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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/amt-2020-355
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-355
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Nov 2020

10 Nov 2020

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This preprint is currently under review for the journal AMT.

Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

Gizachew Kabite Wedajo1,2, Misgana Kebede Muleta3, and Berhan Gessesse Awoke2,4 Gizachew Kabite Wedajo et al.
  • 1Department of Earth Sciences, Wollega University, P.O.Box 395, Nekemte, Ethiopia
  • 2Department of Remote Sensing, Entoto Observatory Research Center, Ethiopia Space Science Technology Institute, P.O.Box 33679, Addis Ababa, Ethiopia
  • 3Department of Civil and Environmental Engineering, California Polytechnic State University, San Luis Obispo, California, 93407
  • 4Department of Geography and Environmental Studies, Kotebe Metropolitan University, Addis Ababa, Ethiopia

Abstract. Precipitation is a crucial driver of hydrological processes. Ironically, reliable characterization of its spatiotemporal variability is challenging. Ground-based rainfall measurements using rain gauges can be more accurate. However, installing a dense gauging network to capture rainfall variability can be impractical. Satellite-based rainfall estimates (SREs) can be good alternatives, especially for data-scarce basins like in Ethiopia. However, SREs rainfall is plagued with uncertainties arising from many sources. The objective of this study was to evaluate the performance of the latest versions of several SREs products (i.e., CHIRPS2, IMERG6, TAMSAT3, and 3B42/3) for the Dhidhessa River Basin (DRB). Both statistical and hydrologic modelling approaches were used for performance evaluation. The Soil and Water Analysis Tool (SWAT) was used for hydrological simulations. The results showed that whereas all four SREs products are promising to estimate and detect rainfall for the DRB, the CHIRPS2 dataset performed the best at annual, seasonal, and monthly timescales. The hydrologic simulation-based evaluation showed that SWAT's calibration results are sensitive to the rainfall dataset. The hydrologic response of the basin is found to be dominated by the subsurface processes, primarily by the groundwater flux. Overall, the study showed that both CHIRPS2 and IMERG6 products can be reliable rainfall data sources for hydrologic analysis of the Dhidhessa River Basin.

Gizachew Kabite Wedajo et al.

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Gizachew Kabite Wedajo et al.

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Short summary
Satellite rainfall Estimates (SREs) are alternative data sources for data-scarce basins. However, the accuracy of the products is plagued by multiple sources of errors. Therefore, SREs should be evaluated for particular basins before using the product for any applications. The results of the study showed that CHIRPS2 and IMERG6 estimated rainfall and predicted hydrologic simulations well for Dhidhessa River Basin; shows remote sensing technology could improve hydrologic studies.
Satellite rainfall Estimates (SREs) are alternative data sources for data-scarce basins....
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