Flow Resistance of Stream Bank Vegetation

Example of a compound bank

Streambanks can be eroded by the shearing forces of water. If left unprotected, eroded material from streambanks can contribute large quantities of sediment to the channel, increasing sediment loads and putting a strain on water resource facilities. Vegetation along the toe of a streambank can slow down water and deflect flow away from banks, altering the forces applied to the bank surface and protecting banks against erosion. However, vegetation also introduces turbulence, roughening flow and introducing localized scour.

In this study, a scaled flume experiment was used to estimate the relative magnitude of difference in channel velocity and turbulence on the streambank due to changes in vegetation planform density (number of plants/horizontal area) and projected area (number of leaves/vertical area).

Left: Example of a compound bank.

FLUME EXPERIMENTSFlow resistance flume without vegetation

Experiments were conducted in a 6.05 × 0.61 × 0.61 m recirculating flume set at a fixed slope of 0.001 m/m. To simulate a bank toe, a 4.88 m long inclined insert was installed along one side of the flume immediately downstream of the flow straighteners. The bank toe was 0.45m wide for a 30° slope and 0.41 m wide for a 15° slope. Bank and artificial vegetation was scaled by a Froude scaling factor of 4.35 from a prototype streambank representing the toe of a compound bank.

Above: Arrows indicate direction of flow, shaded region shows location of vegetation array. Cylinders represent flow straighteners used to help provide uniform flow characteristics. X’s represent cross-sections where velocity measurements at 0.6 of depth were taken. O’s represent locations of boundary velocity measurements. (Not drawn to scale.)

MEASUREMENTS

In order to characterize the depth-averaged velocity , it was assumed that the von Kàrmàn-Prandtl law of the wall was valid and hence velocity was measured at ~0.6 × the flow depth (0.6d) at 7 cross-stream locations within the 9 cross-sections. Near-boundary velocity was measured at 7 or 9 cross-stream locations within 7 cross-sections. Velocities were measured over five minutes at 25 Hz with a 10 MHz Nortek acoustic Doppler velocimeter (ADV). Data were filtered and processed using the WinADV software.

Key variables:

q = angle of bank toe (°)
u, v and w = velocity vectors in the streamwise, lateral, and vertical directions (m/s)
P = cross-sectional area of plant (m2)
D = vegetation planform density (#/m)
Q = discharge (m3/s)

 

SAMPLING DESIGN

Vegetation was installed in two patterns: low density (Dlo) of 202 plants per m2 and high density (Dhi) of 615 plants per m2, which scale to 8 and 24 plants per m2, respectively.

Vegetation was in two forms: low projected area (Plo) and high projected area (Phi). Plo plants were made of 450 mm long, 4.54 mm diameter acrylic rods, scaled down from 2 m tall, 20 mm diameter woody stems. Phi consisted of the same acrylic rods affixed with ten 28-gauge wire “branches” and ten 25 × 35 mm “leaves” made of contact paper (875 mm2 total) spaced to reflect a pattern of projected area found by Wilson et al. (2006).

Fifteen experimental runs were conducted for each slope: 12 with vegetation, and 3 non-vegetated control runs.

High density, low projected area with a 15° bank slope

High density, high projected area with a 30° bank slope

Low density, low projected area
with a 15° bank slope

Low density, high projected area with a 30° bank slope

Run D P Q (m3s-1)
1 lo lo 0.015
2 lo lo 0.03
3 lo lo 0.05
4 lo hi 0.015
5 lo hi 0.03
6 lo hi 0.05
7 hi lo 0.015
8 hi lo 0.03
9 hi lo 0.05
10 hi hi 0.015
11 hi hi 0.03
12 hi hi 0.05

 

PRELIMINARY RESULTS

 

ADV taking measurementsADV taking measurements

  • Vegetation density (D) and projected area (P) are important to include when considering streambank hydraulics. Both D and P decrease streamwise velocity along the bank toe and increase velocity in the main channel. They also alter turbulence patterns across the channel.
  • Plant form impacts turbulence, and thus erosion, along the bank toe. Findings from this study suggest P is more influential than D in increasing turbulence along the already vulnerable bank toe. Higher turbulence may increase erosion and promote channel widening. Therefore, once plants leaf out in the spring, the risk of erosion along the bank toe-channel margin may increase.
  • Vegetation slows and redirects water. This result supports findings from previous research. However, an important finding of this study are observations of a change in flow direction as P increases. This suggests that after leaf out occurs, patterns of scour and deposition may change. Increases in D did not have the same influence.

 

Video of an artificial leaf caught in eddy downstream of the vegetation.

Video of a high density, low projected area flume run.  

 

REFERENCES

Wilson, C. A. M. E., Yagci, O., Rauch, H.-P., and Stoesser, T. (2006). “Application of the drag force approach to model the flow-interaction of natural vegetation.” Int. J. River Basin Mgmt., 4(2), 137-146.

PUBLICATIONS

Tullos, D., Czarnomski, N. M., and Thomas, R. E. 2011. Influence of vegetation density and bank angle on near-bed hydraulics along streambanks. Poster. Coherent Flow Structures in Geophysical Flows at Earth’s Surface, Aug. 3-5, 2011. Burnaby, British Columbia

Czarnomski, N. M., Tullos, D., Simon, A., and Thomas, R. E. 2009. Influence of vegetation density and projected area on streambank hydraulics. Poster. 40th Annual Binghamton Geomorphology Symposium: Geomorphology and Vegetation: Interations, Dependencies, and Feedback Loops. Oct. 2-4, 2009, Virginia Tech, Blacksburg, Virginia.

Czarnomski, N. 2009. Influence of vegetation density and projected area on streambank hydraulics. 2009. Proceedings paper for the 33rd IAHR Congress, Vancouver, BC, August 2009

Czarnomski, N. M., Tullos, D., Simon, A., and Thomas, R. E. 2009. Influence of vegetation density and projected area on streambank erosion.  Poster. Ecosystems Informatics IGERT Annual Meeting 2009, Oregon State University, Corvallis, OR, May 2009

SUPPORT

NSF IGERT graduate fellowship (NSF award 0333257) in the Ecosystem Informatics IGERT program at Oregon State University

USDA-ARS National Sedimentation Laboratory at Oxford, Mississippi