Enhancing Daily Rainfall Data Completeness Using Satellite Rainfall Estimates

Rafika Andari; Nurhamidah Nurhamidah; Darwizal Daoed; Marzuki Marzuki

doi:10.2478/cee-2026-0008

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Enhancing Daily Rainfall Data Completeness Using Satellite Rainfall Estimates

Civil and Environmental Engineering

Volume 22 (2026): Issue 1 (March 2026)

By: Rafika Andari, Nurhamidah Nurhamidah, Darwizal Daoed and Marzuki Marzuki

Open Access

|Mar 2026

Figures & Tables

Map of The Kuranji Watershed (Source : Authors)

Distribution graph between rainfall at Batu Busuk Station and rainfall predicted by satellite data in 2014, a) TRMM satellite, b) GPM-IMERG satellite, and c) GSMaP satellite

Distribution graph between rainfall at Gunung Nago Station and rainfall predicted by satellite data in 2014, a) TRMM satellite, b) GPM-IMERG satellite, and c) GSMaP satellite

Distribution graph between rainfall at Limau Manis Station and rainfall predicted by satellite data in 2014, a) TRMM satellite, b) GPM-IMERG satellite, and c) GSMaP satellite

Performance Assessment Results of the Missing Rainfall Filling Method in 2015

Station Analyzed	Parameter Statistics	Linear Regression Method			Regional Weighting Method
Station Analyzed	Parameter Statistics	TRMM	GPM-IMERG	GSMaP	Regional Weighting Method
Batu Busuk	R [-]	0.78	0.78	0.77	0.63
	RMSE [-]	16.20	15.25	14.86	18.39
	NSE [-]	0.40	0.46	0.49	0.23
	RB [%]	53.89	42.87	36.61	−0.03
Gunung Nago	R [-]	0.63	0.65	0.64	0.74
	RMSE [-]	19.93	19.04	18.72	22.23
	NSE [-]	0.20	0.27	0.29	−0.01
	RB [%]	62.96	52.97	48.36	−0.01
Limau Manis	R [-]	0.77	0.80	0.75	0.67
	RMSE [-]	13.21	11.98	11.92	19.04
	NSE [-]	0.35	0.47	0.47	−0.34
	RB [%]	58.89	47.21	40.01	0.04

Performance Assessment Results of the Missing Rainfall Filling Method in 2016

Station Analyzed	Parameter Statistics	Linear Regression Method			Regional Weighting Method
Station Analyzed	Parameter Statistics	TRMM	GPM-IMERG	GSMaP	Regional Weighting Method
Batu Busuk	R [-]	0.84	0.85	0..83	0.66
	RMSE [-]	19.60	13.27	15.94	22.83
	NSE [-]	0.38	0.71	0.59	0.16
	RB [%]	62.51	14.90	36.95	0.05
Gunung Nago	R [-]	0.50	0.45	0.47	0.55
	RMSE [-]	57.24	55.57	56.37	49.08
	NSE [-]	0.04	0.10	0.07	0.30
	RB [%]	75.40	56.40	65.39	0.04
Limau Manis	R [-]	0.68	0.67	0.70	0.56
	RMSE [-]	16.82	15.33	14.67	23.80
	NSE [-]	0.31	0.42	0.47	−0.39
	RB [%]	50.95	−2.25	19.50	−0.05

Performance Assessment Results of the Missing Rainfall Filling Method in 2014

Station Analyzed	Parameter Statistics	Linear Regression Method			Regional Weighting Method
Station Analyzed	Parameter Statistics	TRMM	GPM-IMERG	GSMaP	Regional Weighting Method
Batu Busuk	R [-]	0.75	0.76	0.75	0.93
	RMSE [-]	16.94	16.17	16.77	8.89
	NSE [-]	0.50	0.54	0.51	0.86
	RB [%]	40.16	24.47	32.52	0.01
Gunung Nago	R [-]	0.74	0.76	0.76	0.92
	RMSE [-]	17.57	16.61	17.27	9.90
	NSE [-]	0.48	0.54	0.50	0.84
	RB [%]	43.54	27.77	36.04	−0.03
Limau Manis	R [-]	0.62	0.65	0.66	0.78
	RMSE [-]	16.53	15.76	15.80	13.72
	NSE [-]	0.37	0.43	0.42	0.57
	RB [%]	25.49	9.32	20.12	0.02

Recapitulation of Linear Regression Equations in Estimating Missing Rainfall Data in 2015

Observation Station	Satellite data	Linear Regression Equation	R² [-]
Batu Busuk	TRMM	y = 0.4335x + 5.6047	0.3089
	GPM-IMERG	y = 0.4357x + 7.8819	0.2985
	GSMaP	y = 0.4505x + 8.6002	0.2961
Gunung Nago	TRMM	y = 0.206x + 7.8342	0.0788
	GPM-IMERG	y = 0.2304x + 9.9243	0.0944
	GSMaP	y = 0.2411x + 10.688	0.0959
Limau Manis	TRMM	y = 0.2778x + 7.6487	0.0784
	GPM-IMERG	y = 0.3133x + 9.6995	0.0954
	GSMaP	y = 0.3262x + 10.464	0.0960

Recapitulation of Linear Regression Equations in Estimating Missing Rainfall Data in 2016

Observation Station	Satellite data	Linear Regression Equation	R² [-]
Batu Busuk	TRMM	y = 0.4595x + 4.6877	0.4659
	GPM-IMERG	y = 0.7002x + 7.8673	0.5021
	GSMaP	y = 0.5752x + 6.8665	0.4637
Gunung Nago	TRMM	y = 0.141x + 8.1554	0.2421
	GPM-IMERG	y = 0.1679x + 13.905	0.1592
	GSMaP	y = 0.1456x + 11.703	0.1639
Limau Manis	TRMM	y = 0.3968x + 5.9521	0.2292
	GPM-IMERG	y = 0.5874x + 9.9886	0.2331
	GSMaP	y = 0.5334x + 8.0376	0.2630

References

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Articles in this issue

DOI: https://doi.org/10.2478/cee-2026-0008 | Journal eISSN: 2199-6512 | Journal ISSN: 1336-5835

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Language: English

Page range: 105 - 118

Submitted on: Jun 22, 2025

Accepted on: Jul 29, 2025

Published on: Mar 24, 2026

Published by: University of Žilina

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

Missing rainfall data,

Linear regression,

Regional weighting,

Satellite

Related subjects:

Business and economics,

Political economics,

Economic theory, systems and structures,

Business management,

Industries,

Environmental management

© 2026 Rafika Andari, Nurhamidah Nurhamidah, Darwizal Daoed, Marzuki Marzuki, published by University of Žilina
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 22 (2026): Issue 1 (March 2026)

Enhancing Daily Rainfall Data Completeness Using Satellite Rainfall Estimates

Figures & Tables

Figure 1:

Figure 2:

Figure 3:

Figure 4:

Performance Assessment Results of the Missing Rainfall Filling Method in 2015

Performance Assessment Results of the Missing Rainfall Filling Method in 2016

Performance Assessment Results of the Missing Rainfall Filling Method in 2014

Recapitulation of Linear Regression Equations in Estimating Missing Rainfall Data in 2015

Recapitulation of Linear Regression Equations in Estimating Missing Rainfall Data in 2016

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