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- W2613066413 abstract "Extreme rainfall events such as floods and prolonged dry spells have become common phenomena in tropical countries like Malaysia. Floods are regular natural disasters in Malaysia, and happen nearly every year during the monsoon season. Recently, the magnitude of streamflow seems to have altered frequently, both spatially and temporally. Therefore, in order to have effective planning and an efficient water management system, it is advisable that streamflow data are analysed continuously over a period of time. If the data are treated as a set of functions rather than as a set of discrete values, then this ensures that they are not restricted by physical time. In addition, the derivatives of the functions may themselves be treated as functional data, which provides new information. The objective of this study is to develop a functional framework for hydrological applications using streamflow as the functional data. The daily flow series from the Kelantan River Basin were used as the main input in this study. Seven streamflow stations were employed in the analysis. Classification between the stations was done using the functional principal component, which was based on the results of the factor scores. The results indicated that two stations, namely the Kelantan River (Guillemard Bridge) and the Galas River, have a different flow pattern from the other streamflow stations. The flow curves of these two rivers are considered as the extreme curves because of their different magnitude and shape." @default.
- W2613066413 created "2017-05-19" @default.
- W2613066413 creator A5026800976 @default.
- W2613066413 date "2017-01-01" @default.
- W2613066413 modified "2023-10-18" @default.
- W2613066413 title "Streamflow profile classification using functional data analysis: A case study on the Kelantan River Basin" @default.
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- W2613066413 doi "https://doi.org/10.1063/1.4982836" @default.
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