A complete daily
rainfall dataset with no missing values is highly demand in a variety of meteorological and hydrological
purpose. In most situations, spatial interpolation techniques such as inverse distance and normal ratio methods were used for estimating missing
rainfall values at a particular target station which based on the available rainfall values recorded at the neighbor
stations. However, these two methods are found to be very useful in the case where the neighbor stations are very close and highly correlated with the target stations. In this study, several modification and improvement have been proposed to these methods in order to estimate the missing rainfall values at the target station using the information at the nearby stations. Four rain gauge stations at different locations are selected as the target stations to test the improvised methods. The result indicated that the modified methods improved the estimation of missing rainfall values at those target stations based on the Similarity Index, root Mean Square Error (RMSE) and Mean Absolute Error (MAE).