Multivariate time series modeling of monthly rainfall amounts


Abstract


This paper discusses the tting of suitable models to rainfall observations.
Daily rainfall amounts were aggregated to monthly data using the Thiessen
polygons method and multivariate seasonal vector integrated autoregressive
moving average models (sVARIMA) were tted to the monthly cumulative rainfall volume. The data were obtained from the 12 Palestinian meteorological gauge stations located across the 5 governorates of the Gaza Strip and incorporated 42 years (from 1973 to 2014) of irregular daily precipitation. It can be concluded that the use of sVARIMAmodels in the environmental science provide a useful method to forecast rainfall data as a preliminary guideline for short and long-term sustainable water resources management.


DOI Code: 10.1285/i20705948v10n1p65

Keywords: sVARIMAmodels, exact maximum likelihood estimation, state space representation, Gaza strip

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