Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment

Sazali Osman, Norizan Abdul Aziz, Nurul Husaif, Lariyah Mohd Sidek, Aminah Shakirah, Faezah Hanum, Hidayah Basri

Research output: Contribution to journalConference article

Abstract

Flood is without doubt the most devastating natural disasters, striking numerous regions in Malaysia each year. During the last decades, the trend in flood damages has been growing exponentially. This is a consequence of the increasing frequency of heavy rain, changes in upstream land-use and a continuously increasing concentration of population and assets in flood prone areas. Malaysia, periodically, have faced with huge floods since previous years. Kelantan River basin, which located in the Northeast of Peninsular Malaysia, is prone to flood events in Malaysia. Kelantan River is the principal cause of flooding because it is constricted at its lower reaches. The capacity of the river at the downstream coastal area is less than 10,000 m3/s, therefore flood that exceeds this capacity will overspill the banks and discharge overland to the sea. Realizing the seriousness of the problems, it is vital in providing in time useful information for making crucial decisions especially to provide warning for any potential flood occurrence. In this study, stochastic flood forecasting model using stage regression method was applied to Kelantan River basin, in which the regression coefficients and equations was derived from the least square principle. The stochastic model were calibrated and validated which then shows that the equations derived are suitable to predict the hydrograph in Kelantan River basin. In conclusion, establishing a flood forecasting system would enhance the effectiveness of all other mitigation measures by providing time for appropriate actions. This has increased the importance of flood modelling for flood forecasts to issue advance warning in severe storm situations to reduce loss of lives and property damage.

Original languageEnglish
Article number07001
JournalMATEC Web of Conferences
Volume203
DOIs
Publication statusPublished - 17 Sep 2018
Event2018 International Conference on Civil, Offshore and Environmental Engineering 2018, ICCOEE 2018 - Kuala Lumpur, Malaysia
Duration: 13 Aug 201814 Aug 2018

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Materials Science(all)
  • Engineering(all)

Fingerprint Dive into the research topics of 'Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment'. Together they form a unique fingerprint.

  • Cite this