Comprehensive evaluation of multi-satellite precipitation products with a dense rain gauge network and optimally merging their simulated hydrological flows using the Bayesian model averaging method

摘要: Summary This study first focuses on comprehensive evaluating three widely used satellite precipitation products (TMPA 3B42V6, TMPA 3B42RT, and CMORPH) with a dense rain gauge network in the Mishui basin (9972 km 2 ) South China then optimally merge their simulated hydrologic flows semi-distributed Xinanjiang model using Bayesian averaging method. The initial data comparisons show that reanalyzed bias of −4.54%, matched best observations, while two near real-time datasets (3B42RT largely underestimated by 42.72% 40.81% respectively. With parameters benchmarked data, behavior streamflow simulation from 3B42V6 was also most optimal amongst products, produced deteriorated biases Nash–Sutcliffe coefficients (NSCEs). Still, when were recalibrated each individual performance simulations significantly improved, thus demonstrating need for specific calibrations hydrological models inputs. Moreover, merged respect to streamflows forced all method, resulted series further improved became more robust. In summary, current state-of-the-art have demonstrated potential research applications. benchmarking, recalibration, merging schemes at scale described present work will hopefully be reference future utilizations global regional