Sains Malaysiana 51(7)(2022): 2003-2012

http://doi.org/10.17576/jsm-2022-5107-05

Simulation and Analysis of Sea-Level Change from Tide Gauge Station by using Artificial Neural Network Models

(Simulasi dan Analisis Perubahan Aras Laut dari Stesen Tolok Air Pasang Surut dengan menggunakan Model Rangkaian Neural Buatan)

MILAD BAGHERI¹, ZELINA Z IBRAHIM², LATIFAH ABD MANAF², MOHD FADZIL AKHIR¹ & WAN IZATUL ASMA WAN TALAAT^1,*

¹Institute of Oceanography and Environment, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu Darul Iman, Malaysia

²Department of Environment, Faculty of Environmental and Forestry, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia

Diserahkan: 9 Oktober 2021/Diterima: 23 Disember 2021

Abstract

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.

Keywords: Climate change; coastal city; FF-NN; NARX-NN; tide gauge; time series analysis

Abstrak

Perubahan paras laut adalah salah satu hasil pemanasan global yang paling pasti. Perubahan paras laut akan meningkatkan hakisan di kawasan pantai, mengakibatkan pencerobohan ke dalam bekalan air, membanjiri paya pantai dan habitat penting lain dan menjadikan harta pantai lebih terdedah kepada hakisan dan banjir. Keadaan ini bertepatan dengan pembangunan sosio-ekonomi yang besar di kawasan bandar pantai. Kawasan pantai di Pantai Timur Semenanjung Malaysia terdedah kepada perubahan paras laut, banjir dan kejadian hakisan yang melampau. Perubahan Purata Aras Laut (MSL) bulanan telah disimulasikan dengan menggunakan dua model Rangkaian Neural Buatan (ANN), Rangkaian Neural Feed Hadapan (FF-NN) dan Model Rangkaian Neural Eksogen Autoregresif Tak Linear (NARX-NN). Kedua-dua model itu berjaya mencipta semula paras laut dan corak turun naiknya, menurut data. Model NARX-NN dengan seni bina (5-6-1) dan empat pilihan ketinggalan, sebaliknya, mendapat hasil terbaik. Penemuan simulasi kenaikan paras laut purata model menunjukkan bahawa Kuala Terengganu akan mempunyai aliran meningkat dan meningkat kira-kira 25.34 mm/tahun. Kertas ini mendedahkan bahawa pantai timur Malaysia sangat terdedah kepada kenaikan paras laut dan oleh itu, memerlukan dasar dan rancangan penyesuaian yang mampan untuk mengurus kesan yang berpotensi. Ia mengesyorkan bahawa pelbagai dasar, yang membolehkan kawasan diduduki lebih lama sebelum berundur akhirnya, boleh disesuaikan untuk menampung penempatan yang terdedah di pantai timur Malaysia.

Kata kunci: Analisis siri masa; bandar pantai; FF-NN; NARX-NN; perubahan iklim; tolok air pasang surut

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^*Pengarang untuk surat-menyurat; email: wia@umt.edu.my