Comparison of the missing rainfall data method in enhancing discharge estimation

Abstract

Missing rainfall data can cause the results of an analysis to be inaccurate. This study aims to compare the performance of different methods in estimating missing rainfall data and to evaluate the estimated missing rainfall data method on hydrograph estimation. The methods used to estimate missing rainfall data in three selected stations include the arithmetic mean (AM) method, the inverse squared distance (ISD) method, and replacing missing value with zero value (ZERO). The study employs root mean square error (RMSE) to assess the accuracy and reliability of the methods. The estimated rainfall data are then utilized in Stormwater Management Modelling Software 5 (SWMM5) to evaluate the data impact on the discharge estimation. The results indicated that the AM method is the best method to estimate missing rainfall data by considering the lowest RMSE value equal to 1.185. In conclusion, the comparison of missing rainfall data methods in this study has shed light on their performance in enhancing discharge estimation.