Hydrological appraisal using multi-source rainfall data in PDM model over the Qinhuai River basin in China

The impacts of climate change are one of the challenges that the world is facing. This study evaluates the behavior of streamflows using various rainfall data in the Qinhuai River basin (China) through the probability distributed model (PDM) rainfall–runoff model. The methodology consisted of (i) assessing the hydrological model capability to reproduce the hydrological processes of the basin using multi-source rainfall and (ii) estimating present (2010:2015) and future (2020:2099) runoff using the regional climate model (RCM) under the representative concentration pathway’s (RCP) scenarios 4.5 and 8.5; it must be noted that the downscaling and bias corrections are done by the China Meteorological Administration. The results are used for these works, (iii) trend analysis based on the Mann–Kendall methods. The results showed a decent performance of the model simulating streamflow over the Qinhuai River basin with 0.95 of R2 for calibration and 0.77 for validation and a root-mean-square error (RMSE), respectively, of 29.7 and 86.25. The performance criteria of this model are determined through R2 statistic and the RMSE. Rainfall data (rain gauge, C-band radar, S-band radar), Climate Prediction Center (CPC) morphing technique (CMORPH), and global precipitation measurement (GPM) satellite rainfall indicated fair adequation between the actual and simulated flows with statistic coefficient greater than 0.95 for calibration. A significant change trend at 0.05 level was found for the future runoff simulated under both RCP’s scenarios at annual time scales.