Simulation and analysis of sea-level change from tide gauge station by using artificial neural network models

Sea level change is one of the most certain results of global warming. Sea level change would increase erosion in coastal areas, result in intrusion into water supplies, inundate coastal marshes and other important habitats, and make the coastal property more vulnerable to erosion and flooding. This situation coincides with the massive socio-economic development of the coastal city areas. The coastal areas of the East Coast of Peninsular Malaysia are vulnerable to sea-level change, flooding, and extreme erosion events. The monthly Mean Sea Level (MSL) change was simulated by using two Artificial Neural Network (ANN) models, Feed Forward- Neural Network (FF-NN) and Nonlinear Autoregressive Exogenous- Neural Network (NARX-NN) models. Both models did well in recreating sea levels and their fluctuating patterns, according to the data. The NARX-NN model with architecture (5-6-1) and four lag options, on the other hand, got the greatest results. The findings of the model’s mean sea level rise simulation show that Kuala Terengganu would have a growing and upward trend of roughly 25.34 mm/year. This paper shows that the eastern coast of Malaysia is highly vulnerable to sea-level rise and therefore, requires sustainable adaptation policies and plans to manage the potential impacts. It recommends that various policies, which enable areas to be occupied for longer before the eventual retreat, could be adapted to accommodate vulnerable settlements on the eastern coast of Malaysia

Firefly distribution and abundance on mangrove vegetation assemblages in Sepetang estuary, Peninsular Malaysia

Pteroptyx fireflies are commonly reported to congregate in large numbers in mangroves. Not much is known about the relationships between firefly distribution and abundance with specific mangrove vegetation assemblages. We conducted a study to investigate the vegetation assemblages that structure the distribution and abundance of Pteroptyx tener in Peninsular Malaysia. The distribution and abundance of fireflies were assessed along an 8 km stretch of mangroves in Sepetang estuary using visual assessment. Statistical analysis was carried out to test the correlation between length of display section and percentage cover of P. tener colonies and the relationship between percentage cover of fireflies with different vegetation assemblages. Five distinct vegetation assemblages were identified comprising different combination of four mangrove species. It was found that shorter display sections had higher percentage cover of P. tener colonies. In addition, vegetation assemblage which consisting of mainly Sonneratia caseolaris and Nypa fruticans was the most preferred type. The results of this study point to the necessity to consider not only a single mangrove species but the entire vegetation assemblage for firefly conservation

Burning embers: towards more transparent and robust climate-change risk assessments

The Intergovernmental Panel on Climate Change (IPCC) reports provide policy-relevant insights about climate impacts, vulnerabilities and adaptation through a process of peer-reviewed literature assessments underpinned by expert judgement. An iconic output from these assessments is the burning embers diagram, first used in the Third Assessment Report to visualize reasons for concern, which aggregate climate-change-related impacts and risks to various systems and sectors. These burning embers use colour transitions to show changes in the assessed level of risk to humans and ecosystems as a function of global mean temperature. In this Review, we outline the history and evolution of the burning embers and associated reasons for concern framework, focusing on the methodological approaches and advances. While the assessment framework and figure design have been broadly retained over time, refinements in methodology have occurred, including the consideration of different risks, use of confidence statements, more formalized protocols and standardized metrics. Comparison across reports reveals that the risk level at a given temperature has generally increased with each assessment cycle, reflecting accumulating scientific evidence. For future assessments, an explicit, transparent and systematic process of expert elicitation is needed to enhance comparability, quality and credibility of burning embers

Hazard Assessment and Modeling of Erosion and Sea Level Rise under Global Climate Change Conditions for Coastal City Management

Sea-level rise in response to climate change and global warming severely impacts coastal cities through increased soil erosion and other hazards. Therefore, simulating threats in coastal locations is critical for coastal city management and planning. The Nonlinear Autoregressive Exogenous-Neural Network (NARX-NN) was used in conjunction with the Bruun model and GIS methods to estimate the rate of sea-level rise, develop a coastal erosion model and coastal hazards maps, and simulate a sea-level increase with a maximum speed of 79.26 mm/year, and an average of about 25.34 mm/year, with a 1.48 m/year average erosion rate simulated from 2013 to 2020 along Merang kechil to Kuala Marang in Terengganu state coastal areas. According to the Bruun model, the areas most vulnerable to shoreline erosion are Kuala Nerus, Pendagan Buluh, and Kuala Ibai. Batu Rakit (Reach 1) has the highest rate of coastal erosion, at 28.16%, compared to 16.5 percent in Kuala Nerus (Reach 2) and 19.1% in Pengadang Buluh (Reach 3). The findings of this study might be utilized to build new coastal hazard erosion maps in a GIS framework, which could then be used as part of Malaysia\u27s East Coast zone vulnerability assessment. The findings may also aid in the prioritization of conservation efforts in afflicted areas or the decision to adapt to the effects of coastal erosion. This article presents a methodological framework and an erosion management prioritization system to help coastal managers, planners, and developers identify hazardous zones and improve coastal management plans using geospatial models

Impacts of future sea-level rise under global warming assessed from tide gauge records: A case study of the east coast economic region of Peninsular Malaysia

The effects of global warming are putting the world’s coasts at risk. Coastal planners need relatively accurate projections of the rate of sea-level rise and its possible consequences, such as extreme sea-level changes, flooding, and coastal erosion. The east coast of Peninsular Malaysia is vulnerable to sea-level change. The purpose of this study is to present an Artificial Neural Network (ANN) model to analyse sea-level change based on observed data of tide gauge, rainfall, sea level pressure, sea surface temperature, and wind. A Feed-forward Neural Network (FNN) approach was used on observed data from 1991 to 2012 to simulate and predict the sea level change until 2020 from five tide gauge stations in Kuala Terengganu along the East Coast of Malaysia. From 1991 to 2020, predictions estimate that sea level would increase at a pace of roughly 4.60 mm/year on average, with a rate of 2.05 ± 7.16 mm on the East Coast of Peninsular Malaysia. This study shows that Peninsular Malaysia’s East Coast is vulnerable to sea-level rise, particularly at Kula Terengganu, Terengganu state, with a rate of 1.38 ± 7.59 mm/year, and Tanjung Gelang, Pahang state, with a rate of 1.87 ± 7.33 mm/year. As a result, strategies and planning for long-term adaptation are needed to control potential consequences. Our research provides crucial information for decision-makers seeking to protect coastal cities from the risks of rising sea levels