ERDC/CHL CETN-IV-27
September 2000
In addition to its plot-making abilities, the SMS can construct vector data sets from scalar data,
and vice versa. Also, the data calculator allows the user to manipulate multiple scalar data sets
with several simple operations to form new scalar data sets. A subsequent section presents an
example of such a manipulation.
PRESENTATION OF OUTPUT: Default output from two-dimensional, depth-averaged,
hydrodynamic models includes water-surface elevation and velocities -- velocity magnitude as a
scalar data set and speed and direction as a vector data set. In addition, model input contains a
bathymetry data set. The drawing of causal relationships between the bathymetry and the speed
and direction is the key to understanding simulation results. Discussion will concentrate on the
creating model output plots that better illustrate these casual relationships and increase
understanding of the acting processes. For all subsequent figures, the example plots were created
from a simulation of the flow at East Pass, FL, during spring ebb tide.
A standard vector plot with an outline of the shoreline is shown in Figure 1. As shown in
Figure 7, vector plots are greatly enhanced when overlaid on a false color bathymetry plot. The
contour range is set at the limits of the bathymetry bounded by the plot rather than the entire
mesh to show greater detail. In addition, the number of contours has been increased from the
default number of 10 to 40 to show even more contrast. The legend on the left hand side has
been expanded from the default length, as shown in Figures 4 through 6, to span the entire height
of the plot. This expansion facilitates contour identification in working with a greater number of
contours. The vector overlay plot includes setting the vector length proportional to the vector
magnitude. From this plot, the influence and control exerted by the local water depths are
readily seen. For example, the velocities decrease following the vertical expansion over the ebb
shoal. Also, the velocities north of the spur jetty show a marked decrease, indicating that the
spur functions in its capacity to deflect high velocity flows away from the shoreline north of the
east jetty. Beyond these observations, distinguishing the flow behavior in the channel is difficult
given that the eye cannot discern the small differences in the vector lengths as water moves from
north to south. Another difficulty associated with this plot is discerning the flow patterns in areas
of small finite elements (e.g., between the jetties). To address this difficulty, SMS contains the
capability to create a grid of vectors at a user defined spacing rather than attach the vectors to
each node. Figure 8 illustrates this capability. From this figure, one can readily discern the flow
patterns between the jetties as opposed to Figure 7 where no patterns are discernable. This
technique must be applied judiciously, however. Too large a grid spacing may not resolve the
flow features that the modeler was trying to capture with the small elements in the first place.
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