MEASURING FLOOD RISK IN RATNAPURA TOWN AREA IN SRI LANKA

  • H. W. Y. J. Hettiwaththa Department of Statistics, University of Colombo, Sri Lanka
  • R. A. B. Abeygunawardana Department of Statistics, University of Colombo, Sri Lanka
Keywords: Flood, Forecasting, Risk, ARIMAX-GARCH

Abstract

Flood is a common chaotic natural problem frequently occurring in Ratnapura district. Recent chain of flood events that occurred in Ratnapura district has raised the question regarding the capability of defending civilian lives and property from this natural disaster. Ratnapura town area mainly face flood risks due to the over flow of Kalu river during the South West monsoon season. Flood risk cannot be directly measured. But flood risk is directly proportional to the river water level. When river water level is increasing, flood risk also increases. Since river water level can be taken as a measurement for flood risk, this analysis is based on forecasting river water level of Kalu River. Data were collected from meteorological stations at Ratnapura, Galabada, Guruluwana and Lellopitiya which are located in upper catchment area of Kalu River. ARIMAX-GARCH model was fitted to forecast water level using the rainfall data and the water discharge rate. The accuracy of the fitted model to forecast water level was high when comparing the estimated values with the actual values. Therefore the ARIMAX-GARCH model can be used to measure the flood risk in Ratnapura town area.

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References

Bolshakov, V. (2013). Regression-based Daugava River Flood Forecasting and Monitoring. Information Technology and Management Science, 137-142. doi:10.2478/itms-2013-0021

Campolo, M., Soldati, A., & Andreussi, P. (2003). Artificial neural network approach to flood forecasting in the River Arno. Hydrological Sciences–Journal–des Sciences Hydrologiques, 48(3), 381-398.

De Silva, M. M., Weerakoon, S. B., Herath, S., & Ratnayake, U. (2012). Flood Inundation Mapping along the Lower Reach of Kelani River Basin under the Impact of Climatic Change. Engineer - Journal of the Institution of Engineers, Sri Lanka, 45(2), 23-29.

Karunanayake, M. M., & Katupotha, J. (1990). An environmental profile of Ratnapura district. Coliombo 10: Central environmental authority.

Ljung, G. M., & Box, G. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303.

Nandalal, K. D. (2009). Use ofa hydrodynamic model to forecast Floods of Kalu River in Sri Lanka. Journal of Flood Risk Management, 151-158. doi:10.1111/j.1753-318X.2009.01032.x

Ratnayake, U., Sachindra, D. A., & Nandalal, K. D. (2010). Rainfall forecasting for flood prediction in the Nilwala basin.Proceedings of the International Conference on Sustainable Built Environment (ICSBE-2010), pp. 355-362.

Shamseldin, A. Y., Abdo, G. M., & Elzein, A. S. (1999). Real-Time Flood Forecasting on the Blue Nile River. Real-Time Flood Forecasting on the Blue Nile River, 24(1), 39-45. doi:10.1080/02508069908692132

Wang, W., Gelder, V. P., Vrijling, J. K., & Ma, J. (2005). Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes. Nonlinear Processes in Geophysics, 55-66.

Yaziz, S. R., Azizan, N. A., Zakaria, R., & Ahmad, M. H. (2013). The performance of hybrid ARIMA-GARCH modeling in forecasting gold price. 20th International Congress on Modelling and Simulation,Adelaide, Australia, 1201-1207.

Zhao, J. H., Dong, Z. Y., & Zhao, M. L. (2009). A statistical model for flood forecasting. Australasian Journal of Water Resources, 13(1), 43-52.

Published
2018-12-24
How to Cite
Hettiwaththa, H. W. Y. J., & Abeygunawardana, R. A. B. (2018). MEASURING FLOOD RISK IN RATNAPURA TOWN AREA IN SRI LANKA. Proceedings of The International Conference on Climate Change, 2(2), 31-41. https://doi.org/10.17501/iccc.2018.2203