## 1 Introduction  
Myanmar is the second largest country in Southeast Asia. Four main rivers travel through the country: the Ayeyarwaddy, Chindwin, Thanlwin, and Sittoung. As the third largest river in Myanmar, the Chindwin River serves as one of the principal water resources of the country. The river flows into the Central Valley Region, which is the most economically developed area of the country (Figure 1). Owing to the effects of complex topography and the southwest monsoon, the Chindwin River basin suffers from severe floods every year at one location or another, causing enormous damage to local society. Myanmar is a country with an underdeveloped economy and limited infrastructure investment, particularly in meteorological observation. The rainfall-monitoring network in the Chindwin River basin is very sparse, with a limited number of rain gauges, which likely affects the accuracy of local flood forecasting for prompt flood control and timely disaster mitigation to some degree. The recent rapid development of satellite-based precipitation retrieving techniques has provided radiologists an unprecedented opportunity to acquire alternative precipitation data sources for flood simulation and forecasting in data-sparse or ungauged basins. The development of satellite-based precipitation products (SPPs) has undergone two important stages, namely, the Tropical Rainfall Measuring Mission (TRMM) era [1] and the Global Precipitation Measurement (GPM) era [2]. The representative SPPs in these two eras include Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN) [3], Climate Precipitation Center morphing method (CMORPH) [4], Climate Hazards Group Infrared Precipitation with Stations [5], TRMM Multi-satellite Precipitation Analysis (TMPA) [1], Global Satellite Mapping of Precipitation (GSMaP) [6], and Integrated Multi-satellite Retrievals for GPM (IMERG) [2]. These SPPs generally provide quasi-global precipitation maps on high spatiotemporal resolutions (finer than 0.25\({}^{\circ}\) spatial resolution and shorter than the daily time interval); TRMM-era SPPs, in particular, have been widely adopted in hydrological applications in many parts of the world [7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23]. Figure 1: Location of the Chindwin River basin. Developed by the Goddard Space Flight Center of the National Aeronautics and Space Administration (NASA), TMPA SPPs are regarded as reliable and were broadly used satellite products during the TRMM era [22; 23; 24; 25]. TMPA combines low-earth orbiting microwave (MW) data and geostationary infrared (IR) data from multiple satellites and provides precipitation estimates on high spatiotemporal resolution (0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) and 3-h interval), thereby covering the 50\({}^{\circ}\)N-50\({}^{\circ}\)S latitude band [1]. TMPA SPPs in near- and post-real-time versions have been extensively used in water resources management, hydrological simulations, and flood monitoring [11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23]. These studies proved that TMPA has acceptable or even satisfactory accuracy and hydrological prediction ability in many regions of the world. The GPM mission was officially launched by NASA and the Japan Aerospace Exploration Agency (JAXA) in February 2014, and the TRMM mission was terminated in April 2015, symbolizing the beginning of a new era for SPPs, that is, the GPM era [2]. As a global successor of TRMM, GPM comprises an international satellite constellation (1 core observatory satellite and approximately 10 partner satellites), and its core observatory satellite is equipped with an advanced Dual-Frequency Precipitation Radar (DRP, the Ku-band at 13.5 GHz and Ka-band at 35.5 GHz) and a multi-channel GPM MW IMAGER (GMI) (frequency of 10-183 GHz) [26]. NASA released its first GPM-era global precipitation product, IMERG, in March 2014.