Statistical Assessment and Hydrological Utility of Multiple Gridded Precipitation Datasets in Upper Aras Basin

Precipitation is an essential meteorological forcing for hydrologic modeling, and its accurate estimation
requires installation and maintenance of dense gauge networks, which is limited for many regions.
Conversely, Gridded Precipitation Datasets (GPDs) can be an alternative to carry out research over
complex topography and snow dominant regions. Therefore, this study aims to evaluate the spatiotemporal
consistency and hydrologic utility of four GPDs (ERA5, CHIRPv2.0, IMERGHHFv0.6, and
PERSIANN) over a mountainous basin (Upper Aras basin) in the eastern part of Turkey. The Kling–
Gupta Efficiency (KGE) is used to compare GPDs with observed precipitation directly, and the
Hanssen–Kuiper (HK) skill score is utilized to assess the detectability strength of selected GPDs for
different precipitation intensities. Moreover, the hydrologic utility of GPDs is tested by exploiting a
conceptual rainfall-runoff model under Kling–Gupta Efficiency (KGE) and Nash–Sutcliffe Efficiency
(NSE) metrics. Generally, all GPDs show low performance compared with observed precipitation
directly while their performance considerably increases for streamflow simulation. ERA5 show high
reproducibility in streamflow (KGE = 0.86), followed by IMERGHHFv06 (KGE = 0.85), PERSIANN
(KGE = 0.77), and CHIRPv2.0 (KGE = 0.70), for the entire period (2015–2019) of the study.