Flood risk pattern recognition by using environmetric technique: A case study in langat river basin

Ahmad Shakir Mohd Saudi, Hafizan Juahir, Azman Azid, Mohd. Ekhwan Toriman, Mohd Khairul Amri Kamarudin, Madihah Mohd Saudi, Ahmad Dasuki Mustafa, Mohammad Azizi Amran

Research output: Contribution to journalArticle

4 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)145-152
Number of pages8
JournalJurnal Teknologi
Volume77
Issue number1
DOIs
Publication statusPublished - 1 Nov 2015

Fingerprint

Water levels
Catchments
Pattern recognition
Rivers
Stream flow
Time series analysis
Flow of solids
Statistical process control
Alarm systems
Factor analysis
Irrigation
Climate change
Drainage
Rain
Neural networks

Keywords

  • Climate change
  • Factor analysis
  • Flood risk
  • Hydrological
  • Time series analysis

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Saudi, A. S. M., Juahir, H., Azid, A., Toriman, M. E., Kamarudin, M. K. A., Saudi, M. M., ... Amran, M. A. (2015). Flood risk pattern recognition by using environmetric technique: A case study in langat river basin. Jurnal Teknologi, 77(1), 145-152. https://doi.org/10.11113/jt.v77.4142

Flood risk pattern recognition by using environmetric technique : A case study in langat river basin. / Saudi, Ahmad Shakir Mohd; Juahir, Hafizan; Azid, Azman; Toriman, Mohd. Ekhwan; Kamarudin, Mohd Khairul Amri; Saudi, Madihah Mohd; Mustafa, Ahmad Dasuki; Amran, Mohammad Azizi.

In: Jurnal Teknologi, Vol. 77, No. 1, 01.11.2015, p. 145-152.

Research output: Contribution to journalArticle

Saudi, ASM, Juahir, H, Azid, A, Toriman, ME, Kamarudin, MKA, Saudi, MM, Mustafa, AD & Amran, MA 2015, 'Flood risk pattern recognition by using environmetric technique: A case study in langat river basin', Jurnal Teknologi, vol. 77, no. 1, pp. 145-152. https://doi.org/10.11113/jt.v77.4142
Saudi, Ahmad Shakir Mohd ; Juahir, Hafizan ; Azid, Azman ; Toriman, Mohd. Ekhwan ; Kamarudin, Mohd Khairul Amri ; Saudi, Madihah Mohd ; Mustafa, Ahmad Dasuki ; Amran, Mohammad Azizi. / Flood risk pattern recognition by using environmetric technique : A case study in langat river basin. In: Jurnal Teknologi. 2015 ; Vol. 77, No. 1. pp. 145-152.
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