Abstract:Uncertainty and sensitivity analysis of four important input conditions on the Environmental Hydrodynamic Fluid Code (EFDC) model results (i.e., water level, water age and currents) was investigated for a large shallow lake, Lake Taihu, China. The four input conditions included three boundary conditions (i.e., inflow/outflow, wind speed, wind direction) and an initial condition (i.e., initial water level). The Latin Hypercube sampling (LHS) as a global sensitivity method was used to estimate the uncertainty and sensitivity from the four input conditions. The results showed that uncertainties in the hydrodynamic process existed due to the uncertainties of model input conditions. Among the four input conditions, the initial water level was the most sensitive factor for the simulated water level and water age with the uncertainty contributions of 85.73% and 66.125% respectively, while it had barely 3% contributions to vertical averaged velocity. Wind speed played a significant role in the uncertainty of the velocity in the surface layer with a sensitivity coefficient of 58.70%, while it only had 5.25% and 3.00% contributions to the simulated water level and water age, respectively. Additionally, there was a similar impact of the four input conditions on the uncertainty of velocities in different layers. The four input conditions’ contributions to the velocities were as follows: wind speed (55%~60%) > wind direction (10%~15%) > initial water level ≈ inflow/outflow (1%~5%). Thus, the results provided reliable information for the model prediction of large shallow lakes like Lake Taihu. For different output targets, improving the precision of the input conditions with priority can efficiently enhance the precision of the hydrodynamic model.