Seasonal Water Level Variations and Predictive Modeling in Kampung Parit Hylam, Johor

¹ Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, MALAYSIA
² Eco Hytech Research Centre, Faculty of Civil Engineering and Built Environment, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, MALAYSIA

^* Corresponding author: sabariah@uthm.edu.my

Abstract

This study aimed to assess seasonal water level variations and their impacts in Kampung Parit Hylam, located on the West Coast of Johor. The research focused on the distinct effects of the Southwest Monsoon (April-September) dry season and the Northeast Monsoon (October-March) wet season. The study quantified water level variations across seasons by analyzing historical tidal records, weather data, and earth-level measurements. Using Minitab software, the project predicted short-term water level changes over 3, 6, and 9 months, based on historical trends and future climate scenarios. The Winter Multiplicative Method model, with a MAPE of 6% for low tides and 0% for high tides, was selected for its accuracy and ability to capture seasonal patterns. For March, June, and September 2024, actual low tide levels were 0.60 m, 0.00 m, and 0.60 m, respectively, while forecasted levels were 0.67 m, 0.68 m, and 0.54 m, with a 95% PI ranging from 0.60 m to 0.80 m, closely matching the actual values. Similarly, actual high tide levels were 2.60 m, 2.30 m, and 2.60 m, with forecasted levels at 2.67 m, 2.72 m, and 2.68 m, with a 95% PI of 2.60 m to 2.70 m, accurately covering the actual levels. These levels were significantly below the minimum bund height of 4 m, indicating effective protection. Additionally, the study evaluated the effectiveness of existing bunds in mitigating water level rise and structural vulnerability. The findings aimed to provide accurate water level forecasts, support effective water resource management, and offer recommendations for enhancing bund design and maintenance. This comprehensive analysis was intended to aid local authorities and the community in planning and preparing for the impacts of seasonal water level fluctuations.