Evaluation and Reliability of CHIRPS Satellite Rainfall Products Against Station Rainfall Data in the Siwaluh Basin
The characteristics of rainfall in the Siwaluh river basin are poorly understood due to a lack of data. Many rainfall data are missing and many rain gauge posts are damaged. The availability of rainfall data is necessary for the planning and management of water resources. Technological advances can...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/84/1/94 |
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| Summary: | The characteristics of rainfall in the Siwaluh river basin are poorly understood due to a lack of data. Many rainfall data are missing and many rain gauge posts are damaged. The availability of rainfall data is necessary for the planning and management of water resources. Technological advances can utilize satellite-derived rainfall products. These offer an alternative for areas where data are limited. However, the use of satellite data must be validated with field data. Statistical analyses used for calibration and validation involve linear regression. Validation with evaluation statistics measures how good the model is. The required data is rainfall for 20 years. This study evaluates data from the Climate Hazard Group InfraRed precipitation with Station Data (CHIRPS) satellite with rainfall station data. Satellite rainfall data were compared with three field rainfall stations. This coding was used for one Siwaluh watershed. The results show that the calibration of CHIPRS satellite data produced a correction factor in the form of a linear regression equation. The validation stage corrected the values of NSE = 0.8, RSR = 0.5, and KR = 3.95% and gave an interpretation of a very good value. This research shows that the CHRIPS data are consistent with the rain station data. These findings provide the potential for satellite data to be used to assist decision-making in areas where rainfall data are limited. |
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| ISSN: | 2673-4591 |