## 2 Materials and Methods
### Conventional Observation from Rain Gauged Stations  
The daily observed precipitation data of 12 gauging stations in Pakistan was collected from Water and Power Development Authority (WAPDA) and Pakistan Meteorological Department (PMD) from January 1981 to December 2009. However, JRB is characterized as a highly complex and transboundary (India and Pakistan) catchment whose accurate information is substantial to water resources management. At the same time, it's hard to collect in-situ observation data due to geopolitical issues. Thus, we used daily summaries of observed precipitation at ten referenced stations provided by the NOAA National Climatic Data Center, accessed from [[https://www.ncdc.noaa.gov/cdo-web/](https://www.ncdc.noaa.gov/cdo-web/)]([https://www.ncdc.noaa.gov/cdo-web/](https://www.ncdc.noaa.gov/cdo-web/)) (accessed on 25 June 2020). Geographical information of in-situ weather stations used in the current study is given in Table S1. The organizations that operate weather stations in the research area follow the WMO standards for meteorological data collection. The distribution of meteorological stations is scarce in the study area (Figure 1c). These stations were installed at different \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**S.No**} & **Name of** & \multirow{2}{*}{**Mean Elevation (m)**} & \multirow{2}{*}{**Area (km\({}^{2}\))**} & **Weather** \\  & **Sub-Basins** & & & **Stations** \\ \hline I & Neelum & 3547 & 7420.98 & 4 \\ II & Kunhar & 2805 & 2660.35 & 2 \\ III & Jhelum & 3019 & 14,396.70 & 9 \\ IV & Kanshi & 2168 & 4191.01 & 3 \\ V & Poonch & 2095 & 4799.69 & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Topological information of five sub-basins of JRB. Figure 1: The geographical location of the study area. (**a**) seasonal influences of precipitation sources (**b**) Elevation (**c**) distribution of rain gauges in SBs. Whereas I, II, III, IV and V represent Neelum, Kunhar, Jhelum, Kanshi and Poonch sub-basins, respectively. elevations, i.e., Mangla is located at the minimum elevation of 335 m (a.s.l. ), while Store is at the elevation of approximately 5432.32 m (a.s.l.) Table S1. These meteorological stations use tipping bucket rain gauges to measure liquid precipitation. In cases of infrequent snowfall, the manually calculated water equivalent is traditionally applied to the daily rainfall data. During 1994-1995, WAPDA installed automatic data collection platforms (DCPs) in high-altitude areas [26]. These DCPs use snow pillows to record solid and liquid precipitation as water equivalents. Due to possible ice bridging and rupture effects, mostly installed snow pillows experienced technical problems with transmission system interfacing and unexpected \"jumps.\" Even though these problems were greatly alleviated in 1996 by attaching a highly precise potentiometer to convert the shaft encoders from digital to analog output, wind-induced errors continue to affect the quality of precipitation records at higher altitudes of >3000 m [31]. As a result, underestimation of precipitation by gauging observations due to wind-induced errors at higher altitudes may cause a slight positive bias in GPPs [25; 26]. Most of the evaluated products integrate rain gauge data from various sources and employ multiple algorithms. Therefore, to ensure an independent evaluation, gauging stations used as ground truth should not be used in the development of these products to be evaluated. Thus, it is worth noting that the gauging stations used in this assessment were not included in the Global Precipitation Climatology Centre (GPCC) network products [25; 26], which justifies the independent evaluation in the present research. In addition, the in-situ gauge-based precipitation estimates are typically regarded as the authoritative source of precipitation data for validating satellite-based precipitation products [32]. Thus, the five GPPs data were evaluated against in-situ gauge-based data.