Hydrological Sciences Journal - 2022 : Multiple imputations by chained equations for recovering missing daily streamflow observations: A case study of Langat River basin in Malaysia

Hamzah, Fatimah Bibi and Mohamad Hamzah, Firdaus and Mohd Razali, Siti Fatin and El-Shafie, Ahmed (2022) Hydrological Sciences Journal - 2022 : Multiple imputations by chained equations for recovering missing daily streamflow observations: A case study of Langat River basin in Malaysia. Hydrological Sciences Journal, 67 (1). 0-0. ISSN 0262-6667

Text Multiple imputations by chained equations for recovering missing daily streamflow observations a case study of Langat River basin in Malaysia.pdf Download (2MB)

Abstract

Missing values in hydrological studies are a common issue for hydrologists, especially in statistical analyses as a complete dataset is required. This work evaluates the performance of the multiple imputations by chained equations (MICE) approach to predicting recurrence in streamflow datasets. To evaluate and verify the effectiveness of the MICE approach in treating missing streamflow data, complete historical daily streamflow data from 2012 to 2014 were used. Later, MICE methods coupled with multiple linear regression (MLR) were applied to restore streamflow rates in Malaysia’s Langat River basin from 1978 to 2016. The best estimation methods are validated with tests such as adjusted R-squared (Adj R2), residual standard error (RSE), and mean absolute percentage error (MAPE). The findings revealed that the classification and regression tree (CART) method combined with MLR outperformed the other approaches tested, with the highest Adj R2 value and the lowest RSE and MAPE values observed regardless of missing conditions.

Item Type:	Article
Uncontrolled Keywords:	KEYWORDS missing data; multiple imputations; chained equations; streamflow; CART; MICE
Divisions:	Institute of Graduate Studies (IGS)
Depositing User:	LIBRARY1 UPTM
Date Deposited:	22 Jul 2025 03:08
Last Modified:	22 Jul 2025 03:08
URI:	http://eprints.kuptm.edu.my/id/eprint/4945

Actions (login required)

View Item