Flood risk index pattern assessment: case study in Langat River Basin

  • A.S.M. Saudi
  • M.K.A. Kamarudin
  • I.S.D. Ridzuan
  • R Ishak
  • A Azid
  • Z.I. Rizman
Keywords: flood risk index, PCA, SPC, artificial neural network, future prediction

Abstract

This study focus on the creation of flood risk index in the study area based on secondary data derived from the Department of Drainage and Irrigation (DID) since 1982-2012. Based on the result, it shows that the water level is the best variable to be taken for the purposed of flood warning alert system as the result for correlation coefficient was 1.000. The risk index has been created from the control limit value with range from 0-100. Result showed that 16.63% out of total result being classified as High Risk class for flood with risk index range from 70 and above. The accuracy of prediction of risk index being clarified by using ANN method and result obtained was 0.9936798 and the lowest RMSE of 0.662591 on the three hidden nodes to achieve an optimal result. The future prediction for UCL for water level in the river basin was 3.6 meter.

Keywords: flood risk index; PCA; SPC; artificial neural network; future prediction

Published
2018-01-16

Journal Identifiers


eISSN: 1112-9867