Evaluating the influence of topography data resolution on lake hydrodynamic model under a simulation uncertainty analysis framework

Abstract

Spatial resolution of topography data significantly impacts computational time of lake hydrodynamic modelling. This study proposes a calibration tool to examine impacts of topography data resolution on simulation uncertainty, evolving from the Generalized Likelihood Uncertainty Analysis framework. Using the EFDC hydrodynamic model, BaiYangDian Lake in North China was simulated at three resolutions: 200, 500, and 1000 m. The first two models show similar accuracy, outperforming the 1000-m model. The parameter space constrained by water level observations and the simulation uncertainties in water level, water age, and velocity from 500-m model closely resembled those from 200-m model, while requiring only 16.7% of the latter's computational time, indicating a feasible spatial resolution range where model performance matches the high-resolution model but with significantly less computational time. The study highlights the importance of calibration with multiple observations and demonstrates potentials of the proposed tool to identify effects of model settings on simulation uncertainty.