• Ekha Yogafanny Department of Environmetal Engineering, Faculty of Mineral Technology, Universitas Pembangunan Nasional Veteran Yogyakarta, 55283, Indonesia
  • Djoko Legono Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta, 55281, Indonesia




Missing rainfall data, Inversed square distance, Arithmetic mean, Missing rainfall data, Inversed square distance, Arithmetic mean, RMSE, MAE


In water resources planning and management, it is essential to have reliable rainfall data. In many cases, rainfall data under the guardian national/ local institution are incomplete. Some data are missing, both monthly and annually. The missing data may persist due to neither damage nor human error. This study aims to estimate the missing rainfall data using two methods, i.e., the inverse square distance and the arithmetic mean methods. The study compared the two mentioned methods using root mean square error (RMSE) and mean absolute error (MAE) and to determine the consistency of rainfall data in all stations using double mass curve analysis. This study utilized the rainfall data from Tepus, Semanu, Rongkop, and Tanjungsari Stations in Gunung Kidul Regency, Yogyakarta Province, Indonesia. The model performance was tested by the root mean square error (RMSE) and mean absolute error (MAE). The rainfall data consistency was determined by double mass curve analysis. The results showed that the arithmetic mean method performed better rather than the inverse square distance method. The smallest RMSE and MAE values in the arithmetic method at the four stations have confirmed the statement. The rainfall data consistency analyzed by the double mass curve is consistent in all stations except Tepus Station.


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How to Cite

Yogafanny, E., & Legono, D. (2022). A COMPARATIVE STUDY OF MISSING RAINFALL DATA ANALYSIS USING THE METHODS OF INVERSED SQUARE DISTANCE AND ARITHMETIC MEAN. ASEAN Engineering Journal, 12(2), 69-74. https://doi.org/10.11113/aej.v12.16974