Spatial distributions of the storms are important since it is a major factor influencing flood formation in urban areas. However, the spatial allocations of rainfall data obtained from the interpolation method have many uncertainties. Thus, it is the objective of this research to derive the spatial distribution of storm events by using grid-based Kriging method. The best semi-variogram (SV) model is found for Kriging interpolation technique. Rectified skew orthomorphic (RSO) coordinates of 28 rainfall stations, located at upper part of the Klang river basin (675 km2) Malaysia, were used for generating a continuous storm event map using raster GIS software. The standard indicator for spatial correlations, Geary’s C, Moran’s I and SV were calculated for all events. These correlation coefficients are indicative of the spatial structure of point data. Continuous theoretical variogram models were plotted by using experimental variogram model. Positive correlation was found at average distance class of 6273 m for the pair-points. Based on the spatial correlation, maximum effective radius for a gauging station was found to be 3136 m. It was found that Gaussian model gave slightly better rainfall estimation at the position of samples as compared to the exponential and spherical models.
Key words: Kriging, spatial correlation, rainfall pattern, Gaussian model, Klang river basin.
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