Spatio-temporal performance evaluation of 14 global precipitation estimation products across river basins in southwest Iran

Karkheh and Karun basins (29°−35°N, 46°−52°E) are two large river basins (area 51,000 and 67,000 km2, respectively) with complex topography in southwest Iran. Access to spatio-temporally consistent precipitation data is a key requirement for hydrological studies, especially in data-scarce regions. This study evaluated 14 global precipitation products against gauge observations from 2003 to 2012 in Karun and Karkheh basins, southwest Iran. Different categorical and statistical indices at varying spatial and temporal resolution, including Kling-Gupta Efficiency (KGE), bias, correlation coefficient, and variability ratio, were used to evaluate the products. For daily time steps, TMPA-3B42V7.0, MERRA-2, and CMORPH-BLDV1.0 outperformed all other products, with KGE > 0.3. TMPA-3B42V7.0, MERRA-2, and PERSIANN-CDR were the best-performing products for monthly time steps, with KGE> 0.5. ERA5-Land showed the highest positive bias (bias>1.5) compared with in-situ observations, particularly for mountainous southeastern parts of Karun basin. Overall, bias-adjusted products obtained by merging ground-based observations in the estimations outperformed the unadjusted versions. The spatial distribution of statistical error metrics indicated that almost all products showed their greatest uncertainties for mountainous regions due to complex precipitation processes in these regions. These results can contribute significantly to hydrological and water resources planning measures in the study region, including early flood warning systems, drought monitoring, and optimization of dam operation. [Display omitted] •MERRA-2 is the most accurate estimation product for daily precipitation across southwest Iran.•TMPA-3B42V7.0 is the most accurate product at monthly time scale in Karun and Karkheh basins.•ERA5-Land showed the highest bias versus observational data.•All products showed greatest uncertainty for mountainous areas.