<![CDATA[Objective: In this research, six sources (TRMM, IMERG, PERSIANN-CDR, GSMaP, and ERA5) of precipitation data collected by satellites/global reanalysis were evaluated to find the best source of precipitation data as an alternative method to monitoring from GWS. Method: The evaluation was based on two methods; the first is the use of statistical metrics (Pearson's Correlation Coefficient (CoC), Mean Error (ME), mean absolute error (MAE), Root Mean Square Error (RMSE), and Bias (BIAS) and the second is the use of precipitation data quality metrics Probability of Detection (POD), the False Alarm Ratio (FAR), and the Critical Success Index (CSI). In both methods, monitoring adopted precipitation data from GWS as the source data (the most accurate), and compared it with estimation data (extracted from remote sensing (RE) techniques /reanalysis data). Results: Based on the results of the quality metrics, it was found that CHIRPS is the most reliable alternative to GWSs for precipitation data, followed by TRMM and IMERG. However, the statistical metrics results indicated that ERA5 outperformed the other data sources. Novelty: The study concludes that quality measures are better at verifying the validity of data when it comes to temporal and numerical discrepancies between GWSs and RE techniques/reanalyzed data, as these measures are not sensitive to the number of observations. Therefore, it was suggested to use CHIRPS data as an alternative source to study drought and hydrology instead of relying exclusively on GWS.]]>
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