Introduction

Accurate precipitation data are key for the hydrological modeling (Duanet al ., 2019a; Monteiro et al ., 2016; Strauch et al ., 2012; Villarán, 2014). However, due to the sparsity of many gauge networks and the large spatio-temporal variabilities of precipitation events (Lu et al ., 2018; Zhu et al ., 2016), obtaining accurate precipitation data has always been challenging for scientists especially in alpine basins (Bhatta et al ., 2019; Hao et al ., 2016; Yuan et al ., 2018), which greatly hindered the research into hydrological simulation thereof (Tuo et al ., 2016). Satellite and reanalysis precipitation products provide an unprecedented opportunity to obtain precipitation data with high spatio-temporal resolution.
To date, many satellite and reanalysis precipitation products have been developed and released to the public, such as Global Precipitation Measurement (GPM) (Hou et al ., 2013), Tropical Rainfall Measuring Mission (TRMM) (Huffman et al ., 2010a), Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) (Funk et al ., 2015), China Meteorological Assimilation Driving Datasets for SWAT model (CMADS) (Meng et al ., 2019), Climate Forecast System Reanalysis (CFSR) (Saha et al ., 2010), etc . These products have the advantages of extensive coverage, high spatio-temporal resolution, and continuity of measurement (Bajracharya et al ., 2015; Prakashet al ., 2016): these have been widely applied in hydrological studies across many regions (Auerbach et al ., 2016; Awangeet al ., 2019; Cao et al ., 2018; De Almeida Bressianiet al ., 2015; Duan et al ., 2019a; Fuka et al ., 2014; Roth and Lemann, 2016). The research on satellite and reanalysis precipitation products in hydrological model can be divided into two categories: one such that these products directly drive hydrological models to study and discuss the influence of precipitation data quality on the accuracy of hydrological simulations (Duan et al ., 2019b; Nhi et al ., 2018; Strauch et al ., 2012; Tuo et al ., 2016; Zhu et al ., 2016); the other aims at satellite and reanalysis precipitation data which are not performing well in hydrological modeling terms. The improvement of satellite and reanalysis precipitation data by different correction methods was studied and discussed (Deng et al ., 2019; Sheng et al ., 2017; Wanget al ., 2020). However, most of these literatures focus on low-altitude basins with dense in-situ gauge observation, because the satellite and reanalysis precipitation products in such areas are less affected by topography, making it is easier to evaluate and correct satellite and reanalysis precipitation data based on a large number of gauge-observed data (GO). Alpine basin areas are important in the conservation of water resources (Immerzeel et al ., 2009; Viviroli and Weingartner, 2004) and are sentinel outpost responding to climate change (Immerzeel et al ., 2010; Shakil et al ., 2015), such as on the Tibetan Plateau, known as ”Asian Water Tower” (Immerzeelet al ., 2010). It is more meaningful to evaluate the quality of satellite and reanalysis precipitation products in an alpine basin and to mine precipitation products suitable for hydrological-runoff simulations thereof.
In recent years, many scholars (Deng et al ., 2019; Duan et al ., 2019a; Yuan et al ., 2018; Yw et al ., 2019) have discussed the hydrological application of satellite and reanalysis precipitation products in alpine basin. However, most of studies focus on the influence of precipitation product quality on hydrological simulation accuracy. Unfortunately, these research results show that the performance of precipitation data from sparse in-situ gauge observation stations in hydrological models is better than that of satellite and reanalysis precipitation products with high spatio-temporal resolution. Yuan et al . (2018) evaluated the quality of the TRMM Multi-satellite Precipitation Analysis 3B42V7 and the Integrated Multi-satellite Retrievals for GPM (IMERG) Final Run Version 05 precipitation products and their hydrological utilities in the Yellow River source region (YRSR), and found that the performance of GO is better than that of IMERG and TRMM precipitation data. In the Upper Gilge Abay basin, Duan et al . (2019a) evaluated the applicability of CHIRPS, TRMM, and CFSR in hydrological models by using the Soil and Water Assessment Tool (SWAT), still finding that the GO performed best. Use of ground-based rain gauge data is generally considered to be a more accurate method as this entails direct measurement of precipitation (Qinet al ., 2014). However, ground-based rain gauges are considered as point measurements within the common problem of the uneven distribution thereof (Chappell et al ., 2013), which may not effectively reflect the spatio-temporal variability of precipitation systems (Anagnostou et al ., 2009). Satellite and reanalysis precipitation products have the advantage of large coverage (Bajracharyaet al ., 2015; Prakash et al ., 2016), which can supplement that precipitation information in areas without stations. How to coordinate the advantages of GO, satellite and reanalysis of precipitation data is the key to hydrological-runoff simulation in alpine basins.
The YRSR, with high solar radiation and a low temperature, is selected as a case study in the present research. Combined with the distributed hydrological model SWAT, two types of satellite precipitation products (TRMM and IMERG) and two types of reanalysis precipitation products (CMADS and CFSR) were statistically and hydrologically verified. This entailed: (1) Using GO to evaluate the quality of TRMM, IMERG, CMADS, and CFSR at grid and basin-scales; (2) The hydrological model is driven by precipitation data pre- and post-correction; (3) The hydrological model is driven by the combination of GO and satellite or reanalysis precipitation products, namely, for that area with GO we adopted GO, and in areas without GO we adopted satellite or reanalysis precipitation products. To the best of our knowledge, the hydrological evaluation of the combination of GO and satellite or reanalysis precipitation products in the YRSR has not yet been reported. The results of this study have implications for improving water supply, flood forecasting, and ecosystem protection for alpine basins and their downstream regions.