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Junaidah Ariffin

Abstract

Countries with tropical climate like Malaysia are subjected to heavy rainfall concentrated in a short duration of time during certain months in a year. Such heavy rainfalls give rise to high runoff with peak flow occurring within a short duration leading to the occurrence of flash flood. A model that forecasts rainfall effectively is imperative as this helps to eliminate damages in the event of flood. Accuracy, reliability and timeliness are the elements required for an accurate forecast. This paper presents diagnostic analysis on the rainfall data using linear and bilinear models. The analysis confirmed that the Akaike’s Information Criterion (AIC), Akaike’s Bayesian Information Criteria (BIC), SBIC and the residual variances for Bilinear (BL) model is smaller than that of ARIMA (Autoregressive Integrated Moving Average) model. This suggests that the bilinear model fits the rainfall better. Thus, the finding may lead to the development of a more accurate model for flood forecasting.

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