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

Catchments; Disasters; Flood control; Floods; Land use; Least squares approximations; Offshore oil well production; Regression analysis; Rivers; Stochastic models; Stochastic systems; Storms; Watersheds; Flood forecasting; Flood forecasting models; Flood prone area; Least square principle; Mitigatio...

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Main Authors: Osman S., Aziz N.A., Husaif N., Sidek L.M., Shakirah A., Hanum F., Basri H.
Other Authors: 57189233135
Format: Conference Paper
Published: EDP Sciences 2023
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spelling my.uniten.dspace-236972023-05-29T14:51:04Z Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment Osman S. Aziz N.A. Husaif N. Sidek L.M. Shakirah A. Hanum F. Basri H. 57189233135 57204417425 57204434706 35070506500 57189241320 57204434777 57065823300 Catchments; Disasters; Flood control; Floods; Land use; Least squares approximations; Offshore oil well production; Regression analysis; Rivers; Stochastic models; Stochastic systems; Storms; Watersheds; Flood forecasting; Flood forecasting models; Flood prone area; Least square principle; Mitigation measures; Natural disasters; Regression coefficient; Regression method; Weather forecasting 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. � The Authors, published by EDP Sciences, 2018. Final 2023-05-29T06:51:04Z 2023-05-29T06:51:04Z 2018 Conference Paper 10.1051/matecconf/201820307001 2-s2.0-85055574952 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055574952&doi=10.1051%2fmatecconf%2f201820307001&partnerID=40&md5=250ac8d7c829e55b399480efce7f17f6 https://irepository.uniten.edu.my/handle/123456789/23697 203 7001 All Open Access, Gold, Green EDP Sciences Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Catchments; Disasters; Flood control; Floods; Land use; Least squares approximations; Offshore oil well production; Regression analysis; Rivers; Stochastic models; Stochastic systems; Storms; Watersheds; Flood forecasting; Flood forecasting models; Flood prone area; Least square principle; Mitigation measures; Natural disasters; Regression coefficient; Regression method; Weather forecasting
author2 57189233135
author_facet 57189233135
Osman S.
Aziz N.A.
Husaif N.
Sidek L.M.
Shakirah A.
Hanum F.
Basri H.
format Conference Paper
author Osman S.
Aziz N.A.
Husaif N.
Sidek L.M.
Shakirah A.
Hanum F.
Basri H.
spellingShingle Osman S.
Aziz N.A.
Husaif N.
Sidek L.M.
Shakirah A.
Hanum F.
Basri H.
Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment
author_sort Osman S.
title Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment
title_short Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment
title_full Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment
title_fullStr Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment
title_full_unstemmed Application of Stochastic Flood Forecasting Model Using Regression Method for Kelantan Catchment
title_sort application of stochastic flood forecasting model using regression method for kelantan catchment
publisher EDP Sciences
publishDate 2023
_version_ 1806427370507206656
score 13.214268