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<p> <?tk 4?>Ground rainfall records are crucial for hydrological modeling but often suffer from gaps due to aging infrastructure, poor data management, institutional challenges, and regional conflicts. This challenge is anticipated to worsen in the future, posing a continued threat to data reliability. Therefore, assessing the suitability of global satellite precipitation datasets is crucial for ensuring reliable hydrological simulations and addressing potential future data gaps. This study aims to simulate runoff in the Modjo catchment, Central Ethiopia, by applying the HEC-HMS model using both observed and satellite-derived precipitation data sets, and to compare the performance of each simulations. The study considered two global gridded precipitation products: CHIRPS and PERSIANN-CDR. In the HEC-HMS model setup, the study used the SCS Curve Number, SCS Unit Hydrograph, and the Muskingum method for the Loss, transform, and routing model, respectively. Hydro-meteorological data, collected daily, were compiled and prepared for the process of model calibration (spanning 2010–2019) and validation (2020–2023). The HEC-HMS model achieved strong performance with observed rainfall data, yielding NSE values of 0.85 (calibration) and 0.77 (validation), alongside high R<sup>2</sup> scores of 0.90 and 0.84, respectively. PBIAS remained minimal at − 4.89% and − 8.68%, indicating slight overestimation. CHIRPS data also performed well, with NSE at 0.73 (calibration) and 0.65 (validation), R<sup>2</sup> at 0.76 and 0.66, and PBIAS at − 5.6% and − 10.98%, showing moderate overestimation. PERSIANN-CDR delivered weaker results, with NSE dropping to 0.63 and 0.56, R<sup>2</sup> at 0.71 and 0.62, and higher PBIAS (− 19.56% and − 25.1%), confirming significant overestimation. CHIRPS outperformed PERSIANN-CDR but lagged behind observed data. The model results have revealed that global precipitation products have highlighted a promising and observed precipitation an effective performance in simulating runoff over the central Ethiopian case. It is recommended to incorporate an alternative remotely sensed rainfall product or apply a merging technique, then evaluate the results and analyze their impact on flow simulation performance.</p>

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Comparative rainfall-runoff hydrological modeling over central Ethiopia using ground observation and global satellite precipitation products: remote sensing support for water resource management

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月23日

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  • Bereket Abera Bedada

摘要

Ground rainfall records are crucial for hydrological modeling but often suffer from gaps due to aging infrastructure, poor data management, institutional challenges, and regional conflicts. This challenge is anticipated to worsen in the future, posing a continued threat to data reliability. Therefore, assessing the suitability of global satellite precipitation datasets is crucial for ensuring reliable hydrological simulations and addressing potential future data gaps. This study aims to simulate runoff in the Modjo catchment, Central Ethiopia, by applying the HEC-HMS model using both observed and satellite-derived precipitation data sets, and to compare the performance of each simulations. The study considered two global gridded precipitation products: CHIRPS and PERSIANN-CDR. In the HEC-HMS model setup, the study used the SCS Curve Number, SCS Unit Hydrograph, and the Muskingum method for the Loss, transform, and routing model, respectively. Hydro-meteorological data, collected daily, were compiled and prepared for the process of model calibration (spanning 2010–2019) and validation (2020–2023). The HEC-HMS model achieved strong performance with observed rainfall data, yielding NSE values of 0.85 (calibration) and 0.77 (validation), alongside high R2 scores of 0.90 and 0.84, respectively. PBIAS remained minimal at − 4.89% and − 8.68%, indicating slight overestimation. CHIRPS data also performed well, with NSE at 0.73 (calibration) and 0.65 (validation), R2 at 0.76 and 0.66, and PBIAS at − 5.6% and − 10.98%, showing moderate overestimation. PERSIANN-CDR delivered weaker results, with NSE dropping to 0.63 and 0.56, R2 at 0.71 and 0.62, and higher PBIAS (− 19.56% and − 25.1%), confirming significant overestimation. CHIRPS outperformed PERSIANN-CDR but lagged behind observed data. The model results have revealed that global precipitation products have highlighted a promising and observed precipitation an effective performance in simulating runoff over the central Ethiopian case. It is recommended to incorporate an alternative remotely sensed rainfall product or apply a merging technique, then evaluate the results and analyze their impact on flow simulation performance.