Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited