## 1 Introduction  
Precipitation plays a critical role in the water cycle and hydrometeorology research [1]. Traditionally, precipitation data are solely acquired from ground-based observations. However, ground-based measurement networks (gauge stations) have the problems of sparse stations in individual areas, uneven spatial distributions, and underrepresentation of regional precipitation, which considerably limit their applicability [2]. Over the past dozen years, with the advances of satellite technology [3], rainfall observation methods using remote sensing, including weather radar and space weather satellite detection, have developed, among which [4], are the representative products comprising the TRMM (Tropical Rainfall Measuring Mission) and the CMORPH (climate prediction center (CPC) morphing technique), etc. These open and free access products enable us to obtain global and large-scale grid precipitation data [5]. The TRMM Multisatellite Precipitation Analysis products (TMPA) have received the most applications due to their high accuracy. Based on the success of TMPA, the Global Precipitation Measurement (GPM) mission further prompted the advance of precipitation retrieval in terms of forecasting accuracy and space coverage, benefiting from the fact that it deployed the world's first dual-frequency precipitation radar. These improvements will enhance the ability to monitor or predict disasters, such as typhoons and other extreme rainfall, floods, drought, and mudslide events. In this study, we will primarily concentrate on the application of the Level-3 product generated by the Day-1 Integrated Multisatellite Retrievals for the GPM (IMERG) algorithm [6]. In recent years, many comprehensive evaluations have been performed on the accuracy of multisatellite products in various regions [7; 8; 9; 10; 11; 12] and studies have focused on the effects of hydrological applications [13; 14; 15; 16]. Some comparative studies have reported that the latest GPM-Era high-resolution satellite precipitation products are superior to other satellite products [17]; however, their performance under various regions and climatic conditions tends to oscillate and needs further research. The reliability and accuracy of satellite data are affected by climatic and geographic conditions as well as seasons [18]. Despite their variability, a general tendency is that the accuracy of IMERG products improves as the time scale increases [19; 20; 21]. The IMERG products more closely resemble the site rainfall data at daily, monthly, and annual scales [12], and the post-real-time IMERG final run (FR) product is relatively more accurate than the near-real-time early run (ER) and late run (LR) products and can play an important role in supplementing or replacing surface precipitation measurements [10; 21]. On the subdaily scale, the performances of the three IMERG products are similar, with the ER and LR products generally considered to be more reliable for early flood warning systems because of their shorter lag time advantages. Although these products have a greater potential for flood forecasting than other products, their accuracies must be continually evaluated [19; 20; 21]. In terms of hydrological applications of satellite-based precipitation products, satellite-based precipitation products have been increasingly applied to the study of water processes [22]. [PERSON] et al. evaluated the role of TRMM products in hydrological modeling in the Taihu Lake basin using the NSE and BIAS. They found that TRMM precipitation data performed well on monthly and annual scales and were well-fit to ground-based frequency rainfall distributions [23]. Evaluations of the accuracy and hydrological applications of IMERG and TRMM products in the Yellow River Basin by [PERSON] et al. showed that IMERG products consistently yielded better results than 3B42 V7 products on the daily scale (NSE: 0.810 versus 0.729) and 3-hourly time intervals (NSE: 0.266 to 0.792 versus \(-\)0.070 to 0.702).