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.