Regional hydrological analysis generally requires meteorological inputs with adequate spatial resolution and coverage. Satellite-derived precipitation covers relatively large areas at various temporal scales. The global precipitation measurement (GPM) began releasing a new generation of global precipitation products in April, 2014, i.e., the integrated multi-satellite retrievals for GPM (IMERG), which has a spatial resolution of 0.1 deg (latitude) × 0.1 deg (longitude). However, IMERG does not have the sufficient resolution required by the most advanced fine-scale hydrological models. Meanwhile, due to the randomness of daily precipitation, it is difficult to obtain stable precipitation influence factors. The results of this work show that: (1) The IMERG V06 shows obvious multifractal characteristics, which makes it possible to use the multifractal method to improve its spatial resolution without the help of other elements. However, the accuracy of precipitation products will suffer a certain loss. (2) The downscaling method considering the influence factors of precipitation did well on a monthly dataset, and the maximum CC can reach 0.911. At the same time, the random forest regression model is significantly better than the traditional multiple linear regression model since the former is better matched with the original monthly precipitation data and can produce more local details. (3) The downscaled monthly precipitation data are helpful to the spatial heterogeneity recovery of daily precipitation. The recovery can enrich the spatial details of the daily precipitation and improve the accuracy to a certain extent. Compared with the multifractal (MF) downscaling results, the accuracy of the MF-RFR model was improved by 10.3%, whereas the MF-MLR model improved by only 4.6%. Among them, the accuracy of the MF-RFR model is higher than that of the original IMERG V06 product, with an obvious increase in dry days. The MF-RFR model-derived precipitation would lead to more accurate meteorological disaster assessments and hydrologic analyses than would otherwise be.