Stochastic modelling of water deficit - B. S. DEORA; R. V. SINGH (Journal of Agrometeorology, 2009)
A stochastic model for weekly water deficit series, using 28 years climatological data, under climatic condition of S.K. Nagar has been developed. The turning point test and Kendall’s rank correlation test are applied for detecting the trend. Correlogram technique is used to detect the periodicity, which is then analyzed by Fourier series method. Significant harmonics were also identified. The statistical properties of the generated water deficit series were compared with observed series. The developed model was validated by predicting two years ahead and compared with the observed water deficit series, The test results indicated the high degree of model fitness. The developed model may be used for representing the time-based structure of the water deficit time series.