title: Hydrodynamic modelling for mangrove afforestation at Haji Dorani, west coast peninsular Malaysia

authors: Awang, Nor Aslinda binti

subjects: Mangrove

abstract: Following the Indian Ocean tsunami disaster of 2004, which increased recognition of the importance of mangal for coastal protection, the Malaysian Government changed its‟ Policy in relation to mangrove and coastal vegetation. Since 2005, considerable effort had been made to establish mangroves in areas affected by the tsunami and rapid coastal development. Mangrove growth is affected by numerous coastal processes such as tides, waves, currents, the type of sediment, nutrient availability, and sediment erosion, transport and deposition. Therefore, a careful assessment of the multiple factors is necessary to facilitate successful replanting.
In this thesis, a study has been carried out to determine whether the tidal flats at Sungai Haji Dorani are suitable for mangrove afforestation. The specific objectives are to establish tidal current velocities and flow patterns from hydrodynamic modelling in order to identify the likely sediment transport pathways, and investigate wave shoaling and their role in sediment transport.
Sungai Haji Dorani is a low gradient muddy shoreline, consisting predominantly of silt and clay, over which occurs a fluid mud layer of about 0.3-0.5 m thick. There are three river sources of predominantly fine sediment, namely: Bernam, Haji Dorani and Selangor rivers. The existing mangal belt is very narrow (~20 m width) in the study area, and there is no natural mangrove regeneration to replace mangroves lost due to the tsunami and coastal development.
Simulations of tides, currents and waves were carried out using the 3DD hydraulic modelling suites. Results were calibrated and validated against measured conditions to facilitate an accurate representation of the study area, and provide a high level of confidence in the model outcomes. The calibrated models were used to simulate the impact of a proposed mangrove replanting project on waves, currents and sediment transport pathways.
Modelling results indicate that without mangroves, the average velocity over Haji Dorani is 0.14 ms-1 and peak velocities varied from 0.1-0.4 ms-1, which is high enough to transport fine sediments. The wave model predicted that at highest offshore spring tide and during storm conditions, waves of 0.2-2.0 m are transformed into 0.2-1.0 m high waves at the Haji Dorani shoreline, which will initiate fluidization of the bed sediment. These high waves, combined with tidal currents, can entrain the bed and transport sediment away.
Results from the POL3DD Particle Tracking Model indicate little sediment is deposited close to the Haji Dorani shore and any deposited would not permanently consolidate. High waves will erode the bed and re-suspend the sediment while strong tidal currents will transport it into deeper waters offshore.
Modelling of simulated mangrove replanting suggests a large reduction in current velocities and storm wave heights due to the increased friction provided by the mangrove roots and trunks. The particle tracking model shows that fine sediment from the Bernam and Haji Dorani rivers will accumulate along the adjacent coasts
in response to the reduced transport capability and reduced potential to re-suspend sediment. These sediments will be trapped by the mangal, which may result in the long term build-up of islands around the trees. Increased sedimentation will also provide habitat and nutrients for mangroves to reproduce and regenerate new trees naturally. At the same time, the mangrove trees will provide nutrients and shelter for marine life and terrestrial animals, as well as behave as a wave breaker, reducing incoming wave heights and tidal currents and thereby protecting the coast from high waves and storm surge.

text: Hydrodynamic modelling for mangrove afforestation at Haji Dorani, west coast peninsular Malaysia Following the Indian Ocean tsunami disaster of 2004, which increased recognition of the importance of mangal for coastal protection, the Malaysian Government changed its‟ Policy in relation to mangrove and coastal vegetation. Since 2005, considerable effort had been made to establish mangroves in areas affected by the tsunami and rapid coastal development. Mangrove growth is affected by numerous coastal processes such as tides, waves, currents, the type of sediment, nutrient availability, and sediment erosion, transport and deposition. Therefore, a careful assessment of the multiple factors is necessary to facilitate successful replanting.
In this thesis, a study has been carried out to determine whether the tidal flats at Sungai Haji Dorani are suitable for mangrove afforestation. The specific objectives are to establish tidal current velocities and flow patterns from hydrodynamic modelling in order to identify the likely sediment transport pathways, and investigate wave shoaling and their role in sediment transport.
Sungai Haji Dorani is a low gradient muddy shoreline, consisting predominantly of silt and clay, over which occurs a fluid mud layer of about 0.3-0.5 m thick. There are three river sources of predominantly fine sediment, namely: Bernam, Haji Dorani and Selangor rivers. The existing mangal belt is very narrow (~20 m width) in the study area, and there is no natural mangrove regeneration to replace mangroves lost due to the tsunami and coastal development.
Simulations of tides, currents and waves were carried out using the 3DD hydraulic modelling suites. Results were calibrated and validated against measured conditions to facilitate an accurate representation of the study area, and provide a high level of confidence in the model outcomes. The calibrated models were used to simulate the impact of a proposed mangrove replanting project on waves, currents and sediment transport pathways.
Modelling results indicate that without mangroves, the average velocity over Haji Dorani is 0.14 ms-1 and peak velocities varied from 0.1-0.4 ms-1, which is high enough to transport fine sediments. The wave model predicted that at highest offshore spring tide and during storm conditions, waves of 0.2-2.0 m are transformed into 0.2-1.0 m high waves at the Haji Dorani shoreline, which will initiate fluidization of the bed sediment. These high waves, combined with tidal currents, can entrain the bed and transport sediment away.
Results from the POL3DD Particle Tracking Model indicate little sediment is deposited close to the Haji Dorani shore and any deposited would not permanently consolidate. High waves will erode the bed and re-suspend the sediment while strong tidal currents will transport it into deeper waters offshore.
Modelling of simulated mangrove replanting suggests a large reduction in current velocities and storm wave heights due to the increased friction provided by the mangrove roots and trunks. The particle tracking model shows that fine sediment from the Bernam and Haji Dorani rivers will accumulate along the adjacent coasts
in response to the reduced transport capability and reduced potential to re-suspend sediment. These sediments will be trapped by the mangal, which may result in the long term build-up of islands around the trees. Increased sedimentation will also provide habitat and nutrients for mangroves to reproduce and regenerate new trees naturally. At the same time, the mangrove trees will provide nutrients and shelter for marine life and terrestrial animals, as well as behave as a wave breaker, reducing incoming wave heights and tidal currents and thereby protecting the coast from high waves and storm surge.

year: 2010

title: The nutrient impacts of forestry

authors: Beets, Peter

abstract: I have been working on New Zealand’s Land Use and Carbon Analysis System (LUCAS) for the Ministry for the Environment to quantify carbon stocks and changes for planted and natural forests. I originally started at Scion when it was called the Forest Research Institute working on tree nutrition. It is relevant for me to discuss this topic now because after we put the carbon models together I was able to come back to tree nutrition. I was amazed to find the papers we published years ago were still in journals and not incorporated into models that we could use for tree nutrition. I suggested to the managers that it was time for me to put away administrative things and managing projects and focus on reading all those publications, not just from Scion, but other agencies too and put them into models.

text: The nutrient impacts of forestry I have been working on New Zealand’s Land Use and Carbon Analysis System (LUCAS) for the Ministry for the Environment to quantify carbon stocks and changes for planted and natural forests. I originally started at Scion when it was called the Forest Research Institute working on tree nutrition. It is relevant for me to discuss this topic now because after we put the carbon models together I was able to come back to tree nutrition. I was amazed to find the papers we published years ago were still in journals and not incorporated into models that we could use for tree nutrition. I suggested to the managers that it was time for me to put away administrative things and managing projects and focus on reading all those publications, not just from Scion, but other agencies too and put them into models.

year: 2017

title: Harnessing Indigenous Tweets: The Reo Maori Twitter corpus

authors: Trye, David

subjects: Science & Technology

abstract: Te reo Māori, the Indigenous language of Aotearoa New Zealand, is a distinctive feature of the nation’s cultural heritage. This paper documents our efforts to build a corpus of 79,000 Māori-language tweets using computational methods. The Reo Māori Twitter (RMT) Corpus was created by targeting Māori-language users identified by the Indigenous Tweets website, pre-processing their data and filtering out non-Māori tweets, together with other sources of noise. Our motivation for creating such a resource is three-fold: (1) it serves as a rich and unique dataset for linguistic analysis of te reo Māori on social media; (2) it can be used as training data to develop and augment Natural Language Processing (NLP) tools with robust, real-world Māori-language applications; and (3) it will potentially promote awareness of, and encourage positive interaction with, the growing community of Māori tweeters, thereby increasing the use and visibility of te reo Māori in an online environment. While the corpus captures data from 2007 to 2020, our analysis shows that the number of tweets in the RMT Corpus peaked in 2014, and the number of active tweeters peaked in 2017, although at least 600 users were still active in 2020. To the best of our knowledge, the RMT Corpus is the largest publicly-available collection of social media data containing (almost) exclusively Māori text, making it a useful resource for language experts, NLP developers and Indigenous researchers alike.

text: Harnessing Indigenous Tweets: The Reo Maori Twitter corpus Te reo Māori, the Indigenous language of Aotearoa New Zealand, is a distinctive feature of the nation’s cultural heritage. This paper documents our efforts to build a corpus of 79,000 Māori-language tweets using computational methods. The Reo Māori Twitter (RMT) Corpus was created by targeting Māori-language users identified by the Indigenous Tweets website, pre-processing their data and filtering out non-Māori tweets, together with other sources of noise. Our motivation for creating such a resource is three-fold: (1) it serves as a rich and unique dataset for linguistic analysis of te reo Māori on social media; (2) it can be used as training data to develop and augment Natural Language Processing (NLP) tools with robust, real-world Māori-language applications; and (3) it will potentially promote awareness of, and encourage positive interaction with, the growing community of Māori tweeters, thereby increasing the use and visibility of te reo Māori in an online environment. While the corpus captures data from 2007 to 2020, our analysis shows that the number of tweets in the RMT Corpus peaked in 2014, and the number of active tweeters peaked in 2017, although at least 600 users were still active in 2020. To the best of our knowledge, the RMT Corpus is the largest publicly-available collection of social media data containing (almost) exclusively Māori text, making it a useful resource for language experts, NLP developers and Indigenous researchers alike.

year: 2022-02-14