Radar rainfall estimates comparison with kriging interpolation of gauged rain

Radar rainfall estimates has become an indispensable complementary to rain gauge data as input to flood prediction model though the use of traditional rain gages at a series of point has been improved with the application of spatial interpolation techniques such as Kriging. The paper presents Kriging interpolation for a network of rain gauges in Klang River Basin. The kriged rain values are compared with radar rainfall estimates to assess the advantages of both methods. Three types of semivariogram functions namely Spherical, Exponential and Gaussian have been applied in the interpolation. The results show that the Spherical semivariogram model performs the best in the interpolation. It is also found that Kriging interpolation of rain gauges data can provide useful comparative values to the radar rainfall estimates.