Modelling monthly rainfall time series for Rahuri region in Maharashtra, India
DOI:
https://doi.org/10.53550/Keywords:
Harmonic analysis, Monthly rainfall time series, Stochastic component, Trend analysisAbstract
A stochastic model of monthly rainfall time series based on rainfall data for the years 1975 to 2010 was developed for Rahuri region in Maharashtra, India. The results indicate no deterministic trend component at 95% confidence level. However, the periodic component was found to be of 4 significant harmonics on the basis of Fourier series analysis. The stochastic components in the series were determined by autoregressive (AR) model of order six using the Statistical Application System (SAS-9.2) software. The independent stochastic component was found to be left skewed and the residual series was transformed by Box-Cox transformation into the normalized form. The developed time series model was used for regeneration and short-term forecast of monthly rainfall for 2009 and 2010. Results indicated that the properties propagated in the regenerated and predicted rainfall data series were comparable to those of the historical series which was revealed by integral square error (ISE), weighted pearson moment (WPM) and coefficient of efficiency (CE) as 3.53, 0.76 and 0.97 in calibration period and 3.05, 0.94 and 0.99 in validation period, respectively.
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