to 100 m in the range from 32.19 to 91.44% (corresponding the wave reduction ratio from 0.65 to 0.09). In addition, the wave reduction coefficient positive correlation with mangroves thickness (r = 0.96). However, the wave reduction ratio inversely correlated with mangroves thickness (r = -0.95). Thus, the tidal-wave energy going through the mangroves with thickness greater or equal of 76.27 m then the inability to influence the coastal zone (compared to standard of the wave reduction coefficient is 80% and the wave reduction ratio is 0.2).
People who read this publication also read
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.
This publication is from a journal that may support self archiving.
Learn more