Uncertainties in the prediction of flow in a long reach of the Sacramento River

Abstract

The accurate prediction of the flow field in a long reach of a complex waterway is prerequisite to the evaluation to acceptable engineering accuracy of strategies for the restoration, resource management and hazard assessment. In this study, we consider some aspects of the numerical prediction of flow in a long reach of the Sacramento River in California with view to gaining a better understanding the sources and the extent of the uncertainties that are present in the predictions. The predictions were obtained using a finite-volume method to solve the time-averaged forms of the equations governing the conservation of mass and momentum. Body-fitted coordinates were used to define the complex river bathymetry. Both depth-averaged and fully three-dimensional (3D) computations were performed. The results were compared with data obtained from a large-scale physical model of the same reach. The outcome of the comparisons served to provide the basis for the assessment of the sensitivity of the solutions to assumptions made regarding the conditions at inlet to the solution domain, the choice of turbulence model used to close the timeaveraged equations and, for the depth-averaged calculations, the choice of method used for prescribing the bed friction. The influence of other parameters such as the density of the computational grid, the method used to define the channel bathymetry, and the unsteadiness of the mean flow that results from vortex shedding from a bridge pier and abutments were also assessed. The results obtained form a useful addition to the growing literature on the computational modelling of flows in natural waterways.

Prediction of Bank Erosion in a Reach of the Sacramento River and its Mitigation with Groynes

“…Therefore, if the purpose of the computations is merely to obtain a general impression of the flow as represented by depth-averaged values then the use of a depth-average model would be quite sufficient. This conclusion is consistent with that arrived at in Ercan and Younis (2008) from their 2D and 3D computations for the same reach with no groynes. Although depth averaged velocities are predicted with similar degree of accuracy using 2D and 3D models, 2D models do not provide depth wise variation of velocity.…”

“…Cubic splines were utilized for the construction of the computational grid. As pointed out in Ercan and Younis (2008), the number and location of the survey points used to construct the channel cross sections can profoundly affect the quality of the grid. In some cases, the survey data are sparse leading to the generation of cross-sectional profiles that differ in essential detail from the real ones.…”

“…9 x-y plane schematic of 2D and 3D computations for the reach of the Sacramento River with five groynes discontinuities are known to slow down the convergence of an iterative solution procedure and, in some instances, produce instabilities that can cause the iterative process to diverge. A detailed discussion of the procedure for grid generation for complex river geometries, and the impact of the grid on the quality of the computed results can be found in Ercan and Younis (2008).…”

“…On the other hand, a significant portion of the uncertainties associated with the computational modeling of near-bank flow is directly attributable to inadequate surface definition and inadequacies in the computational meshes that are used to resolve the flow there. These and other factors which contribute to uncertainties in the computational modeling of river-scale flows are considered in detail in Ercan and Younis (2008) where it was found, for example, that the choice of method used to interpolate field survey data in order to define the computational flow domain exerts a considerable influence on the quality of the computed results. In this study, we use the best practices to emerge from that earlier study to obtain predictions of the flow field and the associated bank erosion.…”

Application of a roughness‐length representation to parameterize energy loss in 3‐D numerical simulations of large rivers

“…There is also a growing track record of effective application of hydrodynamic models to the quantification of river‐channel hydrodynamics in both two dimensions (2‐D) and three dimensions (3‐D) [e.g., Olsen and Stokseth , 1995; Hodskinson , 1996; Ferguson et al , 2003; Lane et al , 1999, 2000, 2004; Ma et al , 2002; Booker et al , 2001, 2004; Rodriguez et al , 2004; Nicholas , 2001, 2005; Ruther et al , 2005; Ruther and Olsen , 2007; Tritthart and Gutnecht , 2007; Abad et al , 2008; Shen and Diplas , 2008; Tritthart et al , 2009], and some of these studies have begun to consider large rivers [e.g., Kleinhans et al , 2008; Ercan and Younis , 2009]. A critical element of such application is the representation of bed roughness elements, which range from individual grains of sand up to large bedforms such as dunes.…”