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<p>Streamflow simulation along with soil erosion hotspot identification is crucial for effective basin management; however, limited observed data pose challenges for modelers. This study tested the performance of the three satellite-based precipitation products (SPPs), namely (1) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), (2) Global Precipitation Measurement (GPM)-Integrated Multi-satellite Retrievals for GPM (IMERG), and (3) African Rainfall Climatology (ARC2), against observed data in the data-constrained transboundary Ruvu River Basin (RRB), Tanzania. Correlation coefficient (CC), root mean square error (RMSE), mean error (ME), and bias were used as evaluation statistics for SPPs. CHIRPS precipitation outperformed others by achieving the CC of 0.67 or higher, and was then combined with observed rainfall into the Soil and Water Assessment Tool (SWAT) model to simulate streamflow. The SWAT model was calibrated (2007–2014) and validated (2015–2018) for streamflow at daily time intervals using SWAT-CUP with the SUFI-2 algorithm. Model performance was evaluated using statistical indices. The SWAT model performed well, achieving <i>R</i><sup>2</sup> values of 0.83 and 0.85 during calibration and validation, respectively, as well as NSE values of 0.76 and 0.81. Simulated sediment yield from the SWAT model was analyzed to identify areas prone to soil erosion. The average annual sediment yield from the entire basin was estimated at 1434 tons yr<sup>−1</sup> with a spatial average of 43 tons<sup>−1</sup> ha&#xa0;yr<sup>−1</sup>. Approximately 10.94% of the RRB requires urgent mitigation measures as critical erosion-susceptible areas. These findings confirm that integrating SPPs into the hydrological model can effectively simulate streamflow and facilitate soil erosion analysis using the model outputs.</p>

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Integrating Ground and Satellite-based Precipitation Data for Streamflow Simulation and Soil Erosion Hotspot Mapping in the Data-Scarce Ruvu River Basin, Tanzania

  • 期刊论文

  • 发表日期：

    2025年6月12日

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  • Deus Michael,
  • Ray Singh Meena,
  • Brijesh Kumar,
  • Richa Kumari

摘要

Streamflow simulation along with soil erosion hotspot identification is crucial for effective basin management; however, limited observed data pose challenges for modelers. This study tested the performance of the three satellite-based precipitation products (SPPs), namely (1) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), (2) Global Precipitation Measurement (GPM)-Integrated Multi-satellite Retrievals for GPM (IMERG), and (3) African Rainfall Climatology (ARC2), against observed data in the data-constrained transboundary Ruvu River Basin (RRB), Tanzania. Correlation coefficient (CC), root mean square error (RMSE), mean error (ME), and bias were used as evaluation statistics for SPPs. CHIRPS precipitation outperformed others by achieving the CC of 0.67 or higher, and was then combined with observed rainfall into the Soil and Water Assessment Tool (SWAT) model to simulate streamflow. The SWAT model was calibrated (2007–2014) and validated (2015–2018) for streamflow at daily time intervals using SWAT-CUP with the SUFI-2 algorithm. Model performance was evaluated using statistical indices. The SWAT model performed well, achieving R2 values of 0.83 and 0.85 during calibration and validation, respectively, as well as NSE values of 0.76 and 0.81. Simulated sediment yield from the SWAT model was analyzed to identify areas prone to soil erosion. The average annual sediment yield from the entire basin was estimated at 1434 tons yr−1 with a spatial average of 43 tons−1 ha yr−1. Approximately 10.94% of the RRB requires urgent mitigation measures as critical erosion-susceptible areas. These findings confirm that integrating SPPs into the hydrological model can effectively simulate streamflow and facilitate soil erosion analysis using the model outputs.