Assessment of satellite-based rainfall products for drought monitoring in the Siak Watershed, Indonesia
Satellite-based rainfall products (SRPs) provide critical precipitation data, particularly in regions with limited or absent rainfall measurement stations. The accuracy of these products necessitates rigorous validation against observed rainfall data. This study evaluates four SRPs—CHIRPS, GPM IMERG...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Environmental Challenges |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667010025000538 |
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| Summary: | Satellite-based rainfall products (SRPs) provide critical precipitation data, particularly in regions with limited or absent rainfall measurement stations. The accuracy of these products necessitates rigorous validation against observed rainfall data. This study evaluates four SRPs—CHIRPS, GPM IMERG F, PERSIANN CCS CDR, and GSMaP—in the Siak Watershed, Riau Province, Indonesia, and investigates their utility in drought monitoring. Bias correction methods, including Modified Linear Correction (MLC), Distribution Mapping (DM), and Modified Linear Correction – Rainfall Intensity Characteristics (MLC-RIC), were applied during calibration and validation phases to enhance SRP accuracy. Validation was performed using data from four rainfall measurement stations spanning 2003 to 2020, with the best-performing SRPs identified through a ranking system based on 34 test parameters at daily, monthly, and annual time scales. The findings indicate that the MLC-RIC method, which introduces six correction factors based on rainfall intensity characteristics, outperforms other bias correction approaches. Among the SRPs, GSMaP demonstrated superior accuracy at daily and annual time scales, while GPM IMERG F excelled in capturing monthly rainfall patterns. Overall, GSMaP emerged as the most reliable product for rainfall estimation and drought monitoring, with GPM IMERG F and PERSIANN CCS CDR ranking second and third, respectively. These results were consistent across pre- and post-correction analyses. Beyond drought analysis, GSMaP shows potential for applications in hydrology, flood forecasting, and meteorology, underscoring its versatility in representing observed rainfall patterns. |
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| ISSN: | 2667-0100 |