Uncertainty Quantification of Large-Eddy Simulation Results of Riverine Flows: A Field and Numerical Study

TL;DR

This study combines field measurements and numerical simulations to quantify uncertainties in large-eddy simulation results of river flows, highlighting the influence of roughness and inflow variations on model accuracy.

Contribution

It introduces a comprehensive uncertainty quantification framework for LES of river flows using polynomial chaos expansion and Sobol indices, validated with real field data.

Findings

Uncertainties in shallow near-bank regions are mainly due to roughness variations.

Inflow discharge variations affect LES results throughout the river.

The developed UQ approach effectively identifies key sources of uncertainty.

Abstract

We present large-eddy simulations (LESs) of riverine flow in a study reach in the Sacramento River, California. The riverbed bathymetry was surveyed in high-resolution using a multibeam echosounder to construct the computational model of the study area, while the topographies were defined using aerial photographs taken by an Unmanned Aircraft System (UAS). In a series of field campaigns, we measured the flow field of the river using the acoustic Doppler current profiler (ADCP) and estimated using large-scale particle velocimetry of the videos taken during the operation UAS. We used the measured data of the river flow field to evaluate the accuracy of the LES-computed hydrodynamics. The propagation of uncertainties in the LES results due to the variations in the effective roughness height of the riverbed and the inflow discharge of the river was studied using uncertainty quantification (UQ) analyses. The polynomial chaos expansion (PCE) method was used to develop a surrogate model, which was randomly sampled sufficiently by the Monte Carlo Sampling (MCS) method to generate confidence intervals for the LES-computed velocity field. Also, Sobol indices derived from the PCE coefficients were calculated to help understand the relative influence of different input parameters on the global uncertainty of the results. The UQ analysis showed that uncertainties of LES results in the shallow near bank regions of the river were mainly related to the roughness, while the variation of inflow discharge leads to uncertainty in the LES results throughout the river, indiscriminately.