Abstract:
S In the field of hydrology, many researchers have developed time series models. Usually, the modelling uses time series data, such as daily rainfall, monthly rainfall, etc. In order to produce a good model, the frequencies used in the model must represent the data being modelled. Otherwise, the inaccurate frequencies used to cause the resulting model to be inaccurate. Several methods or techniques have been used to estimate the frequencies contained in time series data. These methods are the Fast Fourier Transform and Lomb-Scargle periodogram methods. This study used the Lomb-Scargle periodogram method to predict monthly rainfall time series data. In this research, the Lomb periodogram results in rainfall frequencies. The frequencies are created by using monthly rainfall time series data. Using the frequencies, the dominant frequencies can be selected. Periodic modelling of monthly rainfall time series can be adequately simulated using the dominant frequencies. The correlation coefficient between the monthly rainfall data with the monthly rainfall model can be used to measure the accuracy of the monthly rainfall model.
Page(s):
926-936
DOI:
DOI not available
Published:
Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 18, Issue: 8, Year: 2023