<![CDATA[Reliable rainfall data is crucial for managing water resources, especially in agricultural regions like the Bodor Sub Watershed. This study comprehensively evaluates two precipitation products, the satellite-based CHIRPS dataset and the reanalysis ERA 5 dataset within the Bodor Sub Watershed. Both products were compared against gauge data at three timescales (monthly, 15-days, 10-days) for seven locations (Bodor Sub Watershed region and six rain gauges). Statistical parameters, including Nash Sutcliffe Efficiency (NSE), RMSE-observation standard deviation ratio (RSR), Pearson correlation coefficient (CC), and percent bias (PBIAS), were used to assess the performance of each precipitation product. Results consistently demonstrate that ERA 5 outperforms CHIRPS in most locations and time scales, particularly monthly. ERA 5 exhibited superior performance in over 85% of the analyses, with NSE values ranging from 0.164 to 0.862, RSR values from 0.992 to 0.372, and CC values from 0.507 to 0.932. ERA 5 also excelled in 57% of the bias analyses (PBIAS: -13.436 to 10.188). Regional validation consistently showed more favorable results compared to gauge-based validation. Additionally, data availability significantly influences product accuracy, with stations processing longer records exhibiting superior performance. This study offers valuable insights into the suitability of CHIRPS and ERA 5 hydrological applications in Bodor Sub Watershed, particularly in data-scarce regions. It contributes to improved water resources management strategies.]]>
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