FLOOD RISK PATTERN RECOGNITION BY USING ENVIRONMETRIC TECHNIQUE: A CASE STUDY IN LANGAT RIVER BASIN

Authors

  • Ahmad Shakir Mohd Saudi East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Hafizan Juahir East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Azman Azid East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Mohd Ekhwan Toriman School of Social, Development and Environmental Studies, Faculty of Social Sciences and Humanities, National University of Malaysia, 43600 Bangi, Selangor, Malaysia
  • Mohd Khairul Amri Kamarudin East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Madihah Mohd Saudi Faculty Science and Technology, University Science Islam Malaysia, 71800, Nilai, Negeri Sembilan
  • Ahmad Dasuki Mustafa East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Mohammad Azizi Amran East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu

DOI:

https://doi.org/10.11113/jt.v77.4142

Keywords:

Hydrological, climate change, flood risk, time series analysis, Factor analysis

Abstract

This study looks into the downscaling of statistical model to produce and predict hydrological modelling in the study area based on secondary data derived from the Department of Drainage and Irrigation (DID) since 1982-2012. The combination of chemometric method and time series analysis in this study showed that the monsoon season and rainfall did not affect the water level, but the suspended solid, stream flow and water level that revealed high correlation in correlation test with p-value < 0.0001, which affected the water level. The Factor analysis for the variables of the stream flow, suspended solid and water level showed strong factor pattern with coefficient more than 0.7, and 0.987, 1.000 and 1.000, respectively. Based on the Statistical  Process Control (SPC), the Upper Control Limit for water level, suspended solid and stream flow were 21.110 m3/s, 4624.553 tonnes/day, and 8.224 m/s, while the Lower Control Limit were 20.711 m, 2538.92 tonnes/day and 2.040 m/s. This shows that human development in the area gives high impact towards climate change and flood risk, and not the monsoon season. Prediction was carried out using the Artificial Neural Network (ANN) to classify risks into their own classes, and the rate of accuracy for the prediction was 97.1%. This meant that the points in the time series analysis which were located beyond Upper Control Limit were considered as High Risk class, and the probability for flood occurrence is very high. The other classes classified in this prediction are Caution Zone, Low Risk and No risk. This is important to set a trigger for warning system in the case of emergency response plan during flood.

 

Author Biographies

  • Ahmad Shakir Mohd Saudi, East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Hafizan Juahir, East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Azman Azid, East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Mohd Ekhwan Toriman, School of Social, Development and Environmental Studies, Faculty of Social Sciences and Humanities, National University of Malaysia, 43600 Bangi, Selangor, Malaysia

    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu

     

  • Mohd Khairul Amri Kamarudin, East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Madihah Mohd Saudi, Faculty Science and Technology, University Science Islam Malaysia, 71800, Nilai, Negeri Sembilan
    Faculty Science and Technology, University Science Islam Malaysia, 71800, Nilai, Negeri Sembilan
  • Ahmad Dasuki Mustafa, East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
  • Mohammad Azizi Amran, East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu
    East Coast Environmental Research Institute, University Sultan Zainal Abidin, Gong Badak Campus, 21300,Kuala Terengganu, Terengganu

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Published

2015-10-21

Issue

Vol. 77 No. 1: November 2015

Section

Science and Engineering

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How to Cite

FLOOD RISK PATTERN RECOGNITION BY USING ENVIRONMETRIC TECHNIQUE: A CASE STUDY IN LANGAT RIVER BASIN. (2015). Jurnal Teknologi (Sciences & Engineering), 77(1). https://doi.org/10.11113/jt.v77.4142