Parameter uncertainty analysis for large-scale hydrological model: challenges and comprehensive study framework

Hydrological models are integrated approximations of complex hydrological phenomena and processes in nature, and have been extensively applied for many practical purposes, such as flood and drought disaster prevention, water resources development utilization and management. In the current study, difficulties lying in the applications of large-scale hydrological models were discussed, research progresses on the uncertainty of model parameters were summarized, and a framework for parameter uncertainty analysis named, 'Sensitivity analysis—Optimization—Regionalization (SOR)' was introduced with special emphasis on its basic concepts, importance and applications. To improve the accuracy of large-scale hydrology simulation and prediction, a more comprehensive SOR was suggested for the application process of hydrological modelling, so were the developments of advanced distributed hydrological model and more accurate hydrometeorological observation systems to reduce the extra forcing-driven and model structure-driven uncertainty.