Sea-level projections using a NARX-NN model of tide gauge data for the coastal city of Kuala Terengganu in Malaysia

被引:6
作者
Bagheri, Milad [1 ]
Ibrahim, Zelina Z. [2 ]
Wolf, Isabelle D. [3 ,4 ]
Akhir, Mohd Fadzil [1 ]
Talaat, Wan Izatul Asma Wan [1 ]
Oryani, Bahareh [5 ]
机构
[1] Univ Malaysia Terengganu, Inst Oceanog & Environm, Kuala Nerus 21030, Malaysia
[2] Univ Putra Malaysia, Fac Environm & Forestry, Dept Environm, Seri Kembangan 43400, Malaysia
[3] Univ Wollongong, Sch Geog & Sustainable Communities, Northfields Ave, Wollongong, NSW 2522, Australia
[4] Univ New South Wales, Ctr Ecosyst Sci, Sydney, NSW 2052, Australia
[5] Seoul Natl Univ, Coll Engn, Technol Management Econ & Policy Program, 1 Gwanak Ro, Seoul 08826, South Korea
关键词
NARX; Time series; Environmental data analysis; Climatic; Shoreline; Simulation; ARTIFICIAL NEURAL-NETWORKS; RAINFALL; PREDICTION; RUNOFF; IMPACT; RISE; GIS;
D O I
10.1007/s11356-022-21662-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The impact of global warming presents an increased risk to the world's shorelines. The Intergovernmental Panel on Climate Change (IPCC) reported that the twenty-first century experienced a severe global mean sea-level rise due to human-induced climate change. Therefore, coastal planners require reasonably accurate estimates of the rate of sea-level rise and the potential impacts, including extreme sea-level changes, floods, and shoreline erosion. Also, land loss as a result of disturbance of shoreline is of interest as it damages properties and infrastructure. Using a nonlinear autoregressive network with an exogenous input (NARX) model, this study attempted to simulate (1991 to 2012) and predict (2013-2020) sea-level change along Merang kechil to Kuala Marang in Terengganu state shoreline areas. The simulation results show a rising trend with a maximum rate of 28.73 mm/year and an average of about 8.81 mm/year. In comparison, the prediction results show a rising sea level with a maximum rate of 79.26 mm/year and an average of about 25.34 mm/year. The database generated from this study can be used to inform shoreline defense strategies adapting to sea-level rise, flood, and erosion. Scientists can forecast sea-level increases beyond 2020 using simulated sea-level data up to 2020 and apply it for future research. The data also helps decision-makers choose measures for vulnerable shoreline settlements to adapt to sea-level rise. Notably, the data will provide essential information for policy development and implementation to facilitate operational decision-making processes for coastal cities.
引用
收藏
页码:81839 / 81857
页数:19
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