PNNL

Abstract

Flooding is the most impactful natural hazard of all weather-related events. Numerical models that solve the 2-dimensional (2D) shallow water equations (SWE) represent the first-principles approach to simulate all types of spatial flooding, such as pluvial, fluvial, and coastal flooding, and their compound dynamics. Very high spatial resolution (e.g., ?? (10^0-10^1) m) is needed in 2D SWE simulations to accurately capture flood dynamics, resulting in formidable computational challenges. Thus, relatively coarser spatial resolutions should be considered for large-scale applications, which introduce uncertainties in the results. It is unclear how the uncertainty associated with the model resolution is compared to the uncertainties introduced by precipitation datasets and assumptions on boundary conditions when channelized flows interact with other water bodies. In this study, we compare these three sources of uncertainties in 2D SWE simulations for the 2017 Houston flooding event. Our results show that precipitation uncertainty and mesh resolution have larger impacts on the simulated streamflow and inundation dynamics than the choice of the downstream boundary condition at the watershed outlet. However, biases caused by the uniform coarsening of the mesh can be reduced by using a variable resolution mesh (VRM), which preserves critical topographical features. Specifically, in simulation with VRM, the simulated inundation depth over the refined region will not be degraded by the non-refined regions. This study contributes to understanding the challenges and pathways for applying 2D SWE models to improve the realism of flood simulations over large scales.