Abstract: Accurate and high-resolution precipitation data will help in obtaining an accurate monitoring of drought development spatially and temporally. In such an occasion, the quantitative precipitation products bear the potential advantages of monitoring droughts continuously over a wide-span space coverage, compared to traditional ground-based meteorological data. Three quantitative precipitation products were selected in this study to access their accuracies and drought monitoring potentials in Huaihe River Basin for their suitability in calculating the Standardized Precipitation Index (SPI). They are Multi-Source Weighted-Ensemble Precipitation (MSWEP), Climate Hazards Group Infrared Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR).The precipitation data from 27 meteorological stations in Huaihe River Basin from 1983 to 2016 were collected to test the accuracy of monthly accumulative precipitation data of three quantitative precipitation products. The SPI was used as the drought indicator. The Correlation Coefficient (r), the Root Mean Square Error (RMSE), the Critical Success Index (CSI), and the drought level monitoring Accuracy (ACC) were used as evaluation indicators to evaluate the drought monitoring potential of the three quantitative precipitation products (MSWEP, CHIRPS and PERSIANN-CDR). The results showed that: 1) All three quantitative precipitation products underestimated the actual precipitation both in monthly-, seasonal-, and annual-scale; The accuracy of MSWEP outperformed the other two products, in the sense that, the r values of MSWEP reached 0.92-0.97 and the RMSE values were 26.38-124.73 mm; The accuracies of CHIRPS with resolution of 0.05°×0.05° was similar to that of the resolution of 0.25°×0.25°; Also CHIRPS and PERSIANN-CDR had similar accuracy performances; 2) For the estimation of extreme shortage of precipitation, the MSWEP also bears the highest accuracy compared to the other two products, in the sense that the RMSE values are less than 50% than the other two products. In the month of extreme precipitation shortage, the three quantitative precipitation products generally overestimated the amount of precipitation compare to the observed precipitation values. 3) MSWEP's overall performance in drought monitoring was better than other products; the monthly SPI, seasonal SPI and annual SPI calculated by MSWEP had higher accuracies (r≥0.92, RMSE≤0.39), higher accuracies in drought month identification (CSI≥0.89) and higher accuracies in drought level identification (ACC≥80.3%). In case of CHIPRS or PERSIANN-CDR, the CSIs and ACCs in the three time scales were high for the three time scales. It revealed that those two products could also be used for watershed drought monitoring. 4) MSWEP was much more accurate in monitoring different drought levels, especially for that of extreme drought level. It's ACC for determining various drought levels was higher than CHIRPS and PERSIANN-CDR; 5) All the three quantitative precipitation products showed excellent drought monitoring potential in the typical drought events in the Huaihe River Basin; MSWEP identified the spatio-temporal development process of typical drought events from February to June in 2000 more accurately; Compared with the typical drought events monitoring results based on precipitation data of meteorology stations processed by inverse distance weighting interpolation algorithm, the MSWEP's monitoring results were more consistent with the actual drought regime. In general, compared with CHIRPS and PERSIANN-CDR, MSWEP had higher accuracies and greater drought monitoring potential in the Huaihe River Basin. The comparison and evaluation results of the accuracy and drought monitoring potential of quantitative precipitation products presented here can provide a basis for the application of products' precipitation data for meteorological and agricultural drought monitoring.