Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x

2021 
Abstract. Developing accurate and efficient modeling techniques for streamflow at tens-kilometer spatial scale and multi-year temporal scale is critical for evaluating and predicting the impact of climate- and human-induced discharge variations on river hydrodynamics. However, achieving such a goal is challenging because of limited surveys of streambed hydraulic roughness, uncertain boundary condition specifications, and high computational costs. We demonstrate that accurate and efficient three-dimensional (3D) hydrodynamic modeling of natural rivers at 30-kilometer and 5-year scales is feasible using the following three techniques within OpenFOAM, an open source computational fluid dynamics platform: 1) generating a distributed hydraulic roughness field for the streambed by integrating water stage observation data, a rough wall theory, and a local roughness optimization and adjustment strategy; 2) prescribing the boundary condition for the inflow and outflow by integrating pre-computed results of a one-dimensional (1D) hydraulic model with the 3D model; and 3) reducing computational time using multiple parallel runs constrained by 1D inflow and outflow boundary conditions. Streamflow modeling for a 30-kilometer-long reach in the Columbia River (CR) over 58 months can be achieved in less than six days using 1.1 million CPU hours. The mean error between the modeled and the observed water stages for our simulated CR reach ranges from −16 cm to 9 cm (equivalent to ca. ±7 % relative to the average water depth) at seven locations during most of the years between 2011 and 2019. We can reproduce the velocity distribution measured by the acoustic Doppler current profiler (ADCP). The correlation coefficients of the depth-averaged velocity between the model and ADCP measurements are in the range between 0.71 and 0.83 at 75 % of the survey cross-sections. With the validated model, we further show that the relative importance of dynamic pressure versus hydrostatic pressure varies with discharge variations and topography heterogeneity. Given the model's high accuracy and computational efficiency, the model framework provides a generic approach to evaluate and predict the impact of climate- and human-induced discharge variations on river hydrodynamics at tens kilometer and decade scales.
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