Effects of uncertain topographic input data on two‐dimensional flow modeling in a gravel‐bed river

Abstract

[1] Many applications in river research and management rely upon two-dimensional (2D) numerical models to characterize flow fields, assess habitat conditions, and evaluate channel stability. Predictions from such models are potentially highly uncertain due to the uncertainty associated with the topographic data provided as input. This study used a spatial stochastic simulation strategy to examine the effects of topographic uncertainty on flow modeling. Many, equally likely bed elevation realizations for a simple meander bend were generated and propagated through a typical 2D model to produce distributions of watersurface elevation, depth, velocity, and boundary shear stress at each node of the model's computational grid. Ensemble summary statistics were used to characterize the uncertainty associated with these predictions and to examine the spatial structure of this uncertainty in relation to channel morphology. Simulations conditioned to different data configurations indicated that model predictions became increasingly uncertain as the spacing between surveyed cross sections increased. Model sensitivity to topographic uncertainty was greater for base flow conditions than for a higher, subbankfull flow (75% of bankfull discharge). The degree of sensitivity also varied spatially throughout the bend, with the greatest uncertainty occurring over the point bar where the flow field was influenced by topographic steering effects. Uncertain topography can therefore introduce significant uncertainty to analyses of habitat suitability and bed mobility based on flow model output. In the presence of such uncertainty, the results of these studies are most appropriately represented in probabilistic terms using distributions of model predictions derived from a series of topographic realizations.Citation: Legleiter, C. J., P. C. Kyriakidis, R. R. McDonald, and J. M. Nelson (2011), Effects of uncertain topographic input data on two-dimensional flow modeling in a gravel-bed river, Water Resour. Res., 47, W03518,

Effect of point bar development on the local force balance governing flow in a simple, meandering gravel bed river

“…A comparison of the FaS-TMECH output for these two grids indicated that predictions of E and h were fairly robust but that RMS errors for the two velocity components were larger. In general, a related study also conducted on the Merced River found that the most important input to the flow model, regardless of grid resolution, was the bed topography [Legleiter et al, 2011], and the density of our survey data was not sufficient to support the higher-resolution grid. The 1.02 m grid spacing employed here thus represented a compromise between the available topographic data and computational resources and an adequate representation of cross-stream velocities.…”

Channel Representation in Physically Based Models Coupling Groundwater and Surface Water: Pitfalls and How to Avoid Them

“…Legleiter and Kyriakidis (2008) observed a proportional relationship between section spacing and root mean square of the interpolated DEM. Although sampling density impacts the uncertainty of hydrodynamic predictions (Legleiter et al 2011), there is no general rule regarding an optimum spacing. For example, Merwade et al (2008) suggest that the interpolation is no longer realistic when the sections are separated by more than 10 to 15 channel widths.…”

“…For example, Merwade et al (2008) suggest that the interpolation is no longer realistic when the sections are separated by more than 10 to 15 channel widths. Legleiter et al (2011) report that topographic uncertainty is minimal when sections are separated by less than a quarter of the wetted channel width. Horritt and Bates (2002) found that despite widely spaced cross sections (>15 channel widths), their models gave good predictions of bulk flow properties such as discharge and flow extent, failures resulting rather from the parameterization of roughness.…”

“…For example, any deviation from a vertical representation of banks will increase the area of exchange during a stream flow event (Doble et al 2012), and possibly the area adjacent to the unsaturated zone, which tends to slow down the propagation of a flood wave in the shallow subsurface (McCallum et al 2010) (see Figure 3a). As stream flow recedes, smaller bedforms increasingly affect the surface flow field (Horritt et al 2006;Casas et al 2010b;Legleiter et al 2011) (Figure 3b). If sections of a stream become disconnected from each other, bedforms may shape the disconnection pattern (Figure 3e).…”

“…Points can be surveyed directly in the s, n system, or derived from x , y coordinates (e.g., Goff and Nordfjord 2004;Merwade et al 2005;Legleiter and Kyriakidis 2006). To represent anisotropy, kriging appears as one of the most suitable methods (Merwade et al 2006;Casas et al 2010b;Legleiter et al 2011). It is also flexible enough to include cross-sectional asymmetry and topographical break lines, as shown by Legleiter and Kyriakidis (2008).…”